diff --git a/.dockerignore b/.dockerignore new file mode 100644 index 00000000..fe340c05 --- /dev/null +++ b/.dockerignore @@ -0,0 +1,40 @@ +# Version control +.git/ +.gitignore + +# Python bytecode and caches +__pycache__/ +*.pyc +*.pyo +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ + +# Virtual environments +.venv/ +venv/ + +# Local secrets and config +.env +.env.* +!.env.example + +# Runtime data (never bake into image — mount a volume) +*.db +uploads/ +logs/ +htmlcov/ +.coverage + +# Tests (not needed in production image) +tests/ + +# Dev tooling and docs +*.md +reports/ +spec/ +.claude/ +.github/ + +# macOS +.DS_Store diff --git a/.env.example b/.env.example index 7b1de9d7..a76a9fc4 100644 --- a/.env.example +++ b/.env.example @@ -1,15 +1,26 @@ -AGENT_DATABASE_URL=sqlite:///./data/agent.db +# Data Analysis Agent — Environment Variables +# Copy to .env and fill in your values -# LLM provider — auto-detected from whichever key is set below. -# Override explicitly: anthropic | gemini -# AGENT_LLM_PROVIDER=anthropic +# ── Database ──────────────────────────────────────────────────────────────── +# SQLite database file path +DATAANALYSIS_DATABASE_URL=sqlite:///data_analysis.db -# Override model (uses provider default when blank): -# AGENT_LLM_MODEL=claude-sonnet-4-6 (Anthropic default) -# AGENT_LLM_MODEL=gemini-2.5-pro (Gemini default) +# Durable per-session agent memory (LangGraph SqliteSaver) — a SEPARATE SQLite file +DATAANALYSIS_CHECKPOINT_DB=checkpoints.db -# Set exactly ONE provider key: -AGENT_ANTHROPIC_API_KEY= -AGENT_GEMINI_API_KEY= +# Internal parquet datasets directory (one subdirectory per dataset) +DATAANALYSIS_DATASETS_DIR=uploads/datasets +# Enable external database datasets (PostgreSQL, BETA). Default off. +DATAANALYSIS_ENABLE_EXTERNAL_DATASETS=false +# ── LLM ───────────────────────────────────────────────────────────────────── +# OpenRouter API key — leave blank or unset for stub mode +# Get yours at https://openrouter.ai/keys +DATAANALYSIS_OPENROUTER_API_KEY= + +# LLM model name (any model available on OpenRouter) +DATAANALYSIS_LLM_MODEL=google/gemini-2.5-flash + +# ── App ────────────────────────────────────────────────────────────────────── PORT=8001 +DATAANALYSIS_LOG_LEVEL=INFO diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 00000000..44f4a3ba --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,38 @@ +name: CI + +on: + push: + branches: ["**"] + pull_request: + +jobs: + test: + name: Test (Python 3.12) + runs-on: ubuntu-latest + + steps: + - uses: actions/checkout@v4 + + - name: Install uv + uses: astral-sh/setup-uv@v4 + with: + version: "0.5.x" + enable-cache: true + + - name: Install dependencies (including dev) + run: uv sync --dev + + - name: Run tests + env: + DATAANALYSIS_OPENROUTER_API_KEY: ${{ secrets.DATAANALYSIS_OPENROUTER_API_KEY }} + DATAANALYSIS_DATABASE_URL: "sqlite:///ci_test.db" + run: uv run pytest tests/ -v --tb=short + + - name: Upload test results + if: always() + uses: actions/upload-artifact@v4 + with: + name: test-results + path: | + .pytest_cache/ + retention-days: 7 diff --git a/.github/workflows/deploy.yml b/.github/workflows/deploy.yml new file mode 100644 index 00000000..cbcabadf --- /dev/null +++ b/.github/workflows/deploy.yml @@ -0,0 +1,100 @@ +name: Deploy + +# Trigger on push to the app branch (or main after you merge the PR). +# Change the branch name below when you promote to main. +on: + push: + branches: + - feature/data-analysis-agent-v0.1 + - main + workflow_dispatch: # allows manual trigger from GitHub UI + +env: + REGISTRY: ghcr.io + IMAGE_NAME: ${{ github.repository }} + +jobs: + # ── 1. Run full test suite ──────────────────────────────────────────────── + test: + name: Test gate + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v4 + + - name: Install uv + uses: astral-sh/setup-uv@v4 + with: + version: "0.5.x" + enable-cache: true + + - name: Install dependencies + run: uv sync --dev + + - name: Run tests + env: + DATAANALYSIS_OPENROUTER_API_KEY: ${{ secrets.DATAANALYSIS_OPENROUTER_API_KEY }} + DATAANALYSIS_DATABASE_URL: "sqlite:///ci_test.db" + run: uv run pytest tests/ -v --tb=short + + # ── 2. Build Docker image and push to GHCR ─────────────────────────────── + build-and-push: + name: Build & push image + needs: test + runs-on: ubuntu-latest + permissions: + contents: read + packages: write # required to push to ghcr.io + + outputs: + image-tag: ${{ steps.meta.outputs.tags }} + image-digest: ${{ steps.push.outputs.digest }} + + steps: + - uses: actions/checkout@v4 + + - name: Set up Docker Buildx + uses: docker/setup-buildx-action@v3 + + - name: Log in to GitHub Container Registry + uses: docker/login-action@v3 + with: + registry: ${{ env.REGISTRY }} + username: ${{ github.actor }} + password: ${{ secrets.GITHUB_TOKEN }} + + - name: Extract Docker metadata (tags + labels) + id: meta + uses: docker/metadata-action@v5 + with: + images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }} + tags: | + # tag with full commit SHA for traceability + type=sha,format=long,prefix= + # always update :latest on this branch + type=raw,value=latest,enable=true + + - name: Build and push image + id: push + uses: docker/build-push-action@v6 + with: + context: . + push: true + tags: ${{ steps.meta.outputs.tags }} + labels: ${{ steps.meta.outputs.labels }} + # Cache layers across runs using GitHub Actions cache + cache-from: type=gha + cache-to: type=gha,mode=max + platforms: linux/amd64 + + # ── 3. Trigger Render to pull latest image and redeploy ────────────────── + deploy-render: + name: Trigger Render deploy + needs: build-and-push + runs-on: ubuntu-latest + steps: + - name: Deploy to Render + # RENDER_DEPLOY_HOOK_URL is stored as a GitHub Actions secret. + # Get it from: Render dashboard → your service → Settings → Deploy Hook + run: | + curl -sSf --max-time 30 -X POST "${{ secrets.RENDER_DEPLOY_HOOK_URL }}" \ + -o /dev/null -w "HTTP %{http_code}\n" diff --git a/.gitignore b/.gitignore index a43bd6e8..3ef1c840 100644 --- a/.gitignore +++ b/.gitignore @@ -10,9 +10,18 @@ dist/ build/ *.egg-info/ .DS_Store + +# Logs *.log +logs/ +# Runtime data *.db -*.db-shm -*.db-wal -data/ +uploads/ + +# Test / tool caches +.pytest_cache/ +.mypy_cache/ +.ruff_cache/ +htmlcov/ +.coverage diff --git a/Dockerfile b/Dockerfile new file mode 100644 index 00000000..c75ef779 --- /dev/null +++ b/Dockerfile @@ -0,0 +1,38 @@ +FROM python:3.12-slim + +# Install uv for reproducible dependency installs +COPY --from=ghcr.io/astral-sh/uv:0.5 /uv /usr/local/bin/uv + +WORKDIR /app + +# Disable uv's venv relinking — we copy files, not symlinks +ENV UV_LINK_MODE=copy +ENV UV_COMPILE_BYTECODE=1 + +# Layer 1: install third-party deps only (cache busts only on lock file change, +# not on application source changes). --no-install-project skips the local package. +COPY pyproject.toml uv.lock ./ +RUN uv sync --frozen --no-dev --no-install-project + +# Layer 2: application source (changes most frequently — keeps layer 1 cached) +COPY alembic.ini alembic.ini +COPY alembic/ alembic/ +COPY src/ src/ + +# Layer 3: install the local package itself (fast — deps are already installed) +RUN uv sync --frozen --no-dev + +# Runtime defaults — override these with Render env vars or docker run -e +ENV DATAANALYSIS_DATABASE_URL=sqlite:////data/app.db +ENV DATAANALYSIS_CHECKPOINT_DB=/data/checkpoints.db +ENV DATAANALYSIS_DATASETS_DIR=/data/datasets +ENV DATAANALYSIS_UPLOAD_DIR=/data/uploads +ENV DATAANALYSIS_LOG_FILE=/data/logs/app.log +ENV DATAANALYSIS_LOG_LEVEL=INFO + +EXPOSE 8000 + +COPY docker-entrypoint.sh /docker-entrypoint.sh +RUN chmod +x /docker-entrypoint.sh + +ENTRYPOINT ["/docker-entrypoint.sh"] diff --git a/README.md b/README.md index fecc07f0..f941b1f8 100644 --- a/README.md +++ b/README.md @@ -1,176 +1,125 @@ -# Zero Shot SDD Harness for Building Agents +# Data Analysis Agent -Give it a one-line idea. Walk away with a working, tested, phased agent. +Upload a CSV (or connect a database) and ask questions about your data in plain English. Each dataset becomes a **Model Context Protocol (MCP) server** whose **tools, resources, and prompts** are LLM-generated by a sync pipeline and served over a JSON-RPC endpoint. A LangGraph ReAct agent answers questions by running read-only DuckDB SQL over the data; an LLM (via OpenRouter) does the reasoning. -A lean, Claude-Code-native harness for building agentic software **spec-first**. One person with an idea and one API key can drive a real, production-shaped agent into existence — and a senior engineer opening the result finds a conventional, reviewable stack, not generated mush. +> **All commands run from the repo root.** --- -## The Spirit +## Quick Start -Six convictions the whole repo is built around: +### 1. Install dependencies -1. **Spec is the source of truth.** The spec is written before the code, always. When spec and code disagree, the spec wins and the code is fixed (`/zero-shot-sync`). Every AI session reads the same requirements instead of re-deriving them. -2. **Built for two audiences at once.** A non-coder drives it with a single sentence; a senior engineer inherits a clean FastAPI + LangGraph stack they can read, review, and own. Neither audience is an afterthought. -3. **Lean harness, not a framework.** `harness/` is engineering *mindfulness* — rules and patterns that keep every session consistent — deliberately Claude-Code-only and kept small. The product runtime stays provider-agnostic; the harness does not. -4. **Smallest first-time-right win, phase by phase.** Each phase ships the smallest increment a human can actually test, and it must work the *first* time they test it — real on the tested path, with clearly-labelled stubs for everything still to come. No rough edges on the path you're handed. -5. **A human gates every phase.** The build is autonomous *within* a phase and stops at each boundary for you to test the increment. You stay in control of what "done" means. -6. **Real LLM/API or it doesn't count.** Gates, tests, and evals run against the real model with keys from `.env`. A stubbed pass is not a pass. - ---- - -## What This Is - -A starting point for building AI agents spec-first. The repo ships with: - -- A working **baseline agent** in `src/` (FastAPI + LangGraph + SQLite, provider-agnostic LLM — Anthropic or Gemini, `transform_text` as the capability slot) — tests pass out of the box -- A **spec template** in `spec/` covering roadmap, architecture, capabilities, data model, API, UI, and agent graph -- Three **zero-shot skills** (`/zero-shot-build`, `/zero-shot-fix`, `/zero-shot-sync`) -- A four-agent **team** — agent-builder orchestrates (plans, fans out, owns git/PR); spec-writer is the single design authority; code-generator implements one slice per instance (parallelised); qa-auditor reviews and gates -- Engineering rules and patterns in `harness/` so every Claude Code session is consistent -- **Human testing gate between phases** — autonomous within a phase, you test each increment before the next starts - ---- +```bash +# Install uv if you don't have it +curl -LsSf https://astral.sh/uv/install.sh | sh -## How to Use This +# Install project dependencies +uv sync +``` -### Step 1 — Clone +### 2. Configure environment ```bash -git clone https://github.com/smallTechOrg/zero-shot-sdd-harness.git my-agent -cd my-agent +cp .env.example .env +# Edit .env and set DATAANALYSIS_OPENROUTER_API_KEY to your OpenRouter key +# Leave it blank to run in stub mode (offline, no real AI) ``` -### Step 2 — Open in Claude Code +### 3. Apply database migrations ```bash -claude +uv run alembic upgrade head +uv run alembic current # must print a revision hash — blank means migration failed ``` -### Step 3 — Build +### 4. Run the app -``` -/zero-shot-build An agent that monitors my Shopify store for low-inventory products and drafts restock emails to suppliers +```bash +uv run python -m data_analysis_agent ``` -One intake round (scope, stack, API keys → fill `.env`), then the agent builds phase by phase and stops at each boundary for you to test. +Open [http://localhost:8001](http://localhost:8001) in your browser. --- -## What Happens (Intake → Phase by Phase) - -``` -Your idea - ↓ -INTAKE — scope, stack, LLM provider, constraints; fill .env with the required API key - ↓ -[spec-writer] → Full spec: architecture + agent-graph + phased plan (self-reviewed) - ↓ -[agent-builder] → Feature branch + PR, scaffold - ↓ -per phase — all slices concurrently: - [code-generator: slice-a] ──→ [qa-auditor: slice-a] ─┐ - [code-generator: slice-b] ──→ [qa-auditor: slice-b] ─┤→ commit + push - [code-generator: slice-c] ──→ [qa-auditor: slice-c] ─┘ - ↓ -HUMAN TESTING GATE — exact run commands + expected result; you confirm before next phase - ↓ -(issue → qa-auditor classifies SPEC-vs-CODE → code-generator fixes → re-gate) - ↓ -repeat per phase → SHIP -``` +## Features (v0.1) -Phase 1 is the smallest first-time-right win — real on the tested path, with labelled stubs for everything coming later. Each later phase wires one more stub into real functionality. +- **MCP servers** — the primary entity. Each is backed 1:1 by a dataset (a named directory of Parquet files from uploaded CSVs, or an external PostgreSQL database in BETA). Its **tools, resources, and prompts** are LLM-generated by a 5-stage sync pipeline (title → JSONSchema → entities → GET-API tools → prompts), **versioned** and **soft-delete-only**. +- **MCP JSON-RPC API** — `POST /mcpserver/{id}` implements the MCP 2025-06-18 read surface: `tools/list` · `tools/call` · `resources/list` · `resources/read` · `prompts/list` · `prompts/get` (cursor pagination), for the UI and external MCP clients. +- **Natural Language Q&A** — type a question; a LangGraph ReAct agent calls a server (`{"tool","arguments"}`) and runs read-only DuckDB SQL (joins across a server's tables supported) +- **Sessions with memory** — each session keeps one MCP pool over its servers and remembers prior Q&A (durable across restarts), so follow-up questions have context +- **Query History** — review past questions and answers per session --- -## Repo Layout +## Stub Mode -``` -src/ ← baseline agent (FastAPI + LangGraph + SQLite, Anthropic/Gemini) - api/ ← FastAPI routers (create_app, health, runs) - config/ ← Pydantic BaseSettings - db/ ← SQLAlchemy models + session - domain/ ← Pydantic request/response models - graph/ ← LangGraph nodes, edges, state, runner ← CAPABILITY SLOT - llm/ ← LLM client + providers/ (anthropic, gemini) - prompts/ ← prompt templates (.md) - observability/ -frontend/ ← Next.js static export (served by FastAPI at /app) -tests/ - unit/ ← passes with no API key - integration/ ← requires real key in .env -spec/ ← your spec: roadmap, architecture, capabilities/, data, api, ui, agent -harness/ - rules/ ← ai-agents, git, secret-hygiene - patterns/ ← spec-driven, phases, project-layout, tech-stack, code, test-driven, ui-ux, agentic-ai, engineering-practices -.claude/ - skills/ ← /zero-shot-build, /zero-shot-fix, /zero-shot-sync - agents/ ← agent-builder, spec-writer, code-generator, qa-auditor -CLAUDE.md -pyproject.toml -alembic.ini ← Alembic migrations (alembic/) -agent.py ← verify setup (default); --run to start the server -.env.example -``` - -**Capability slot** — the three files to replace for your agent: -- `src/graph/nodes.py` — replace `transform_text` with your logic -- `src/prompts/transform.md` — replace with your system prompt -- `frontend/src/app/page.tsx` — replace the transform form with your UI - -Everything else (graph wiring, API, DB, settings, tests) is already working. +If `DATAANALYSIS_OPENROUTER_API_KEY` is not set, the app runs in **stub mode**: +- A yellow banner appears on every page +- Answers are placeholder text (not real AI output) +- No API calls are made — safe for offline development --- -## Running the Baseline +## Running Tests ```bash -cp .env.example .env -# edit .env: set exactly ONE provider key — -# AGENT_ANTHROPIC_API_KEY= or AGENT_GEMINI_API_KEY= -# the provider is auto-detected from whichever key is set -uv sync -python agent.py # verify tools, .env, deps, tests (default) -python agent.py --run # migrations + frontend build + start server +uv run pytest ``` -Once running: - -| URL | What | -|-----|------| -| `http://localhost:8001/app/` | **UI** — transform form (the capability slot) | -| `http://localhost:8001/health` | API health check | -| `http://localhost:8001/docs` | Interactive API docs (Swagger) | - -Tests: - -```bash -uv run pytest tests/unit/ -v # no key needed -uv run pytest tests/ -v # requires real key in .env -``` +All tests pass with no OpenRouter API key required (stub mode exercises the full sync + MCP + DuckDB pipeline). --- -## Rules AI Agents Follow +## Project Structure -Full rules in `harness/rules/ai-agents.md`. Summary: +``` +src/data_analysis_agent/ +├── api/ ← FastAPI routes: mcpserver.py, sessions.py, queries.py, home.py, health.py +├── config/ ← Settings (pydantic-settings) +├── db/ ← SQLAlchemy models + session +├── domain/ ← Pydantic domain models +├── graph/ ← LangGraph pipeline (state, nodes, edges, runner); SqliteSaver memory +├── llm/ ← OpenRouter + stub provider +├── tools/ ← CSV→Parquet ingestion, table naming +│ ├── connectors/ ← dataset connectors: uri, base (protocol+factory), parquet, postgres (BETA) +│ ├── sync/ ← 5-stage LLM capability generation (pipeline.py, stages.py) +│ └── mcp/ ← agent pool (pool.py) + per-server MCP (server.py) + JSON-RPC dispatch (dispatch.py) +└── templates/ ← Jinja2 HTML templates (home, session, mcpserver, base, error) + +# internal datasets live under DATAANALYSIS_DATASETS_DIR/{slug(name)}/{table}.parquet -- Read the full spec before writing any code -- Never skip a phase; commit every logical unit -- Tests run against the real LLM/API using keys from `.env` — stubbed runs do not count as passing -- Each phase is tested by the human before the next phase starts -- The build record is git history + the PR + the per-phase test-handoffs +tests/ +├── unit/ ← Pure unit tests (no DB, no network) +└── integration/ ← End-to-end pipeline + golden-path UI tests +``` --- -## FAQ +## Stack + +| Component | Choice | +|-----------|--------| +| Language | Python 3.12 | +| Web framework | FastAPI + uvicorn | +| UI | Jinja2 templates (React/Vite in Phase 4) | +| Agent | LangGraph (async nodes; one MCP pool + memory per session) | +| Primary entity | **MCP server** (1:1 with a dataset URI); children = tools/resources/prompts, generated by the sync pipeline (versioned, soft-delete) | +| Tool protocol | Model Context Protocol 2025-06-18 — `POST /mcpserver/{id}` JSON-RPC (DB-backed dispatcher) + official `mcp` SDK 1.28.0 (in-process FastMCP per server, generic `query` tool) for the agent | +| Datasets | URI-addressed metadata on the server: internal `parquet:///{name}` (dir of Parquet files) or external `postgresql://…` (BETA, flag-gated) | +| Query engine | DuckDB (read-only; `read_parquet` for internal, `ATTACH … READ_ONLY` for Postgres) | +| Agent memory | LangGraph `SqliteSaver` checkpointer (durable, per session) | +| LLM | via OpenRouter (default model `google/gemini-2.5-flash`) | +| Metadata DB | SQLite + SQLAlchemy 2.0 | +| Migrations | Alembic | -**What if I already have a stack in mind?** -State it in the idea: `/zero-shot-build [idea] — use Python + FastAPI + PostgreSQL`. Stack choices are binding. +--- -**What if something breaks?** -Run `/zero-shot-fix [what's broken]` — qa-auditor classifies the problem (SPEC vs CODE), the right generator fixes it, qa-auditor re-gates. +## Deferred (Future Phases) -**What if spec and code drift?** -Run `/zero-shot-sync` — qa-auditor classifies each divergence, generators fix, spec wins. +- Charts and visualizations (Phase 4) +- AI-written insights / dataset summaries (Phase 5) +- React/Vite frontend (Phase 4) +- Multi-dataset management (Phase 6) +- User authentication (Phase 7) diff --git a/agent.py b/agent.py deleted file mode 100644 index ce0cbbd9..00000000 --- a/agent.py +++ /dev/null @@ -1,263 +0,0 @@ -#!/usr/bin/env python3 -""" -agent.py — verify local setup or run the agent - -Usage: - python agent.py # verify all tools, .env, deps, and tests - python agent.py --run # verify + apply migrations + build frontend + start server -""" -import argparse -import os -import shutil -import subprocess -import sys -from pathlib import Path - -ROOT = Path(__file__).resolve().parent - -# ── colours ────────────────────────────────────────────────────────────────── -GREEN = "\033[32m" -RED = "\033[31m" -YELLOW = "\033[33m" -CYAN = "\033[36m" -RESET = "\033[0m" -BOLD = "\033[1m" - -def ok(msg: str) -> None: print(f" {GREEN}✓{RESET} {msg}") -def fail(msg: str) -> None: print(f" {RED}✗{RESET} {msg}"); _failures.append(msg) -def warn(msg: str) -> None: print(f" {YELLOW}!{RESET} {msg}") -def info(msg: str) -> None: print(f" {CYAN}→{RESET} {msg}") -def header(msg: str) -> None: print(f"\n{BOLD}{msg}{RESET}") - -_failures: list[str] = [] - - -# ── helpers ─────────────────────────────────────────────────────────────────── -def run(cmd: list[str], *, cwd: Path = ROOT, capture: bool = True) -> subprocess.CompletedProcess: - return subprocess.run(cmd, cwd=cwd, capture_output=capture, text=True) - -def which(name: str) -> bool: - return shutil.which(name) is not None - -def cmd_version(cmd: list[str]) -> str | None: - r = run(cmd) - return r.stdout.strip().splitlines()[0] if r.returncode == 0 else None - -def env_key_set(path: Path, key: str) -> bool: - if not path.exists(): - return False - for line in path.read_text().splitlines(): - if line.startswith(f"{key}="): - val = line.split("=", 1)[1].strip() - return bool(val) and val != "#" - return False - - -# ── checks ──────────────────────────────────────────────────────────────────── -def check_tools() -> None: - header("Tools") - - v = cmd_version(["git", "--version"]) - if v: ok(v) - else: fail("git not found — install git") - - vi = sys.version_info - if vi >= (3, 11): - ok(f"Python {vi.major}.{vi.minor}.{vi.micro}") - else: - fail(f"Python {vi.major}.{vi.minor} found — need 3.11+") - - v = cmd_version(["uv", "--version"]) - if v: ok(v) - else: fail("uv not found — install: curl -LsSf https://astral.sh/uv/install.sh | sh") - - v = cmd_version(["claude", "--version"]) - if v: ok(v) - else: fail("claude CLI not found — install Claude Code") - - if which("node"): - nv = cmd_version(["node", "--version"]) or "" - try: - major = int(nv.lstrip("v").split(".")[0]) - if major >= 20: - ok(f"node {nv}") - else: - fail(f"node {nv} found — need 20+; install from https://nodejs.org/") - except ValueError: - warn(f"could not parse node version: {nv}") - v = cmd_version(["pnpm", "--version"]) - if v: ok(f"pnpm {v}") - else: warn("pnpm not found — needed for frontend build: npm install -g pnpm") - else: - warn("node not found — needed for frontend build only; API works without it") - - -def check_env() -> None: - header("Environment (.env)") - - env = ROOT / ".env" - if not env.exists(): - fail(".env not found — run: cp .env.example .env and fill in your API key") - return - ok(".env exists") - - providers = { - "AGENT_ANTHROPIC_API_KEY": "Anthropic", - "AGENT_GEMINI_API_KEY": "Gemini", - } - found = [name for key, name in providers.items() if env_key_set(env, key)] - if found: - ok(f"API key set: {', '.join(found)}") - else: - fail("No provider key found in .env — set AGENT_ANTHROPIC_API_KEY or AGENT_GEMINI_API_KEY") - - -def check_python_env() -> None: - header("Python environment") - - if not (ROOT / ".venv").exists(): - fail(".venv not found — run: uv sync") - return - ok(".venv present") - - r = run(["uv", "run", "python", "-c", "import fastapi, sqlalchemy, langgraph, anthropic"]) - if r.returncode == 0: - ok("core packages importable (fastapi, sqlalchemy, langgraph, anthropic)") - else: - fail("missing packages — run: uv sync") - - -def check_db() -> None: - header("Database") - - (ROOT / "data").mkdir(exist_ok=True) - ok("data/ directory ready") - - r = run(["uv", "run", "alembic", "current"]) - if r.returncode == 0 and r.stdout.strip(): - ok(f"alembic migration applied: {r.stdout.strip().splitlines()[0]}") - elif r.returncode == 0: - warn("no migration applied yet — will apply on next run") - else: - warn("alembic check failed — will attempt on next run") - - -def check_tests() -> None: - header("Unit tests") - - r = run(["uv", "run", "pytest", "tests/unit/", "-q", "--tb=short"]) - if r.returncode == 0: - lines = [l for l in r.stdout.splitlines() if l.strip()] - ok(lines[-1] if lines else "tests passed") - else: - fail("unit tests failed:\n" + r.stdout[-800:]) - - -def check_frontend() -> None: - header("Frontend") - - fe = ROOT / "frontend" - if not fe.exists(): - warn("frontend/ not found — skipping") - return - - if not (fe / "node_modules").exists(): - warn("node_modules missing — run: cd frontend && pnpm install") - return - ok("node_modules present") - - if (fe / "out").exists(): - ok("frontend/out/ built — will serve UI at /app/") - else: - warn("frontend not built — will build on next run") - - -# ── run ─────────────────────────────────────────────────────────────────────── -def do_run() -> None: - # ensure data dir exists before alembic tries to open the sqlite file - (ROOT / "data").mkdir(exist_ok=True) - - # migrations - info("applying migrations...") - r = run(["uv", "run", "alembic", "upgrade", "head"], capture=False) - if r.returncode != 0: - print(f"\n{RED}alembic upgrade failed — fix before running.{RESET}") - sys.exit(1) - - # frontend build - fe = ROOT / "frontend" - if which("pnpm") and fe.exists(): - info("building frontend...") - r = run(["pnpm", "build"], cwd=fe, capture=False) - if r.returncode != 0: - print(f"\n{RED}frontend build failed.{RESET}") - sys.exit(1) - - # start - print(f"\n{GREEN}{BOLD}Starting…{RESET}") - print(f" {CYAN}http://localhost:8001{RESET} (API)") - if (ROOT / "frontend" / "out").exists(): - print(f" {CYAN}http://localhost:8001/app/{RESET} (UI)") - print() - env = os.environ.copy() - env["PYTHONPATH"] = str(ROOT / "src") - os.execvpe("uv", ["uv", "run", "uvicorn", "api:app", "--host", "0.0.0.0", "--port", "8001"], env) - - -# ── main ────────────────────────────────────────────────────────────────────── -def do_check() -> None: - print(f"\n{BOLD}=== Setup Check ==={RESET}") - check_tools() - check_env() - check_python_env() - check_db() - check_tests() - check_frontend() - print() - if _failures: - print(f"{RED}{BOLD}{len(_failures)} issue(s) found — fix before running.{RESET}") - for f in _failures: - print(f" {RED}✗{RESET} {f}") - sys.exit(1) - else: - print(f"{GREEN}{BOLD}All checks passed. Run: python agent.py --run{RESET}\n") - - -def main() -> None: -<<<<<<< HEAD - parser = argparse.ArgumentParser(description="Check local setup (default) or run the agent") - parser.add_argument("--run", action="store_true", help="build frontend + apply migrations + start server") -======= - parser = argparse.ArgumentParser(description="Verify local setup or run the agent") - parser.add_argument("--run", action="store_true", help="apply migrations, build frontend, and start server") ->>>>>>> 599e02c (fix: tighten version requirements and fix agent.py startup) - args = parser.parse_args() - - if args.run: - do_run() -<<<<<<< HEAD - return - - print(f"\n{BOLD}=== Setup Check ==={RESET}") - check_tools() - check_env() - check_python_env() - check_db() - check_tests() - check_frontend() - print() - if _failures: - print(f"{RED}{BOLD}{len(_failures)} issue(s) found — fix before running.{RESET}") - for f in _failures: - print(f" {RED}✗{RESET} {f}") - sys.exit(1) - else: - print(f"{GREEN}{BOLD}All checks passed. Run: python agent.py --run{RESET}\n") -======= - else: - do_check() ->>>>>>> 599e02c (fix: tighten version requirements and fix agent.py startup) - - -if __name__ == "__main__": - main() diff --git a/alembic.ini b/alembic.ini index 49b5fd3d..371d60d5 100644 --- a/alembic.ini +++ b/alembic.ini @@ -3,7 +3,7 @@ script_location = alembic prepend_sys_path = . version_path_separator = os -sqlalchemy.url = sqlite:///./agent.db +[post_write_hooks] [loggers] keys = root,sqlalchemy,alembic diff --git a/alembic/env.py b/alembic/env.py index 664f8688..d2f2ca93 100644 --- a/alembic/env.py +++ b/alembic/env.py @@ -1,31 +1,25 @@ -import sys -from pathlib import Path - from logging.config import fileConfig from sqlalchemy import engine_from_config, pool from alembic import context -# Make src/ importable -sys.path.insert(0, str(Path(__file__).parent.parent / "src")) - -from config.settings import get_settings -from db.models import Base - config = context.config if config.config_file_name is not None: fileConfig(config.config_file_name) +from data_analysis_agent.db.models import Base target_metadata = Base.metadata -# Override sqlalchemy.url from settings -config.set_main_option("sqlalchemy.url", get_settings().database_url) + +def get_url() -> str: + from data_analysis_agent.config.settings import get_settings + return get_settings().database_url def run_migrations_offline() -> None: - url = config.get_main_option("sqlalchemy.url") + url = get_url() context.configure( url=url, target_metadata=target_metadata, @@ -37,13 +31,19 @@ def run_migrations_offline() -> None: def run_migrations_online() -> None: + cfg = config.get_section(config.config_ini_section, {}) + cfg["sqlalchemy.url"] = get_url() connectable = engine_from_config( - config.get_section(config.config_ini_section, {}), + cfg, prefix="sqlalchemy.", poolclass=pool.NullPool, ) with connectable.connect() as connection: - context.configure(connection=connection, target_metadata=target_metadata) + context.configure( + connection=connection, + target_metadata=target_metadata, + render_as_batch=connection.dialect.name == "sqlite", # batch ALTER is SQLite-only + ) with context.begin_transaction(): context.run_migrations() diff --git a/alembic/script.py.mako b/alembic/script.py.mako index a4cb435d..fbc4b07d 100644 --- a/alembic/script.py.mako +++ b/alembic/script.py.mako @@ -1,4 +1,4 @@ -${message} +"""${message} Revision ID: ${up_revision} Revises: ${down_revision | comma,n} diff --git a/alembic/versions/0001_initial.py b/alembic/versions/0001_initial.py deleted file mode 100644 index 353be76b..00000000 --- a/alembic/versions/0001_initial.py +++ /dev/null @@ -1,34 +0,0 @@ -"""initial - -Revision ID: 0001 -Revises: -Create Date: 2026-01-01 00:00:00.000000 - -""" -from typing import Sequence, Union - -from alembic import op -import sqlalchemy as sa - -revision: str = "0001" -down_revision: Union[str, None] = None -branch_labels: Union[str, Sequence[str], None] = None -depends_on: Union[str, Sequence[str], None] = None - - -def upgrade() -> None: - op.create_table( - "runs", - sa.Column("id", sa.Text(), nullable=False), - sa.Column("status", sa.Text(), nullable=False), - sa.Column("input_text", sa.Text(), nullable=True), - sa.Column("output_text", sa.Text(), nullable=True), - sa.Column("error_message", sa.Text(), nullable=True), - sa.Column("created_at", sa.TIMESTAMP(timezone=True), nullable=False), - sa.Column("updated_at", sa.TIMESTAMP(timezone=True), nullable=False), - sa.PrimaryKeyConstraint("id"), - ) - - -def downgrade() -> None: - op.drop_table("runs") diff --git a/alembic/versions/835cdb8ae996_initial_mcp_server_schema.py b/alembic/versions/835cdb8ae996_initial_mcp_server_schema.py new file mode 100644 index 00000000..450ffa53 --- /dev/null +++ b/alembic/versions/835cdb8ae996_initial_mcp_server_schema.py @@ -0,0 +1,167 @@ +"""initial database (MCP server instance) schema + +Revision ID: 835cdb8ae996 +Revises: +Create Date: 2026-06-26 02:01:01.827371 + +The primary entity is a **database** (an instance of an MCP server type). Its MCP capabilities +(mcp_tools / mcp_resources / mcp_prompts) are child rows keyed by ``database_id``. Partial-unique +indexes carry BOTH ``sqlite_where`` and ``postgresql_where`` (uniqueness over active rows) and are +created with ``op.create_index`` (not batch mode) so they apply on PostgreSQL as well as SQLite. +""" +from typing import Sequence, Union + +from alembic import op +import sqlalchemy as sa + + +# revision identifiers, used by Alembic. +revision: str = '835cdb8ae996' +down_revision: Union[str, None] = None +branch_labels: Union[str, Sequence[str], None] = None +depends_on: Union[str, Sequence[str], None] = None + +_ACTIVE = sa.text('deleted_at IS NULL') + + +def upgrade() -> None: + op.create_table('agent_runs', + sa.Column('id', sa.Text(), nullable=False), + sa.Column('query_record_id', sa.Text(), nullable=False), + sa.Column('status', sa.Text(), nullable=False), + sa.Column('error_message', sa.Text(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.Column('updated_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + + op.create_table('mcp_prompts', + sa.Column('name', sa.Text(), nullable=False), + sa.Column('title', sa.Text(), nullable=True), + sa.Column('description', sa.Text(), nullable=True), + sa.Column('arguments_json', sa.Text(), nullable=True), + sa.Column('template_json', sa.Text(), nullable=True), + sa.Column('id', sa.Text(), nullable=False), + sa.Column('database_id', sa.Text(), nullable=False), + sa.Column('created_version', sa.Integer(), nullable=False), + sa.Column('deleted_at', sa.TIMESTAMP(timezone=True), nullable=True), + sa.Column('deleted_version', sa.Integer(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.Column('updated_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + op.create_index('ix_mcp_prompts_database_id', 'mcp_prompts', ['database_id'], unique=False) + op.create_index('uq_mcp_prompts_active_name', 'mcp_prompts', ['database_id', 'name'], unique=True, + sqlite_where=_ACTIVE, postgresql_where=_ACTIVE) + + op.create_table('mcp_resources', + sa.Column('uri', sa.Text(), nullable=False), + sa.Column('name', sa.Text(), nullable=False), + sa.Column('title', sa.Text(), nullable=True), + sa.Column('description', sa.Text(), nullable=True), + sa.Column('mime_type', sa.Text(), nullable=True), + sa.Column('kind', sa.Text(), nullable=False), + sa.Column('content_json', sa.Text(), nullable=True), + sa.Column('size', sa.Integer(), nullable=True), + sa.Column('id', sa.Text(), nullable=False), + sa.Column('database_id', sa.Text(), nullable=False), + sa.Column('created_version', sa.Integer(), nullable=False), + sa.Column('deleted_at', sa.TIMESTAMP(timezone=True), nullable=True), + sa.Column('deleted_version', sa.Integer(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.Column('updated_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + op.create_index('ix_mcp_resources_database_id', 'mcp_resources', ['database_id'], unique=False) + op.create_index('uq_mcp_resources_active_uri', 'mcp_resources', ['uri'], unique=True, + sqlite_where=_ACTIVE, postgresql_where=_ACTIVE) + + op.create_table('databases', + sa.Column('id', sa.Text(), nullable=False), + sa.Column('name', sa.Text(), nullable=False), + sa.Column('title', sa.Text(), nullable=True), + sa.Column('description', sa.Text(), nullable=True), + sa.Column('type', sa.Text(), nullable=False), + sa.Column('uri', sa.Text(), nullable=False), + sa.Column('version', sa.Integer(), server_default='1', nullable=False), + sa.Column('last_synced_at', sa.TIMESTAMP(timezone=True), nullable=True), + sa.Column('last_sync_status', sa.Text(), nullable=True), + sa.Column('connection_error', sa.Text(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id'), + sa.UniqueConstraint('name'), + sa.UniqueConstraint('uri') + ) + + op.create_table('mcp_tools', + sa.Column('name', sa.Text(), nullable=False), + sa.Column('title', sa.Text(), nullable=True), + sa.Column('description', sa.Text(), nullable=False), + sa.Column('execution_json', sa.Text(), nullable=False), + sa.Column('output_schema_json', sa.Text(), nullable=True), + sa.Column('annotations_json', sa.Text(), nullable=True), + sa.Column('id', sa.Text(), nullable=False), + sa.Column('database_id', sa.Text(), nullable=False), + sa.Column('created_version', sa.Integer(), nullable=False), + sa.Column('deleted_at', sa.TIMESTAMP(timezone=True), nullable=True), + sa.Column('deleted_version', sa.Integer(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.Column('updated_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + op.create_index('ix_mcp_tools_database_id', 'mcp_tools', ['database_id'], unique=False) + op.create_index('uq_mcp_tools_active_name', 'mcp_tools', ['database_id', 'name'], unique=True, + sqlite_where=_ACTIVE, postgresql_where=_ACTIVE) + + op.create_table('query_records', + sa.Column('id', sa.Text(), nullable=False), + sa.Column('session_id', sa.Text(), nullable=False), + sa.Column('question', sa.Text(), nullable=False), + sa.Column('answer', sa.Text(), nullable=True), + sa.Column('status', sa.Text(), nullable=False), + sa.Column('error_message', sa.Text(), nullable=True), + sa.Column('iteration_count', sa.Integer(), nullable=True), + sa.Column('query_history_json', sa.Text(), nullable=True), + sa.Column('input_tokens', sa.Integer(), nullable=True), + sa.Column('output_tokens', sa.Integer(), nullable=True), + sa.Column('total_tokens', sa.Integer(), nullable=True), + sa.Column('estimated_cost_usd', sa.Float(), nullable=True), + sa.Column('api_request_count', sa.Integer(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.Column('updated_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + + op.create_table('session_databases', + sa.Column('session_id', sa.Text(), nullable=False), + sa.Column('database_id', sa.Text(), nullable=False), + sa.PrimaryKeyConstraint('session_id', 'database_id') + ) + + op.create_table('sessions', + sa.Column('id', sa.Text(), nullable=False), + sa.Column('name', sa.Text(), nullable=True), + sa.Column('created_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.Column('updated_at', sa.TIMESTAMP(timezone=True), nullable=False), + sa.PrimaryKeyConstraint('id') + ) + + +def downgrade() -> None: + op.drop_table('sessions') + op.drop_table('session_databases') + op.drop_table('query_records') + op.drop_index('uq_mcp_tools_active_name', table_name='mcp_tools', + sqlite_where=_ACTIVE, postgresql_where=_ACTIVE) + op.drop_index('ix_mcp_tools_database_id', table_name='mcp_tools') + op.drop_table('mcp_tools') + op.drop_table('databases') + op.drop_index('uq_mcp_resources_active_uri', table_name='mcp_resources', + sqlite_where=_ACTIVE, postgresql_where=_ACTIVE) + op.drop_index('ix_mcp_resources_database_id', table_name='mcp_resources') + op.drop_table('mcp_resources') + op.drop_index('uq_mcp_prompts_active_name', table_name='mcp_prompts', + sqlite_where=_ACTIVE, postgresql_where=_ACTIVE) + op.drop_index('ix_mcp_prompts_database_id', table_name='mcp_prompts') + op.drop_table('mcp_prompts') + op.drop_table('agent_runs') diff --git a/docker-entrypoint.sh b/docker-entrypoint.sh new file mode 100644 index 00000000..bdbf415b --- /dev/null +++ b/docker-entrypoint.sh @@ -0,0 +1,12 @@ +#!/bin/sh +set -e + +# Ensure runtime dirs exist (Render persistent disk or local volume) +mkdir -p /data/uploads /data/logs + +# Run DB migrations on every startup — idempotent, safe for rolling restarts +/app/.venv/bin/alembic upgrade head + +exec /app/.venv/bin/uvicorn data_analysis_agent.api:app \ + --host 0.0.0.0 \ + --port "${PORT:-8000}" diff --git a/frontend/.gitignore b/frontend/.gitignore deleted file mode 100644 index 2fc7f351..00000000 --- a/frontend/.gitignore +++ /dev/null @@ -1,3 +0,0 @@ -.next/ -out/ -node_modules/ diff --git a/frontend/next-env.d.ts b/frontend/next-env.d.ts deleted file mode 100644 index 1b3be084..00000000 --- a/frontend/next-env.d.ts +++ /dev/null @@ -1,5 +0,0 @@ -/// -/// - -// NOTE: This file should not be edited -// see https://nextjs.org/docs/app/api-reference/config/typescript for more information. diff --git a/frontend/next.config.ts b/frontend/next.config.ts deleted file mode 100644 index 2e38c9ba..00000000 --- a/frontend/next.config.ts +++ /dev/null @@ -1,9 +0,0 @@ -import type { NextConfig } from 'next' - -const config: NextConfig = { - output: 'export', - basePath: '/app', - trailingSlash: true, -} - -export default config diff --git a/frontend/package.json b/frontend/package.json deleted file mode 100644 index 879293aa..00000000 --- a/frontend/package.json +++ /dev/null @@ -1,27 +0,0 @@ -{ - "name": "agent-frontend", - "version": "0.1.0", - "private": true, - 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optional: true - - lightningcss-linux-arm64-gnu@1.32.0: - optional: true - - lightningcss-linux-arm64-musl@1.32.0: - optional: true - - lightningcss-linux-x64-gnu@1.32.0: - optional: true - - lightningcss-linux-x64-musl@1.32.0: - optional: true - - lightningcss-win32-arm64-msvc@1.32.0: - optional: true - - lightningcss-win32-x64-msvc@1.32.0: - optional: true - - lightningcss@1.32.0: - dependencies: - detect-libc: 2.1.2 - optionalDependencies: - lightningcss-android-arm64: 1.32.0 - lightningcss-darwin-arm64: 1.32.0 - lightningcss-darwin-x64: 1.32.0 - lightningcss-freebsd-x64: 1.32.0 - lightningcss-linux-arm-gnueabihf: 1.32.0 - lightningcss-linux-arm64-gnu: 1.32.0 - lightningcss-linux-arm64-musl: 1.32.0 - lightningcss-linux-x64-gnu: 1.32.0 - lightningcss-linux-x64-musl: 1.32.0 - lightningcss-win32-arm64-msvc: 1.32.0 - lightningcss-win32-x64-msvc: 1.32.0 - - magic-string@0.30.21: - dependencies: - '@jridgewell/sourcemap-codec': 1.5.5 - - nanoid@3.3.15: {} - - next@15.3.0(react-dom@19.2.7(react@19.2.7))(react@19.2.7): - dependencies: - '@next/env': 15.3.0 - '@swc/counter': 0.1.3 - '@swc/helpers': 0.5.15 - busboy: 1.6.0 - caniuse-lite: 1.0.30001799 - postcss: 8.4.31 - react: 19.2.7 - react-dom: 19.2.7(react@19.2.7) - styled-jsx: 5.1.6(react@19.2.7) - optionalDependencies: - '@next/swc-darwin-arm64': 15.3.0 - '@next/swc-darwin-x64': 15.3.0 - '@next/swc-linux-arm64-gnu': 15.3.0 - '@next/swc-linux-arm64-musl': 15.3.0 - '@next/swc-linux-x64-gnu': 15.3.0 - '@next/swc-linux-x64-musl': 15.3.0 - '@next/swc-win32-arm64-msvc': 15.3.0 - '@next/swc-win32-x64-msvc': 15.3.0 - sharp: 0.34.5 - transitivePeerDependencies: - - '@babel/core' - - babel-plugin-macros - - picocolors@1.1.1: {} - - postcss@8.4.31: - dependencies: - nanoid: 3.3.15 - picocolors: 1.1.1 - source-map-js: 1.2.1 - - postcss@8.5.15: - dependencies: - nanoid: 3.3.15 - picocolors: 1.1.1 - source-map-js: 1.2.1 - - react-dom@19.2.7(react@19.2.7): - dependencies: - react: 19.2.7 - scheduler: 0.27.0 - - react@19.2.7: {} - - scheduler@0.27.0: {} - - semver@7.8.5: - optional: true - - sharp@0.34.5: - dependencies: - '@img/colour': 1.1.0 - detect-libc: 2.1.2 - semver: 7.8.5 - optionalDependencies: - '@img/sharp-darwin-arm64': 0.34.5 - '@img/sharp-darwin-x64': 0.34.5 - '@img/sharp-libvips-darwin-arm64': 1.2.4 - '@img/sharp-libvips-darwin-x64': 1.2.4 - '@img/sharp-libvips-linux-arm': 1.2.4 - '@img/sharp-libvips-linux-arm64': 1.2.4 - '@img/sharp-libvips-linux-ppc64': 1.2.4 - '@img/sharp-libvips-linux-riscv64': 1.2.4 - '@img/sharp-libvips-linux-s390x': 1.2.4 - '@img/sharp-libvips-linux-x64': 1.2.4 - '@img/sharp-libvips-linuxmusl-arm64': 1.2.4 - '@img/sharp-libvips-linuxmusl-x64': 1.2.4 - '@img/sharp-linux-arm': 0.34.5 - '@img/sharp-linux-arm64': 0.34.5 - '@img/sharp-linux-ppc64': 0.34.5 - '@img/sharp-linux-riscv64': 0.34.5 - '@img/sharp-linux-s390x': 0.34.5 - '@img/sharp-linux-x64': 0.34.5 - '@img/sharp-linuxmusl-arm64': 0.34.5 - '@img/sharp-linuxmusl-x64': 0.34.5 - '@img/sharp-wasm32': 0.34.5 - '@img/sharp-win32-arm64': 0.34.5 - '@img/sharp-win32-ia32': 0.34.5 - '@img/sharp-win32-x64': 0.34.5 - optional: true - - source-map-js@1.2.1: {} - - streamsearch@1.1.0: {} - - styled-jsx@5.1.6(react@19.2.7): - dependencies: - client-only: 0.0.1 - react: 19.2.7 - - tailwindcss@4.3.1: {} - - tapable@2.3.3: {} - - tslib@2.8.1: {} - - typescript@5.9.3: {} - - undici-types@6.21.0: {} diff --git a/frontend/pnpm-workspace.yaml b/frontend/pnpm-workspace.yaml deleted file mode 100644 index 163e4aed..00000000 --- a/frontend/pnpm-workspace.yaml +++ /dev/null @@ -1,2 +0,0 @@ -allowBuilds: - sharp: false diff --git a/frontend/src/app/globals.css b/frontend/src/app/globals.css deleted file mode 100644 index f1d8c73c..00000000 --- a/frontend/src/app/globals.css +++ /dev/null @@ -1 +0,0 @@ -@import "tailwindcss"; diff --git a/frontend/src/app/layout.tsx b/frontend/src/app/layout.tsx deleted file mode 100644 index 8e6c96e3..00000000 --- a/frontend/src/app/layout.tsx +++ /dev/null @@ -1,15 +0,0 @@ -import type { Metadata } from 'next' -import './globals.css' - -export const metadata: Metadata = { - title: 'Agent', - description: 'AI agent interface', -} - -export default function RootLayout({ children }: { children: React.ReactNode }) { - return ( - - {children} - - ) -} diff --git a/frontend/src/app/page.tsx b/frontend/src/app/page.tsx deleted file mode 100644 index 7e6926c1..00000000 --- a/frontend/src/app/page.tsx +++ /dev/null @@ -1,77 +0,0 @@ -'use client' - -import { useState } from 'react' - -export default function Home() { - const [input, setInput] = useState('') - const [result, setResult] = useState(null) - const [error, setError] = useState(null) - const [loading, setLoading] = useState(false) - - async function handleSubmit(e: React.FormEvent) { - e.preventDefault() - if (!input.trim()) return - setLoading(true) - setError(null) - setResult(null) - try { - const res = await fetch('/runs', { - method: 'POST', - headers: { 'Content-Type': 'application/json' }, - body: JSON.stringify({ input_text: input }), - }) - const data = await res.json() - if (!res.ok) { - setError(data.detail?.message ?? `Request failed (${res.status})`) - } else if (data.data?.error) { - setError(data.data.error) - } else { - setResult(data.data.output_text) - } - } catch { - setError('Network error — is the server running?') - } finally { - setLoading(false) - } - } - - return ( -
-

Agent

- -
- + + + +
+ + +
+ + + + + + + + + + + + +
+ + + + + +
+ + +
+ +
+ +
+
Databases + {{ server_total }}
+
+
+ + +
+
+ + +
+
Upload data files
+ + + + +
+
+
⇓
+
Drop a file or click to browse
+
.csv · .tsv · .json · .xlsx · .xls
+ +
+
+ + + +
+
+ + +
+
+
Working…
+
The agent is analysing your data
+
+ +
+
+ + {% if active_session %} +
+ {{ active_session.name }} + + {% for srv in active_session.servers %}{{ srv.name }}{% endfor %} + +
+ +
+ + + + +
+ + {% else %} +
+
💬
+

Select a session to start a conversation

+

Pick a session on the left, or click + New to create one + {% if not servers %}(after uploading a dataset){% endif %}.

+
+ {% endif %} +
+
+ + +
+ {% if active_server %} + {% set srv = active_server %} +
+
+
+ {{ srv.name }} + {{ srv.type|upper }} + v{{ srv.version }} +
+ {% if srv.title %}
{{ srv.title }}
{% endif %} +
{{ srv.uri_display }} + {% if srv.last_sync_status %} · last sync: {{ srv.last_sync_status }}{% if srv.last_synced_at %} ({{ srv.last_synced_at.strftime('%b %d %H:%M') }}){% endif %}{% endif %}
+
+
+ +
+ +
+ {% if srv.is_parquet %} + + + {% endif %} +
+
+ + {% if srv.connection_error %}
⚠ {{ srv.connection_error }}
{% endif %} + +
+ +
+
+
+ EER diagram · {{ srv.tables|length }} table{{ 's' if srv.tables|length != 1 }} + + number + text + date + other + +
+
+ +
+
+ + +
+
+
MCP capabilities +
+ +
+
+

Tools ({{ srv.tool_count }})

+
+
+
+ + +
+
+ +
+
+

Resources ({{ srv.resource_count }})

+
+
+ + +
+
+ +
+
+

Prompts ({{ srv.prompt_count }})

+
+
+
+ + +
+
+
+
+
+ {% else %} +
+
+
🗄️
+

Inspect a database

+

Pick a server to view its schema, tools, resources, and prompts.

+
+ {% if servers %} + + {% endif %} +
+ {% endif %} +
+ +
+
+{% endblock %} + +{% block scripts %} + +{% endblock %} diff --git a/src/observability/__init__.py b/src/data_analysis_agent/tools/__init__.py similarity index 100% rename from src/observability/__init__.py rename to src/data_analysis_agent/tools/__init__.py diff --git a/src/data_analysis_agent/tools/connectors/__init__.py b/src/data_analysis_agent/tools/connectors/__init__.py new file mode 100644 index 00000000..a0d0b79b --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/__init__.py @@ -0,0 +1,6 @@ +"""Dataset connectors: abstract dataset access behind a ``DatasetConnector`` protocol. + +A dataset (the agent's "tool") is addressed by a URI; a connector knows how to validate the +connection, discover its tables, and build the dataset's in-process MCP server. ``ParquetConnector`` +(internal) is fully implemented; ``PostgresConnector`` (external) is BETA and flag-gated. +""" diff --git a/src/data_analysis_agent/tools/connectors/base.py b/src/data_analysis_agent/tools/connectors/base.py new file mode 100644 index 00000000..421a6937 --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/base.py @@ -0,0 +1,112 @@ +"""Database connector base class + factory. + +The query/sync path must never branch on database type. Every connector **inherits from +:class:`BaseConnector`** and implements the same methods returning the same shapes, so callers use any +connector interchangeably without checking its type. ``get_connector`` dispatches on ``type`` to the +concrete subclass. New engines = one new subclass + one branch here. +""" +from __future__ import annotations + +from abc import ABC, abstractmethod + +from mcp.server.fastmcp import FastMCP + +from data_analysis_agent.tools.connectors.uri import DatasetURI +from data_analysis_agent.tools.mcp.server import DEFAULT_MAX_ROWS + + +class DatasetConnectionError(Exception): + """A database's URI could not be connected/validated. Messages are ALWAYS credential-free.""" + + +class BaseConnector(ABC): + """How the app validates, **inspects**, and serves a database (parquet, postgres, sqlite, …). + + The connector is the single source of truth for a database's physical tables: it inspects the + underlying store live (``discover_tables``) — the app stores no table catalog. Subclasses differ only + in their internals; the method signatures and returned shapes are identical across all of them. + """ + + def __init__(self, server: dict) -> None: + self._server = server + self._uri = DatasetURI(server.get("uri") or "") + + # --- required (type-specific internals) ------------------------------- + + @abstractmethod + def connection_check(self) -> None: + """Validate the database is reachable/readable; raise ``DatasetConnectionError`` on failure. + + Abstracts the type-specific check (parquet: the directory is accessible — zero tables is valid; + external: a real connect). Never leaks credentials. + """ + + @abstractmethod + def discover_tables(self) -> list[dict]: + """Inspect the store and return its tables (**sync only** — not on the serving path). + + ``[{table_name, parquet_path?, column_names, schema, row_count}]`` — may be empty. + """ + + @abstractmethod + def build_server(self, table_names: list[str], max_rows: int = DEFAULT_MAX_ROWS) -> FastMCP: + """Build the in-process MCP server (one generic ``query`` tool) over the **given** tables. + + ``table_names`` come from the caller (the resources table outside sync; freshly-discovered tables + during sync) — ``build_server`` does NOT inspect, so the serving path never re-hits the store's + metadata. The connector knows how to materialize a view for each named table for its type. + """ + + # --- optional (sensible defaults; override when the store supports it) - + + def discover_relationships(self) -> list[dict]: + """Foreign-key relationships ``[{from, to, on}]`` when the store exposes them (default: none).""" + return [] + + def drop_table(self, table_name: str) -> None: + """Remove a table from the database (default: no-op — external stores are never mutated).""" + return None + + +# The database (MCP-server) types the UI offers. ``parquet`` is the internal file-upload type; the rest +# are external (a connection URI). One entry = one connector below. +# ``(value, label, is_external, uri_hint)`` — ``uri_hint`` is the per-type placeholder the UI shows in +# the Connection-URI field once that type is selected (empty for the file-upload type). +DATABASE_TYPES: list[tuple[str, str, bool, str]] = [ + ("parquet", "Upload a file", False, ""), + ("postgresql", "PostgreSQL", True, "postgresql://user:pass@host:5432/dbname"), + ("sqlite", "SQLite", True, "sqlite:///path/to/file.db"), + ("mongodb", "MongoDB", True, "mongodb://host:27017/dbname"), + ("snowflake", "Snowflake", True, "snowflake://user:pw@account/DB/SCHEMA"), +] + +EXTERNAL_TYPES = frozenset(v for v, _, ext, _ in DATABASE_TYPES if ext) + +# type → (module, class) registry. The connector module is imported lazily (avoids a base↔connector +# import cycle and keeps each external driver optional — drivers are imported inside the methods). +_REGISTRY: dict[str, tuple[str, str]] = { + "parquet": ("parquet", "ParquetConnector"), + "postgresql": ("postgres", "PostgresConnector"), + "postgres": ("postgres", "PostgresConnector"), # alias + "sqlite": ("sqlite", "SQLiteConnector"), + "mongodb": ("mongodb", "MongoDBConnector"), + "snowflake": ("snowflake", "SnowflakeConnector"), +} + + +def get_connector(server: dict) -> BaseConnector: + """Return the connector for a database dict (``type`` + ``uri`` + ``name``). + + Dispatch is a registry lookup (no type branching); the connector inspects its own tables (no catalog + passed in). + + Raises: + DatasetConnectionError: for an unknown database type. + """ + import importlib + entry = _REGISTRY.get((server.get("type") or "parquet").lower()) + if entry is None: + raise DatasetConnectionError(f"Unsupported database type: {server.get('type')!r}") + module, cls = entry + connector_cls = getattr(importlib.import_module(f"data_analysis_agent.tools.connectors.{module}"), cls) + return connector_cls(server) diff --git a/src/data_analysis_agent/tools/connectors/mongodb.py b/src/data_analysis_agent/tools/connectors/mongodb.py new file mode 100644 index 00000000..75ff33cf --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/mongodb.py @@ -0,0 +1,86 @@ +"""MongoDB database connector (BETA): collections are the "tables". + +MongoDB is not SQL, so there is no native DuckDB scanner. We introspect with ``pymongo`` (collections + +sampled field names) and, for querying, **load** each collection's documents into a DuckDB-registered +DataFrame so the generic read-only SELECT path works unchanged. ``pymongo`` is imported lazily — install +it (``pip install pymongo``) to use this type. +""" +from __future__ import annotations + +from data_analysis_agent.tools.connectors.base import BaseConnector, DatasetConnectionError +from data_analysis_agent.tools.mcp.server import DEFAULT_MAX_ROWS, build_server, new_connection, register_dataframe_view + +_SAMPLE_LIMIT = 2000 # documents loaded per collection for the query path (BETA) + + +class MongoDBConnector(BaseConnector): + """Serves a `mongodb` database; introspects + loads collections via pymongo.""" + + def _client(self): + try: + import pymongo + except ImportError: + raise DatasetConnectionError("MongoDB support requires 'pymongo' (pip install pymongo).") + return pymongo.MongoClient(self._uri.raw(), serverSelectionTimeoutMS=5000) + + def _db(self, client): + from pymongo.uri_parser import parse_uri + name = parse_uri(self._uri.raw()).get("database") + if not name: + raise DatasetConnectionError("MongoDB URI must include a database name (mongodb://host/db).") + return client[name] + + def connection_check(self) -> None: + """Connect + ``ping``; raise a sanitized error on failure.""" + try: + client = self._client() + try: + client.admin.command("ping") + finally: + client.close() + except DatasetConnectionError: + raise + except Exception as exc: + raise DatasetConnectionError(f"Could not connect to {self._uri.display()}: {exc}") + + def discover_tables(self) -> list[dict]: + """List collections and infer columns from a sampled document.""" + try: + client = self._client() + try: + db = self._db(client) + tables: list[dict] = [] + for coll in db.list_collection_names(): + doc = db[coll].find_one() or {} + cols = [k for k in doc.keys() if k != "_id"] + tables.append({ + "table_name": coll, + "column_names": cols, + "schema": [{"name": k, "dtype": type(doc[k]).__name__, "nullable": True} for k in cols], + "row_count": db[coll].estimated_document_count(), + }) + return tables + finally: + client.close() + except DatasetConnectionError: + raise + except Exception as exc: + raise DatasetConnectionError(f"Could not introspect {self._uri.display()}: {exc}") + + def build_server(self, table_names: list[str], max_rows: int = DEFAULT_MAX_ROWS): + """Load each **given** collection (capped) into a DuckDB-registered DataFrame (no introspect).""" + import pandas as pd + client = self._client() + conn = new_connection() + try: + db = self._db(client) + for name in table_names: + docs = list(db[name].find(limit=_SAMPLE_LIMIT)) + for d in docs: + d.pop("_id", None) + df = pd.json_normalize(docs) if docs else pd.DataFrame() + register_dataframe_view(conn, name, df) + return build_server(self._server.get("name") or "database", conn, + [{"table_name": n} for n in table_names], max_rows) + finally: + client.close() diff --git a/src/data_analysis_agent/tools/connectors/parquet.py b/src/data_analysis_agent/tools/connectors/parquet.py new file mode 100644 index 00000000..4d9eb40e --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/parquet.py @@ -0,0 +1,95 @@ +"""Internal Parquet database connector: a directory of Parquet files, one view (table) per file. + +The connector owns its physical-table inspection — it scans `{datasets_dir}/{slug(name)}/*.parquet` +live. The app stores no table catalog. +""" +from __future__ import annotations + +from pathlib import Path + +import duckdb +import pyarrow.parquet as pq +import structlog + +from data_analysis_agent.tools.connectors.base import BaseConnector, DatasetConnectionError +from data_analysis_agent.tools.mcp.server import ( + DEFAULT_MAX_ROWS, + build_server, + new_connection, + register_parquet_view, +) + +log = structlog.get_logger() + + +class ParquetConnector(BaseConnector): + """Serves a `parquet` database: a directory of Parquet files keyed by the database name.""" + + def _directory(self) -> Path: + """The on-disk directory holding this database's Parquet files (`{datasets_dir}/{slug(name)}`).""" + from data_analysis_agent.config.settings import get_settings + from data_analysis_agent.tools.table_naming import sql_table_name + return Path(get_settings().datasets_dir) / sql_table_name(self._server.get("name") or "") + + def connection_check(self) -> None: + """Validate the directory is accessible and any present Parquet files are readable. + + A parquet database with **zero tables is valid** (e.g. just created, nothing uploaded yet), so a + missing directory passes. + """ + directory = self._directory() + if not directory.exists(): + return # empty database — no tables uploaded yet + try: + tables = self.discover_tables() + except Exception as exc: + raise DatasetConnectionError(f"Could not read the database directory: {exc}") + for table in tables: + path = table.get("parquet_path") + try: + conn = duckdb.connect(database=":memory:") + conn.execute(f"SELECT * FROM read_parquet('{(path or '').replace(chr(39), chr(39) * 2)}') LIMIT 0") + conn.close() + except duckdb.Error as exc: + raise DatasetConnectionError( + f"Dataset file unreadable for table '{table.get('table_name')}': {exc}" + ) + + def discover_tables(self) -> list[dict]: + """Scan the directory and return one table dict per Parquet file (empty if none).""" + directory = self._directory() + if not directory.exists(): + return [] + tables: list[dict] = [] + for path in sorted(directory.glob("*.parquet")): + pf = pq.ParquetFile(str(path)) + schema = pf.schema_arrow + tables.append({ + "table_name": path.stem, + "parquet_path": str(path.resolve()), + "column_names": list(schema.names), + "schema": [{"name": f.name, "dtype": str(f.type), "nullable": f.nullable} for f in schema], + "row_count": pf.metadata.num_rows, + }) + return tables + + def build_server(self, table_names: list[str], max_rows: int = DEFAULT_MAX_ROWS): + """Register one view per named Parquet file (path derived from the name) and build the server. + + No directory scan — the table set comes from the caller (resources/sync). A name whose file is + gone (out-of-band deletion) is skipped so one stale row can't break the whole server. + """ + directory = self._directory() + conn = new_connection() + registered: list[dict] = [] + for name in table_names: + try: + register_parquet_view(conn, name, str(directory / f"{name}.parquet")) + registered.append({"table_name": name}) + except FileNotFoundError as exc: + log.warning("parquet.view_missing", table=name, error=str(exc)) + return build_server(self._server.get("name") or "database", conn, registered, max_rows) + + def drop_table(self, table_name: str) -> None: + """Delete a table's Parquet file from the directory (best-effort).""" + (self._directory() / f"{table_name}.parquet").unlink(missing_ok=True) diff --git a/src/data_analysis_agent/tools/connectors/postgres.py b/src/data_analysis_agent/tools/connectors/postgres.py new file mode 100644 index 00000000..6e6a7133 --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/postgres.py @@ -0,0 +1,151 @@ +"""External PostgreSQL dataset connector (BETA, flag-gated). + +Two independent paths: +- connection_check / discover_tables via **psycopg2** (a real connect + ``SELECT 1`` + an + ``information_schema`` introspection), each wrapped in a hard wall-clock timeout because + ``psycopg2``'s own ``connect_timeout`` does not cover every stall. +- the query path via DuckDB ``ATTACH … (TYPE postgres, READ_ONLY)`` + one view per table, so the + SELECT-only guard, row cap, and within-dataset JOINs are shared with parquet datasets. + +The raw URI (with the password) is read only here, at connect time. Every error surfaced to the +caller is sanitized through ``DatasetURI.display()`` so credentials never leak. +""" +from __future__ import annotations + +import concurrent.futures +from urllib.parse import urlsplit + +from data_analysis_agent.tools.connectors.base import BaseConnector, DatasetConnectionError +from data_analysis_agent.tools.mcp.server import DEFAULT_MAX_ROWS, build_server, new_connection + +_CONNECT_TIMEOUT_SECONDS = 8 # hard wall-clock cap around the whole connect/introspect + + +class PostgresConnector(BaseConnector): + """Serves an external `postgresql` database; introspects its tables live via psycopg2.""" + + def connection_check(self) -> None: + """Connect + ``SELECT 1`` within a hard timeout; raise a sanitized error on any failure.""" + def probe() -> None: + import psycopg2 + conn = psycopg2.connect(self._uri.raw(), connect_timeout=5) + try: + cur = conn.cursor() + cur.execute("SELECT 1") + cur.fetchone() + finally: + conn.close() + + self._with_timeout(probe, "connect to") + + def discover_tables(self) -> list[dict]: + """Introspect ``information_schema`` for base tables in the ``public`` schema.""" + def introspect() -> list[dict]: + import psycopg2 + conn = psycopg2.connect(self._uri.raw(), connect_timeout=5) + try: + cur = conn.cursor() + cur.execute( + "SELECT table_name FROM information_schema.tables " + "WHERE table_schema='public' AND table_type='BASE TABLE' ORDER BY table_name" + ) + names = [r[0] for r in cur.fetchall()] + tables: list[dict] = [] + for name in names: + cur.execute( + "SELECT column_name, data_type, is_nullable FROM information_schema.columns " + "WHERE table_schema='public' AND table_name=%s ORDER BY ordinal_position", + (name,), + ) + cols = cur.fetchall() + tables.append({ + "table_name": name, + "column_names": [c[0] for c in cols], + "schema": [{"name": c[0], "dtype": c[1], "nullable": c[2] == "YES"} for c in cols], + "row_count": None, + }) + return tables + finally: + conn.close() + + return self._with_timeout(introspect, "introspect") + + def discover_relationships(self) -> list[dict]: + """Foreign keys from ``information_schema`` in the canonical FK-edge format (``[]`` on failure).""" + def introspect() -> list[dict]: + import psycopg2 + conn = psycopg2.connect(self._uri.raw(), connect_timeout=5) + try: + cur = conn.cursor() + cur.execute( + "SELECT tc.table_name, kcu.column_name, ccu.table_name, ccu.column_name " + "FROM information_schema.table_constraints tc " + "JOIN information_schema.key_column_usage kcu " + " ON tc.constraint_name = kcu.constraint_name AND tc.table_schema = kcu.table_schema " + "JOIN information_schema.constraint_column_usage ccu " + " ON ccu.constraint_name = tc.constraint_name AND ccu.table_schema = tc.table_schema " + "WHERE tc.constraint_type = 'FOREIGN KEY' AND tc.table_schema = 'public'" + ) + return [{"from_table": r[0], "from_column": r[1], "to_table": r[2], "to_column": r[3]} + for r in cur.fetchall()] + finally: + conn.close() + + try: + return self._with_timeout(introspect, "introspect") + except DatasetConnectionError: + return [] + + def build_server(self, table_names: list[str], max_rows: int = DEFAULT_MAX_ROWS): + """ATTACH the database read-only in DuckDB and expose one view per **given** table (no introspect).""" + import duckdb + + conn = new_connection() + try: + conn.execute("INSTALL postgres") + conn.execute("LOAD postgres") + dsn = self._libpq_dsn().replace("'", "''") + conn.execute(f"ATTACH '{dsn}' AS pgdb (TYPE postgres, READ_ONLY)") + for name in table_names: + safe = name.replace('"', '""') + conn.execute(f'CREATE VIEW "{safe}" AS SELECT * FROM pgdb.public."{safe}"') + except duckdb.Error as exc: + conn.close() + raise DatasetConnectionError(f"Could not attach {self._uri.display()}: {self._sanitize(exc)}") + return build_server(self._server.get("name") or "database", conn, + [{"table_name": n} for n in table_names], max_rows) + + # ---- helpers --------------------------------------------------------- + + def _with_timeout(self, fn, verb: str): + try: + with concurrent.futures.ThreadPoolExecutor(max_workers=1) as ex: + return ex.submit(fn).result(timeout=_CONNECT_TIMEOUT_SECONDS) + except concurrent.futures.TimeoutError: + raise DatasetConnectionError(f"Timed out trying to {verb} {self._uri.display()}.") + except Exception as exc: + raise DatasetConnectionError(f"Could not {verb} {self._uri.display()}: {self._sanitize(exc)}") + + def _libpq_dsn(self) -> str: + """Build a libpq conninfo string from the URI (raw password used only here).""" + p = urlsplit(self._uri.raw()) + parts = [] + if p.hostname: + parts.append(f"host={p.hostname}") + if p.port: + parts.append(f"port={p.port}") + if p.path.lstrip("/"): + parts.append(f"dbname={p.path.lstrip('/')}") + if p.username: + parts.append(f"user={p.username}") + if p.password: + parts.append(f"password={p.password}") + return " ".join(parts) + + def _sanitize(self, exc: Exception) -> str: + """Scrub the raw URI + password out of a driver error message.""" + msg = str(exc).replace(self._uri.raw(), self._uri.display()) + password = urlsplit(self._uri.raw()).password + if password: + msg = msg.replace(password, "***") + return msg diff --git a/src/data_analysis_agent/tools/connectors/snowflake.py b/src/data_analysis_agent/tools/connectors/snowflake.py new file mode 100644 index 00000000..61179af0 --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/snowflake.py @@ -0,0 +1,102 @@ +"""Snowflake database connector (BETA). + +Introspects via ``information_schema`` and, for querying, **loads** each table (capped) into a +DuckDB-registered DataFrame (DuckDB has no native Snowflake scanner). ``snowflake-connector-python`` is +imported lazily — install it (``pip install snowflake-connector-python``) to use this type. The raw URI +(with the password) is read only here, at connect time; errors are credential-sanitized. +""" +from __future__ import annotations + +from urllib.parse import parse_qs, urlsplit + +from data_analysis_agent.tools.connectors.base import BaseConnector, DatasetConnectionError +from data_analysis_agent.tools.mcp.server import DEFAULT_MAX_ROWS, build_server, new_connection, register_dataframe_view + +_LOAD_LIMIT = 2000 # rows loaded per table for the query path (BETA) + + +class SnowflakeConnector(BaseConnector): + """Serves a `snowflake` database. URI: ``snowflake://user:pw@account/DB/SCHEMA?warehouse=WH``.""" + + def _connect(self): + try: + import snowflake.connector as sf + except ImportError: + raise DatasetConnectionError( + "Snowflake support requires 'snowflake-connector-python' (pip install snowflake-connector-python)." + ) + p = urlsplit(self._uri.raw()) + params = parse_qs(p.query) + path = [x for x in (p.path or "").split("/") if x] + try: + return sf.connect( + account=p.hostname, user=p.username, password=p.password, + database=path[0] if path else None, + schema=path[1] if len(path) > 1 else None, + warehouse=(params.get("warehouse") or [None])[0], + login_timeout=8, network_timeout=8, + ) + except DatasetConnectionError: + raise + except Exception as exc: + raise DatasetConnectionError(f"Could not connect to {self._uri.display()}: {self._sanitize(exc)}") + + def connection_check(self) -> None: + """Connect + ``SELECT 1``; raise a sanitized error on failure.""" + conn = self._connect() + try: + cur = conn.cursor() + cur.execute("SELECT 1") + cur.fetchone() + finally: + conn.close() + + def discover_tables(self) -> list[dict]: + """Introspect ``information_schema`` for tables/columns in the current schema.""" + conn = self._connect() + try: + cur = conn.cursor() + cur.execute("SELECT table_name FROM information_schema.tables " + "WHERE table_schema = CURRENT_SCHEMA() ORDER BY table_name") + names = [r[0] for r in cur.fetchall()] + tables: list[dict] = [] + for name in names: + cur.execute("SELECT column_name, data_type, is_nullable FROM information_schema.columns " + "WHERE table_name = %s AND table_schema = CURRENT_SCHEMA() ORDER BY ordinal_position", + (name,)) + cols = cur.fetchall() + tables.append({ + "table_name": name, + "column_names": [c[0] for c in cols], + "schema": [{"name": c[0], "dtype": c[1], "nullable": c[2] == "YES"} for c in cols], + "row_count": None, + }) + return tables + finally: + conn.close() + + def build_server(self, table_names: list[str], max_rows: int = DEFAULT_MAX_ROWS): + """Load each **given** table (capped) into a DuckDB-registered DataFrame (no introspect).""" + import pandas as pd + conn = self._connect() + duck = new_connection() + try: + cur = conn.cursor() + for name in table_names: + cur.execute(f'SELECT * FROM "{name}" LIMIT {_LOAD_LIMIT}') + if hasattr(cur, "fetch_pandas_all"): + df = cur.fetch_pandas_all() + else: + df = pd.DataFrame(cur.fetchall(), columns=[d[0] for d in cur.description]) + register_dataframe_view(duck, name, df) + return build_server(self._server.get("name") or "database", duck, + [{"table_name": n} for n in table_names], max_rows) + finally: + conn.close() + + def _sanitize(self, exc: Exception) -> str: + msg = str(exc).replace(self._uri.raw(), self._uri.display()) + password = urlsplit(self._uri.raw()).password + if password: + msg = msg.replace(password, "***") + return msg diff --git a/src/data_analysis_agent/tools/connectors/sqlite.py b/src/data_analysis_agent/tools/connectors/sqlite.py new file mode 100644 index 00000000..c3029296 --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/sqlite.py @@ -0,0 +1,99 @@ +"""SQLite database connector: a single ``.db`` file addressed by a ``sqlite:///path`` URI. + +Introspection uses the stdlib ``sqlite3``; the query path uses DuckDB's ``sqlite_scanner`` (``ATTACH … +(TYPE sqlite)`` + one view per table), so the SELECT-only guard, row cap, and within-database JOINs are +shared with the other connectors. We never drop the user's tables. +""" +from __future__ import annotations + +import sqlite3 + +from data_analysis_agent.tools.connectors.base import BaseConnector, DatasetConnectionError +from data_analysis_agent.tools.mcp.server import DEFAULT_MAX_ROWS, build_server, new_connection + + +class SQLiteConnector(BaseConnector): + """Serves a `sqlite` database (a ``.db`` file); inspects it live via ``sqlite3``.""" + + def __init__(self, server: dict) -> None: + super().__init__(server) + self._path = self._file_path(server.get("uri") or "") + + @staticmethod + def _file_path(uri: str) -> str: + from sqlalchemy.engine import make_url + try: + return make_url(uri).database or "" + except Exception: + return uri.replace("sqlite://", "", 1).lstrip("/") + + def connection_check(self) -> None: + """Open the file and run ``SELECT 1``; raise a sanitized error on failure.""" + try: + conn = sqlite3.connect(self._path) + conn.execute("SELECT 1") + conn.close() + except Exception as exc: + raise DatasetConnectionError(f"Could not open SQLite database {self._uri.display()}: {exc}") + + def discover_tables(self) -> list[dict]: + """Introspect ``sqlite_master`` + ``PRAGMA table_info`` for user tables (empty on failure).""" + try: + conn = sqlite3.connect(self._path) + try: + names = [r[0] for r in conn.execute( + "SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%' " + "ORDER BY name")] + tables: list[dict] = [] + for name in names: + cols = conn.execute(f'PRAGMA table_info("{name}")').fetchall() # (cid,name,type,notnull,dflt,pk) + row_count = conn.execute(f'SELECT COUNT(*) FROM "{name}"').fetchone()[0] + tables.append({ + "table_name": name, + "column_names": [c[1] for c in cols], + "schema": [{"name": c[1], "dtype": c[2] or "", "nullable": c[3] == 0} for c in cols], + "row_count": row_count, + }) + return tables + finally: + conn.close() + except Exception as exc: + raise DatasetConnectionError(f"Could not introspect {self._uri.display()}: {exc}") + + def discover_relationships(self) -> list[dict]: + """Declared foreign keys (``PRAGMA foreign_key_list``) in the canonical FK-edge format.""" + rels: list[dict] = [] + try: + conn = sqlite3.connect(self._path) + try: + names = [r[0] for r in conn.execute( + "SELECT name FROM sqlite_master WHERE type='table' AND name NOT LIKE 'sqlite_%'")] + for name in names: + for fk in conn.execute(f'PRAGMA foreign_key_list("{name}")').fetchall(): + # (id, seq, table, from, to, on_update, on_delete, match) + rels.append({"from_table": name, "from_column": fk[3], + "to_table": fk[2], "to_column": fk[4]}) + finally: + conn.close() + except Exception: + return [] + return rels + + def build_server(self, table_names: list[str], max_rows: int = DEFAULT_MAX_ROWS): + """ATTACH the SQLite file in DuckDB and expose one read-only view per **given** table (no introspect).""" + import duckdb + + conn = new_connection() + try: + conn.execute("INSTALL sqlite") + conn.execute("LOAD sqlite") + safe_path = self._path.replace("'", "''") + conn.execute(f"ATTACH '{safe_path}' AS sqlitedb (TYPE sqlite, READ_ONLY)") + for name in table_names: + safe = name.replace('"', '""') + conn.execute(f'CREATE VIEW "{safe}" AS SELECT * FROM sqlitedb."{safe}"') + except duckdb.Error as exc: + conn.close() + raise DatasetConnectionError(f"Could not open {self._uri.display()}: {exc}") + return build_server(self._server.get("name") or "database", conn, + [{"table_name": n} for n in table_names], max_rows) diff --git a/src/data_analysis_agent/tools/connectors/uri.py b/src/data_analysis_agent/tools/connectors/uri.py new file mode 100644 index 00000000..e83e127e --- /dev/null +++ b/src/data_analysis_agent/tools/connectors/uri.py @@ -0,0 +1,67 @@ +"""Dataset URI value object. + +Parses a dataset URI and, crucially, exposes a ``display()`` that strips credentials. EVERY log +line, stored ``connection_error``, template field, and surfaced exception must use ``display()`` — +the raw URI (with any password) is read only at connect time inside a connector. + +Forms: +- internal: ``parquet:///{name}`` (scheme ``parquet``, empty authority, path = URL-encoded name) +- external: ``{type}://{user}:{pass}@{host}:{port}/{db}`` (e.g. ``postgresql://u:p@h:5432/sales``) +""" +from __future__ import annotations + +from urllib.parse import unquote, urlsplit + + +class DatasetURI: + """Credential-aware parse of a dataset URI; ``display()`` never reveals the password.""" + + def __init__(self, raw: str) -> None: + self._raw = raw or "" + self._parts = urlsplit(self._raw) + + @property + def scheme(self) -> str: + return self._parts.scheme + + @property + def host(self) -> str | None: + return self._parts.hostname + + @property + def port(self) -> int | None: + return self._parts.port + + @property + def username(self) -> str | None: + return self._parts.username + + @property + def has_password(self) -> bool: + return self._parts.password is not None + + @property + def is_internal(self) -> bool: + """True for the internal ``parquet`` scheme (no host, no credentials).""" + return self._parts.scheme == "parquet" + + @property + def database(self) -> str: + """The database / logical name (URL-decoded path segment).""" + return unquote(self._parts.path.lstrip("/")) + + def raw(self) -> str: + """The raw URI INCLUDING any credentials — use only inside a connector at connect time.""" + return self._raw + + def display(self) -> str: + """A credential-free rendering safe for logs, templates, errors, and storage.""" + parts = self._parts + if not parts.hostname and not parts.username: # internal parquet:///name + return f"{parts.scheme}:///{parts.path.lstrip('/')}" + host = parts.hostname or "" + port = f":{parts.port}" if parts.port else "" + return f"{parts.scheme}://{host}{port}{parts.path}" + + def __str__(self) -> str: # never leak credentials via str() + return self.display() diff --git a/src/data_analysis_agent/tools/ingester.py b/src/data_analysis_agent/tools/ingester.py new file mode 100644 index 00000000..05822362 --- /dev/null +++ b/src/data_analysis_agent/tools/ingester.py @@ -0,0 +1,94 @@ +from __future__ import annotations + +import io +import json +from dataclasses import dataclass +from pathlib import Path +from typing import BinaryIO + +import pandas as pd + + +@dataclass +class IngestResult: + parquet_path: str + column_names: list[str] + schema_json: str # JSON: [{"name": str, "dtype": str, "nullable": bool}] + row_count: int + file_size_bytes: int + + +class FileIngester: + """ + Converts an uploaded data file to Parquet and extracts schema metadata. + + Supported source formats: .csv (future: .xlsx, .xls, .json) + + Single public method: + ingest(source_path, dest_dir, stem) -> IngestResult + + The Parquet file is written to dest_dir/.parquet using Snappy + compression. `stem` should be the DataSource UUID to guarantee + filename uniqueness while remaining cross-referenceable to the DB. + """ + + _READERS: dict[str, object] = { + ".csv": lambda p: pd.read_csv(p), + ".xlsx": lambda p: pd.read_excel(p), + ".xls": lambda p: pd.read_excel(p), + ".json": lambda p: pd.read_json(p), + } + + def ingest_stream( + self, stream: BinaryIO, suffix: str, dest_dir: Path, stem: str + ) -> IngestResult: + """ + Read from an upload stream (no temp file written), convert to Parquet. + `suffix` must include the leading dot, e.g. '.csv'. + `stem` should be the DataSource UUID. + """ + reader = self._READERS.get(suffix.lower()) + if reader is None: + supported = ", ".join(self._READERS) + raise ValueError( + f"Unsupported file type {suffix!r}. Supported: {supported}" + ) + + raw = io.BytesIO(stream.read()) + df: pd.DataFrame = reader(raw) + return self._write_parquet(df, dest_dir, stem) + + def ingest(self, source_path: str, dest_dir: Path, stem: str) -> IngestResult: + """Read from an existing file on disk and convert to Parquet.""" + suffix = Path(source_path).suffix.lower() + reader = self._READERS.get(suffix) + if reader is None: + supported = ", ".join(self._READERS) + raise ValueError( + f"Unsupported file type {suffix!r}. Supported: {supported}" + ) + df: pd.DataFrame = reader(source_path) + return self._write_parquet(df, dest_dir, stem) + + def _write_parquet(self, df: pd.DataFrame, dest_dir: Path, stem: str) -> IngestResult: + """Write a DataFrame to ``dest_dir/.parquet`` and return its metadata.""" + dest_dir.mkdir(parents=True, exist_ok=True) + parquet_path = dest_dir / f"{stem}.parquet" + df.to_parquet(str(parquet_path), index=False, engine="pyarrow", compression="snappy") + + schema = [ + { + "name": col, + "dtype": str(df[col].dtype), + "nullable": bool(df[col].isna().any()), + } + for col in df.columns + ] + + return IngestResult( + parquet_path=str(parquet_path), + column_names=list(df.columns), + schema_json=json.dumps(schema), + row_count=len(df), + file_size_bytes=parquet_path.stat().st_size, + ) diff --git a/src/data_analysis_agent/tools/mcp/__init__.py b/src/data_analysis_agent/tools/mcp/__init__.py new file mode 100644 index 00000000..7c8b8589 --- /dev/null +++ b/src/data_analysis_agent/tools/mcp/__init__.py @@ -0,0 +1,2 @@ +"""MCP tool layer: per-source in-process MCP servers (``server.py``) and the +session-scoped client pool (``pool.py``). The only place the ``mcp`` SDK is imported.""" diff --git a/src/data_analysis_agent/tools/mcp/dispatch.py b/src/data_analysis_agent/tools/mcp/dispatch.py new file mode 100644 index 00000000..279db5a4 --- /dev/null +++ b/src/data_analysis_agent/tools/mcp/dispatch.py @@ -0,0 +1,329 @@ +"""DB-backed MCP JSON-RPC 2.0 dispatcher for ``POST /database/{id}``. + +Answers the MCP read surface (tools/list+call, resources/list+read, prompts/list+get) directly from +the database's stored capability rows — it does NOT use FastMCP (which cannot represent custom +inputSchema / resources / prompts). Canned tools execute via the shared DuckDB read-only path with +parameter binding, over views built from the **resources table** (no store inspection). This is a +different surface from the agent's session pool (``tools/mcp/pool.py``). + +It also serves the write surface (``MUTATION_METHODS``): ``tools|prompts|resources`` ``add``/``update`` +(LLM-driven additive cascade) and ``delete`` (manual hard-delete + pruning cascade) — each in one +transaction (``_mutate``/``_delete`` roll back on any failure); the route bumps the version once and +refreshes pools post-commit. +""" +from __future__ import annotations + +import base64 +import json +from datetime import datetime + +import structlog +from sqlalchemy import and_, or_ +from sqlalchemy.orm import Session + +import data_analysis_agent.tools.sync as sync +from data_analysis_agent.config.settings import get_settings +from data_analysis_agent.db.models import ( + McpPromptRow, + McpResourceRow, + DatabaseRow, + McpToolRow, +) +from data_analysis_agent.tools.connectors.base import DatasetConnectionError, get_connector +from data_analysis_agent.tools.mcp.server import RecoverableQueryError, _run_select_params, bind_params + +log = structlog.get_logger() + +METHOD_NOT_FOUND = -32601 +INVALID_PARAMS = -32602 + +# Non-standard write methods (the route invalidates pools after these succeed). add/update apply an +# LLM-driven additive cascade; delete is a MANUAL hard-delete + an LLM-driven pruning cascade. +MUTATION_METHODS = frozenset({ + "tools/add", "tools/update", "tools/delete", + "prompts/add", "prompts/update", "prompts/delete", + "resources/add", "resources/update", "resources/delete", +}) + + +def handle_jsonrpc(db: Session, server: DatabaseRow, payload: dict) -> dict: + """Route a JSON-RPC request over a server's stored capabilities; return a JSON-RPC response.""" + req_id = payload.get("id") if isinstance(payload, dict) else None + method = payload.get("method") if isinstance(payload, dict) else None + params = payload.get("params") or {} + try: + handler = _METHODS.get(method) + if handler is None: + return _error(req_id, METHOD_NOT_FOUND, f"Unknown method: {method!r}") + return _result(req_id, handler(db, server, params)) + except _RpcError as exc: + return _error(req_id, exc.code, exc.message) + except Exception as exc: # never leak a stack trace as a 500 + log.error("mcp_dispatch.error", method=method, error=str(exc)) + return _error(req_id, INVALID_PARAMS, str(exc)) + + +# --- methods ---------------------------------------------------------------- + +def _tools_list(db, server, params): + rows, cursor = _page(db, McpToolRow, server.id, params) + tools = [] + for r in rows: + tool = {"name": r.name, "description": r.description, "inputSchema": r.input_schema} + if r.title: + tool["title"] = r.title + if r.output_schema is not None: + tool["outputSchema"] = r.output_schema + if r.annotations is not None: + tool["annotations"] = r.annotations + # `_meta` (MCP's reserved extension key) carries the executor spec the management UI edits; + # protocol clients ignore it. inputSchema stays the public, derived view of the parameters. + tool["_meta"] = {"execution": r.execution} + tools.append(tool) + return _with_cursor({"tools": tools}, cursor) + + +def _tools_call(db, server, params): + name = params.get("name") + arguments = params.get("arguments") or {} + row = _active_one(db, McpToolRow, server.id, McpToolRow.name == name) + if row is None: + raise _RpcError(INVALID_PARAMS, f"Unknown tool: {name!r}") + try: + table_names = [t["table_name"] for t in sync.active_entity_tables(db, server.id)] + text = _execute_canned(server, row, arguments, table_names) + return {"content": [{"type": "text", "text": text}], "isError": False} + except (RecoverableQueryError, DatasetConnectionError, Exception) as exc: + return {"content": [{"type": "text", "text": f"Tool error: {exc}"}], "isError": True} + + +def _resources_list(db, server, params): + rows, cursor = _page(db, McpResourceRow, server.id, params) + resources = [] + for r in rows: + res = {"uri": r.uri, "name": r.name} + if r.title: + res["title"] = r.title + if r.description: + res["description"] = r.description + if r.mime_type: + res["mimeType"] = r.mime_type + # `_meta`: entity-kind + size + relationship/column content the UI needs (kind drives the + # primary↔secondary toggle and schema-vs-entity edit branch; content backs the schema editor). + res["_meta"] = {"kind": r.kind, "size": r.size, "content": r.content} + resources.append(res) + return _with_cursor({"resources": resources}, cursor) + + +def _resources_read(db, server, params): + uri = params.get("uri") + row = _active_one(db, McpResourceRow, server.id, McpResourceRow.uri == uri) + if row is None: + raise _RpcError(INVALID_PARAMS, f"Unknown resource: {uri!r}") + content = row.content # schema resource stores its relationships/FKs in content (source of truth) + text = json.dumps(content) if content is not None else (row.description or "") + return {"contents": [{"uri": row.uri, "mimeType": row.mime_type or "application/json", "text": text}]} + + +def _prompts_list(db, server, params): + rows, cursor = _page(db, McpPromptRow, server.id, params) + prompts = [] + for r in rows: + p = {"name": r.name, "arguments": r.arguments} + if r.title: + p["title"] = r.title + if r.description: + p["description"] = r.description + # `_meta`: the message template the UI edits (prompts/get returns it too, but inlining here + # lets the Edit modal open without a second round-trip). + p["_meta"] = {"template": r.template} + prompts.append(p) + return _with_cursor({"prompts": prompts}, cursor) + + +def _prompts_get(db, server, params): + name = params.get("name") + row = _active_one(db, McpPromptRow, server.id, McpPromptRow.name == name) + if row is None: + raise _RpcError(INVALID_PARAMS, f"Unknown prompt: {name!r}") + return {"description": row.description or "", "messages": row.template or []} + + +# --- mutation methods (Phase B) --------------------------------------------- + +def _need_name(definition): + if not definition.get("name"): + raise _RpcError(INVALID_PARAMS, "definition.name is required.") + + +def _need_uri(definition): + if not definition.get("uri"): + raise _RpcError(INVALID_PARAMS, "definition.uri is required.") + + +def _mutate(db, server, params, op_fn, need_key): + """Apply a client-supplied capability + its additive cascade; roll back on ANY failure.""" + definition = params.get("definition") + if not isinstance(definition, dict): + raise _RpcError(INVALID_PARAMS, "params.definition (an object) is required.") + need_key(definition) + try: + result = op_fn(db, server, definition) + except sync.ValidationError as exc: + db.rollback() + raise _RpcError(INVALID_PARAMS, str(exc)) + except _RpcError: + db.rollback() + raise + except Exception as exc: # IntegrityError, etc. — never half-commit a mutation + db.rollback() + raise _RpcError(INVALID_PARAMS, str(exc)) + return { + "ok": True, + "version": server.version, + "applied": {"child": result.child, "op": result.op, "key": result.key}, + "cascade": {"tools": result.tools_changed, "prompts": result.prompts_changed}, + "status": result.status, + } + + +def _tools_add(db, server, params): return _mutate(db, server, params, sync.add_tool, _need_name) +def _tools_update(db, server, params): return _mutate(db, server, params, sync.update_tool, _need_name) +def _prompts_add(db, server, params): return _mutate(db, server, params, sync.add_prompt, _need_name) +def _prompts_update(db, server, params): return _mutate(db, server, params, sync.update_prompt, _need_name) +def _resources_add(db, server, params): return _mutate(db, server, params, sync.add_resource, _need_uri) +def _resources_update(db, server, params): return _mutate(db, server, params, sync.update_resource, _need_uri) + + +def _delete(db, server, params, op_fn, key_name): + """Manually hard-delete a capability by key, then run its pruning cascade; roll back on failure.""" + key = params.get(key_name) + if not key: + raise _RpcError(INVALID_PARAMS, f"params.{key_name} is required.") + try: + result = op_fn(db, server, key) + except sync.ValidationError as exc: + db.rollback() + raise _RpcError(INVALID_PARAMS, str(exc)) + except _RpcError: + db.rollback() + raise + except Exception as exc: + db.rollback() + raise _RpcError(INVALID_PARAMS, str(exc)) + return { + "ok": True, + "version": server.version, + "applied": {"child": result.child, "op": result.op, "key": result.key}, + "cascade": {"tools": result.tools_changed, "prompts": result.prompts_changed}, + "status": result.status, + } + + +def _tools_delete(db, server, params): return _delete(db, server, params, sync.delete_tool, "name") +def _prompts_delete(db, server, params): return _delete(db, server, params, sync.delete_prompt, "name") +def _resources_delete(db, server, params): return _delete(db, server, params, sync.delete_resource, "uri") + + +_METHODS = { + "tools/list": _tools_list, + "tools/call": _tools_call, + "resources/list": _resources_list, + "resources/read": _resources_read, + "prompts/list": _prompts_list, + "prompts/get": _prompts_get, + "tools/add": _tools_add, + "tools/update": _tools_update, + "tools/delete": _tools_delete, + "prompts/add": _prompts_add, + "prompts/update": _prompts_update, + "prompts/delete": _prompts_delete, + "resources/add": _resources_add, + "resources/update": _resources_update, + "resources/delete": _resources_delete, +} + + +# --- canned-query execution ------------------------------------------------- + +def _execute_canned(server: DatabaseRow, tool: McpToolRow, arguments: dict, table_names: list[str]) -> str: + """Run a tool's ``sql_template`` with bound parameters over the database's (resource-derived) tables.""" + fast = get_connector(_server_dict(server)).build_server(table_names) + conn = getattr(fast, "_duckdb_conn", None) + try: + params = bind_params(tool.input_schema, arguments) + max_rows = get_settings().mcp_max_result_rows + return _run_select_params(conn, tool.sql_template, params, max_rows) + finally: + if conn is not None: + conn.close() + + +def _server_dict(server: DatabaseRow) -> dict: + return {"id": server.id, "name": server.name, "type": server.type, "uri": server.uri} + + +# --- pagination (opaque keyset cursor) -------------------------------------- + +def _page(db, model, database_id, params): + """Return ``(rows, next_cursor)`` for an active-row listing, keyset-paginated.""" + page_size = get_settings().mcp_list_page_size + q = db.query(model).filter(model.database_id == database_id, model.deleted_at.is_(None)) + cursor = _decode_cursor(params.get("cursor")) + if cursor is not None: + c_created, c_id = cursor + q = q.filter(or_(model.created_at > c_created, + and_(model.created_at == c_created, model.id > c_id))) + rows = q.order_by(model.created_at, model.id).limit(page_size + 1).all() + next_cursor = None + if len(rows) > page_size: + rows = rows[:page_size] + next_cursor = _encode_cursor(rows[-1].created_at, rows[-1].id) + return rows, next_cursor + + +def _encode_cursor(created_at: datetime, row_id: str) -> str: + raw = f"{created_at.isoformat()}|{row_id}".encode() + return base64.urlsafe_b64encode(raw).decode() + + +def _decode_cursor(cursor: str | None): + if not cursor: + return None + try: + raw = base64.urlsafe_b64decode(cursor.encode()).decode() + created, row_id = raw.split("|", 1) + return datetime.fromisoformat(created), row_id + except Exception: + raise _RpcError(INVALID_PARAMS, "Invalid cursor.") + + +def _with_cursor(result: dict, next_cursor: str | None) -> dict: + if next_cursor: + result["nextCursor"] = next_cursor + return result + + +def _active_one(db, model, database_id, predicate): + return ( + db.query(model) + .filter(model.database_id == database_id, model.deleted_at.is_(None), predicate) + .first() + ) + + +# --- JSON-RPC envelope ------------------------------------------------------ + +class _RpcError(Exception): + def __init__(self, code: int, message: str) -> None: + super().__init__(message) + self.code = code + self.message = message + + +def _result(req_id, result: dict) -> dict: + return {"jsonrpc": "2.0", "id": req_id, "result": result} + + +def _error(req_id, code: int, message: str) -> dict: + return {"jsonrpc": "2.0", "id": req_id, "error": {"code": code, "message": message}} diff --git a/src/data_analysis_agent/tools/mcp/pool.py b/src/data_analysis_agent/tools/mcp/pool.py new file mode 100644 index 00000000..a606f565 --- /dev/null +++ b/src/data_analysis_agent/tools/mcp/pool.py @@ -0,0 +1,352 @@ +"""Session-scoped pool of in-process MCP servers — the agent's MCP client layer. + +A **session** owns one pool: one in-process MCP server **per attached database**, each exposing a +generic read-only ``query`` tool over that database's tables (read from the **resources table** — the +pool never inspects the underlying store; that happens only in sync). Built lazily on the session's +first query and reused. This is the ONLY module that imports ``mcp.shared.memory`` (the in-memory +transport). + +Concurrency (see spec/product/07-agent-graph.md): +- LangGraph runs each node in its own asyncio task, so MCP ``ClientSession``s are **transient** + (opened/closed within a single call). The pool holds only plain objects across nodes/queries: + the built ``FastMCP`` servers and their DuckDB connections. +- A session's DuckDB connections are not concurrency-safe, so queries on one session are serialized + by a per-session ``threading.Lock`` (held by ``run_pipeline`` for the whole query). ``close()`` + acquires that lock before teardown so a server change never closes a connection mid-query. +- Pools are idle/LRU-evicted; eviction skips sessions whose lock is currently held (in use). +""" +from __future__ import annotations + +import threading +import time +from dataclasses import dataclass +from importlib.metadata import version + +import structlog +from mcp.server.fastmcp import FastMCP +from mcp.shared.memory import create_connected_server_and_client_session + +from data_analysis_agent.config.settings import get_settings +from data_analysis_agent.db.models import DatabaseRow, McpToolRow, SessionDatabaseRow +from data_analysis_agent.db.session import create_db_session +from data_analysis_agent.tools.connectors.base import get_connector +from data_analysis_agent.tools.mcp.server import RecoverableQueryError, _run_select_params, bind_params +from data_analysis_agent.tools.sync import active_entity_tables + +log = structlog.get_logger() + +# Relies on the in-memory transport helper, which exists in mcp 1.x and is removed in 2.x. +_MCP_VERSION = version("mcp") +if not _MCP_VERSION.startswith("1."): + raise RuntimeError( + f"mcp {_MCP_VERSION} is installed but this code targets the 1.x in-memory transport. " + f"Pin mcp==1.28.0." + ) + +_GENERIC_TOOL = "query" + + +class NoServersError(Exception): + """Raised when a session has no attached MCP servers to build a pool from.""" + + +@dataclass +class _GenTool: + """A server's generated GET-API tool, executed directly on the shared DuckDB connection.""" + + name: str + description: str + input_schema: dict + sql_template: str + + +@dataclass +class _Server: + """One attached database and its in-process FastMCP server (generic SQL tool over resource tables).""" + + name: str + server: FastMCP + description: str + tables: list[dict] # [{"table": str, "columns": list[str]}] + gen_tools: dict[str, _GenTool] # name -> generated GET-API tool (active rows only) + + +@dataclass +class SessionPool: + """A session's MCP servers, addressed single-level by server ``name`` (+ optional capability).""" + + session_id: str + servers: dict[str, _Server] + last_used: float + + def snapshot(self) -> list[dict]: + """Flat, agent-facing tool list for the planning prompt (one entry per server).""" + return [ + { + "tool": s.name, + "description": s.description, + "tables": s.tables, + "capabilities": [ + {"name": g.name, "description": g.description, + "params": list(((g.input_schema or {}).get("properties") or {}).keys())} + for g in s.gen_tools.values() + ], + } + for s in self.servers.values() + ] + + async def call_tool(self, tool: str, arguments: dict, capability: str | None = None) -> tuple[str, bool]: + """Route a call to a generated GET-API tool (when ``capability`` is given) or generic SQL.""" + s = self.servers.get(tool) + if s is None: + valid = ", ".join(self.servers) or "(none)" + return f"Unknown tool '{tool}'. Valid tools: {valid}.", True + if capability: + return self._call_gen_tool(s, capability, arguments) + async with create_connected_server_and_client_session(s.server) as session: + result = await session.call_tool(_GENERIC_TOOL, arguments) + text = result.content[0].text if result.content else "" + return text, bool(result.isError) + + def _call_gen_tool(self, s: "_Server", capability: str, arguments: dict) -> tuple[str, bool]: + """Execute a generated tool's SQL with bound params on the server's DuckDB conn (read-only guard).""" + g = s.gen_tools.get(capability) + if g is None: + valid = ", ".join(s.gen_tools) or "(none)" + return (f"Unknown capability '{capability}' on '{s.name}'. Valid: {valid}. " + f"Omit 'capability' to run free SQL."), True + conn = getattr(s.server, "_duckdb_conn", None) + if conn is None: + return f"Server '{s.name}' has no connection.", True + params = bind_params(g.input_schema, arguments) + try: + text = _run_select_params(conn, g.sql_template, params, get_settings().mcp_max_result_rows) + return text, False + except RecoverableQueryError as exc: + return f"Tool error: {exc}", True + + def aclose(self) -> None: + """Close every server's DuckDB connection (plain, task-safe).""" + for s in self.servers.values(): + conn = getattr(s.server, "_duckdb_conn", None) + if conn is not None: + try: + conn.close() + except Exception: + pass + + +class SessionPoolManager: + """Builds, caches, serializes, and evicts one MCP pool per session.""" + + def __init__(self, max_pools: int, idle_seconds: float) -> None: + self._pools: dict[str, SessionPool] = {} + self._locks: dict[str, threading.Lock] = {} + self._registry = threading.Lock() # guards _pools and _locks + self._max_pools = max_pools + self._idle_seconds = idle_seconds + + def session_lock(self, session_id: str) -> threading.Lock: + """Return the per-session lock (created on first use).""" + with self._registry: + lock = self._locks.get(session_id) + if lock is None: + lock = self._locks[session_id] = threading.Lock() + return lock + + async def acquire(self, session_id: str) -> SessionPool: + """Return the session's pool, building it lazily on first use. + + Call while holding ``session_lock(session_id)``. Raises :class:`NoServersError` + if the session has no attached servers. + """ + with self._registry: + pool = self._pools.get(session_id) + if pool is not None: + pool.last_used = time.monotonic() + return pool + + pool = await self._build(session_id) # async (list_tools) — outside the registry lock + + with self._registry: + existing = self._pools.get(session_id) + if existing is not None: # built concurrently — keep the first + pool.aclose() + existing.last_used = time.monotonic() + return existing + self._pools[session_id] = pool + self._evict_locked() + log.info("session_pool.built", session_id=session_id, servers=len(pool.servers), + active_pools=len(self._pools)) + return pool + + def snapshot(self, session_id: str) -> list[dict]: + """Return the flat server/tool list for ``plan_action`` (empty if not built).""" + with self._registry: + pool = self._pools.get(session_id) + if pool is None: + return [] + pool.last_used = time.monotonic() + return pool.snapshot() + + async def call_tool(self, session_id: str, tool: str, arguments: dict, + capability: str | None = None) -> tuple[str, bool]: + """Route a tool call to the session's pool (must be acquired first).""" + with self._registry: + pool = self._pools.get(session_id) + if pool is not None: + pool.last_used = time.monotonic() + if pool is None: + return f"No MCP pool for session '{session_id}'.", True + return await pool.call_tool(tool, arguments, capability) + + def close(self, session_id: str) -> None: + """Close a session's pool, waiting for any in-flight query first. Idempotent. + + Acquires the per-session lock before teardown so a server change (sync/delete) never closes + a DuckDB connection mid-query on the pipeline thread. + """ + lock = self.session_lock(session_id) + with lock: + with self._registry: + pool = self._pools.pop(session_id, None) + if pool is not None: + pool.aclose() + log.info("session_pool.closed", session_id=session_id) + + def close_all(self) -> None: + """Close every pool (on app shutdown).""" + with self._registry: + pools = list(self._pools.values()) + self._pools.clear() + for pool in pools: + pool.aclose() + + def close_sessions_for_database(self, database_id: str) -> None: + """Close the pools of every session attached to a given server (after a change).""" + with create_db_session() as db: + links = ( + db.query(SessionDatabaseRow) + .filter(SessionDatabaseRow.database_id == database_id) + .all() + ) + session_ids = [link.session_id for link in links] + for sid in session_ids: + self.close(sid) + + # ---- internals ------------------------------------------------------- + + async def _build(self, session_id: str) -> SessionPool: + loaded = _load_databases(session_id) + if not loaded: + raise NoServersError("No databases attached to this session") + max_rows = get_settings().mcp_max_result_rows + servers: dict[str, _Server] = {} + for server_dict, tables, gen_tools in loaded: + # ``tables`` come from the resources table — the pool NEVER inspects the store (sync-only). + fast = get_connector(server_dict).build_server([t["table_name"] for t in tables], max_rows) + await _verify_server(fast) + servers[server_dict["name"]] = _Server( + name=server_dict["name"], + server=fast, + description=server_dict.get("description") or "", + tables=[{"table": t["table_name"], "columns": t.get("column_names") or []} for t in tables], + gen_tools={ + g["name"]: _GenTool(g["name"], g["description"], g["input_schema"], g["sql_template"]) + for g in gen_tools + }, + ) + return SessionPool(session_id, servers, time.monotonic()) + + def _evict_locked(self) -> None: + """Evict idle + over-cap pools, skipping in-use (locked) sessions. Holds ``_registry``.""" + now = time.monotonic() + for sid, pool in list(self._pools.items()): + if now - pool.last_used > self._idle_seconds: + self._try_close_locked(sid) + while len(self._pools) > self._max_pools: + sid = min(self._pools, key=lambda s: self._pools[s].last_used) + if not self._try_close_locked(sid): + break + + def _try_close_locked(self, sid: str) -> bool: + """Close a pool iff its session is not currently in use. Holds ``_registry``.""" + lock = self._locks.get(sid) + if lock is not None and not lock.acquire(blocking=False): + return False + try: + pool = self._pools.pop(sid, None) + if pool is not None: + pool.aclose() + log.info("session_pool.evicted", session_id=sid) + return True + finally: + if lock is not None: + lock.release() + + +async def _verify_server(server: FastMCP) -> None: + """Open a transient session once to confirm the server exposes the generic ``query`` tool.""" + async with create_connected_server_and_client_session(server) as session: + listed = await session.list_tools() + names = {t.name for t in listed.tools} + if _GENERIC_TOOL not in names: + raise RuntimeError(f"MCP server is missing the '{_GENERIC_TOOL}' tool (has: {sorted(names)})") + + +def _load_databases(session_id: str) -> list[tuple[dict, list[dict], list[dict]]]: + """Load a session's attached databases + their tables (**from resources**) + active generated tools. + + Tables come from the resources table (``active_entity_tables``) — the pool never inspects the store. + """ + with create_db_session() as db: + links = ( + db.query(SessionDatabaseRow) + .filter(SessionDatabaseRow.session_id == session_id) + .all() + ) + loaded: list[tuple[dict, list[dict], list[dict]]] = [] + for link in links: + srv = db.get(DatabaseRow, link.database_id) + if srv is None: + continue + loaded.append((_serialize_database(srv), active_entity_tables(db, srv.id), + _load_gen_tools(db, srv.id))) + return loaded + + +def _load_gen_tools(db, database_id: str) -> list[dict]: + """Active generated GET-API tools for a server, projected to plain dicts (no detached ORM rows).""" + rows = ( + db.query(McpToolRow) + .filter(McpToolRow.database_id == database_id, McpToolRow.deleted_at.is_(None)) + .order_by(McpToolRow.created_at, McpToolRow.id) + .all() + ) + return [ + {"name": r.name, "description": r.description or "", + "input_schema": r.input_schema, "sql_template": r.sql_template} + for r in rows + ] + + +def _serialize_database(srv: DatabaseRow) -> dict: + return { + "id": srv.id, + "name": srv.name, + "type": srv.type, + "uri": srv.uri, + "description": srv.description or srv.title or "", + } + + +_manager: SessionPoolManager | None = None + + +def get_manager() -> SessionPoolManager: + """Return the process-wide :class:`SessionPoolManager` singleton.""" + global _manager + if _manager is None: + s = get_settings() + _manager = SessionPoolManager(s.max_session_pools, s.session_pool_idle_seconds) + return _manager diff --git a/src/data_analysis_agent/tools/mcp/server.py b/src/data_analysis_agent/tools/mcp/server.py new file mode 100644 index 00000000..7d5b81b2 --- /dev/null +++ b/src/data_analysis_agent/tools/mcp/server.py @@ -0,0 +1,172 @@ +from __future__ import annotations + +import re +from pathlib import Path + +import duckdb +from mcp.server.fastmcp import FastMCP + +DEFAULT_MAX_ROWS = 200 + +# Statement types that must never run via the read-only query path (R-SQLi). A query that starts +# with SELECT/WITH and contains no statement separator cannot BE one of these, but we reject the +# keywords defensively. (Common column names are not in this set, so no false positives.) +_FORBIDDEN = ("ATTACH", "DETACH", "COPY", "PRAGMA", "INSTALL", "LOAD", "EXPORT", "IMPORT") +_WORD = re.compile(r"[A-Za-z_]+") + +# DuckDB filesystem table functions read ARBITRARY files inside an ordinary SELECT (e.g. +# `SELECT * FROM read_text('/etc/passwd')`) — they use none of the forbidden KEYWORDS, so they must +# be blocked by name. Legitimate queries reference the dataset's registered VIEWS by name; only the +# view definitions (built by us) use read_parquet, never the user/agent/tool SQL. This guard is the +# single chokepoint for every read path (agent free-SQL, generated tools, and write-time validation). +_FORBIDDEN_FUNCS = frozenset({ + "read_text", "read_blob", "read_csv", "read_csv_auto", "read_parquet", "parquet_scan", + "read_json", "read_json_auto", "read_json_objects", "read_ndjson", "read_ndjson_auto", + "read_ndjson_objects", "glob", "sniff_csv", "read_xlsx", "read_csvgz", +}) +_FUNC_CALL = re.compile(r"\b([a-z_][a-z0-9_]*)\s*\(") + + +class RecoverableQueryError(ValueError): + """A query problem the LLM can fix by retrying. + + FastMCP turns any exception raised inside a tool into a ``CallToolResult`` with + ``isError=True``, so raising this is how a recoverable error (bad SQL, non-SELECT) + is surfaced to the agent for self-correction. + """ + + +def _guard_select(query: str) -> str: + """Validate a read-only single-statement SELECT/WITH; return the trimmed SQL or raise.""" + q = query.strip().rstrip(";").strip() + if not q: + raise RecoverableQueryError("Empty query.") + if ";" in q: + raise RecoverableQueryError("Only a single statement is allowed (no ';').") + upper = q.upper() + if not (upper.startswith("SELECT") or upper.startswith("WITH")): + raise RecoverableQueryError(f"Only SELECT statements are allowed. Got: {query[:80]}") + bad = sorted(set(_WORD.findall(upper)) & set(_FORBIDDEN)) + if bad: + raise RecoverableQueryError(f"Disallowed keyword(s): {', '.join(bad)}. Read-only SELECT only.") + bad_funcs = sorted({f for f in _FUNC_CALL.findall(q.lower())} & _FORBIDDEN_FUNCS) + if bad_funcs: + raise RecoverableQueryError( + f"Disallowed function(s): {', '.join(bad_funcs)}. Query the dataset's tables by name only." + ) + return q + + +def _to_csv(cursor, max_rows: int) -> str: + """Render a DuckDB cursor as a compact CSV string, capped at ``max_rows``.""" + columns = [d[0] for d in cursor.description] if cursor.description else [] + rows = cursor.fetchmany(max_rows) + lines = [",".join(columns)] + lines += [",".join("" if v is None else str(v) for v in row) for row in rows] + return "\n".join(lines) + + +def _run_select(conn: duckdb.DuckDBPyConnection, query: str, max_rows: int) -> str: + """Validate and run a SELECT, returning a compact CSV string (``max_rows`` cap).""" + sql = _guard_select(query) + try: + cursor = conn.execute(sql) + except duckdb.Error as exc: + raise RecoverableQueryError(str(exc)) + return _to_csv(cursor, max_rows) + + +def bind_params(input_schema: dict | None, arguments: dict) -> dict | None: + """Filter call arguments to a tool's declared params (named ``$param`` in its SQL). + + Returns ``None`` when the tool declares no params (so ``execute`` runs without binding). Shared by + the JSON-RPC dispatcher and the agent pool so both bind identically. + """ + props = (input_schema or {}).get("properties") or {} + if not props: + return None + return {k: arguments.get(k) for k in props} + + +def _run_select_params( + conn: duckdb.DuckDBPyConnection, query: str, params: dict | list | None, max_rows: int +) -> str: + """Validate and run a parameter-bound SELECT (canned tools); params bind via DuckDB, never f-strings.""" + sql = _guard_select(query) + try: + cursor = conn.execute(sql, params) if params else conn.execute(sql) + except duckdb.Error as exc: + raise RecoverableQueryError(str(exc)) + return _to_csv(cursor, max_rows) + + +# --- Per-server (multi-table) DuckDB-backed MCP server ---------------------- +# A connector opens ONE DuckDB connection with all of the server's tables as views, then calls +# build_server to expose a single generic `query` tool. All tables share the connection, so a +# query may JOIN the server's other tables. (The generated GET-API tools live in the DB and are +# served by tools/mcp/dispatch.py, NOT here.) + +def new_connection() -> duckdb.DuckDBPyConnection: + """Return a fresh in-memory DuckDB connection (the caller registers views / ATTACHes).""" + return duckdb.connect(database=":memory:") + + +def register_parquet_view(conn: duckdb.DuckDBPyConnection, table_name: str, parquet_path: str | None) -> None: + """Register a Parquet file as a read-only view named ``table_name`` on ``conn``.""" + if not parquet_path or not Path(parquet_path).exists(): + raise FileNotFoundError(f"Parquet file not found for table {table_name!r}: {parquet_path!r}") + safe_path = parquet_path.replace("'", "''") + safe_table = table_name.replace('"', '""') + conn.execute(f'CREATE VIEW "{safe_table}" AS SELECT * FROM read_parquet(\'{safe_path}\')') + + +def register_dataframe_view(conn: duckdb.DuckDBPyConnection, table_name: str, df) -> None: + """Register a pandas DataFrame as a queryable table named ``table_name`` on ``conn``. + + Used by connectors that have no native DuckDB scanner (e.g. MongoDB, Snowflake): they load the + rows into DataFrames and register them so the generic read-only query path works unchanged. + """ + conn.register(table_name, df) + + +def build_server( + server_name: str, + conn: duckdb.DuckDBPyConnection, + tables: list[dict], + max_rows: int = DEFAULT_MAX_ROWS, +) -> FastMCP: + """Build one in-process MCP server exposing a generic read-only ``query`` tool over ``conn``. + + Args: + server_name: The MCP-server (agent tool) name — used as the server label. + conn: A DuckDB connection where every table is already a view (parquet views or ATTACH). + tables: Dicts with ``table_name`` (and optional ``column_names``). + max_rows: Row cap per query. + + Returns: + A :class:`FastMCP` server with the connection attached as ``server._duckdb_conn``. + """ + server = FastMCP(f"database::{server_name}") + table_names = [t["table_name"] for t in tables] + server.add_tool( + _make_query(conn, max_rows), + name="query", + description=_generic_tool_description(table_names), + ) + server._duckdb_conn = conn # type: ignore[attr-defined] + server._table_names = table_names # type: ignore[attr-defined] + return server + + +def _make_query(conn: duckdb.DuckDBPyConnection, max_rows: int): + """Return a ``query(query: str) -> str`` tool fn bound to a server's DuckDB connection.""" + def query(query: str) -> str: + """Run a read-only SQL SELECT against this server's tables and return CSV rows.""" + return _run_select(conn, query, max_rows) + return query + + +def _generic_tool_description(table_names: list[str]) -> str: + """Describe the generic query tool, naming the JOINable tables.""" + tables = ", ".join(table_names) or "(none)" + return f"Run a read-only SQL SELECT over this server's tables ({tables}); you may JOIN them." diff --git a/src/data_analysis_agent/tools/sync/__init__.py b/src/data_analysis_agent/tools/sync/__init__.py new file mode 100644 index 00000000..6f722009 --- /dev/null +++ b/src/data_analysis_agent/tools/sync/__init__.py @@ -0,0 +1,31 @@ +"""LLM-driven MCP capability generation (the 5-stage sync pipeline) + granular mutations. + +- Full sync: ``run_sync`` + ``apply_sync_result`` (regenerate all, soft-delete dropped). +- Granular Phase-B mutations: ``add_tool``/``update_tool``/``add_prompt``/``update_prompt``/ + ``add_resource``/``update_resource`` (apply one capability + additive downstream cascade). +""" +from data_analysis_agent.tools.sync.pipeline import ( + PartialResult, + SyncResult, + ValidationError, + active_entity_tables, + add_prompt, + add_resource, + add_tool, + apply_sync_result, + delete_prompt, + delete_resource, + delete_tool, + run_sync, + update_prompt, + update_resource, + update_tool, +) + +__all__ = [ + "SyncResult", "PartialResult", "ValidationError", + "run_sync", "apply_sync_result", "active_entity_tables", + "add_tool", "update_tool", "delete_tool", + "add_prompt", "update_prompt", "delete_prompt", + "add_resource", "update_resource", "delete_resource", +] diff --git a/src/data_analysis_agent/tools/sync/pipeline.py b/src/data_analysis_agent/tools/sync/pipeline.py new file mode 100644 index 00000000..096ac2ec --- /dev/null +++ b/src/data_analysis_agent/tools/sync/pipeline.py @@ -0,0 +1,723 @@ +"""Sync orchestration. + +- Full sync (`run_sync` + `apply_sync_result`): regenerate all 5 stages and **soft-delete** dropped + capabilities (the only pruning operation). +- Partial sync (`apply_partial` + the six `add_*`/`update_*` ops): apply ONE client-supplied capability, + then run an **ADDITIVE** cascade of the downstream stages — insert/update only, never soft-delete a + sibling. One transaction, one version bump. +""" +from __future__ import annotations + +import json +import re +from dataclasses import dataclass +from datetime import datetime, timezone +from pathlib import Path + +import structlog +from sqlalchemy.orm import Session + +from data_analysis_agent.db.models import ( + McpPromptRow, + McpResourceRow, + DatabaseRow, + McpToolRow, +) +from data_analysis_agent.tools.connectors.base import get_connector +from data_analysis_agent.tools.mcp.server import ( + RecoverableQueryError, + _guard_select, + _run_select_params, +) +from data_analysis_agent.tools.sync import stages + +log = structlog.get_logger() + +_PARAM = re.compile(r"\$(\w+)") + + +def _now() -> datetime: + return datetime.now(timezone.utc) + + +def _server_dict(server: DatabaseRow) -> dict: + return {"id": server.id, "name": server.name, "type": server.type, "uri": server.uri} + + +def _connector(server: DatabaseRow): + """The database's connector — inspects tables (sync) and builds the query server over named tables.""" + return get_connector(_server_dict(server)) + + +def _discover_relationships(connector) -> list[dict]: + """Foreign-key relationships from inspection, when the connector exposes them (else ``[]``).""" + try: + return connector.discover_relationships() or [] + except Exception: + return [] + + +def _entities_from_inspection(database_name: str, tables: list[dict], llm_entities: list[dict]) -> list[dict]: + """Build one entity per **inspected** table (definite); take only title/description from the LLM. + + The set of entities is the connector's inspected tables — the LLM never invents or drops one. The + LLM's per-table title/description is used as backfill, with a deterministic default otherwise. + """ + by_name = {e.get("name"): e for e in (llm_entities or [])} + entities: list[dict] = [] + for t in tables: + tname = t["table_name"] + e = by_name.get(tname) or {} + entities.append({ + "name": tname, + "title": e.get("title") or tname.replace("_", " ").title(), + "description": e.get("description") or f"The '{tname}' entity.", + "kind": e.get("kind") or "primary_entity", + "uri": f"entity://{database_name}/{tname}", + "mime_type": "application/json", + }) + return entities + + +class ValidationError(Exception): + """A client-supplied capability definition is invalid (surfaced as JSON-RPC -32602).""" + + +@dataclass +class SyncResult: + """The capabilities a full sync run proposes for a server.""" + + title: str + description: str + dataset_schema: dict + resources: list[dict] + tools: list[dict] + prompts: list[dict] + status: str # "ok" | "partial" + + +@dataclass +class CascadeFlags: + """Which downstream stages a mutation must regenerate (additively), in dependency order.""" + + tools: bool = False + prompts: bool = False + + +@dataclass +class PartialResult: + """Outcome of a single granular mutation + its additive cascade.""" + + child: str + op: str + key: str + tools_changed: bool + prompts_changed: bool + status: str + + +# --- Full sync (run + apply) ------------------------------------------------ + +def run_sync(db: Session, server: DatabaseRow) -> SyncResult: + """Run the 5 LLM stages over the database's tables + existing capabilities. Never raises. + + Physical tables are **inspected live via the connector** (no stored catalog) — the connector knows + the database type and how to introspect it. + """ + name = server.name + connector = _connector(server) + tables = connector.discover_tables() # the ONLY inspection of the underlying store (sync only) + active = _active(db, server.id) + + td = stages.stage_title(name, tables, {"title": server.title, "description": server.description}) + # Entities are DEFINITE — exactly the inspected tables. The LLM only backfills title/description. + entities = _entities_from_inspection( + name, tables, stages.stage_entities(name, tables, _meta(active["resources"], "uri", "name"))) + # Relationships come from inspection when the connector exposes FKs; otherwise the LLM backfills them. + conn_rels = _discover_relationships(connector) + schema = ({"relationships": conn_rels} if conn_rels + else stages.stage_schema(name, tables, _active_schema_content(active["resources"]))) + tools = stages.stage_tools(name, entities, tables, _meta(active["tools"], "name")) + prompts = stages.stage_prompts(name, tools, _meta(active["prompts"], "name")) + + tools, dropped = _validate_tools(server, connector, [t["table_name"] for t in tables], tools) + tables_by_name = {t["table_name"]: t for t in tables} + resources = [_schema_resource(name, schema)] + [ + _entity_resource(name, e, tables_by_name) for e in entities + ] + status = "partial" if dropped else "ok" + log.info("sync.run", server=name, tools=len(tools), resources=len(resources), prompts=len(prompts), + status=status) + return SyncResult(td["title"], td["description"], schema, resources, tools, prompts, status) + + +def apply_sync_result(db: Session, server: DatabaseRow, result: SyncResult) -> None: + """Apply a full :class:`SyncResult`: insert/update/soft-delete children + bump version once.""" + new_version = (server.version or 1) + 1 + _apply_all(db, server, new_version, result) + server.version = new_version + server.title = result.title + server.description = result.description + server.last_synced_at = _now() + server.last_sync_status = result.status + + +def _apply_all(db: Session, server: DatabaseRow, new_version: int, result: SyncResult) -> None: + """Diff-apply all three child types at ``new_version`` (delete-absent = full-sync semantics).""" + active = _active(db, server.id) + _apply(db, server.id, new_version, result.tools, active["tools"], "name", _tool_fields) + _apply(db, server.id, new_version, result.resources, active["resources"], "uri", _resource_fields) + _apply(db, server.id, new_version, result.prompts, active["prompts"], "name", _prompt_fields) + + +# --- Partial sync (granular mutation + additive cascade) -------------------- + +_CHILD = { + "tool": (McpToolRow, "name"), + "resource": (McpResourceRow, "uri"), + "prompt": (McpPromptRow, "name"), +} +_SETTERS = {} # populated after the field setters are defined (see bottom) + + +def add_tool(db, server, definition): + return apply_partial(db, server, child="tool", op="add", definition=definition, + cascade=CascadeFlags(prompts=True)) + + +def update_tool(db, server, definition): + return apply_partial(db, server, child="tool", op="update", definition=definition, + cascade=CascadeFlags(prompts=True)) + + +def add_prompt(db, server, definition): + return apply_partial(db, server, child="prompt", op="add", definition=definition, + cascade=CascadeFlags()) + + +def update_prompt(db, server, definition): + return apply_partial(db, server, child="prompt", op="update", definition=definition, + cascade=CascadeFlags()) + + +def add_resource(db, server, definition): + return apply_partial(db, server, child="resource", op="add", definition=definition, + cascade=CascadeFlags(tools=True, prompts=True)) + + +def update_resource(db, server, definition): + """Update a resource. The schema (entity-relationship) resource edits relationships/FKs (cascades); + an entity resource edits **title + description + kind** (cosmetic, no cascade). ``kind`` may be + flipped between ``primary_entity`` and ``secondary_entity`` only — never to/from ``schema``.""" + uri = definition.get("uri") + existing = _active_one(db, McpResourceRow, server.id, "uri", uri) if uri else None + if existing is None: + raise ValidationError(f"unknown resource '{uri}'") + if existing.kind == "schema": + return _update_schema_resource(db, server, existing, definition) + safe = {"uri": uri} + if "title" in definition: + safe["title"] = definition["title"] + if "description" in definition: + safe["description"] = definition["description"] + if "kind" in definition: + kind = definition["kind"] + if kind not in ("primary_entity", "secondary_entity"): + raise ValidationError("entity kind must be 'primary_entity' or 'secondary_entity'") + safe["kind"] = kind + return apply_partial(db, server, child="resource", op="update", definition=safe, cascade=CascadeFlags()) + + +# --- Hard delete (manual; not LLM-driven) + LLM-driven prune cascade -------- + +def delete_tool(db, server, name): + """Hard-delete a tool, then regenerate prompts (prune) so orphaned prompts drop out.""" + return _delete_child(db, server, child="tool", key_val=name, cascade=CascadeFlags(prompts=True)) + + +def delete_prompt(db, server, name): + """Hard-delete a prompt (a leaf — no cascade).""" + return _delete_child(db, server, child="prompt", key_val=name, cascade=CascadeFlags()) + + +def delete_resource(db, server, uri): + """Hard-delete an entity resource: drop its backing table, clean the entity-relationship schema, + then regenerate tools + prompts (prune). The schema resource itself cannot be deleted.""" + new_version = (server.version or 1) + 1 + row = _active_one(db, McpResourceRow, server.id, "uri", uri) + if row is None: + raise ValidationError(f"unknown resource '{uri}'") + if row.kind == "schema": + raise ValidationError("the entity-relationship (schema) resource cannot be deleted") + table_name = (row.content or {}).get("table") or row.name + db.delete(row) # hard delete the entity resource (manual action) + db.flush() + _drop_table(server, table_name) # remove backing parquet table + catalog entry + _remove_table_from_schema(db, server, table_name) # clean relationships referencing it + tools_changed, dropped = _cascade_tools(db, server, new_version, prune=True) + prompts_changed = _cascade_prompts(db, server, new_version, prune=True) + server.version = new_version + server.last_synced_at = _now() + server.last_sync_status = "partial" if dropped else "ok" + log.info("sync.delete_resource", server=server.name, uri=uri, table=table_name, version=new_version) + return PartialResult("resource", "delete", uri, tools_changed, prompts_changed, server.last_sync_status) + + +def _delete_child(db: Session, server: DatabaseRow, *, child: str, key_val: str, + cascade: CascadeFlags) -> PartialResult: + """Hard-delete one tool/prompt by key, then run a pruning cascade of dependents (one version bump).""" + model, key = _CHILD[child] + row = _active_one(db, model, server.id, key, key_val) + if row is None: + raise ValidationError(f"unknown {child} '{key_val}'") + new_version = (server.version or 1) + 1 + db.delete(row) # hard delete (manual action — not a reversible LLM suggestion) + db.flush() + tools_changed = prompts_changed = False + status = "ok" + if cascade.tools: + tools_changed, dropped = _cascade_tools(db, server, new_version, prune=True) + if dropped: + status = "partial" + if cascade.prompts: + prompts_changed = _cascade_prompts(db, server, new_version, prune=True) + server.version = new_version + server.last_synced_at = _now() + server.last_sync_status = status + log.info("sync.delete", server=server.name, child=child, key=key_val, version=new_version) + return PartialResult(child, "delete", key_val, tools_changed, prompts_changed, status) + + +def _update_schema_resource(db: Session, server: DatabaseRow, existing, definition: dict) -> PartialResult: + """Manually edit the entity-relationship schema (relationships/FKs, title/description), then cascade. + + The schema lives on this resource's ``content`` (the source of truth) — there is no entity column. + """ + new_version = (server.version or 1) + 1 + src = definition.get("content") if isinstance(definition.get("content"), dict) else definition + content = _schema_content({"relationships": src.get("relationships") or []}) + if "title" in definition: + existing.title = definition["title"] + if "description" in definition: + existing.description = definition["description"] + existing.content = content + existing.size = len(json.dumps(content).encode()) + db.flush() + tools_changed, dropped = _cascade_tools(db, server, new_version, prune=False) + prompts_changed = _cascade_prompts(db, server, new_version, prune=False) + server.version = new_version + server.last_synced_at = _now() + server.last_sync_status = "partial" if dropped else "ok" + log.info("sync.update_schema", server=server.name, version=new_version) + return PartialResult("resource", "update", existing.uri, tools_changed, prompts_changed, + server.last_sync_status) + + +def _drop_table(server: DatabaseRow, table_name: str) -> None: + """Drop a table from the underlying database via its connector (parquet: file; external: no-op).""" + try: + _connector(server).drop_table(table_name) + except Exception as exc: + log.warning("sync.drop_table.failed", table=table_name, error=str(exc)) + + +def _remove_table_from_schema(db: Session, server: DatabaseRow, table_name: str) -> None: + """Drop any relationships/FKs referencing ``table_name`` from the schema resource's content.""" + schema_row = ( + db.query(McpResourceRow) + .filter(McpResourceRow.database_id == server.id, McpResourceRow.deleted_at.is_(None), + McpResourceRow.kind == "schema") + .first() + ) + if schema_row is None: + return + rels = [r for r in (schema_row.content or {}).get("relationships", []) + if table_name not in (r.get("from_table"), r.get("to_table"))] + content = {"relationships": rels} + schema_row.content = content + schema_row.size = len(json.dumps(content).encode()) + + +def apply_partial(db: Session, server: DatabaseRow, *, child: str, op: str, + definition: dict, cascade: CascadeFlags) -> PartialResult: + """Apply ONE explicit mutation + its additive cascade at one new version, in the caller's txn.""" + new_version = (server.version or 1) + 1 + key_val = _apply_one(db, server, new_version, child, op, definition) + tools_changed = prompts_changed = False + status = "ok" + if cascade.tools: + tools_changed, dropped = _cascade_tools(db, server, new_version) + if dropped: + status = "partial" + if cascade.prompts: + prompts_changed = _cascade_prompts(db, server, new_version) + server.version = new_version + server.last_synced_at = _now() + server.last_sync_status = status + log.info("sync.partial", server=server.name, child=child, op=op, key=key_val, version=new_version, + status=status) + return PartialResult(child, op, key_val, tools_changed, prompts_changed, status) + + +def _apply_one(db: Session, server: DatabaseRow, new_version: int, child: str, op: str, + definition: dict) -> str: + """Insert-or-update exactly ONE child row at ``new_version``. Validates before mutating.""" + if child not in _CHILD: + raise ValidationError(f"unknown capability type: {child!r}") + model, key = _CHILD[child] + set_fields = _SETTERS[child] + key_val = definition.get(key) + if not key_val: + raise ValidationError(f"missing '{key}'") + existing = _active_one(db, model, server.id, key, key_val) + if op == "add": + if existing is not None: + raise ValidationError(f"{child} '{key_val}' already exists; use {child}s/update") + if child == "resource" and definition.get("kind") == "schema": + raise ValidationError("the 'schema' resource is managed by sync and cannot be added") + effective = definition + if child == "tool": + _validate_tool_definition(db, server, effective) + row = model() + row.database_id = server.id + row.created_version = new_version + set_fields(row, effective) + db.add(row) + elif op == "update": + if existing is None: + raise ValidationError(f"unknown {child} '{key_val}'") + if child == "resource" and existing.kind == "schema": + raise ValidationError("the 'schema' resource is managed by sync and cannot be edited") + # PATCH semantics: keep fields the client didn't supply (don't reset to defaults). + effective = {**_row_to_def(child, existing), **definition} + if child == "tool": + _validate_tool_definition(db, server, effective) + set_fields(existing, effective) + else: + raise ValidationError(f"unknown op: {op!r}") + db.flush() + return key_val + + +def _row_to_def(child: str, row) -> dict: + """Project a capability row back to its stage-shaped definition (for patch-merge on update).""" + if child == "tool": + return {"name": row.name, "title": row.title, "description": row.description, + "execution": row.execution, "output_schema": row.output_schema, + "annotations": row.annotations} + if child == "resource": + return {"uri": row.uri, "name": row.name, "title": row.title, "description": row.description, + "mime_type": row.mime_type, "kind": row.kind, "content": row.content, "size": row.size} + return {"name": row.name, "title": row.title, "description": row.description, + "arguments": row.arguments, "template": row.template} + + +def _cascade_tools(db: Session, server: DatabaseRow, new_version: int, prune: bool = False) -> tuple[bool, bool]: + """Regenerate tools from current active entities + physical tables. + + ``prune=False`` (add/update): additive — insert/update only. ``prune=True`` (delete): also + soft-delete tools no longer proposed (an LLM-driven regen, so reversible soft-delete). + """ + active = _active(db, server.id) + entities = [{"name": r.name, "kind": r.kind} for r in active["resources"] + if r.kind in ("primary_entity", "secondary_entity")] + tables = active_entity_tables(db, server.id) # from resources — cascades never re-inspect the store + proposed = stages.stage_tools(server.name, entities, tables, _meta(active["tools"], "name")) + proposed, dropped = _validate_tools(server, _connector(server), [t["table_name"] for t in tables], proposed) + _apply(db, server.id, new_version, proposed, active["tools"], "name", _tool_fields, delete_absent=prune) + db.flush() + return bool(proposed), dropped + + +def _cascade_prompts(db: Session, server: DatabaseRow, new_version: int, prune: bool = False) -> bool: + """Regenerate prompts from current active tools (``prune`` soft-deletes orphaned prompts on delete).""" + active = _active(db, server.id) + proposed = stages.stage_prompts(server.name, _meta(active["tools"], "name"), + _meta(active["prompts"], "name")) + _apply(db, server.id, new_version, proposed, active["prompts"], "name", _prompt_fields, + delete_absent=prune) + db.flush() + return bool(proposed) + + +def _validate_tool_definition(db: Session, server: DatabaseRow, definition: dict) -> None: + """Reject a non-SELECT / multi-statement / forbidden / undeclared-param tool at write time. + + Validates the canonical ``execution`` object: the ``sql_template`` (with ``$param`` embeddings) and + the ``parameters`` declaring each embedding. Every ``$param`` must be declared in ``parameters``. + The compile-check builds views over the database's resource-table tables (no re-inspection). + """ + execution = normalize_execution(definition) + sql = (execution.get("sql_template") or "").strip() + if not sql: + raise ValidationError("tool execution.sql_template is required") + try: + _guard_select(sql) + except RecoverableQueryError as exc: + raise ValidationError(f"sql_template rejected: {exc}") + used = set(_PARAM.findall(sql)) + declared = {p.get("name") for p in (execution.get("parameters") or []) if p.get("name")} + missing = used - declared + if missing: + raise ValidationError( + f"sql_template uses param(s) not declared in execution.parameters: {', '.join(sorted(missing))}") + if not used and (server.type or "parquet") == "parquet": + table_names = [t["table_name"] for t in active_entity_tables(db, server.id)] + conn = getattr(_connector(server).build_server(table_names), "_duckdb_conn", None) + try: + _run_select_params(conn, f"SELECT * FROM ({sql}) AS _v LIMIT 0", None, 0) + except Exception as exc: + raise ValidationError(f"sql_template does not compile: {exc}") + finally: + if conn is not None: + conn.close() + + +# --- Generic diff/merge apply ----------------------------------------------- + +def _apply(db, database_id, new_version, proposed, active_rows, key, set_fields, delete_absent=True): + """Insert new / update matched. If ``delete_absent`` (full sync), soft-delete rows not proposed.""" + by_key = {getattr(r, key): r for r in active_rows} + seen: set[str] = set() + for item in proposed: + k = item.get(key) + if not k or k in seen: + continue + seen.add(k) + existing = by_key.get(k) + if existing is not None: + set_fields(existing, item) + else: + new_row = _new_row_for(set_fields) + new_row.database_id = database_id + new_row.created_version = new_version + set_fields(new_row, item) + db.add(new_row) + if delete_absent: + for k, row in by_key.items(): + if k not in seen: + row.deleted_at = _now() + row.deleted_version = new_version + + +def _new_row_for(set_fields): + return {_tool_fields: McpToolRow, _resource_fields: McpResourceRow, _prompt_fields: McpPromptRow}[set_fields]() + + +def _tool_fields(row: McpToolRow, item: dict) -> None: + row.name = item["name"] + row.title = item.get("title") + row.description = item.get("description") or "" + row.execution_json = json.dumps(normalize_execution(item)) + row.output_schema_json = json.dumps(item["output_schema"]) if item.get("output_schema") else None + row.annotations_json = json.dumps(item["annotations"]) if item.get("annotations") else None + + +def _params_from_input_schema(input_schema: dict | None) -> list[dict]: + """Derive execution ``parameters`` from a legacy/clientside MCP ``inputSchema`` object.""" + props = ((input_schema or {}).get("properties")) or {} + required = set((input_schema or {}).get("required") or []) + params: list[dict] = [] + for name, spec in props.items(): + p: dict = {"name": name, "type": (spec or {}).get("type") or "string"} + if (spec or {}).get("description"): + p["description"] = spec["description"] + if name in required: + p["required"] = True + params.append(p) + return params + + +def normalize_execution(item: dict) -> dict: + """Coerce a tool definition into the canonical ``{"sql_template", "parameters"}`` execution object. + + Accepts the new ``execution`` object directly, or a legacy top-level ``sql_template`` (+ optional + ``input_schema`` from which parameter specs are derived) so older callers/tests still work. + """ + execution = item.get("execution") + if isinstance(execution, dict) and (execution.get("sql_template") or execution.get("parameters")): + params = execution.get("parameters") + if params is None: + params = _params_from_input_schema(item.get("input_schema")) + return {"sql_template": execution.get("sql_template") or "", "parameters": params or []} + return { + "sql_template": item.get("sql_template") or "", + "parameters": _params_from_input_schema(item.get("input_schema")), + } + + +def _resource_fields(row: McpResourceRow, item: dict) -> None: + row.uri = item["uri"] + row.name = item.get("name") or item["uri"] + row.title = item.get("title") + row.description = item.get("description") + row.mime_type = item.get("mime_type") + row.kind = item.get("kind") or "primary_entity" + row.content = item["content"] if item.get("content") is not None else None + row.size = item.get("size") + + +def _prompt_fields(row: McpPromptRow, item: dict) -> None: + row.name = item["name"] + row.title = item.get("title") + row.description = item.get("description") + row.arguments_json = json.dumps(item.get("arguments") or []) + row.template_json = json.dumps(item["template"]) if item.get("template") is not None else None + + +_SETTERS.update({"tool": _tool_fields, "resource": _resource_fields, "prompt": _prompt_fields}) + + +# --- Helpers ---------------------------------------------------------------- + +def _active(db: Session, database_id: str) -> dict[str, list]: + """Load the active (non-soft-deleted) child rows for a server.""" + def q(model): + return ( + db.query(model) + .filter(model.database_id == database_id, model.deleted_at.is_(None)) + .order_by(model.created_at, model.id) + .all() + ) + return {"tools": q(McpToolRow), "resources": q(McpResourceRow), "prompts": q(McpPromptRow)} + + +def active_entity_tables(db: Session, database_id: str) -> list[dict]: + """The database's tables **from the resources table** (entity resources), in ``discover_tables`` shape. + + This is the materialized source of truth used everywhere OUTSIDE sync (pool build, query execution, + write-time validation, the EER view) — so the serving path never re-inspects the underlying store. + """ + rows = ( + db.query(McpResourceRow) + .filter(McpResourceRow.database_id == database_id, McpResourceRow.deleted_at.is_(None), + McpResourceRow.kind != "schema") + .order_by(McpResourceRow.created_at, McpResourceRow.id) + .all() + ) + tables: list[dict] = [] + for r in rows: + content = r.content or {} + cols = content.get("columns") or [] + tables.append({ + "table_name": content.get("table") or r.name, + "column_names": [c.get("name") for c in cols], + "schema": cols, + "row_count": content.get("row_count"), + }) + return tables + + +def _active_schema_content(resources: list) -> dict: + """The entity-relationship schema content from the active ``kind='schema'`` resource (or ``{}``).""" + for r in resources: + if r.kind == "schema": + return r.content or {} + return {} + + +def _active_one(db, model, database_id, key, key_val): + return ( + db.query(model) + .filter(model.database_id == database_id, model.deleted_at.is_(None), getattr(model, key) == key_val) + .first() + ) + + +def _meta(rows: list, *fields: str) -> list[dict]: + """Project active rows to plain dicts for the stage prompts (existing-capability hints).""" + return [{f: getattr(r, f, None) for f in fields} for r in rows] + + +def _schema_resource(name: str, schema: dict) -> dict: + """The entity-relationship resource: relationships + foreign keys ONLY (no per-table columns). + + Together with the per-entity resources (which carry each table's columns) this is the full schema + source of truth. This resource is tied to the server's existence (never added/deleted, only updated). + """ + content = _schema_content(schema) + return { + "uri": f"dataset://{name}/schema", + "name": "schema", + "title": "Entity relationships", + "description": "Foreign-key and entity relationships across the dataset's tables.", + "kind": "schema", + "mime_type": "application/json", + "content": content, + "size": len(json.dumps(content).encode()), # size of the relationship content (bytes) + } + + +def _schema_content(schema: dict) -> dict: + """Project to the **canonical schema-resource shape** — a single relationship (FK-edge) list. + + ``{"relationships": [{"from_table","from_column","to_table","to_column"}]}`` — the one format the + EER diagram reads and every connector + the LLM must produce, regardless of database type. + """ + rels = (schema or {}).get("relationships") or [] + norm = [ + { + "from_table": r.get("from_table") or r.get("from"), + "from_column": r.get("from_column") or r.get("on"), + "to_table": r.get("to_table") or r.get("to"), + "to_column": r.get("to_column") or r.get("on"), + } + for r in rels + ] + return {"relationships": [r for r in norm if r["from_table"] and r["to_table"]]} + + +def _entity_resource(name: str, entity: dict, tables_by_name: dict) -> dict: + """A per-entity resource carrying its backing table's columns (the per-table schema source).""" + table = entity.get("name") + t = tables_by_name.get(table) or {} + columns = t.get("schema") or [{"name": c} for c in (t.get("column_names") or [])] + return { + "uri": entity.get("uri") or f"entity://{name}/{table}", + "name": table or "entity", + "title": entity.get("title"), + "description": entity.get("description"), + "kind": entity.get("kind") or "primary_entity", + "mime_type": entity.get("mime_type") or "application/json", + "content": {"table": table, "columns": columns, "row_count": t.get("row_count")}, + "size": _table_size(t.get("parquet_path")), # size of the backing table file (bytes) + } + + +def _table_size(parquet_path: str | None) -> int | None: + """Return the on-disk size (bytes) of a table's Parquet file, or ``None`` if unavailable.""" + if not parquet_path: + return None + try: + return Path(parquet_path).stat().st_size + except Exception: + return None + + +def _validate_tools(server: DatabaseRow, connector, table_names: list[str], tools: list[dict]) -> tuple[list[dict], bool]: + """Drop tools whose zero-param SQL doesn't compile against the database (parquet only). + + Compile-checks against a connection the connector builds over ``table_names`` (no re-inspection). + """ + if (server.type or "parquet") != "parquet": + return tools, False # external (BETA): trust the generated SQL + conn = getattr(connector.build_server(table_names), "_duckdb_conn", None) + try: + kept: list[dict] = [] + dropped = False + for tool in tools: + execution = normalize_execution(tool) + sql = execution.get("sql_template") or "" + if execution.get("parameters"): + kept.append(tool) # can't safely compile-check parameterized SQL — trust it + continue + try: + _run_select_params(conn, f"SELECT * FROM ({sql}) AS _v LIMIT 0", None, 0) + kept.append(tool) + except Exception as exc: + dropped = True + log.warning("sync.tool_invalid", name=tool.get("name"), error=str(exc)) + return kept, dropped + finally: + if conn is not None: + conn.close() diff --git a/src/data_analysis_agent/tools/sync/stages.py b/src/data_analysis_agent/tools/sync/stages.py new file mode 100644 index 00000000..18739488 --- /dev/null +++ b/src/data_analysis_agent/tools/sync/stages.py @@ -0,0 +1,233 @@ +"""The five LLM sync stages: title → schema → entities → tools → prompts. + +Each stage builds a prompt (with first-5-row samples + the existing capabilities, for incremental +edits), calls the LLM, and parses JSON — falling back to a deterministic template on any failure so +sync never hard-fails. Each stage injects a distinct ```` tag so the offline stub +branches deterministically (see ``llm/providers/stub.py``). +""" +from __future__ import annotations + +import json + +import pandas as pd +import structlog + +log = structlog.get_logger() + +TAG_TITLE = "" +TAG_SCHEMA = "" +TAG_ENTITIES = "" +TAG_TOOLS = "" +TAG_PROMPTS = "" + + +def _llm(prompt: str) -> str: + from data_analysis_agent.llm.client import get_llm_client + return get_llm_client().complete(prompt).text or "" + + +def _sample(parquet_path: str | None) -> str: + """Return a small CSV sample (first 5 rows) of a Parquet file, or '' on any failure.""" + if not parquet_path: + return "" + try: + return pd.read_parquet(parquet_path).head(5).to_csv(index=False) + except Exception: + return "" + + +def _strip_fences(text: str) -> str: + """Remove a leading ``` fence (and optional language tag) some models emit.""" + text = text.strip() + if not text.startswith("```"): + return text + lines = text.split("\n") + end = len(lines) - 1 if lines[-1].strip() == "```" else len(lines) + return "\n".join(lines[1:end]).strip() + + +def _parse(raw: str) -> dict: + return json.loads(_strip_fences(raw)) + + +def _table_block(tables: list[dict]) -> list[str]: + """Render each table's columns + a sample, for a stage prompt.""" + lines: list[str] = [] + for t in tables: + schema = t.get("schema") or [] + cols = ", ".join( + f"{c['name']} ({c['dtype']}{'?' if c.get('nullable') else ''})" for c in schema + ) or ", ".join(t.get("column_names") or []) or "(unknown)" + lines.append(f"Table: {t['table_name']} columns: {cols}") + sample = _sample(t.get("parquet_path")) + if sample: + lines.append(" sample (first rows):") + lines.append(sample) + return lines + + +# --- Stage a: title + description ------------------------------------------- + +def stage_title(name: str, tables: list[dict], existing: dict) -> dict: + """Return ``{"title", "description"}`` for the server.""" + fallback = { + "title": existing.get("title") or name, + "description": existing.get("description") + or f"MCP server for dataset '{name}' ({len(tables)} table(s)).", + } + table_names = ", ".join(t["table_name"] for t in tables) or "(none)" + prompt = "\n".join([ + TAG_TITLE, + "You write metadata for an MCP server backed by a tabular dataset.", + f"Dataset name: {name}", + f"Tables: {table_names}", + *_table_block(tables), + f"Existing title: {existing.get('title') or '(none)'}", + f"Existing description: {existing.get('description') or '(none)'}", + 'Respond with ONLY JSON: {"title": "...", "description": "..."}', + ]) + try: + parsed = _parse(_llm(prompt)) + return { + "title": parsed.get("title") or fallback["title"], + "description": parsed.get("description") or fallback["description"], + } + except Exception as exc: + log.warning("sync.stage_title.fallback", error=str(exc)) + return fallback + + +# --- Stage b: dataset JSONSchema -------------------------------------------- + +def stage_schema(name: str, tables: list[dict], existing_schema: dict) -> dict: + """Return the entity-relationship schema in the **canonical** shape — a single FK-edge list: + + ``{"relationships": [{"from_table","from_column","to_table","to_column"}]}``. Relationships ONLY — + per-table columns live on the individual entity resources, not here. This is the one format the EER + diagram reads; the LLM must emit exactly this (used only when the connector can't supply FKs). + """ + fallback = {"relationships": (existing_schema or {}).get("relationships") or []} + prompt = "\n".join([ + TAG_SCHEMA, + "Infer the FOREIGN-KEY relationships between the dataset's tables (which column references which).", + "Do NOT list table columns — only how the tables relate.", + f"Dataset name: {name}", + *_table_block(tables), + f"Existing relationships: {json.dumps(existing_schema) if existing_schema else '(none)'}", + 'Respond with ONLY JSON: {"relationships": [{"from_table": "", "from_column": "", ' + '"to_table": "
", "to_column": ""}]}', + ]) + try: + return {"relationships": _parse(_llm(prompt)).get("relationships") or []} + except Exception as exc: + log.warning("sync.stage_schema.fallback", error=str(exc)) + return fallback + + +# --- Stage c: entities → resources ------------------------------------------ + +def stage_entities(name: str, tables: list[dict], existing_resources: list[dict]) -> list[dict]: + """Return entity resources ``[{name, title, description, kind, uri, mime_type}]`` (one per table).""" + table_names = [t["table_name"] for t in tables] + fallback = [ + { + "name": t, + "title": t.replace("_", " ").title(), + "description": f"The '{t}' entity.", + "kind": "primary_entity", + "uri": f"entity://{name}/{t}", + "mime_type": "application/json", + } + for t in table_names + ] + existing_names = ", ".join(r.get("name", "") for r in existing_resources) or "(none)" + prompt = "\n".join([ + TAG_ENTITIES, + "List the primary and secondary entities (one per physical table) backing this dataset.", + f"Dataset name: {name}", + f"Schema tables: {', '.join(table_names) or '(none)'}", + f"Existing resources: {existing_names}", + 'Respond with ONLY JSON: {"entities": [{"name","title","description","kind","uri","mime_type"}]}', + 'name MUST be a physical table name; kind is "primary_entity" or "secondary_entity"; ' + 'uri like "entity:///".', + ]) + try: + parsed = _parse(_llm(prompt)) + entities = parsed.get("entities") + return entities if isinstance(entities, list) and entities else fallback + except Exception as exc: + log.warning("sync.stage_entities.fallback", error=str(exc)) + return fallback + + +# --- Stage d: GET-API tools ------------------------------------------------- + +def stage_tools(name: str, entities: list[dict], tables: list[dict], existing_tools: list[dict]) -> list[dict]: + """Return GET-API tools ``[{name, title, description, input_schema, sql_template, output_schema?}]``.""" + table_names = [t["table_name"] for t in tables] + fallback = [ + { + "name": f"list_{t}", + "title": f"List {t}", + "description": f"Return rows from the '{t}' table.", + "execution": {"sql_template": f"SELECT * FROM {t} LIMIT 100", "parameters": []}, + } + for t in table_names + ] + entity_lines = [f"Entity: {e.get('name')}" for e in entities] + existing_names = ", ".join(t.get("name", "") for t in existing_tools) or "(none)" + prompt = "\n".join([ + TAG_TOOLS, + "Propose GET-API tools — each a read-only SELECT — over these entities.", + f"Dataset name: {name}", + *entity_lines, + f"Tables available: {', '.join(table_names) or '(none)'}", + f"Existing tools: {existing_names}", + 'Respond with ONLY JSON: {"tools": [{"name","title","description","output_schema",' + '"execution": {"sql_template": "SELECT ... WHERE col > $param", ' + '"parameters": [{"name": "param", "type": "integer", "description": "..."}]}}]}', + "execution.sql_template is a single read-only SELECT; every $param embedded in it MUST be " + "declared in execution.parameters with its type.", + ]) + try: + parsed = _parse(_llm(prompt)) + tools = parsed.get("tools") + return tools if isinstance(tools, list) and tools else fallback + except Exception as exc: + log.warning("sync.stage_tools.fallback", error=str(exc)) + return fallback + + +# --- Stage e: prompt templates ---------------------------------------------- + +def stage_prompts(name: str, tools: list[dict], existing_prompts: list[dict]) -> list[dict]: + """Return prompt templates ``[{name, title, description, arguments, template}]``.""" + fallback = [ + { + "name": f"explore_{t.get('name')}", + "title": f"Explore via {t.get('name')}", + "description": f"Guidance for using the '{t.get('name')}' tool.", + "arguments": [], + "template": [ + {"role": "user", "content": f"Use the '{t.get('name')}' tool to answer questions about {name}."} + ], + } + for t in tools + ] + tool_lines = [f"Tool: {t.get('name')}" for t in tools] + existing_names = ", ".join(p.get("name", "") for p in existing_prompts) or "(none)" + prompt = "\n".join([ + TAG_PROMPTS, + "Propose prompt templates that help a user drive these tools.", + f"Dataset name: {name}", + *tool_lines, + f"Existing prompts: {existing_names}", + 'Respond with ONLY JSON: {"prompts": [{"name","title","description","arguments","template"}]}', + ]) + try: + parsed = _parse(_llm(prompt)) + prompts = parsed.get("prompts") + return prompts if isinstance(prompts, list) and prompts else fallback + except Exception as exc: + log.warning("sync.stage_prompts.fallback", error=str(exc)) + return fallback diff --git a/src/data_analysis_agent/tools/table_naming.py b/src/data_analysis_agent/tools/table_naming.py new file mode 100644 index 00000000..723ac8c1 --- /dev/null +++ b/src/data_analysis_agent/tools/table_naming.py @@ -0,0 +1,24 @@ +from __future__ import annotations + +import re + + +def sql_table_name(source_name: str) -> str: + """Derive a SQL-safe table name from a data source name or filename. + + Lowercases the filename stem, replaces every non-word character with an + underscore, collapses repeats, and prefixes ``ds_`` if the result would + otherwise start with a digit. Falls back to ``data`` for empty input. + + Args: + source_name: The data source display name, e.g. ``"2024 Sales.csv"``. + + Returns: + A lowercase identifier safe to use as a SQL table name, e.g. ``ds_2024_sales``. + """ + stem = source_name.rsplit(".", 1)[0] + name = re.sub(r"[^\w]", "_", stem).lower() + name = re.sub(r"_+", "_", name).strip("_") or "data" + if name[0].isdigit(): + name = "ds_" + name + return name diff --git a/src/db/models.py b/src/db/models.py deleted file mode 100644 index 978422e4..00000000 --- a/src/db/models.py +++ /dev/null @@ -1,33 +0,0 @@ -from datetime import datetime, timezone -from uuid import uuid4 - -from sqlalchemy import Text, TIMESTAMP -from sqlalchemy.orm import DeclarativeBase, Mapped, mapped_column - - -def _uuid() -> str: - return str(uuid4()) - - -def _now() -> datetime: - return datetime.now(timezone.utc) - - -class Base(DeclarativeBase): - pass - - -class RunRow(Base): - __tablename__ = "runs" - - id: Mapped[str] = mapped_column(Text, primary_key=True, default=_uuid) - status: Mapped[str] = mapped_column(Text, nullable=False, default="pending") - input_text: Mapped[str | None] = mapped_column(Text, nullable=True) - output_text: Mapped[str | None] = mapped_column(Text, nullable=True) - error_message: Mapped[str | None] = mapped_column(Text, nullable=True) - created_at: Mapped[datetime] = mapped_column( - TIMESTAMP(timezone=True), nullable=False, default=_now - ) - updated_at: Mapped[datetime] = mapped_column( - TIMESTAMP(timezone=True), nullable=False, default=_now, onupdate=_now - ) diff --git a/src/db/session.py b/src/db/session.py deleted file mode 100644 index 50b6a447..00000000 --- a/src/db/session.py +++ /dev/null @@ -1,51 +0,0 @@ -from contextlib import contextmanager -from collections.abc import Generator - -from sqlalchemy import create_engine, Engine -from sqlalchemy.orm import Session, sessionmaker - -_engine: Engine | None = None -_SessionLocal: sessionmaker | None = None - - -def _get_engine() -> Engine: - global _engine - if _engine is None: - from config.settings import get_settings - _engine = create_engine(get_settings().database_url, echo=False) - return _engine - - -def _get_session_factory() -> sessionmaker: - global _SessionLocal - if _SessionLocal is None: - _SessionLocal = sessionmaker(bind=_get_engine(), autoflush=False, autocommit=False) - return _SessionLocal - - -def get_session() -> Generator[Session, None, None]: - """FastAPI dependency.""" - with _get_session_factory()() as session: - try: - yield session - session.commit() - except Exception: - session.rollback() - raise - - -@contextmanager -def create_db_session() -> Generator[Session, None, None]: - """Standalone — for graph nodes, CLI, scripts.""" - with _get_session_factory()() as session: - try: - yield session - session.commit() - except Exception: - session.rollback() - raise - - -def init_db() -> None: - from db.models import Base - Base.metadata.create_all(bind=_get_engine()) diff --git a/src/domain/__init__.py b/src/domain/__init__.py deleted file mode 100644 index 37d4e3d0..00000000 --- a/src/domain/__init__.py +++ /dev/null @@ -1,3 +0,0 @@ -from domain.run import RunRequest, RunResponse - -__all__ = ["RunRequest", "RunResponse"] diff --git a/src/domain/run.py b/src/domain/run.py deleted file mode 100644 index 3dc4e6a7..00000000 --- a/src/domain/run.py +++ /dev/null @@ -1,12 +0,0 @@ -from pydantic import BaseModel - - -class RunRequest(BaseModel): - input_text: str - - -class RunResponse(BaseModel): - run_id: str - status: str - output_text: str | None = None - error: str | None = None diff --git a/src/graph/agent.py b/src/graph/agent.py deleted file mode 100644 index d0bcc390..00000000 --- a/src/graph/agent.py +++ /dev/null @@ -1,24 +0,0 @@ -from langgraph.graph import StateGraph, END - -from graph.state import AgentState -from graph.nodes import transform_text, handle_error, finalize -from graph.edges import after_transform - - -def _build_graph() -> StateGraph: - g = StateGraph(AgentState) - g.add_node("transform_text", transform_text) - g.add_node("handle_error", handle_error) - g.add_node("finalize", finalize) - g.set_entry_point("transform_text") - g.add_conditional_edges( - "transform_text", - after_transform, - {"finalize": "finalize", "handle_error": "handle_error"}, - ) - g.add_edge("finalize", END) - g.add_edge("handle_error", END) - return g.compile() - - -agentic_ai = _build_graph() diff --git a/src/graph/edges.py b/src/graph/edges.py deleted file mode 100644 index 2992e266..00000000 --- a/src/graph/edges.py +++ /dev/null @@ -1,7 +0,0 @@ -from graph.state import AgentState - - -def after_transform(state: AgentState) -> str: - if state.get("error"): - return "handle_error" - return "finalize" diff --git a/src/graph/nodes.py b/src/graph/nodes.py deleted file mode 100644 index 1e47327d..00000000 --- a/src/graph/nodes.py +++ /dev/null @@ -1,29 +0,0 @@ -from pathlib import Path - -from graph.state import AgentState -from llm.client import LLMClient - -_PROMPT_PATH = Path(__file__).parent.parent / "prompts" / "transform.md" - - -def _load_prompt() -> str: - return _PROMPT_PATH.read_text(encoding="utf-8").strip() - - -def transform_text(state: AgentState) -> AgentState: - try: - prompt_template = _load_prompt() - result = LLMClient().call_model( - f"{prompt_template}\n\nInput: {state['input_text']}" - ) - return {**state, "output_text": result} - except Exception as exc: - return {**state, "error": str(exc)} - - -def handle_error(state: AgentState) -> AgentState: - return {**state, "status": "failed"} - - -def finalize(state: AgentState) -> AgentState: - return {**state, "status": "completed"} diff --git a/src/graph/runner.py b/src/graph/runner.py deleted file mode 100644 index 4dfaad9a..00000000 --- a/src/graph/runner.py +++ /dev/null @@ -1,25 +0,0 @@ -from graph.agent import agentic_ai -from graph.state import AgentState -from db.session import create_db_session, init_db -from db.models import RunRow - - -def run_agent(input_text: str) -> str: - init_db() - - with create_db_session() as session: - run = RunRow(input_text=input_text) - session.add(run) - session.flush() - run_id = run.id - - initial: AgentState = {"run_id": run_id, "input_text": input_text, "error": None} - final = agentic_ai.invoke(initial) - - with create_db_session() as session: - run = session.get(RunRow, run_id) - run.status = final.get("status", "completed") - run.output_text = final.get("output_text") - run.error_message = final.get("error") - - return run_id diff --git a/src/graph/state.py b/src/graph/state.py deleted file mode 100644 index bccd0b87..00000000 --- a/src/graph/state.py +++ /dev/null @@ -1,9 +0,0 @@ -from typing import TypedDict - - -class AgentState(TypedDict, total=False): - run_id: str - input_text: str - output_text: str - error: str | None - messages: list # [{role: "user"|"assistant", content: str}, ...] — chat-turn history diff --git a/src/llm/client.py b/src/llm/client.py deleted file mode 100644 index 7b60403b..00000000 --- a/src/llm/client.py +++ /dev/null @@ -1,35 +0,0 @@ -from config.settings import get_settings - - -def _make_provider(): - s = get_settings() - provider = s.llm_provider - - # auto-detect from whichever key is set - if not provider: - if s.anthropic_api_key: - provider = "anthropic" - elif s.gemini_api_key: - provider = "gemini" - else: - raise RuntimeError( - "No LLM provider configured. Set AGENT_ANTHROPIC_API_KEY or " - "AGENT_GEMINI_API_KEY in .env, or set AGENT_LLM_PROVIDER explicitly." - ) - - if provider == "anthropic": - from llm.providers.anthropic import AnthropicProvider - return AnthropicProvider(api_key=s.anthropic_api_key, model=s.llm_model) - if provider == "gemini": - from llm.providers.gemini import GeminiProvider - return GeminiProvider(api_key=s.gemini_api_key, model=s.llm_model) - - raise RuntimeError(f"Unknown LLM provider: {provider!r}. Supported: anthropic, gemini") - - -class LLMClient: - def __init__(self) -> None: - self._provider = _make_provider() - - def call_model(self, prompt: str, *, system: str | None = None) -> str: - return self._provider.call_model(prompt, system=system) diff --git a/src/llm/providers/anthropic.py b/src/llm/providers/anthropic.py deleted file mode 100644 index f752118d..00000000 --- a/src/llm/providers/anthropic.py +++ /dev/null @@ -1,20 +0,0 @@ -import anthropic as _sdk - - -class AnthropicProvider: - DEFAULT_MODEL = "claude-sonnet-4-6" - - def __init__(self, api_key: str, model: str) -> None: - self._client = _sdk.Anthropic(api_key=api_key) - self._model = model or self.DEFAULT_MODEL - - def call_model(self, prompt: str, *, system: str | None = None) -> str: - kwargs: dict = dict( - model=self._model, - max_tokens=1024, - messages=[{"role": "user", "content": prompt}], - ) - if system: - kwargs["system"] = system - msg = self._client.messages.create(**kwargs) - return msg.content[0].text diff --git a/src/llm/providers/gemini.py b/src/llm/providers/gemini.py deleted file mode 100644 index f86abf4f..00000000 --- a/src/llm/providers/gemini.py +++ /dev/null @@ -1,21 +0,0 @@ -from google import genai -from google.genai import types - - -class GeminiProvider: - DEFAULT_MODEL = "gemini-2.5-pro" - - def __init__(self, api_key: str, model: str) -> None: - self._client = genai.Client(api_key=api_key) - self._model = model or self.DEFAULT_MODEL - - def call_model(self, prompt: str, *, system: str | None = None) -> str: - config = types.GenerateContentConfig( - system_instruction=system, - ) if system else None - response = self._client.models.generate_content( - model=self._model, - contents=prompt, - config=config, - ) - return response.text diff --git a/src/observability/events.py b/src/observability/events.py deleted file mode 100644 index 46a441da..00000000 --- a/src/observability/events.py +++ /dev/null @@ -1,21 +0,0 @@ -import structlog - - -def configure_logging(log_level: str = "INFO") -> None: - structlog.configure( - processors=[ - structlog.stdlib.add_log_level, - structlog.stdlib.add_logger_name, - structlog.processors.TimeStamper(fmt="iso"), - structlog.processors.JSONRenderer(), - ], - wrapper_class=structlog.make_filtering_bound_logger( - getattr(__import__("logging"), log_level, 20) - ), - context_class=dict, - logger_factory=structlog.PrintLoggerFactory(), - ) - - -def get_logger(name: str = "agent") -> structlog.BoundLogger: - return structlog.get_logger(name) diff --git a/src/prompts/transform.md b/src/prompts/transform.md deleted file mode 100644 index f052919a..00000000 --- a/src/prompts/transform.md +++ /dev/null @@ -1 +0,0 @@ -You are a concise text processor. Given the input text, produce a clear 1-2 sentence summary or rephrasing that captures the key idea. Return ONLY the transformed text, no preamble. diff --git a/tests/__init__.py b/tests/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/conftest.py b/tests/conftest.py index 1ab26073..e0da9a3f 100644 --- a/tests/conftest.py +++ b/tests/conftest.py @@ -1,44 +1,20 @@ import pytest +import data_analysis_agent.config.settings as settings_module +import data_analysis_agent.tools.mcp.pool as pool_module @pytest.fixture(autouse=True) def _reset_settings_singleton(): - import config.settings as m - m._settings = None + """Reset cached settings so env patches take effect in every test.""" + settings_module._settings = None yield - m._settings = None + settings_module._settings = None @pytest.fixture(autouse=True) -def _isolated_db(tmp_path, monkeypatch): - from sqlalchemy import create_engine - from sqlalchemy.orm import sessionmaker - from db.models import Base - import db.session as session_module - - engine = create_engine(f"sqlite:///{tmp_path}/test.db") - Base.metadata.create_all(engine) - factory = sessionmaker(bind=engine, autoflush=False, autocommit=False) - monkeypatch.setattr(session_module, "_engine", engine) - monkeypatch.setattr(session_module, "_SessionLocal", factory) - monkeypatch.setattr(session_module, "init_db", lambda: None) - yield engine - engine.dispose() - - -@pytest.fixture -def _require_llm_key(): - """Skip if no LLM provider key is set — works for Anthropic or Gemini.""" - from config.settings import get_settings - s = get_settings() - if not s.anthropic_api_key and not s.gemini_api_key: - pytest.skip("No LLM key set in .env (AGENT_ANTHROPIC_API_KEY or AGENT_GEMINI_API_KEY)") - - -@pytest.fixture -def api_client(_isolated_db): - """FastAPI test client with isolated DB.""" - from fastapi.testclient import TestClient - from api import app - with TestClient(app) as client: - yield client +def _reset_pool_manager(): + """Tear down the session-pool manager after each test so pools/locks don't leak.""" + yield + if pool_module._manager is not None: + pool_module._manager.close_all() + pool_module._manager = None diff --git a/tests/integration/__init__.py b/tests/integration/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/integration/test_database_api.py b/tests/integration/test_database_api.py new file mode 100644 index 00000000..d00bab84 --- /dev/null +++ b/tests/integration/test_database_api.py @@ -0,0 +1,275 @@ +"""API tests for the MCP-server model: upload→create (auto-sync), duplicate rejection, external 501, +MCP JSON-RPC dispatch (tools/list+call, errors), sync version bump (soft-delete), and delete — all in +stub mode against a tmp SQLite DB.""" +import csv +import io +from pathlib import Path + +import pytest +from fastapi.testclient import TestClient + +import data_analysis_agent.db.session as session_module +from data_analysis_agent.db.database import Database +from data_analysis_agent.db.models import DatabaseRow, McpResourceRow, McpToolRow + + +@pytest.fixture(autouse=True) +def _env(tmp_path, monkeypatch): + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", "") + monkeypatch.setenv("DATAANALYSIS_UPLOAD_DIR", str(tmp_path / "uploads")) + monkeypatch.setenv("DATAANALYSIS_DATASETS_DIR", str(tmp_path / "datasets")) + monkeypatch.setenv("DATAANALYSIS_CHECKPOINT_DB", str(tmp_path / "ckpt.db")) + db = Database(f"sqlite:///{tmp_path / 'app.db'}") + db._init_schema() + monkeypatch.setattr(session_module, "_db", db) + monkeypatch.setattr(session_module, "init_db", lambda: None) + yield + db._dispose() + monkeypatch.setattr(session_module, "_db", None) + + +@pytest.fixture +def client(): + import data_analysis_agent.llm.client as llm_module + llm_module._client = None + from data_analysis_agent.api import create_app + with TestClient(create_app(), raise_server_exceptions=True) as c: + yield c + + +def _csv(*rows) -> bytes: + buf = io.StringIO() + w = csv.writer(buf) + for r in rows: + w.writerow(r) + return buf.getvalue().encode() + + +def _orders() -> bytes: + return _csv(["id", "amount"], [1, 5], [2, 7]) + + +def _create(client, name: str, data: bytes | None = None, filename: str = "orders.csv"): + up = client.post("/database/upload", data={"database_name": name}, + files={"file": (filename, data or _orders(), "text/csv")}) + assert up.status_code == 200, up.text + uri = up.json()["uri"] + return client.post("/database", data={"name": name, "database_type": "parquet", "database_uri": uri}, + follow_redirects=True) + + +def _table_count(db, database_id: str) -> int: + """Active entity (non-schema) resources = the database's tables (no stored physical catalog).""" + return ( + db.query(McpResourceRow) + .filter(McpResourceRow.database_id == database_id, McpResourceRow.deleted_at.is_(None), + McpResourceRow.kind != "schema") + .count() + ) + + +def _only_server(): + with session_module.create_db_session() as db: + srv = db.query(DatabaseRow).one() + return srv.id, srv.version, _table_count(db, srv.id) + + +def test_create_builds_server_and_capabilities(client): + r = _create(client, "Sales DB") + assert r.status_code == 200 + with session_module.create_db_session() as db: + srv = db.query(DatabaseRow).one() + assert srv.name == "Sales DB" and srv.type == "parquet" + assert srv.uri == "parquet:///Sales%20DB" + assert srv.title and srv.description # generated by the sync stub + assert srv.version >= 2 # create(1) + sync apply bumps to 2 + assert _table_count(db, srv.id) == 1 # one entity resource per inspected table + tools = db.query(McpToolRow).filter_by(database_id=srv.id, deleted_at=None).all() + assert len(tools) >= 1 + + +def test_duplicate_name_rejected(client): + _create(client, "Dupe") + up = client.post("/database/upload", data={"database_name": "Dupe"}, + files={"file": ("b.csv", _orders(), "text/csv")}) + uri = up.json()["uri"] + r = client.post("/database", data={"name": "Dupe", "database_type": "parquet", "database_uri": uri}, + follow_redirects=False) + assert r.status_code == 400 + + +def test_create_without_upload_succeeds_with_zero_tables(client): + # A parquet database may contain zero tables (nothing uploaded yet) — that is valid. + r = client.post("/database", + data={"name": "Empty", "database_type": "parquet", "database_uri": "parquet:///Empty"}, + follow_redirects=True) + assert r.status_code == 200 + _, _, n_tables = _only_server() + assert n_tables == 0 + + +def test_jsonrpc_tools_list_call_and_errors(client): + _create(client, "RPC DB") + database_id, _, _ = _only_server() + + listed = client.post(f"/database/{database_id}", + json={"jsonrpc": "2.0", "id": 1, "method": "tools/list"}) + assert listed.status_code == 200 + body = listed.json() + tools = body["result"]["tools"] + assert tools and "inputSchema" in tools[0] + tool_name = tools[0]["name"] + + called = client.post(f"/database/{database_id}", + json={"jsonrpc": "2.0", "id": 2, "method": "tools/call", + "params": {"name": tool_name, "arguments": {}}}).json() + assert called["result"]["isError"] is False + assert called["result"]["content"][0]["type"] == "text" + + # resources + prompts also list + res = client.post(f"/database/{database_id}", + json={"jsonrpc": "2.0", "id": 3, "method": "resources/list"}).json() + assert any(r["uri"].endswith("/schema") for r in res["result"]["resources"]) + + # unknown method → -32601, unknown tool → -32602 + unk = client.post(f"/database/{database_id}", + json={"jsonrpc": "2.0", "id": 4, "method": "nope/x"}).json() + assert unk["error"]["code"] == -32601 + bad = client.post(f"/database/{database_id}", + json={"jsonrpc": "2.0", "id": 5, "method": "tools/call", + "params": {"name": "does_not_exist", "arguments": {}}}).json() + assert bad["error"]["code"] == -32602 + + +def test_sync_bumps_version(client): + _create(client, "SyncDB") + database_id, v_before, _ = _only_server() + r = client.post(f"/database/{database_id}/sync", follow_redirects=False) + assert r.status_code == 303 + _, v_after, _ = _only_server() + assert v_after == v_before + 1 + + +def test_add_table_via_upload_then_sync(client): + # Adding a table = the upload API reused + a sync (which re-inspects the directory). + _create(client, "GrowDB") + database_id, _, n_before = _only_server() + up = client.post("/database/upload", data={"database_name": "GrowDB"}, + files={"file": ("customers.csv", _csv(["id", "region"], [1, "N"]), "text/csv")}) + assert up.status_code == 200, up.text + r = client.post(f"/database/{database_id}/sync", follow_redirects=False) + assert r.status_code == 303 + _, _, n_after = _only_server() + assert n_after == n_before + 1 + + +def _rpc(client, database_id, method, params=None, rpc_id=1): + body = {"jsonrpc": "2.0", "id": rpc_id, "method": method} + if params is not None: + body["params"] = params + return client.post(f"/database/{database_id}", json=body).json() + + +_GOOD_TOOL = {"name": "recent_orders", "description": "Recent orders", + "sql_template": "SELECT * FROM orders LIMIT 3", + "input_schema": {"type": "object", "properties": {}}} + + +def test_tools_add_succeeds_and_cascades_prompts(client): + _create(client, "MutDB") + database_id, v_before, _ = _only_server() + res = _rpc(client, database_id, "tools/add", {"definition": _GOOD_TOOL})["result"] + assert res["ok"] is True and res["applied"]["key"] == "recent_orders" + _, v_after, _ = _only_server() + assert v_after == v_before + 1 + tools = _rpc(client, database_id, "tools/list")["result"]["tools"] + assert any(t["name"] == "recent_orders" for t in tools) + prompts = _rpc(client, database_id, "prompts/list")["result"]["prompts"] + assert any(p["name"] == "explore_recent_orders" for p in prompts) # additive cascade + + +def test_tools_add_duplicate_is_invalid_params(client): + _create(client, "DupTool") + database_id, _, _ = _only_server() + _rpc(client, database_id, "tools/add", {"definition": _GOOD_TOOL}) + dup = _rpc(client, database_id, "tools/add", {"definition": _GOOD_TOOL}) + assert dup["error"]["code"] == -32602 + + +def test_tools_add_bad_sql_is_invalid_params_and_not_persisted(client): + _create(client, "BadSql") + database_id, _, n0 = _only_server() + before = len(_rpc(client, database_id, "tools/list")["result"]["tools"]) + bad = {"definition": {"name": "evil", "sql_template": "DELETE FROM orders", + "input_schema": {"type": "object", "properties": {}}}} + resp = _rpc(client, database_id, "tools/add", bad) + assert resp["error"]["code"] == -32602 + after = len(_rpc(client, database_id, "tools/list")["result"]["tools"]) + assert after == before # nothing persisted + + +def test_prompts_add_succeeds(client): + _create(client, "PromptDB") + database_id, _, _ = _only_server() + res = _rpc(client, database_id, "prompts/add", + {"definition": {"name": "my_prompt", "description": "mine"}})["result"] + assert res["ok"] is True + prompts = _rpc(client, database_id, "prompts/list")["result"]["prompts"] + assert any(p["name"] == "my_prompt" for p in prompts) + + +def test_unknown_method_is_method_not_found(client): + _create(client, "NoMethod") + database_id, _, _ = _only_server() + resp = _rpc(client, database_id, "tools/rename", {"definition": {"name": "x"}}) + assert resp["error"]["code"] == -32601 # not a real method → -32601 + + +def test_tools_delete_hard_deletes_and_prunes_prompts(client): + _create(client, "DelTool") + database_id, v_before, _ = _only_server() + _rpc(client, database_id, "tools/add", {"definition": _GOOD_TOOL}) + assert any(p["name"] == "explore_recent_orders" + for p in _rpc(client, database_id, "prompts/list")["result"]["prompts"]) + res = _rpc(client, database_id, "tools/delete", {"name": "recent_orders"})["result"] + assert res["ok"] is True and res["applied"]["op"] == "delete" + tools = {t["name"] for t in _rpc(client, database_id, "tools/list")["result"]["tools"]} + assert "recent_orders" not in tools # gone (hard delete) + prompts = {p["name"] for p in _rpc(client, database_id, "prompts/list")["result"]["prompts"]} + assert "explore_recent_orders" not in prompts # pruned by the cascade + + +def test_resources_delete_drops_table(client): + _create(client, "DelRes") + database_id, _, _ = _only_server() + resources = _rpc(client, database_id, "resources/list")["result"]["resources"] + entity = next(r for r in resources if not r["uri"].endswith("/schema")) + res = _rpc(client, database_id, "resources/delete", {"uri": entity["uri"]})["result"] + assert res["ok"] is True + with session_module.create_db_session() as db: + assert _table_count(db, database_id) == 0 # backing table dropped + re-inspected + + +def test_resources_delete_schema_is_rejected(client): + _create(client, "KeepSchema") + database_id, _, _ = _only_server() + resources = _rpc(client, database_id, "resources/list")["result"]["resources"] + schema = next(r for r in resources if r["uri"].endswith("/schema")) + resp = _rpc(client, database_id, "resources/delete", {"uri": schema["uri"]}) + assert resp["error"]["code"] == -32602 # schema resource is undeletable + + +def test_delete_removes_dir_and_rows(client): + from data_analysis_agent.config.settings import get_settings + from data_analysis_agent.tools.table_naming import sql_table_name + _create(client, "ToDelete") + database_id, _, _ = _only_server() + dataset_dir = Path(get_settings().datasets_dir) / sql_table_name("ToDelete") + assert dataset_dir.exists() + + r = client.post(f"/database/{database_id}/delete", follow_redirects=True) + assert r.status_code == 200 + with session_module.create_db_session() as db: + assert db.query(DatabaseRow).count() == 0 + assert db.query(McpToolRow).count() == 0 + assert not dataset_dir.exists() diff --git a/tests/integration/test_golden_path.py b/tests/integration/test_golden_path.py new file mode 100644 index 00000000..82c61c91 --- /dev/null +++ b/tests/integration/test_golden_path.py @@ -0,0 +1,103 @@ +"""Golden-path UI smoke test: upload CSV → create MCP server (auto-sync) → create session → ask a +question → see the answer inline. Stub mode, tmp SQLite.""" +import csv +import io +import re + +import pytest +from fastapi.testclient import TestClient + +import data_analysis_agent.db.session as session_module +from data_analysis_agent.db.database import Database + + +@pytest.fixture(autouse=True) +def _stub_env(monkeypatch): + monkeypatch.setenv("DATAANALYSIS_DATABASE_URL", "sqlite:///golden_test.db") + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", "") + + +@pytest.fixture(autouse=True) +def _use_sqlite(tmp_path, monkeypatch): + db = Database(f"sqlite:///{tmp_path / 'golden.db'}") + db._init_schema() + monkeypatch.setattr(session_module, "_db", db) + monkeypatch.setattr(session_module, "init_db", lambda: None) + monkeypatch.setenv("DATAANALYSIS_CHECKPOINT_DB", str(tmp_path / "ckpt.db")) + monkeypatch.setenv("DATAANALYSIS_DATASETS_DIR", str(tmp_path / "datasets")) + yield + db._dispose() + monkeypatch.setattr(session_module, "_db", None) + + +@pytest.fixture +def client(tmp_path, monkeypatch): + monkeypatch.setenv("DATAANALYSIS_UPLOAD_DIR", str(tmp_path / "uploads")) + import data_analysis_agent.llm.client as llm_module + llm_module._client = None + from data_analysis_agent.api import create_app + with TestClient(create_app(), raise_server_exceptions=True) as c: + yield c + + +def _make_csv() -> bytes: + buf = io.StringIO() + writer = csv.writer(buf) + writer.writerow(["product", "revenue", "units"]) + writer.writerow(["Widget A", 5000, 25]) + writer.writerow(["Widget B", 3000, 15]) + return buf.getvalue().encode() + + +def _create_server(client, name: str, filename: str = "data.csv") -> str: + """Run the upload → create two-step the UI performs; return the home HTML after create.""" + up = client.post("/database/upload", data={"database_name": name}, + files={"file": (filename, _make_csv(), "text/csv")}) + assert up.status_code == 200, up.text + uri = up.json()["uri"] + r = client.post("/database", data={"name": name, "database_type": "parquet", "database_uri": uri}, + follow_redirects=True) + assert r.status_code == 200, r.text + return r.text + + +def test_home_page_loads(client): + r = client.get("/") + assert r.status_code == 200 + assert "Databases" in r.text + assert "Sessions" in r.text + + +def test_stub_banner_visible_on_home(client): + assert "Stub mode" in client.get("/").text + + +def test_create_server_shows_on_home(client): + html = _create_server(client, "Sales DB") + assert "Sales DB" in html + + +def test_golden_path_end_to_end(client): + # 1. Upload CSV + create the MCP server (which auto-syncs into tools/resources/prompts) + home = _create_server(client, "Test DB", "test_data.csv") + + # 2. Extract the server id from the session-create checkboxes, then create a session + m = re.search(r'name="database_ids" value="([^"]+)"', home) + assert m, "database_ids checkbox not found on home page" + database_id = m.group(1) + r2 = client.post("/sessions", data={"database_ids": database_id}, follow_redirects=True) + assert r2.status_code == 200 + session_id = str(r2.url).rstrip("/").split("/")[-1].split("?")[0] + + # 3. Ask a question + r3 = client.post(f"/sessions/{session_id}/query", + data={"question": "What is the total revenue?"}, follow_redirects=True) + assert r3.status_code == 200 + assert "stub" in r3.text.lower() or "analysis" in r3.text.lower() + assert "total revenue" in r3.text.lower() + + +def test_health_endpoint(client): + r = client.get("/health") + assert r.status_code == 200 + assert r.json() == {"status": "ok"} diff --git a/tests/integration/test_list_pagination.py b/tests/integration/test_list_pagination.py new file mode 100644 index 00000000..9dd52ecf --- /dev/null +++ b/tests/integration/test_list_pagination.py @@ -0,0 +1,150 @@ +"""Integration tests for the AJAX-loaded list surfaces: + +- the relocated HTML-fragment endpoints (GET /databases, /sessions, /sessions/{id}/queries) with keyset + cursors carried in ``X-Next-Cursor``; +- the ``_meta`` enrichment the management UI reads off the MCP JSON-RPC ``*/list`` responses. + +All in stub mode against a tmp SQLite DB, with ``ui_page_size`` forced to 2 so paging is exercised. +""" +import csv +import io + +import pytest +from fastapi.testclient import TestClient + +import data_analysis_agent.db.session as session_module +from data_analysis_agent.db.database import Database +from data_analysis_agent.db.models import ( + DatabaseRow, + QueryRecordRow, + SessionDatabaseRow, + SessionRow, +) + + +@pytest.fixture(autouse=True) +def _env(tmp_path, monkeypatch): + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", "") + monkeypatch.setenv("DATAANALYSIS_UPLOAD_DIR", str(tmp_path / "uploads")) + monkeypatch.setenv("DATAANALYSIS_DATASETS_DIR", str(tmp_path / "datasets")) + monkeypatch.setenv("DATAANALYSIS_CHECKPOINT_DB", str(tmp_path / "ckpt.db")) + monkeypatch.setenv("DATAANALYSIS_UI_PAGE_SIZE", "2") # tiny pages so Prev/Next has work to do + db = Database(f"sqlite:///{tmp_path / 'app.db'}") + db._init_schema() + monkeypatch.setattr(session_module, "_db", db) + monkeypatch.setattr(session_module, "init_db", lambda: None) + yield + db._dispose() + monkeypatch.setattr(session_module, "_db", None) + + +@pytest.fixture +def client(): + import data_analysis_agent.llm.client as llm_module + llm_module._client = None + from data_analysis_agent.api import create_app + with TestClient(create_app(), raise_server_exceptions=True) as c: + yield c + + +def _orders() -> bytes: + buf = io.StringIO() + csv.writer(buf).writerows([["id", "amount"], [1, 5], [2, 7]]) + return buf.getvalue().encode() + + +def _make_database(client, name: str) -> str: + up = client.post("/database/upload", data={"database_name": name}, + files={"file": ("orders.csv", _orders(), "text/csv")}) + assert up.status_code == 200, up.text + r = client.post("/database", data={"name": name, "database_type": "parquet", "database_uri": up.json()["uri"]}, + follow_redirects=True) + assert r.status_code == 200 + with session_module.create_db_session() as db: + return db.query(DatabaseRow).filter(DatabaseRow.name == name).one().id + + +def _seed_sessions(database_id: str, n: int) -> list[str]: + ids = [] + with session_module.create_db_session() as db: + for i in range(n): + row = SessionRow(name=f"S{i}") + db.add(row) + db.flush() + db.add(SessionDatabaseRow(session_id=row.id, database_id=database_id)) + ids.append(row.id) + return ids + + +def _seed_queries(session_id: str, n: int) -> None: + with session_module.create_db_session() as db: + for i in range(n): + db.add(QueryRecordRow(session_id=session_id, question=f"Q{i}", status="completed", answer=f"A{i}")) + + +# --- relocated HTML-fragment endpoints (cursor + X-Next-Cursor) -------------- + +def test_databases_fragment_paginates(client): + for name in ("alpha", "beta", "gamma"): + _make_database(client, name) + p1 = client.get("/databases") + assert p1.status_code == 200 + assert p1.text.count("srv-row") == 2 # page size 2 + cursor = p1.headers.get("X-Next-Cursor") + assert cursor # a third database remains + p2 = client.get("/databases", params={"cursor": cursor}) + assert p2.text.count("srv-row") == 1 + assert "X-Next-Cursor" not in p2.headers # exhausted + + +def test_sessions_fragment_paginates_and_marks_active(client): + db_id = _make_database(client, "db") + ids = _seed_sessions(db_id, 3) + p1 = client.get("/sessions", params={"active": ids[0]}) + assert p1.status_code == 200 + assert p1.text.count("session-item") == 2 + assert p1.headers.get("X-Next-Cursor") + # the active session (most-recently-updated last → may be on a later page); fetch all and check the class + seen = p1.text + seen += client.get("/sessions", params={"cursor": p1.headers["X-Next-Cursor"], "active": ids[0]}).text + assert "session-item active" in seen + + +def test_queries_fragment_paginates(client): + db_id = _make_database(client, "db") + sess_id = _seed_sessions(db_id, 1)[0] + _seed_queries(sess_id, 3) + p1 = client.get(f"/sessions/{sess_id}/queries") + assert p1.status_code == 200 + assert p1.text.count('id="q-') == 2 # one turn container per record + assert p1.headers.get("X-Next-Cursor") + p2 = client.get(f"/sessions/{sess_id}/queries", params={"cursor": p1.headers["X-Next-Cursor"]}) + assert p2.text.count('id="q-') == 1 + assert "X-Next-Cursor" not in p2.headers + + +def test_invalid_cursor_is_400(client): + _make_database(client, "db") + r = client.get("/databases", params={"cursor": "not-a-real-cursor"}) + assert r.status_code == 400 + assert r.json()["detail"]["code"] == "INVALID_CURSOR" + + +# --- _meta enrichment on the JSON-RPC list surface --------------------------- + +def _rpc(client, database_id, method): + return client.post(f"/database/{database_id}", + json={"jsonrpc": "2.0", "id": 1, "method": method}).json()["result"] + + +def test_list_methods_carry_meta_for_the_ui(client): + database_id = _make_database(client, "db") + tool = _rpc(client, database_id, "tools/list")["tools"][0] + assert "sql_template" in tool["_meta"]["execution"] # editor payload, not in the public inputSchema + + resources = _rpc(client, database_id, "resources/list")["resources"] + assert all("kind" in r["_meta"] for r in resources) # drives the kind pill + edit branch + assert any(r["_meta"]["kind"] == "schema" for r in resources) + + prompts = _rpc(client, database_id, "prompts/list")["prompts"] + assert all("template" in p["_meta"] for p in prompts) diff --git a/tests/integration/test_pipeline.py b/tests/integration/test_pipeline.py index 079a9c5c..c71d0b1c 100644 --- a/tests/integration/test_pipeline.py +++ b/tests/integration/test_pipeline.py @@ -1,49 +1,112 @@ -"""Integration tests — require real LLM key (Anthropic or Gemini).""" +"""Integration test: stubbed pipeline runs end-to-end with no OpenRouter key.""" +import csv + import pytest -from sqlalchemy.orm import Session - -from graph.runner import run_agent -from db import session as session_module -from db.models import RunRow - - -@pytest.mark.usefixtures("_require_llm_key") -def test_pipeline_runs_end_to_end(_isolated_db): - run_id = run_agent("Explain why the sky is blue in one sentence.") - assert run_id is not None - with Session(session_module._engine) as s: - run = s.get(RunRow, run_id) - assert run is not None - assert run.status == "completed" - assert run.output_text and len(run.output_text) > 10 - assert run.error_message is None - - -@pytest.mark.usefixtures("_require_llm_key") -def test_pipeline_stores_input(_isolated_db): - input_text = "The quick brown fox." - run_id = run_agent(input_text) - with Session(session_module._engine) as s: - run = s.get(RunRow, run_id) - assert run.input_text == input_text - - -@pytest.mark.usefixtures("_require_llm_key") -def test_pipeline_via_api(api_client): - """Full HTTP round-trip: POST /runs -> 200 with output_text.""" - r = api_client.post("/runs", json={"input_text": "Say hello in three words."}) - assert r.status_code == 200 - body = r.json() - assert body["data"]["status"] == "completed" - assert body["data"]["output_text"] - assert not body["data"].get("error") - - -@pytest.mark.usefixtures("_require_llm_key") -def test_pipeline_error_surfaces_in_api(api_client): - """Error must appear in response body, never silently swallowed.""" - r = api_client.post("/runs", json={"input_text": "x"}) - assert r.status_code == 200 - body = r.json() - # Either output or error must be set - assert body["data"]["output_text"] or body["data"].get("error") + +import data_analysis_agent.db.session as session_module +from data_analysis_agent.db.database import Database +from data_analysis_agent.db.models import ( + AgentRunRow, + DatabaseRow, + QueryRecordRow, + SessionDatabaseRow, + SessionRow, +) +from data_analysis_agent.tools.ingester import FileIngester + + +@pytest.fixture(autouse=True) +def _stub_env(monkeypatch): + monkeypatch.setenv("DATAANALYSIS_DATABASE_URL", "sqlite:///stub_test.db") + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", "") + + +@pytest.fixture(autouse=True) +def _use_sqlite(tmp_path, monkeypatch): + db = Database(f"sqlite:///{tmp_path / 'test.db'}") + db._init_schema() + monkeypatch.setattr(session_module, "_db", db) + monkeypatch.setattr(session_module, "init_db", lambda: None) + monkeypatch.setenv("DATAANALYSIS_CHECKPOINT_DB", str(tmp_path / "ckpt.db")) + monkeypatch.setenv("DATAANALYSIS_DATASETS_DIR", str(tmp_path / "datasets")) + yield + db._dispose() + monkeypatch.setattr(session_module, "_db", None) + + +@pytest.fixture +def csv_file(tmp_path): + path = tmp_path / "sample.csv" + with path.open("w", newline="") as f: + writer = csv.writer(f) + writer.writerow(["region", "sales", "units"]) + writer.writerow(["North", 10000, 50]) + writer.writerow(["South", 8000, 40]) + writer.writerow(["East", 12000, 60]) + return str(path) + + +@pytest.fixture +def session_and_query(csv_file, tmp_path): + # Ingest into the database's datasets directory so the connector discovers the table live. + from data_analysis_agent.tools.table_naming import sql_table_name + FileIngester().ingest(csv_file, tmp_path / "datasets" / sql_table_name("sample_db"), "sample") + with session_module.create_db_session() as db: + srv = DatabaseRow(name="sample_db", type="parquet", uri="parquet:///sample_db", + description="Execute SQL SELECT queries against the dataset.") + db.add(srv) + db.flush() + sess = SessionRow(name="Test session") + db.add(sess) + db.flush() + db.add(SessionDatabaseRow(session_id=sess.id, database_id=srv.id)) + qr = QueryRecordRow(session_id=sess.id, question="What is the total sales?") + db.add(qr) + db.flush() + return sess.id, qr.id + + +def test_pipeline_runs_end_to_end(session_and_query): + from data_analysis_agent.graph.runner import run_pipeline + import data_analysis_agent.llm.client as llm_module + llm_module._client = None + + session_id, query_record_id = session_and_query + final_state = run_pipeline( + query_record_id=query_record_id, session_id=session_id, question="What is the total sales?", + ) + assert final_state.get("error") is None, f"Pipeline error: {final_state.get('error')}" + + with session_module.create_db_session() as s: + qr = s.get(QueryRecordRow, query_record_id) + assert qr is not None + assert qr.status == "completed" + assert qr.answer + assert qr.iteration_count == 1 + # single-level trace shape (no 'capability' key) + assert qr.query_history and "capability" not in qr.query_history[0] + runs = s.query(AgentRunRow).filter_by(query_record_id=query_record_id).all() + assert len(runs) == 1 and runs[0].status == "completed" + + +def _add_query(session_id: str, question: str) -> str: + with session_module.create_db_session() as db: + qr = QueryRecordRow(session_id=session_id, question=question) + db.add(qr) + db.flush() + return qr.id + + +def test_session_memory_accumulates_across_queries(session_and_query): + """Two queries in one session → the durable `conversation` carries both turns.""" + from data_analysis_agent.graph.runner import run_pipeline + import data_analysis_agent.llm.client as llm_module + llm_module._client = None + + session_id, qr1 = session_and_query + run_pipeline(query_record_id=qr1, session_id=session_id, question="What is the total sales?") + qr2 = _add_query(session_id, "And the average?") + final2 = run_pipeline(query_record_id=qr2, session_id=session_id, question="And the average?") + + convo = final2.get("conversation", []) + assert [t["question"] for t in convo] == ["What is the total sales?", "And the average?"], convo diff --git a/tests/unit/__init__.py b/tests/unit/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/api/__init__.py b/tests/unit/api/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/api/test_pagination.py b/tests/unit/api/test_pagination.py new file mode 100644 index 00000000..6de1681d --- /dev/null +++ b/tests/unit/api/test_pagination.py @@ -0,0 +1,61 @@ +"""Unit tests for the keyset (cursor) pagination helper backing the AJAX-loaded UI lists.""" +from datetime import datetime, timedelta, timezone + +import pytest +from sqlalchemy import create_engine +from sqlalchemy.orm import Session + +from data_analysis_agent.api._pagination import ( + InvalidCursor, + decode_cursor, + encode_cursor, + keyset_page, +) +from data_analysis_agent.db.models import Base, SessionRow + + +def _session_with_rows(n: int) -> Session: + engine = create_engine("sqlite:///:memory:") + Base.metadata.create_all(engine) + s = Session(engine) + base = datetime(2026, 1, 1, tzinfo=timezone.utc) + for i in range(n): + s.add(SessionRow(id=f"id{i:02d}", name=f"s{i}", + created_at=base + timedelta(minutes=i), + updated_at=base + timedelta(minutes=i))) + s.commit() + return s + + +def _page(s, cursor, limit, descending): + return keyset_page(s.query(SessionRow), sort_col=SessionRow.created_at, id_col=SessionRow.id, + sort_attr="created_at", cursor=cursor, limit=limit, descending=descending) + + +def test_cursor_roundtrip(): + dt = datetime(2026, 1, 2, 3, 4, 5, tzinfo=timezone.utc) + assert decode_cursor(encode_cursor(dt, "abc")) == (dt, "abc") + assert decode_cursor(None) is None + + +def test_decode_invalid_raises(): + with pytest.raises(InvalidCursor): + decode_cursor("@@@ not a cursor @@@") + + +def test_descending_walk_to_exhaustion(): + s = _session_with_rows(7) + rows, cur = _page(s, None, 3, True) + assert [r.name for r in rows] == ["s6", "s5", "s4"] and cur + rows2, cur2 = _page(s, cur, 3, True) + assert [r.name for r in rows2] == ["s3", "s2", "s1"] and cur2 + rows3, cur3 = _page(s, cur2, 3, True) + assert [r.name for r in rows3] == ["s0"] + assert cur3 is None # last page → no next cursor + + +def test_ascending_exact_limit_has_no_next(): + s = _session_with_rows(4) + rows, cur = _page(s, None, 4, False) + assert [r.name for r in rows] == ["s0", "s1", "s2", "s3"] + assert cur is None # exactly `limit` rows → no further page diff --git a/tests/unit/config/__init__.py b/tests/unit/config/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/config/test_settings.py b/tests/unit/config/test_settings.py new file mode 100644 index 00000000..5d052c2d --- /dev/null +++ b/tests/unit/config/test_settings.py @@ -0,0 +1,24 @@ +import pytest +from data_analysis_agent.config.settings import get_settings + + +def test_defaults(monkeypatch): + monkeypatch.setenv("DATAANALYSIS_DATABASE_URL", "sqlite:///test.db") + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", "") + s = get_settings() + assert s.database_url == "sqlite:///test.db" + assert s.resolved_llm_provider == "stub" + + +def test_openrouter_provider_when_key_set(monkeypatch): + monkeypatch.setenv("DATAANALYSIS_DATABASE_URL", "sqlite:///test.db") + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", "sk-or-fake-key-123") + s = get_settings() + assert s.resolved_llm_provider == "openrouter" + + +def test_inline_comment_stripped_from_key(monkeypatch): + monkeypatch.setenv("DATAANALYSIS_DATABASE_URL", "sqlite:///test.db") + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", " # empty comment ") + s = get_settings() + assert s.resolved_llm_provider == "stub" diff --git a/tests/unit/db/__init__.py b/tests/unit/db/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/db/test_migration.py b/tests/unit/db/test_migration.py new file mode 100644 index 00000000..029233c5 --- /dev/null +++ b/tests/unit/db/test_migration.py @@ -0,0 +1,73 @@ +"""Migration test for the fresh single initial schema (835cdb8ae996): upgrade from empty builds the +whole MCP-server schema, the partial-unique index over active capability rows is enforced, and +downgrade to base drops everything (round-trip).""" +import sqlite3 +from pathlib import Path + +import pytest +from alembic import command +from alembic.config import Config + +_REPO = Path(__file__).resolve().parents[3] +_TABLES = { + "databases", "mcp_tools", "mcp_resources", "mcp_prompts", + "sessions", "session_databases", "query_records", "agent_runs", +} + + +def _cfg() -> Config: + cfg = Config(str(_REPO / "alembic.ini")) + cfg.set_main_option("script_location", str(_REPO / "alembic")) + return cfg + + +@pytest.fixture +def cfg_db(tmp_path, monkeypatch): + db_path = tmp_path / "mig.db" + monkeypatch.setenv("DATAANALYSIS_DATABASE_URL", f"sqlite:///{db_path}") + return _cfg(), db_path + + +def _table_names(db_path: Path) -> set[str]: + conn = sqlite3.connect(db_path) + try: + return {r[0] for r in conn.execute("SELECT name FROM sqlite_master WHERE type='table'")} + finally: + conn.close() + + +def test_upgrade_creates_schema(cfg_db): + cfg, db_path = cfg_db + command.upgrade(cfg, "head") + assert _TABLES <= _table_names(db_path) + + +def test_partial_unique_index_enforced(cfg_db): + cfg, db_path = cfg_db + command.upgrade(cfg, "head") + conn = sqlite3.connect(db_path) + conn.execute( + "INSERT INTO databases (id,name,type,uri,version,created_at) " + "VALUES ('s','s','parquet','parquet:///s',1,'2026-01-01 00:00:00')" + ) + conn.execute( + "INSERT INTO mcp_tools (id,database_id,name,description,execution_json," + "created_version,created_at,updated_at) " + "VALUES ('t1','s','dup','d','{}',1,'2026-01-01 00:00:00','2026-01-01 00:00:00')" + ) + conn.commit() + with pytest.raises(sqlite3.IntegrityError): + conn.execute( + "INSERT INTO mcp_tools (id,database_id,name,description,execution_json," + "created_version,created_at,updated_at) " + "VALUES ('t2','s','dup','d','{}',1,'2026-01-01 00:00:00','2026-01-01 00:00:00')" + ) + conn.commit() + conn.close() + + +def test_downgrade_reverses(cfg_db): + cfg, db_path = cfg_db + command.upgrade(cfg, "head") + command.downgrade(cfg, "base") + assert not (_TABLES & _table_names(db_path)) diff --git a/tests/unit/db/test_models.py b/tests/unit/db/test_models.py new file mode 100644 index 00000000..2a6c33d1 --- /dev/null +++ b/tests/unit/db/test_models.py @@ -0,0 +1,133 @@ +import pytest +from sqlalchemy import create_engine +from sqlalchemy.orm import Session + +from data_analysis_agent.db.models import ( + AgentRunRow, + Base, + McpPromptRow, + McpResourceRow, + DatabaseRow, + McpToolRow, + QueryRecordRow, + SessionDatabaseRow, + SessionRow, +) + + +@pytest.fixture +def db(tmp_path): + engine = create_engine(f"sqlite:///{tmp_path}/test.db") + Base.metadata.create_all(engine) + with Session(engine) as session: + yield session + engine.dispose() + + +def test_create_database(db): + srv = DatabaseRow(name="sales", type="parquet", uri="parquet:///sales") + db.add(srv) + db.commit() + assert srv.id is not None + assert srv.version == 1 + + +def test_server_name_and_uri_unique(db): + db.add(DatabaseRow(name="a", type="parquet", uri="parquet:///a")) + db.commit() + db.add(DatabaseRow(name="a", type="parquet", uri="parquet:///b")) + with pytest.raises(Exception): + db.commit() + db.rollback() + + +def _tool(database_id, name, sql="SELECT 1", params=None, description="d") -> McpToolRow: + """Build a tool row with the execution object (the canonical store).""" + t = McpToolRow(database_id=database_id, name=name, description=description, created_version=1) + t.execution = {"sql_template": sql, "parameters": params or []} + return t + + +def test_tool_execution_accessors_and_partial_unique(db): + srv = DatabaseRow(name="s", type="parquet", uri="parquet:///s") + db.add(srv) + db.flush() + t = _tool(srv.id, "list_orders", "SELECT * FROM orders WHERE q = $q", + [{"name": "q", "type": "string", "description": "filter"}]) + db.add(t) + db.commit() + db.refresh(t) + assert t.sql_template.startswith("SELECT") # derived from execution + assert t.parameters[0]["name"] == "q" + assert t.input_schema["properties"]["q"]["type"] == "string" # MCP inputSchema derived from params + + # A second ACTIVE tool with the same (database_id, name) violates the partial-unique index. + db.add(_tool(srv.id, "list_orders", "SELECT 2")) + with pytest.raises(Exception): + db.commit() + db.rollback() + + +def test_partial_unique_allows_readd_after_soft_delete(db): + from datetime import datetime, timezone + srv = DatabaseRow(name="s2", type="parquet", uri="parquet:///s2") + db.add(srv) + db.flush() + old = _tool(srv.id, "t", "SELECT 1", description="old") + db.add(old) + db.commit() + old.deleted_at = datetime.now(timezone.utc) # soft-delete + db.add(_tool(srv.id, "t", "SELECT 2", description="new")) + db.commit() # re-add of a soft-deleted name must NOT collide + active = db.query(McpToolRow).filter_by(database_id=srv.id, name="t", deleted_at=None).all() + assert len(active) == 1 and active[0].description == "new" + + +def test_resource_uri_unique_and_size(db): + srv = DatabaseRow(name="s_uri", type="parquet", uri="parquet:///s_uri") + db.add(srv) + db.flush() + r = McpResourceRow(database_id=srv.id, uri="entity://s_uri/orders", name="orders", + kind="primary_entity", size=2048, created_version=1) + db.add(r) + db.commit() + assert db.get(McpResourceRow, r.id).size == 2048 + # A second ACTIVE resource with the same URI violates the DB-level partial-unique index. + db.add(McpResourceRow(database_id=srv.id, uri="entity://s_uri/orders", name="dup", + kind="primary_entity", created_version=1)) + with pytest.raises(Exception): + db.commit() + db.rollback() + + +def test_resource_and_prompt_rows(db): + srv = DatabaseRow(name="s3", type="parquet", uri="parquet:///s3") + db.add(srv) + db.flush() + r = McpResourceRow(database_id=srv.id, uri="dataset://s3/schema", name="schema", kind="schema") + r.content = {"tables": {}} + p = McpPromptRow(database_id=srv.id, name="explore") + db.add_all([r, p]) + db.commit() + db.refresh(r) + assert r.content == {"kind": "schema", "tables": {}} + assert p.arguments == [] + + +def test_session_servers_and_query_record(db): + srv = DatabaseRow(name="s4", type="parquet", uri="parquet:///s4") + db.add(srv) + db.flush() + sess = SessionRow(name="Test session") + db.add(sess) + db.flush() + db.add(SessionDatabaseRow(session_id=sess.id, database_id=srv.id)) + qr = QueryRecordRow(session_id=sess.id, question="What is the average?") + db.add(qr) + db.flush() + db.add(AgentRunRow(query_record_id=qr.id)) + db.commit() + assert qr.status == "pending" + assert qr.query_history == [] + links = db.query(SessionDatabaseRow).filter_by(session_id=sess.id).all() + assert len(links) == 1 diff --git a/tests/unit/domain/__init__.py b/tests/unit/domain/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/domain/test_models.py b/tests/unit/domain/test_models.py new file mode 100644 index 00000000..3e36d1ac --- /dev/null +++ b/tests/unit/domain/test_models.py @@ -0,0 +1,28 @@ +from data_analysis_agent.domain.models import Database, Session, QueryRecord, AgentRunRecord + + +def test_database_defaults(): + s = Database(name="sales") + assert s.id is not None + assert s.type == "parquet" + assert s.version == 1 + + +def test_session_defaults(): + s = Session(database_ids=["s1", "s2"]) + assert s.id is not None + assert s.name is None + assert s.database_ids == ["s1", "s2"] + + +def test_query_record_defaults(): + qr = QueryRecord(session_id="s1", question="What is the total?") + assert qr.id is not None + assert qr.status == "pending" + assert qr.answer is None + + +def test_agent_run_record_defaults(): + run = AgentRunRecord(query_record_id="xyz") + assert run.id is not None + assert run.status == "pending" diff --git a/tests/unit/graph/__init__.py b/tests/unit/graph/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/graph/test_agent.py b/tests/unit/graph/test_agent.py deleted file mode 100644 index 7acab2e1..00000000 --- a/tests/unit/graph/test_agent.py +++ /dev/null @@ -1,4 +0,0 @@ -def test_graph_compiles(): - """Graph compiles without requiring any env vars.""" - from graph.agent import agentic_ai - assert agentic_ai is not None diff --git a/tests/unit/graph/test_execution.py b/tests/unit/graph/test_execution.py new file mode 100644 index 00000000..d5a8500b --- /dev/null +++ b/tests/unit/graph/test_execution.py @@ -0,0 +1,35 @@ +"""Unit tests for single-level parsing + the optional Phase-B `capability` field.""" +from data_analysis_agent.graph.execution import observation, parse_tool_call + + +def test_parse_free_sql_has_no_capability_key(): + call, err = parse_tool_call('{"tool": "s", "arguments": {"query": "SELECT 1"}}') + assert err is None + assert call == {"tool": "s", "arguments": {"query": "SELECT 1"}} # byte-identical to Phase A + + +def test_parse_generated_tool_carries_capability(): + call, err = parse_tool_call('{"tool": "s", "capability": "top", "arguments": {"n": 1}}') + assert err is None + assert call["tool"] == "s" and call["capability"] == "top" and call["arguments"] == {"n": 1} + + +def test_parse_missing_tool_is_error(): + call, err = parse_tool_call('{"arguments": {}}') + assert call is None and err is not None + + +def test_parse_bad_json_is_error(): + call, err = parse_tool_call("not json") + assert call is None and err is not None + + +def test_observation_omits_capability_when_absent(): + assert observation("s", {"query": "SELECT 1"}, "r", False) == { + "tool": "s", "arguments": {"query": "SELECT 1"}, "result": "r", "is_error": False + } + + +def test_observation_includes_capability_when_present(): + entry = observation("s", {"n": 1}, "r", False, "top") + assert entry["capability"] == "top" diff --git a/tests/unit/test_api.py b/tests/unit/test_api.py deleted file mode 100644 index 3028c3ff..00000000 --- a/tests/unit/test_api.py +++ /dev/null @@ -1,45 +0,0 @@ -"""API contract tests — no LLM key required, graph is not invoked.""" -import pytest -from unittest.mock import patch - - -def test_health(api_client): - r = api_client.get("/health") - assert r.status_code == 200 - assert r.json()["data"]["status"] == "ok" - - -def test_run_returns_200_with_output(api_client, _isolated_db): - from sqlalchemy.orm import Session - from db.models import RunRow - - # Pre-insert a completed run so run_agent just returns its id - with Session(_isolated_db) as s: - row = RunRow(input_text="test", status="completed", output_text="Hello from mock LLM") - s.add(row) - s.commit() - run_id = row.id - - with patch("api.runs.run_agent", return_value=run_id): - r = api_client.post("/runs", json={"input_text": "test"}) - - assert r.status_code == 200 - data = r.json() - assert data["data"]["output_text"] == "Hello from mock LLM" - - -def test_run_missing_body(api_client): - r = api_client.post("/runs", json={}) - assert r.status_code == 422 - - -def test_get_run_not_found(api_client): - r = api_client.get("/runs/nonexistent-id") - assert r.status_code == 404 - - -def test_run_empty_input_rejected(api_client): - r = api_client.post("/runs", json={"input_text": ""}) - # empty string is technically valid JSON — server accepts it; LLM handles it - # just confirm we get a structured response - assert r.status_code in (200, 422, 500) diff --git a/tests/unit/test_db.py b/tests/unit/test_db.py deleted file mode 100644 index 7c55e360..00000000 --- a/tests/unit/test_db.py +++ /dev/null @@ -1,53 +0,0 @@ -"""DB layer tests — no LLM key required.""" -from sqlalchemy.orm import Session -from db.models import RunRow -import db.session as session_module - - -def test_run_row_roundtrip(_isolated_db): - with Session(_isolated_db) as s: - run = RunRow(input_text="hello world") - s.add(run) - s.commit() - run_id = run.id - - with Session(_isolated_db) as s: - fetched = s.get(RunRow, run_id) - assert fetched is not None - assert fetched.input_text == "hello world" - assert fetched.status == "pending" - assert fetched.output_text is None - - -def test_run_row_status_update(_isolated_db): - with Session(_isolated_db) as s: - run = RunRow(input_text="test") - s.add(run) - s.commit() - run_id = run.id - - with Session(_isolated_db) as s: - run = s.get(RunRow, run_id) - run.status = "completed" - run.output_text = "some output" - s.commit() - - with Session(_isolated_db) as s: - run = s.get(RunRow, run_id) - assert run.status == "completed" - assert run.output_text == "some output" - - -def test_multiple_runs_independent(_isolated_db): - ids = [] - with Session(_isolated_db) as s: - for i in range(3): - run = RunRow(input_text=f"input {i}") - s.add(run) - s.commit() - # fetch all - runs = s.query(RunRow).all() - ids = [r.id for r in runs] - - assert len(ids) == 3 - assert len(set(ids)) == 3 # all unique diff --git a/tests/unit/test_settings.py b/tests/unit/test_settings.py deleted file mode 100644 index 5d10ce8d..00000000 --- a/tests/unit/test_settings.py +++ /dev/null @@ -1,54 +0,0 @@ -"""Settings + provider auto-detection — no LLM key required.""" -import pytest -import os - - -def test_auto_detects_anthropic(monkeypatch, tmp_path): - monkeypatch.setenv("AGENT_ANTHROPIC_API_KEY", "sk-ant-fake") - monkeypatch.setenv("AGENT_GEMINI_API_KEY", "") - monkeypatch.setenv("AGENT_LLM_PROVIDER", "") - monkeypatch.setenv("AGENT_DATABASE_URL", f"sqlite:///{tmp_path}/t.db") - - import config.settings as m - m._settings = None - s = m.get_settings() - assert s.anthropic_api_key == "sk-ant-fake" - assert s.gemini_api_key == "" - - -def test_auto_detects_gemini(monkeypatch, tmp_path): - monkeypatch.setenv("AGENT_ANTHROPIC_API_KEY", "") - monkeypatch.setenv("AGENT_GEMINI_API_KEY", "AIza-fake") - monkeypatch.setenv("AGENT_LLM_PROVIDER", "") - monkeypatch.setenv("AGENT_DATABASE_URL", f"sqlite:///{tmp_path}/t.db") - - import config.settings as m - m._settings = None - s = m.get_settings() - assert s.gemini_api_key == "AIza-fake" - - -def test_provider_raises_with_no_key(monkeypatch, tmp_path): - monkeypatch.setenv("AGENT_ANTHROPIC_API_KEY", "") - monkeypatch.setenv("AGENT_GEMINI_API_KEY", "") - monkeypatch.setenv("AGENT_LLM_PROVIDER", "") - monkeypatch.setenv("AGENT_DATABASE_URL", f"sqlite:///{tmp_path}/t.db") - - import config.settings as m - m._settings = None - - from llm.client import _make_provider - with pytest.raises(RuntimeError, match="No LLM provider configured"): - _make_provider() - - -def test_explicit_provider_wins(monkeypatch, tmp_path): - monkeypatch.setenv("AGENT_ANTHROPIC_API_KEY", "sk-ant-fake") - monkeypatch.setenv("AGENT_GEMINI_API_KEY", "AIza-fake") - monkeypatch.setenv("AGENT_LLM_PROVIDER", "gemini") - monkeypatch.setenv("AGENT_DATABASE_URL", f"sqlite:///{tmp_path}/t.db") - - import config.settings as m - m._settings = None - s = m.get_settings() - assert s.llm_provider == "gemini" diff --git a/tests/unit/test_smoke.py b/tests/unit/test_smoke.py index c24a68e6..989e21b4 100644 --- a/tests/unit/test_smoke.py +++ b/tests/unit/test_smoke.py @@ -1,4 +1,5 @@ -def test_package_importable(): - from config.settings import get_settings # noqa: F401 - from api._common import ok # noqa: F401 - from db.models import Base # noqa: F401 +import data_analysis_agent + + +def test_version(): + assert data_analysis_agent.__version__ == "0.1.0" diff --git a/tests/unit/tools/__init__.py b/tests/unit/tools/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/tests/unit/tools/test_connectors.py b/tests/unit/tools/test_connectors.py new file mode 100644 index 00000000..4521dac1 --- /dev/null +++ b/tests/unit/tools/test_connectors.py @@ -0,0 +1,135 @@ +"""Unit tests for the connector seam: DatasetURI (credential-free display) and the ParquetConnector +(connection-check + build a server with a generic ``query`` tool and within-server JOINs), exercised +through the real in-memory MCP client.""" +import asyncio + +import pandas as pd +import pytest +from mcp.shared.memory import create_connected_server_and_client_session + +from data_analysis_agent.tools.connectors.base import DatasetConnectionError, get_connector +from data_analysis_agent.tools.connectors.parquet import ParquetConnector +from data_analysis_agent.tools.connectors.uri import DatasetURI + + +def test_uri_internal_parquet(): + u = DatasetURI("parquet:///Q2%20Sales") + assert u.scheme == "parquet" + assert u.is_internal is True + assert u.database == "Q2 Sales" # URL-decoded + assert u.host is None and u.username is None and u.has_password is False + assert u.display() == "parquet:///Q2%20Sales" + + +def test_uri_external_strips_credentials(): + u = DatasetURI("postgresql://analyst:secret@db.internal:5432/sales") + assert u.scheme == "postgresql" + assert u.host == "db.internal" and u.port == 5432 + assert u.username == "analyst" and u.has_password is True + assert u.database == "sales" + shown = u.display() + assert shown == "postgresql://db.internal:5432/sales" + assert "secret" not in shown and "analyst" not in shown # credentials never displayed + + +def _two_table_server(tmp_path, monkeypatch): + """A parquet database whose two tables the connector will discover from its datasets directory.""" + monkeypatch.setenv("DATAANALYSIS_DATASETS_DIR", str(tmp_path / "datasets")) + directory = tmp_path / "datasets" / "sales_db" + directory.mkdir(parents=True) + pd.DataFrame({"id": [1, 2, 3], "cust": [10, 10, 20], "amount": [5, 7, 3]}).to_parquet(directory / "orders.parquet") + pd.DataFrame({"id": [10, 20], "region": ["N", "S"]}).to_parquet(directory / "customers.parquet") + return {"name": "sales_db", "type": "parquet", "uri": "parquet:///sales_db"} + + +def test_parquet_connection_check_ok_and_corrupt(tmp_path, monkeypatch): + server = _two_table_server(tmp_path, monkeypatch) + ParquetConnector(server).connection_check() # no raise + + (tmp_path / "datasets" / "sales_db" / "broken.parquet").write_text("not a parquet file") + with pytest.raises(DatasetConnectionError): + ParquetConnector(server).connection_check() + + +def test_get_connector_dispatches_to_parquet(tmp_path, monkeypatch): + server = _two_table_server(tmp_path, monkeypatch) + assert isinstance(get_connector(server), ParquetConnector) + + +def test_get_connector_dispatches_by_type(): + from data_analysis_agent.tools.connectors.postgres import PostgresConnector + from data_analysis_agent.tools.connectors.sqlite import SQLiteConnector + from data_analysis_agent.tools.connectors.mongodb import MongoDBConnector + from data_analysis_agent.tools.connectors.snowflake import SnowflakeConnector + # External databases are always enabled; dispatch attempts no connection (drivers import lazily). + assert isinstance(get_connector({"name": "x", "type": "postgresql", "uri": "postgresql://h/db"}), PostgresConnector) + assert isinstance(get_connector({"name": "x", "type": "sqlite", "uri": "sqlite:///x.db"}), SQLiteConnector) + assert isinstance(get_connector({"name": "x", "type": "mongodb", "uri": "mongodb://h/db"}), MongoDBConnector) + assert isinstance(get_connector({"name": "x", "type": "snowflake", "uri": "snowflake://u:p@a/DB/SC"}), SnowflakeConnector) + + +def test_sqlite_connector_discovers_and_queries(tmp_path): + import sqlite3 + from data_analysis_agent.tools.connectors.sqlite import SQLiteConnector + db_path = tmp_path / "shop.db" + conn = sqlite3.connect(db_path) + conn.execute("CREATE TABLE orders (id INTEGER, amount INTEGER)") + conn.executemany("INSERT INTO orders VALUES (?, ?)", [(1, 5), (2, 7)]) + conn.commit() + conn.close() + + c = SQLiteConnector({"name": "shop", "type": "sqlite", "uri": f"sqlite:///{db_path}"}) + c.connection_check() # no raise + tables = c.discover_tables() + assert [t["table_name"] for t in tables] == ["orders"] + assert tables[0]["column_names"] == ["id", "amount"] and tables[0]["row_count"] == 2 + + try: + fast = c.build_server(["orders"]) + except DatasetConnectionError as exc: + pytest.skip(f"duckdb sqlite extension unavailable offline: {exc}") + + async def body(): + async with create_connected_server_and_client_session(fast) as s: + res = await s.call_tool("query", {"query": "SELECT SUM(amount) AS t FROM orders"}) + return res.content[0].text, res.isError + + text, is_error = asyncio.run(body()) + fast._duckdb_conn.close() + assert is_error is False and text.strip() == "t\n12" + + +def test_sqlite_discovers_foreign_keys(tmp_path): + import sqlite3 + from data_analysis_agent.tools.connectors.sqlite import SQLiteConnector + db_path = tmp_path / "fk.db" + conn = sqlite3.connect(db_path) + conn.execute("CREATE TABLE customers (id INTEGER PRIMARY KEY)") + conn.execute("CREATE TABLE orders (id INTEGER PRIMARY KEY, " + "customer_id INTEGER REFERENCES customers(id))") + conn.commit() + conn.close() + rels = SQLiteConnector({"name": "fk", "type": "sqlite", "uri": f"sqlite:///{db_path}"}).discover_relationships() + assert rels == [{"from_table": "orders", "from_column": "customer_id", + "to_table": "customers", "to_column": "id"}] # canonical FK-edge format + + +def test_parquet_build_server_generic_query_with_join(tmp_path, monkeypatch): + server = _two_table_server(tmp_path, monkeypatch) + fast = ParquetConnector(server).build_server(["orders", "customers"]) + + async def body(): + async with create_connected_server_and_client_session(fast) as s: + listed = await s.list_tools() + names = sorted(t.name for t in listed.tools) + res = await s.call_tool("query", { + "query": "SELECT c.region, SUM(o.amount) AS total FROM orders o " + "JOIN customers c ON o.cust = c.id GROUP BY c.region ORDER BY c.region" + }) + return names, res.content[0].text, res.isError + + names, text, is_error = asyncio.run(body()) + fast._duckdb_conn.close() + assert names == ["query"] # one generic tool per server + assert is_error is False + assert text.strip() == "region,total\nN,12\nS,3" diff --git a/tests/unit/tools/test_mcp_pool.py b/tests/unit/tools/test_mcp_pool.py new file mode 100644 index 00000000..c1525a6f --- /dev/null +++ b/tests/unit/tools/test_mcp_pool.py @@ -0,0 +1,227 @@ +"""Unit tests for the session pool: flat snapshot, server routing, within-server JOINs, reuse, LRU +eviction, cleanup, and Phase-B hybrid routing (generated GET-API tools via optional `capability`). +Servers are stubbed (no DB) by patching ``_load_databases``; the in-process MCP servers + DuckDB are real.""" +import asyncio + +import pandas as pd +import pytest + +import data_analysis_agent.tools.mcp.pool as pool_module +from data_analysis_agent.tools.mcp.pool import SessionPoolManager + + +@pytest.fixture(autouse=True) +def _datasets_dir(monkeypatch, tmp_path): + """Point the connector's inspection at this test's datasets directory.""" + monkeypatch.setenv("DATAANALYSIS_DATASETS_DIR", str(tmp_path / "datasets")) + + +def _server(tmp_path, name, tables_spec, gen_tools=None): + """Build a ``(server_dict, tables, gen_tools)`` triple (tables in the resources/`discover` shape). + + Writes the Parquet files at the canonical location so ``build_server(table_names)`` registers them. + ``tables`` stands in for what ``active_entity_tables`` would return from the resources table. + """ + from data_analysis_agent.tools.table_naming import sql_table_name + directory = tmp_path / "datasets" / sql_table_name(name) + directory.mkdir(parents=True, exist_ok=True) + tables = [] + for table_name, frame in tables_spec.items(): + pd.DataFrame(frame).to_parquet(directory / f"{table_name}.parquet") + tables.append({"table_name": table_name, "column_names": list(frame.keys()), + "schema": [{"name": c} for c in frame], "row_count": len(next(iter(frame.values())))}) + server = {"id": name, "name": name, "type": "parquet", "uri": f"parquet:///{name}", + "description": f"Server {name}"} + return server, tables, gen_tools or [] + + +@pytest.fixture +def patch_servers(monkeypatch): + """Return a mutable {session_id: [(server, tables, gen_tools), ...]} map, bypassing the DB.""" + mapping: dict[str, list] = {} + monkeypatch.setattr(pool_module, "_load_databases", lambda sid: mapping.get(sid, [])) + return mapping + + +def test_snapshot_flat_and_single_level_routing(tmp_path, patch_servers): + patch_servers["s1"] = [_server(tmp_path, "sales_db", { + "orders": {"id": [1, 2, 3], "cust": [10, 10, 20], "amount": [5, 7, 3]}, + "customers": {"id": [10, 20], "region": ["N", "S"]}, + })] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + snap = mgr.snapshot("s1") + ok = await mgr.call_tool("s1", "sales_db", { + "query": "SELECT c.region, SUM(o.amount) AS t FROM orders o JOIN customers c " + "ON o.cust = c.id GROUP BY c.region ORDER BY c.region" + }) + bad = await mgr.call_tool("s1", "nope", {"query": "SELECT 1"}) + return snap, ok, bad + + snap, ok, bad = asyncio.run(body()) + assert len(snap) == 1 and snap[0]["tool"] == "sales_db" + assert sorted(t["table"] for t in snap[0]["tables"]) == ["customers", "orders"] + assert snap[0]["capabilities"] == [] # no generated tools + assert ok == ("region,t\nN,12\nS,3", False) # within-server JOIN + assert bad[1] is True and "Unknown tool" in bad[0] + + +def test_snapshot_carries_tables_and_columns(tmp_path, patch_servers): + patch_servers["s1"] = [_server(tmp_path, "d", {"orders": {"id": [1], "total": [5]}})] + mgr = SessionPoolManager(8, 1000) + asyncio.run(mgr.acquire("s1")) + snap = mgr.snapshot("s1")[0] + assert snap["description"] == "Server d" + assert snap["tables"][0] == {"table": "orders", "columns": ["id", "total"]} + + +def test_pool_never_inspects_the_store(tmp_path, patch_servers, monkeypatch): + """The pool builds + queries entirely from the resources table — it must NOT call discover_tables.""" + import data_analysis_agent.tools.connectors.parquet as parquet_mod + monkeypatch.setattr(parquet_mod.ParquetConnector, "discover_tables", + lambda self: (_ for _ in ()).throw(AssertionError("pool inspected the store!"))) + patch_servers["s1"] = [_server(tmp_path, "shop", {"products": {"name": ["A", "B"], "n": [1, 2]}})] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + return await mgr.call_tool("s1", "shop", {"query": "SELECT COUNT(*) AS c FROM products"}) + + text, is_error = asyncio.run(body()) + assert is_error is False and text.strip() == "c\n2" # built + queried with no discover_tables call + + +def test_non_select_is_recoverable_error(tmp_path, patch_servers): + patch_servers["s1"] = [_server(tmp_path, "d", {"t": {"x": [1]}})] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + return await mgr.call_tool("s1", "d", {"query": "DROP TABLE t"}) + + text, is_error = asyncio.run(body()) + assert is_error is True and "SELECT" in text + + +# --- Phase B: hybrid generated-tool routing --------------------------------- + +def _gen_tool(name, sql, params=None): + props = {p: {"type": "integer"} for p in (params or [])} + return {"name": name, "description": f"gen {name}", "sql_template": sql, + "input_schema": {"type": "object", "properties": props}} + + +def test_snapshot_includes_capabilities(tmp_path, patch_servers): + gt = [_gen_tool("top_products", "SELECT name FROM products WHERE revenue > $min", ["min"])] + patch_servers["s1"] = [_server(tmp_path, "shop", {"products": {"name": ["A", "B"], "revenue": [100, 50]}}, gt)] + mgr = SessionPoolManager(8, 1000) + asyncio.run(mgr.acquire("s1")) + caps = mgr.snapshot("s1")[0]["capabilities"] + assert caps and caps[0]["name"] == "top_products" and caps[0]["params"] == ["min"] + + +def test_call_generated_tool_binds_params(tmp_path, patch_servers): + gt = [_gen_tool("top_products", "SELECT name FROM products WHERE revenue > $min ORDER BY name", ["min"])] + patch_servers["s1"] = [_server(tmp_path, "shop", {"products": {"name": ["A", "B"], "revenue": [100, 50]}}, gt)] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + return await mgr.call_tool("s1", "shop", {"min": 60}, capability="top_products") + + text, is_error = asyncio.run(body()) + assert is_error is False + assert text.strip() == "name\nA" # only revenue>60 → A; param bound + + +def test_capability_absent_runs_free_sql(tmp_path, patch_servers): + gt = [_gen_tool("noop", "SELECT 1 AS x")] + patch_servers["s1"] = [_server(tmp_path, "shop", {"products": {"name": ["A"]}}, gt)] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + return await mgr.call_tool("s1", "shop", {"query": "SELECT COUNT(*) AS c FROM products"}) + + assert asyncio.run(body()) == ("c\n1", False) # free SQL still routes to generic tool + + +def test_unknown_capability_is_recoverable(tmp_path, patch_servers): + patch_servers["s1"] = [_server(tmp_path, "shop", {"products": {"name": ["A"]}}, [_gen_tool("x", "SELECT 1")])] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + return await mgr.call_tool("s1", "shop", {}, capability="nope") + + text, is_error = asyncio.run(body()) + assert is_error is True and "Unknown capability" in text and "free SQL" in text + + +def test_free_sql_blocks_file_reading_functions(tmp_path, patch_servers): + patch_servers["s1"] = [_server(tmp_path, "d", {"t": {"x": [1]}})] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + return await mgr.call_tool("s1", "d", {"query": "SELECT * FROM read_text('/etc/hosts')"}) + + text, is_error = asyncio.run(body()) + assert is_error is True and "Disallowed function" in text # arbitrary file read blocked + + +def test_generated_tool_blocks_non_select(tmp_path, patch_servers): + gt = [_gen_tool("danger", "DROP TABLE products")] + patch_servers["s1"] = [_server(tmp_path, "shop", {"products": {"name": ["A"]}}, gt)] + mgr = SessionPoolManager(8, 1000) + + async def body(): + await mgr.acquire("s1") + return await mgr.call_tool("s1", "shop", {}, capability="danger") + + text, is_error = asyncio.run(body()) + assert is_error is True and "SELECT" in text # read-only guard runs on generated tools too + + +# --- lifecycle (unchanged from Phase A) ------------------------------------- + +def test_acquire_reuses_pool(tmp_path, patch_servers): + patch_servers["s1"] = [_server(tmp_path, "d", {"t": {"x": [1]}})] + mgr = SessionPoolManager(8, 1000) + + async def body(): + return await mgr.acquire("s1") is await mgr.acquire("s1") + + assert asyncio.run(body()) is True + + +def test_no_servers_raises(patch_servers): + mgr = SessionPoolManager(8, 1000) + with pytest.raises(pool_module.NoServersError): + asyncio.run(mgr.acquire("missing")) + + +def test_lru_eviction(tmp_path, patch_servers): + for sid in ("s1", "s2", "s3"): + patch_servers[sid] = [_server(tmp_path, f"d_{sid}", {"t": {"x": [1]}})] + mgr = SessionPoolManager(max_pools=2, idle_seconds=1000) + + async def body(): + await mgr.acquire("s1") + await mgr.acquire("s2") + await mgr.acquire("s3") # exceeds cap → evicts LRU (s1) + + asyncio.run(body()) + assert mgr.snapshot("s1") == [] # evicted + assert mgr.snapshot("s2") and mgr.snapshot("s3") + + +def test_close_is_idempotent(tmp_path, patch_servers): + patch_servers["s1"] = [_server(tmp_path, "d", {"t": {"x": [1]}})] + mgr = SessionPoolManager(8, 1000) + asyncio.run(mgr.acquire("s1")) + mgr.close("s1") + mgr.close("s1") # must not raise + assert mgr.snapshot("s1") == [] diff --git a/tests/unit/tools/test_postgres_connector.py b/tests/unit/tools/test_postgres_connector.py new file mode 100644 index 00000000..e0fc72a5 --- /dev/null +++ b/tests/unit/tools/test_postgres_connector.py @@ -0,0 +1,91 @@ +"""Unit tests for the PostgresConnector (BETA): connection-check + introspection against a MOCKED +psycopg2, credential sanitization, and get_connector flag gating. One live test is skipped unless +DATAANALYSIS_TEST_PG_URI is set (the live Postgres path is BETA and not part of the offline gate).""" +import os + +import pytest + +from data_analysis_agent.tools.connectors.base import DatasetConnectionError, get_connector +from data_analysis_agent.tools.connectors.postgres import PostgresConnector + +PG_DATASET = {"name": "pg", "type": "postgresql", "uri": "postgresql://u:secret@h:5432/db"} + +_TABLES = { + "orders": [("id", "integer", "NO"), ("amount", "integer", "YES")], + "customers": [("id", "integer", "NO"), ("region", "text", "YES")], +} + + +class _FakeCursor: + def __init__(self): + self._rows: list = [] + + def execute(self, sql, params=None): + if "SELECT 1" in sql: + self._rows = [(1,)] + elif "information_schema.tables" in sql: + self._rows = [(t,) for t in _TABLES] + elif "information_schema.columns" in sql: + self._rows = [(c[0], c[1], c[2]) for c in _TABLES[params[0]]] + else: + self._rows = [] + + def fetchone(self): + return self._rows[0] if self._rows else None + + def fetchall(self): + return list(self._rows) + + def close(self): + pass + + +class _FakeConn: + def cursor(self): + return _FakeCursor() + + def close(self): + pass + + +@pytest.fixture +def fake_pg(monkeypatch): + monkeypatch.setattr("psycopg2.connect", lambda *a, **k: _FakeConn()) + + +def test_connection_check_ok(fake_pg): + PostgresConnector(PG_DATASET).connection_check() # no raise + + +def test_discover_tables(fake_pg): + tables = PostgresConnector(PG_DATASET).discover_tables() + assert sorted(t["table_name"] for t in tables) == ["customers", "orders"] + orders = next(t for t in tables if t["table_name"] == "orders") + assert orders["column_names"] == ["id", "amount"] + assert orders["schema"][0] == {"name": "id", "dtype": "integer", "nullable": False} + + +def test_connection_failure_sanitizes_credentials(monkeypatch): + def boom(*a, **k): + raise Exception("FATAL: auth failed; conninfo postgresql://u:secret@h:5432/db password=secret") + monkeypatch.setattr("psycopg2.connect", boom) + with pytest.raises(DatasetConnectionError) as ei: + PostgresConnector(PG_DATASET).connection_check() + msg = str(ei.value) + assert "secret" not in msg # password scrubbed + assert "postgresql://h:5432/db" in msg # credential-free display present + + +def test_get_connector_dispatches_to_postgres(): + # External databases are always enabled; dispatch attempts no connection. + assert isinstance(get_connector(PG_DATASET), PostgresConnector) + + +@pytest.mark.external_db +def test_live_postgres_roundtrip(): + uri = os.environ.get("DATAANALYSIS_TEST_PG_URI") + if not uri: + pytest.skip("set DATAANALYSIS_TEST_PG_URI to run the live Postgres test (BETA)") + connector = PostgresConnector({"name": "live", "type": "postgresql", "uri": uri}) + connector.connection_check() + assert isinstance(connector.discover_tables(), list) diff --git a/tests/unit/tools/test_sync.py b/tests/unit/tools/test_sync.py new file mode 100644 index 00000000..e3f32fc2 --- /dev/null +++ b/tests/unit/tools/test_sync.py @@ -0,0 +1,329 @@ +"""Unit tests for the 5-stage sync pipeline (stub mode): generation of tools/resources/prompts, +version bump, soft-delete of dropped capabilities, and stub coverage of every stage tag.""" +import datetime as _dt + +import pandas as pd +import pytest +from sqlalchemy import create_engine +from sqlalchemy.orm import Session + +from data_analysis_agent.db.models import Base, McpPromptRow, McpResourceRow, DatabaseRow, McpToolRow +from data_analysis_agent.tools.sync import ( + ValidationError, + add_prompt, + add_resource, + add_tool, + apply_sync_result, + delete_prompt, + delete_resource, + delete_tool, + run_sync, + update_resource, + update_tool, +) + + +@pytest.fixture +def db(tmp_path): + engine = create_engine(f"sqlite:///{tmp_path}/sync.db") + Base.metadata.create_all(engine) + with Session(engine) as s: + yield s + engine.dispose() + + +@pytest.fixture(autouse=True) +def _stub(monkeypatch, tmp_path): + monkeypatch.setenv("DATAANALYSIS_OPENROUTER_API_KEY", "") + monkeypatch.setenv("DATAANALYSIS_DATASETS_DIR", str(tmp_path / "datasets")) + import data_analysis_agent.llm.client as llm_module + llm_module._client = None + yield + llm_module._client = None + + +def _server(db, tmp_path, name="sales") -> DatabaseRow: + """Create a parquet database whose table the connector will discover from its datasets directory.""" + from data_analysis_agent.tools.table_naming import sql_table_name + directory = tmp_path / "datasets" / sql_table_name(name) + directory.mkdir(parents=True, exist_ok=True) + pd.DataFrame({"id": [1, 2, 3], "amount": [5, 7, 3]}).to_parquet(directory / "orders.parquet") + srv = DatabaseRow(name=name, type="parquet", uri=f"parquet:///{name}") + db.add(srv) + db.flush() + return srv + + +def _discovered_tables(srv) -> list[str]: + """Table names the connector inspects from the database's directory.""" + from data_analysis_agent.tools.connectors.base import get_connector + conn = get_connector({"id": srv.id, "name": srv.name, "type": srv.type, "uri": srv.uri}) + return [t["table_name"] for t in conn.discover_tables()] + + +def _active(db, model, database_id): + return db.query(model).filter_by(database_id=database_id, deleted_at=None).all() + + +def test_run_sync_generates_capabilities(db, tmp_path): + srv = _server(db, tmp_path) + apply_sync_result(db, srv, run_sync(db, srv)) + db.commit() + assert srv.version == 2 and srv.title and srv.description + assert srv.last_sync_status == "ok" + tools = _active(db, McpToolRow, srv.id) + resources = _active(db, McpResourceRow, srv.id) + prompts = _active(db, McpPromptRow, srv.id) + assert len(tools) >= 1 and len(prompts) >= 1 + assert any(r.kind == "schema" for r in resources) # the dataset schema resource + # the generated tool's SQL must compile (validated at apply) + assert all(t.sql_template.upper().startswith("SELECT") for t in tools) + + +def test_resync_soft_deletes_dropped_tool(db, tmp_path): + srv = _server(db, tmp_path) + apply_sync_result(db, srv, run_sync(db, srv)) + db.commit() + # Inject an extra active tool the next sync won't propose; it must be SOFT-deleted, not removed. + orphan = McpToolRow(database_id=srv.id, name="orphan_tool", description="x", created_version=srv.version) + orphan.execution = {"sql_template": "SELECT 1", "parameters": []} + db.add(orphan) + db.commit() + apply_sync_result(db, srv, run_sync(db, srv)) + db.commit() + refreshed = db.get(McpToolRow, orphan.id) + assert refreshed.deleted_at is not None # soft-deleted (never hard-deleted) + assert db.get(McpToolRow, orphan.id) is not None # row still exists + + +def _synced(db, tmp_path): + srv = _server(db, tmp_path) + apply_sync_result(db, srv, run_sync(db, srv)) + db.commit() + return srv + + +def _tombstoned(db, model, database_id): + return db.query(model).filter(model.database_id == database_id, model.deleted_at.isnot(None)).count() + + +_OK_TOOL = {"name": "top_orders", "description": "top", + "sql_template": "SELECT * FROM orders LIMIT 5", + "input_schema": {"type": "object", "properties": {}}} + + +def test_add_tool_cascades_prompts_additively(db, tmp_path): + srv = _synced(db, tmp_path) + v0 = srv.version + add_tool(db, srv, _OK_TOOL) + db.commit() + assert srv.version == v0 + 1 + tools = {t.name for t in _active(db, McpToolRow, srv.id)} + assert "top_orders" in tools and "list_orders" in tools # additive: old tool kept + prompts = {p.name for p in _active(db, McpPromptRow, srv.id)} + assert "explore_top_orders" in prompts # cascaded prompt for the new tool + assert _tombstoned(db, McpToolRow, srv.id) == 0 # cascade never soft-deletes + assert _tombstoned(db, McpPromptRow, srv.id) == 0 + + +def test_add_tool_single_version_bump(db, tmp_path): + srv = _synced(db, tmp_path) + v0 = srv.version + add_tool(db, srv, _OK_TOOL) + db.commit() + assert srv.version == v0 + 1 + tool = next(t for t in _active(db, McpToolRow, srv.id) if t.name == "top_orders") + prompt = next(p for p in _active(db, McpPromptRow, srv.id) if p.name == "explore_top_orders") + assert tool.created_version == srv.version == prompt.created_version # one version across add+cascade + + +def test_add_tool_rejects_active_duplicate(db, tmp_path): + srv = _synced(db, tmp_path) + add_tool(db, srv, _OK_TOOL) + db.commit() + with pytest.raises(ValidationError): + add_tool(db, srv, _OK_TOOL) # duplicate active name + db.rollback() + + +def test_update_tool_requires_existing(db, tmp_path): + srv = _synced(db, tmp_path) + with pytest.raises(ValidationError): + update_tool(db, srv, {"name": "does_not_exist", "sql_template": "SELECT 1"}) + db.rollback() + + +def test_add_tool_rejects_bad_sql(db, tmp_path): + srv = _synced(db, tmp_path) + for bad in ( + {"name": "a", "sql_template": "DELETE FROM orders"}, # non-SELECT + {"name": "b", "sql_template": "SELECT 1; DROP TABLE orders"}, # multi-statement + {"name": "c", "sql_template": "SELECT * FROM orders WHERE id > $x"}, # undeclared $param + ): + with pytest.raises(ValidationError): + add_tool(db, srv, bad) + db.rollback() + + +def test_add_prompt_has_no_cascade(db, tmp_path): + srv = _synced(db, tmp_path) + tools_before = {t.name for t in _active(db, McpToolRow, srv.id)} + add_prompt(db, srv, {"name": "my_custom", "description": "mine"}) + db.commit() + assert "my_custom" in {p.name for p in _active(db, McpPromptRow, srv.id)} + assert {t.name for t in _active(db, McpToolRow, srv.id)} == tools_before # tools untouched + + +def test_cascade_preserves_manually_added_prompt(db, tmp_path): + srv = _synced(db, tmp_path) + add_prompt(db, srv, {"name": "my_custom", "description": "mine"}) + db.commit() + add_tool(db, srv, _OK_TOOL) # cascades prompts (additively) + db.commit() + prompts = {p.name for p in _active(db, McpPromptRow, srv.id)} + assert "my_custom" in prompts # additive cascade must NOT soft-delete a manual prompt + assert "explore_top_orders" in prompts + + +def test_add_resource_bumps_version_and_keeps_siblings(db, tmp_path): + srv = _synced(db, tmp_path) + v0 = srv.version + tools_before = {t.name for t in _active(db, McpToolRow, srv.id)} + add_resource(db, srv, {"uri": "entity://sales/foo", "name": "foo", "kind": "primary_entity"}) + db.commit() + assert srv.version == v0 + 1 + assert "entity://sales/foo" in {r.uri for r in _active(db, McpResourceRow, srv.id)} + # a pure entity (no physical table) adds no tool, and the cascade never drops existing tools + assert {t.name for t in _active(db, McpToolRow, srv.id)} == tools_before + assert _tombstoned(db, McpToolRow, srv.id) == 0 + + +def test_add_tool_rejects_file_reading_functions(db, tmp_path): + srv = _synced(db, tmp_path) + for bad in ( + {"name": "leak", "sql_template": "SELECT content FROM read_text('/etc/passwd')"}, + {"name": "leak2", "sql_template": "SELECT * FROM read_csv('/etc/hosts')"}, + # parameterized path skips the compile-check but the guard must still block the function + {"name": "leak3", "sql_template": "SELECT * FROM read_blob($p)", + "input_schema": {"type": "object", "properties": {"p": {"type": "string"}}}}, + ): + with pytest.raises(ValidationError): + add_tool(db, srv, bad) + db.rollback() + + +def test_update_tool_is_patch_not_replace(db, tmp_path): + srv = _synced(db, tmp_path) + tool = _active(db, McpToolRow, srv.id)[0] + original_sql = tool.sql_template + update_tool(db, srv, {"name": tool.name, "description": "updated desc only"}) + db.commit() + refreshed = next(t for t in _active(db, McpToolRow, srv.id) if t.name == tool.name) + assert refreshed.description == "updated desc only" + assert refreshed.sql_template == original_sql # omitted field preserved (patch, not replace) + + +def test_schema_resource_cannot_be_added_or_deleted_but_can_be_updated(db, tmp_path): + srv = _synced(db, tmp_path) + schema_uri = f"dataset://{srv.name}/schema" + # add of a schema-kind resource is rejected (tied to the server's existence) + with pytest.raises(ValidationError): + add_resource(db, srv, {"uri": "entity://x/y", "name": "y", "kind": "schema"}) + db.rollback() + # delete of the schema resource is rejected + with pytest.raises(ValidationError): + delete_resource(db, srv, schema_uri) + db.rollback() + # but manual update of its relationships IS allowed + update_resource(db, srv, {"uri": schema_uri, + "content": {"relationships": [{"from": "orders", "to": "x", "on": "id"}]}}) + db.commit() + schema_res = next(r for r in _active(db, McpResourceRow, srv.id) if r.kind == "schema") + rels = schema_res.content["relationships"] # canonical FK-edge list on the schema resource + assert rels and rels[0]["from_table"] == "orders" and rels[0]["to_table"] == "x" + assert "tables" not in schema_res.content # NOT per-table columns + + +def test_delete_tool_hard_deletes_and_prunes_prompts(db, tmp_path): + srv = _synced(db, tmp_path) + add_tool(db, srv, _OK_TOOL) + db.commit() + assert "explore_top_orders" in {p.name for p in _active(db, McpPromptRow, srv.id)} + tool = next(t for t in _active(db, McpToolRow, srv.id) if t.name == "top_orders") + tool_id = tool.id + delete_tool(db, srv, "top_orders") + db.commit() + assert db.get(McpToolRow, tool_id) is None # HARD delete (manual) — row gone + assert "top_orders" not in {t.name for t in _active(db, McpToolRow, srv.id)} + assert "explore_top_orders" not in {p.name for p in _active(db, McpPromptRow, srv.id)} # pruned cascade + + +def test_delete_prompt_hard_deletes_no_cascade(db, tmp_path): + srv = _synced(db, tmp_path) + add_prompt(db, srv, {"name": "my_custom", "description": "mine"}) + db.commit() + pid = next(p.id for p in _active(db, McpPromptRow, srv.id) if p.name == "my_custom") + tools_before = {t.name for t in _active(db, McpToolRow, srv.id)} + delete_prompt(db, srv, "my_custom") + db.commit() + assert db.get(McpPromptRow, pid) is None # hard delete + assert {t.name for t in _active(db, McpToolRow, srv.id)} == tools_before # leaf — no cascade + + +def test_delete_resource_drops_table_and_regenerates(db, tmp_path): + srv = _synced(db, tmp_path) + entity_uri = f"entity://{srv.name}/orders" + assert "orders" in _discovered_tables(srv) + delete_resource(db, srv, entity_uri) + db.commit() + # backing table file dropped (re-inspection finds nothing) + the entity resource gone + assert "orders" not in _discovered_tables(srv) + assert entity_uri not in {r.uri for r in _active(db, McpResourceRow, srv.id)} + # tools that referenced the dropped table are pruned (regenerated against remaining tables) + assert "list_orders" not in {t.name for t in _active(db, McpToolRow, srv.id)} + assert any(r.kind == "schema" for r in _active(db, McpResourceRow, srv.id)) # schema resource survives + + +def test_tool_execution_object_is_stored_and_derived(db, tmp_path): + srv = _synced(db, tmp_path) + add_tool(db, srv, { + "name": "by_amount", "description": "filter", + "execution": {"sql_template": "SELECT * FROM orders WHERE amount > $min", + "parameters": [{"name": "min", "type": "integer"}]}, + }) + db.commit() + tool = next(t for t in _active(db, McpToolRow, srv.id) if t.name == "by_amount") + assert tool.execution["sql_template"].startswith("SELECT") + assert tool.execution["parameters"][0] == {"name": "min", "type": "integer"} + assert tool.input_schema["properties"]["min"]["type"] == "integer" # derived MCP inputSchema + + +def test_entities_are_exactly_the_inspected_tables(db, tmp_path): + from data_analysis_agent.tools.table_naming import sql_table_name + srv = _server(db, tmp_path) # writes orders.parquet + directory = tmp_path / "datasets" / sql_table_name(srv.name) + pd.DataFrame({"customer_id": [10, 20], "region": ["N", "S"]}).to_parquet(directory / "customers.parquet") + apply_sync_result(db, srv, run_sync(db, srv)) + db.commit() + entity_names = sorted(r.name for r in _active(db, McpResourceRow, srv.id) if r.kind != "schema") + assert entity_names == sorted(_discovered_tables(srv)) == ["customers", "orders"] # definite, 1 per table + orders = next(r for r in _active(db, McpResourceRow, srv.id) if r.name == "orders") + assert [c["name"] for c in orders.content["columns"]] == ["id", "amount"] # columns from inspection + + +def test_entity_resource_carries_columns_and_size(db, tmp_path): + srv = _synced(db, tmp_path) + entity = next(r for r in _active(db, McpResourceRow, srv.id) if r.kind != "schema") + assert entity.content["table"] == "orders" + assert any(c.get("name") == "id" for c in entity.content["columns"]) # per-table columns live here + assert entity.size and entity.size > 0 # backing parquet file size + + +def test_stub_handles_all_node_tags(): + from data_analysis_agent.llm.providers.stub import StubLLMProvider + stub = StubLLMProvider() + tags = ["", "", "", + "", "", ""] + for tag in tags: + out = stub.complete(f"{tag}\nDataset name: d\nTable: t\nTables available: t\nTool: list_t").text + assert "unrecognized node tag" not in out, f"{tag} not handled by stub" diff --git a/uv.lock b/uv.lock index d214d215..3b3d8037 100644 --- a/uv.lock +++ b/uv.lock @@ -1,48 +1,23 @@ version 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