From 3b81a946a0b3758e144e0bd51505b6d990e1c71c Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Sat, 11 Apr 2026 12:50:14 -0700 Subject: [PATCH 01/12] Add CLAUDE.md with architecture overview and dev guidance Co-Authored-By: Claude Sonnet 4.6 --- CLAUDE.md | 74 +++++++++++++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 74 insertions(+) create mode 100644 CLAUDE.md diff --git a/CLAUDE.md b/CLAUDE.md new file mode 100644 index 000000000..3c4a5322c --- /dev/null +++ b/CLAUDE.md @@ -0,0 +1,74 @@ +# CLAUDE.md + +This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository. + +## Running the Application + +Requires Python 3.13+ and `uv`. On Windows, use Git Bash. Always use `uv` to run Python and manage all dependencies — never use `pip` directly. + +```bash +# Install dependencies +uv sync + +# Copy and populate the environment file +cp .env.example .env # then add ANTHROPIC_API_KEY + +# Start the server (from repo root) +./run.sh +# or manually: +cd backend && uv run uvicorn app:app --reload --port 8000 +``` + +App runs at `http://localhost:8000`. On startup, course documents in `/docs` are automatically loaded into ChromaDB (skipping any already indexed). + +## Architecture + +This is a full-stack RAG (Retrieval-Augmented Generation) application. The FastAPI backend serves both the API and the static frontend from a single port. + +### Query Flow + +1. Frontend (`frontend/script.js`) POSTs `{ query, session_id }` to `/api/query` +2. `app.py` routes to `RAGSystem.query()`, creating a session if needed +3. `RAGSystem` fetches conversation history from `SessionManager` and calls `AIGenerator.generate_response()` with the `search_course_content` tool available +4. **First Claude call** — Claude decides to answer directly or invoke the search tool +5. If tool use: `CourseSearchTool` calls `VectorStore.search()`, which optionally resolves a fuzzy course name via semantic search on the `course_catalog` collection, then queries the `course_content` collection using `sentence-transformers` embeddings +6. **Second Claude call** — Claude synthesizes a final answer from the retrieved chunks +7. Sources (course + lesson labels) and the answer are returned to the frontend + +### Key Design Decisions + +- **Two ChromaDB collections**: `course_catalog` (course-level metadata for fuzzy name resolution) and `course_content` (chunked lesson text for semantic search) +- **Agentic tool loop**: Claude decides whether to search; the tool call and result are injected back into the message thread before a second API call forces a final text response +- **Session history** is passed in the system prompt as formatted text (not as message-role history), capped at `MAX_HISTORY=2` exchanges +- **Course title is the unique ID** in ChromaDB — re-ingesting the same course is a no-op +- **ChromaDB persists** to `backend/chroma_db/`. To force a full re-index, delete that directory or call `vector_store.clear_all_data()` + +### Extending the Search Tool + +New tools should implement the `Tool` ABC in `backend/search_tools.py` (implement `get_tool_definition()` and `execute()`), then register with `ToolManager.register_tool()` in `RAGSystem.__init__()`. The tool definition must follow the Anthropic tool schema format. + +### Document Format + +Course `.txt` files in `/docs` must follow this structure: +``` +Course Title: +Course Link: <url> +Course Instructor: <name> +Lesson 0: <lesson title> +Lesson Link: <url> +<lesson content> +Lesson 1: <lesson title> +... +``` + +### Configuration (`backend/config.py`) + +| Setting | Default | Purpose | +|---|---|---| +| `ANTHROPIC_MODEL` | `claude-sonnet-4-20250514` | Model for generation | +| `EMBEDDING_MODEL` | `all-MiniLM-L6-v2` | Sentence transformer for embeddings | +| `CHUNK_SIZE` | `800` | Max characters per chunk | +| `CHUNK_OVERLAP` | `100` | Character overlap between chunks | +| `MAX_RESULTS` | `5` | Max chunks returned per search | +| `MAX_HISTORY` | `2` | Conversation exchanges retained | +| `CHROMA_PATH` | `./chroma_db` | ChromaDB persistence directory | From 9a86ae22c884ecc58f0170bddbce3cb75396cbb9 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Sat, 11 Apr 2026 15:40:05 -0700 Subject: [PATCH 02/12] Add new chat button, style sidebar, and improve source links - Add + NEW CHAT button to sidebar with distinct bordered style - Wire new chat button to clear session history via DELETE /api/session - Deduplicate sources and return label+url pairs from search tool - Render sources as clickable links in the chat UI - Update CLAUDE.md with uv install step Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- CLAUDE.md | 3 +++ backend/app.py | 8 +++++++- backend/search_tools.py | 27 ++++++++++++++++----------- frontend/index.html | 5 +++++ frontend/script.js | 19 ++++++++++++++++--- frontend/style.css | 34 ++++++++++++++++++++++++++++++++++ 6 files changed, 81 insertions(+), 15 deletions(-) diff --git a/CLAUDE.md b/CLAUDE.md index 3c4a5322c..8d4608416 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -7,6 +7,9 @@ This file provides guidance to Claude Code (claude.ai/code) when working with co Requires Python 3.13+ and `uv`. On Windows, use Git Bash. Always use `uv` to run Python and manage all dependencies — never use `pip` directly. ```bash +# Install uv (one-time, run in Git Bash) +curl -LsSf https://astral.sh/uv/install.sh | sh + # Install dependencies uv sync diff --git a/backend/app.py b/backend/app.py index 5a69d741d..7e105d1d0 100644 --- a/backend/app.py +++ b/backend/app.py @@ -43,7 +43,7 @@ class QueryRequest(BaseModel): class QueryResponse(BaseModel): """Response model for course queries""" answer: str - sources: List[str] + sources: List[dict] session_id: str class CourseStats(BaseModel): @@ -85,6 +85,12 @@ async def get_course_stats(): except Exception as e: raise HTTPException(status_code=500, detail=str(e)) +@app.delete("/api/session/{session_id}") +async def clear_session(session_id: str): + """Clear conversation history for a session""" + rag_system.session_manager.clear_session(session_id) + return {"status": "cleared"} + @app.on_event("startup") async def startup_event(): """Load initial documents on startup""" diff --git a/backend/search_tools.py b/backend/search_tools.py index adfe82352..21f466c16 100644 --- a/backend/search_tools.py +++ b/backend/search_tools.py @@ -89,28 +89,33 @@ def _format_results(self, results: SearchResults) -> str: """Format search results with course and lesson context""" formatted = [] sources = [] # Track sources for the UI - + seen = set() # Deduplicate sources + for doc, meta in zip(results.documents, results.metadata): course_title = meta.get('course_title', 'unknown') lesson_num = meta.get('lesson_number') - + # Build context header header = f"[{course_title}" if lesson_num is not None: header += f" - Lesson {lesson_num}" header += "]" - - # Track source for the UI - source = course_title - if lesson_num is not None: - source += f" - Lesson {lesson_num}" - sources.append(source) - + + # Track source for the UI (deduplicated) + source_key = f"{course_title}_{lesson_num}" + if source_key not in seen: + seen.add(source_key) + label = course_title + if lesson_num is not None: + label += f" - Lesson {lesson_num}" + url = self.store.get_lesson_link(course_title, lesson_num) if lesson_num is not None else None + sources.append({"label": label, "url": url}) + formatted.append(f"{header}\n{doc}") - + # Store sources for retrieval self.last_sources = sources - + return "\n\n".join(formatted) class ToolManager: diff --git a/frontend/index.html b/frontend/index.html index f8e25a62f..30692e0f8 100644 --- a/frontend/index.html +++ b/frontend/index.html @@ -19,6 +19,11 @@ <h1>Course Materials Assistant</h1> <div class="main-content"> <!-- Left Sidebar --> <aside class="sidebar"> + <!-- New Chat Button --> + <div class="sidebar-section"> + <button class="new-chat-btn" id="newChatBtn">+ NEW CHAT</button> + </div> + <!-- Course Stats --> <div class="sidebar-section"> <details class="stats-collapsible"> diff --git a/frontend/script.js b/frontend/script.js index 562a8a363..339e1d776 100644 --- a/frontend/script.js +++ b/frontend/script.js @@ -28,8 +28,9 @@ function setupEventListeners() { chatInput.addEventListener('keypress', (e) => { if (e.key === 'Enter') sendMessage(); }); - - + + document.getElementById('newChatBtn').addEventListener('click', createNewSession); + // Suggested questions document.querySelectorAll('.suggested-item').forEach(button => { button.addEventListener('click', (e) => { @@ -122,10 +123,15 @@ function addMessage(content, type, sources = null, isWelcome = false) { let html = `<div class="message-content">${displayContent}</div>`; if (sources && sources.length > 0) { + const sourceLinks = sources.map(s => + s.url + ? `<a href="${s.url}" target="_blank" rel="noopener noreferrer">${escapeHtml(s.label)}</a>` + : escapeHtml(s.label) + ).join(', '); html += ` <details class="sources-collapsible"> <summary class="sources-header">Sources</summary> - <div class="sources-content">${sources.join(', ')}</div> + <div class="sources-content">${sourceLinks}</div> </details> `; } @@ -147,6 +153,13 @@ function escapeHtml(text) { // Removed removeMessage function - no longer needed since we handle loading differently async function createNewSession() { + if (currentSessionId) { + try { + await fetch(`${API_URL}/session/${currentSessionId}`, { method: 'DELETE' }); + } catch (e) { + // Non-critical — proceed with frontend reset regardless + } + } currentSessionId = null; chatMessages.innerHTML = ''; addMessage('Welcome to the Course Materials Assistant! I can help you with questions about courses, lessons and specific content. What would you like to know?', 'assistant', null, true); diff --git a/frontend/style.css b/frontend/style.css index 825d03675..24b12ecd0 100644 --- a/frontend/style.css +++ b/frontend/style.css @@ -111,6 +111,29 @@ header h1 { margin-bottom: 0; } +/* New Chat Button */ +.new-chat-btn { + width: auto; + padding: 0.5rem 1rem; + background: transparent; + border: 1px solid var(--primary-color); + border-radius: 6px; + cursor: pointer; + font-size: 0.875rem; + font-weight: 600; + color: var(--primary-color); + text-transform: uppercase; + letter-spacing: 0.5px; + text-align: left; + display: block; + transition: background 0.2s ease, color 0.2s ease; +} + +.new-chat-btn:hover { + background: var(--primary-color); + color: white; +} + /* Main Chat Area */ .chat-main { flex: 1; @@ -245,6 +268,17 @@ header h1 { color: var(--text-secondary); } +.sources-content a { + color: #60a5fa; + text-decoration: underline; + text-underline-offset: 2px; + transition: color 0.2s ease; +} + +.sources-content a:hover { + color: #93c5fd; +} + /* Markdown formatting styles */ .message-content h1, .message-content h2, From bf25e9f2deeb6c8aef8c9dab53c5d8a054fdc38b Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Sat, 11 Apr 2026 16:42:01 -0700 Subject: [PATCH 03/12] Add custom skills and notes reference file - Add /log skill to append session learnings to notes.md - Add /commit skill to stage and commit project changes - Add /push skill to push current branch to origin - Add notes.md with entries on MCP servers and custom skill setup Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- .claude/settings.local.json | 9 ++++++++ .claude/skills/commit/SKILL.md | 12 +++++++++++ .claude/skills/log/SKILL.md | 12 +++++++++++ .claude/skills/push/SKILL.md | 10 +++++++++ notes.md | 38 ++++++++++++++++++++++++++++++++++ 5 files changed, 81 insertions(+) create mode 100644 .claude/settings.local.json create mode 100644 .claude/skills/commit/SKILL.md create mode 100644 .claude/skills/log/SKILL.md create mode 100644 .claude/skills/push/SKILL.md create mode 100644 notes.md diff --git a/.claude/settings.local.json b/.claude/settings.local.json new file mode 100644 index 000000000..87fefe214 --- /dev/null +++ b/.claude/settings.local.json @@ -0,0 +1,9 @@ +{ + "permissions": { + "allow": [ + "mcp__playwright__browser_navigate", + "mcp__playwright__browser_take_screenshot", + "mcp__playwright__browser_evaluate" + ] + } +} diff --git a/.claude/skills/commit/SKILL.md b/.claude/skills/commit/SKILL.md new file mode 100644 index 000000000..5b3c7e6f1 --- /dev/null +++ b/.claude/skills/commit/SKILL.md @@ -0,0 +1,12 @@ +--- +name: commit +description: Stage all modified tracked files and create a git commit with an appropriate message +disable-model-invocation: true +--- + +Stage all modified tracked files (do not include untracked files like .claude/, .playwright-mcp/, or image files unless they are clearly part of the project). Then review the diff and write a concise commit message that describes what changed and why. Format the commit message as a short summary line followed by a bullet list of key changes if needed. + +Always co-author the commit: +Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> + +Use a HEREDOC to pass the commit message to avoid formatting issues. diff --git a/.claude/skills/log/SKILL.md b/.claude/skills/log/SKILL.md new file mode 100644 index 000000000..cd2ee0953 --- /dev/null +++ b/.claude/skills/log/SKILL.md @@ -0,0 +1,12 @@ +--- +name: log +description: Logs the most recent explanation or answer from the conversation into notes.md +disable-model-invocation: true +--- + +Look at the most recent explanation or answer you gave in this conversation. Extract the topic and key points, then append a new entry to `notes.md` in the repo root using this format: + +## <topic title> +<concise explanation of what was discovered, in plain language> + +If `notes.md` does not exist, create it with a `# Notes` heading first. Do not overwrite or modify any existing entries. diff --git a/.claude/skills/push/SKILL.md b/.claude/skills/push/SKILL.md new file mode 100644 index 000000000..174117d06 --- /dev/null +++ b/.claude/skills/push/SKILL.md @@ -0,0 +1,10 @@ +--- +name: push +description: Push the current branch to origin +disable-model-invocation: true +--- + +Push the current branch to origin using: +git push origin <current-branch> + +First check the current branch name with `git branch --show-current`, then push to origin. Report back whether the push succeeded or if everything was already up to date. diff --git a/notes.md b/notes.md new file mode 100644 index 000000000..1c355ed96 --- /dev/null +++ b/notes.md @@ -0,0 +1,38 @@ +# Notes + +## MCP Servers (Model Context Protocol) + +MCP stands for Model Context Protocol — an open standard that lets Claude connect to external tools and data sources, acting like a plugin system. + +By default Claude Code can read files, run bash commands, search code, etc. MCP servers extend that with new capabilities. + +**What we used:** The Playwright MCP server gave Claude browser control tools — `browser_navigate`, `browser_take_screenshot`, and `browser_evaluate` — allowing Claude to interact with a live browser directly instead of asking the user to describe what they see. + +**Other examples of MCP servers:** +- Gmail — read/send emails +- Google Calendar — check/create events +- Databases — query Postgres or SQLite +- Slack — post messages + +**How they work:** +1. An MCP server runs as a separate process on your machine (or remotely) +2. Claude Code connects to it via the `/mcp` command or settings +3. The server exposes tools that Claude can call just like any built-in tool + +## Setting Up a Custom Skill (/log command) + +Custom slash commands in Claude Code are called **skills** and must follow a specific folder structure to be recognized. + +**Correct structure:** +``` +.claude/skills/<skill-name>/SKILL.md +``` + +**SKILL.md requires two parts:** +1. YAML frontmatter (between `---` markers) with fields like `name`, `description`, and `disable-model-invocation: true` to only trigger on explicit use +2. Markdown instructions telling Claude what to do when the skill is invoked + +**What didn't work:** +- `.claude/commands/log.md` — the old format, no longer supported + +**Important:** Claude Code only scans for skills on startup — a full restart is required after creating a new skill for it to be recognized. From 32ea9c24ca6d45e6427919005ea5ffdd244d2443 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Sat, 11 Apr 2026 17:03:07 -0700 Subject: [PATCH 04/12] Remove push and ssh skills - Removed /push skill (SSH agent isolation makes it unusable from Claude's shell) - Removed /ssh skill (Claude terminal cannot handle interactive SSH passphrase prompts) - Pushing to GitHub will be done manually from Git Bash Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- .claude/skills/push/SKILL.md | 10 ---------- 1 file changed, 10 deletions(-) delete mode 100644 .claude/skills/push/SKILL.md diff --git a/.claude/skills/push/SKILL.md b/.claude/skills/push/SKILL.md deleted file mode 100644 index 174117d06..000000000 --- a/.claude/skills/push/SKILL.md +++ /dev/null @@ -1,10 +0,0 @@ ---- -name: push -description: Push the current branch to origin -disable-model-invocation: true ---- - -Push the current branch to origin using: -git push origin <current-branch> - -First check the current branch name with `git branch --show-current`, then push to origin. Report back whether the push succeeded or if everything was already up to date. From f023384827674e033704db374c3096b56998e437 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Sat, 11 Apr 2026 17:15:15 -0700 Subject: [PATCH 05/12] Add /wrap skill for end-of-session memory logging - Creates a /wrap skill that captures date/time, accomplishments, where we left off, and next steps - Writes session summary to project_session_progress.md in the memory folder for automatic recall next session Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- .claude/skills/wrap/SKILL.md | 32 ++++++++++++++++++++++++++++++++ 1 file changed, 32 insertions(+) create mode 100644 .claude/skills/wrap/SKILL.md diff --git a/.claude/skills/wrap/SKILL.md b/.claude/skills/wrap/SKILL.md new file mode 100644 index 000000000..2a950af29 --- /dev/null +++ b/.claude/skills/wrap/SKILL.md @@ -0,0 +1,32 @@ +--- +name: wrap +description: Log a session summary to memory at the end of a working session +disable-model-invocation: true +--- + +Run `date` to get the current date and time. Then review the conversation and write a session summary to: + +`C:\Users\lcplu\.claude\projects\C--Users-lcplu-OneDrive-Documents-ClaudeCodeLearning\memory\project_session_progress.md` + +Overwrite the entire file with the following format: + +``` +--- +name: Session Progress & Next Steps +description: What was done in the latest session and what to pick up next +type: project +--- + +## Session — <date and time from the date command> + +### Accomplished +- <bullet list of what was done this session> + +### Where We Left Off +- <what we were doing at the end of the session> + +### Next Steps +- <planned follow-ups or things to explore next> +``` + +Be specific and concise. This file is automatically loaded by Claude at the start of the next session. From fe9efac077b908fdd317975f54e0b78d00de8e97 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Tue, 14 Apr 2026 17:03:06 -0700 Subject: [PATCH 06/12] Add CourseOutlineTool, sequential tool calling, and full test suite - Add CourseOutlineTool to search_tools.py: returns course title, link, and full lesson list using VectorStore.get_course_outline() with fuzzy name resolution; register alongside CourseSearchTool in RAGSystem - Add VectorStore.get_course_outline() method - Refactor _handle_tool_execution into a bounded loop (MAX_ROUNDS=2): intermediate calls keep tools for chaining; forced final call strips them; tool exceptions caught and returned as graceful tool_result - Update system prompt to guide Claude on tool chaining vs direct answers - Fix defensive gap: stop_reason="tool_use" with no tool_manager now returns a graceful message instead of crashing - Add backend/tests/ with 78 passing tests across four files: test_course_search_tool, test_ai_generator, test_rag_system, test_vector_store (real ChromaDB integration + config validation) Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- backend/ai_generator.py | 306 +++++++++-------- backend/backend-tool-refactor.md | 30 ++ backend/rag_system.py | 4 +- backend/search_tools.py | 36 ++ backend/tests/__init__.py | 0 backend/tests/conftest.py | 91 ++++++ backend/tests/test_ai_generator.py | 399 +++++++++++++++++++++++ backend/tests/test_course_search_tool.py | 254 +++++++++++++++ backend/tests/test_rag_system.py | 208 ++++++++++++ backend/tests/test_vector_store.py | 241 ++++++++++++++ backend/vector_store.py | 23 ++ notes.md | 80 +++++ 12 files changed, 1536 insertions(+), 136 deletions(-) create mode 100644 backend/backend-tool-refactor.md create mode 100644 backend/tests/__init__.py create mode 100644 backend/tests/conftest.py create mode 100644 backend/tests/test_ai_generator.py create mode 100644 backend/tests/test_course_search_tool.py create mode 100644 backend/tests/test_rag_system.py create mode 100644 backend/tests/test_vector_store.py diff --git a/backend/ai_generator.py b/backend/ai_generator.py index 0363ca90c..52d20b7df 100644 --- a/backend/ai_generator.py +++ b/backend/ai_generator.py @@ -1,135 +1,171 @@ -import anthropic -from typing import List, Optional, Dict, Any - -class AIGenerator: - """Handles interactions with Anthropic's Claude API for generating responses""" - - # Static system prompt to avoid rebuilding on each call - SYSTEM_PROMPT = """ You are an AI assistant specialized in course materials and educational content with access to a comprehensive search tool for course information. - -Search Tool Usage: -- Use the search tool **only** for questions about specific course content or detailed educational materials -- **One search per query maximum** -- Synthesize search results into accurate, fact-based responses -- If search yields no results, state this clearly without offering alternatives - -Response Protocol: -- **General knowledge questions**: Answer using existing knowledge without searching -- **Course-specific questions**: Search first, then answer -- **No meta-commentary**: - - Provide direct answers only — no reasoning process, search explanations, or question-type analysis - - Do not mention "based on the search results" - - -All responses must be: -1. **Brief, Concise and focused** - Get to the point quickly -2. **Educational** - Maintain instructional value -3. **Clear** - Use accessible language -4. **Example-supported** - Include relevant examples when they aid understanding -Provide only the direct answer to what was asked. -""" - - def __init__(self, api_key: str, model: str): - self.client = anthropic.Anthropic(api_key=api_key) - self.model = model - - # Pre-build base API parameters - self.base_params = { - "model": self.model, - "temperature": 0, - "max_tokens": 800 - } - - def generate_response(self, query: str, - conversation_history: Optional[str] = None, - tools: Optional[List] = None, - tool_manager=None) -> str: - """ - Generate AI response with optional tool usage and conversation context. - - Args: - query: The user's question or request - conversation_history: Previous messages for context - tools: Available tools the AI can use - tool_manager: Manager to execute tools - - Returns: - Generated response as string - """ - - # Build system content efficiently - avoid string ops when possible - system_content = ( - f"{self.SYSTEM_PROMPT}\n\nPrevious conversation:\n{conversation_history}" - if conversation_history - else self.SYSTEM_PROMPT - ) - - # Prepare API call parameters efficiently - api_params = { - **self.base_params, - "messages": [{"role": "user", "content": query}], - "system": system_content - } - - # Add tools if available - if tools: - api_params["tools"] = tools - api_params["tool_choice"] = {"type": "auto"} - - # Get response from Claude - response = self.client.messages.create(**api_params) - - # Handle tool execution if needed - if response.stop_reason == "tool_use" and tool_manager: - return self._handle_tool_execution(response, api_params, tool_manager) - - # Return direct response - return response.content[0].text - - def _handle_tool_execution(self, initial_response, base_params: Dict[str, Any], tool_manager): - """ - Handle execution of tool calls and get follow-up response. - - Args: - initial_response: The response containing tool use requests - base_params: Base API parameters - tool_manager: Manager to execute tools - - Returns: - Final response text after tool execution - """ - # Start with existing messages - messages = base_params["messages"].copy() - - # Add AI's tool use response - messages.append({"role": "assistant", "content": initial_response.content}) - - # Execute all tool calls and collect results - tool_results = [] - for content_block in initial_response.content: - if content_block.type == "tool_use": - tool_result = tool_manager.execute_tool( - content_block.name, - **content_block.input - ) - - tool_results.append({ - "type": "tool_result", - "tool_use_id": content_block.id, - "content": tool_result - }) - - # Add tool results as single message - if tool_results: - messages.append({"role": "user", "content": tool_results}) - - # Prepare final API call without tools - final_params = { - **self.base_params, - "messages": messages, - "system": base_params["system"] - } - - # Get final response - final_response = self.client.messages.create(**final_params) - return final_response.content[0].text \ No newline at end of file +import anthropic +from typing import List, Optional, Dict, Any + +class AIGenerator: + """Handles interactions with Anthropic's Claude API for generating responses""" + + MAX_ROUNDS = 2 # Maximum sequential tool-calling rounds per query + + # Static system prompt to avoid rebuilding on each call + SYSTEM_PROMPT = """ You are an AI assistant specialized in course materials and educational content with access to a comprehensive search tool for course information. + +Search Tool Usage: +- Use **get_course_outline** for questions about a course's structure, outline, or lesson list — it returns the course title, link, and all lesson numbers and titles +- Use **search_course_content** only for questions about specific course content or detailed educational materials +- You may make up to 2 sequential tool calls when a query requires chaining +- Use a second tool call only when the result of the first is needed to form the next query + (e.g., use get_course_outline to find a lesson title, then search_course_content with that title) +- After receiving tool results, respond in text as soon as you have enough information +- Do not chain tool calls speculatively — only when the second depends on the first +- Synthesize results into accurate, fact-based responses +- If a tool yields no results, state this clearly without offering alternatives + +Response Protocol: +- **General knowledge questions**: Answer using existing knowledge without searching +- **Course outline questions**: Call get_course_outline and return the course title, course link, and the complete numbered lesson list +- **Course-specific questions**: Call search_course_content first, then answer +- **No meta-commentary**: + - Provide direct answers only — no reasoning process, search explanations, or question-type analysis + - Do not mention "based on the search results" + + +All responses must be: +1. **Brief, Concise and focused** - Get to the point quickly +2. **Educational** - Maintain instructional value +3. **Clear** - Use accessible language +4. **Example-supported** - Include relevant examples when they aid understanding +Provide only the direct answer to what was asked. +""" + + def __init__(self, api_key: str, model: str): + self.client = anthropic.Anthropic(api_key=api_key) + self.model = model + + # Pre-build base API parameters + self.base_params = { + "model": self.model, + "temperature": 0, + "max_tokens": 800 + } + + def generate_response(self, query: str, + conversation_history: Optional[str] = None, + tools: Optional[List] = None, + tool_manager=None) -> str: + """ + Generate AI response with optional tool usage and conversation context. + + Args: + query: The user's question or request + conversation_history: Previous messages for context + tools: Available tools the AI can use + tool_manager: Manager to execute tools + + Returns: + Generated response as string + """ + + # Build system content efficiently - avoid string ops when possible + system_content = ( + f"{self.SYSTEM_PROMPT}\n\nPrevious conversation:\n{conversation_history}" + if conversation_history + else self.SYSTEM_PROMPT + ) + + # Prepare API call parameters efficiently + api_params = { + **self.base_params, + "messages": [{"role": "user", "content": query}], + "system": system_content + } + + # Add tools if available + if tools: + api_params["tools"] = tools + api_params["tool_choice"] = {"type": "auto"} + + # Get response from Claude + response = self.client.messages.create(**api_params) + + # Handle tool execution if needed + if response.stop_reason == "tool_use": + if tool_manager: + return self._handle_tool_execution(response, api_params, tool_manager) + return "I tried to look up information but tool execution is not available." + + # Return direct response + return response.content[0].text + + def _handle_tool_execution(self, initial_response, base_params: Dict[str, Any], tool_manager): + """ + Handle sequential tool calls up to MAX_ROUNDS, then force a final text response. + + Each round: + 1. Execute all tool_use blocks in the current response + 2. Append assistant turn + tool results to the message thread + 3. If rounds remain and no error, make an intermediate call WITH tools + 4. If Claude answers without a tool call, return immediately (early exit) + + After the loop, make one final call WITHOUT tools so Claude is forced to answer. + + Args: + initial_response: The first response containing tool use requests + base_params: API parameters from generate_response (includes tools/tool_choice) + tool_manager: Manager to execute tools + + Returns: + Final response text + """ + messages = base_params["messages"].copy() + current_response = initial_response + + for round_num in range(self.MAX_ROUNDS): + # --- Execute all tool calls in this round --- + tool_results = [] + had_error = False + for block in current_response.content: + if block.type == "tool_use": + try: + result = tool_manager.execute_tool(block.name, **block.input) + except Exception as e: + result = f"Tool execution failed: {e}" + had_error = True + tool_results.append({ + "type": "tool_result", + "tool_use_id": block.id, + "content": result, + }) + + # --- Append this round to the message thread --- + messages.append({"role": "assistant", "content": current_response.content}) + if tool_results: + messages.append({"role": "user", "content": tool_results}) + + is_last_round = (round_num == self.MAX_ROUNDS - 1) + + # Stop conditions (b) exception or (c) rounds exhausted + if had_error or is_last_round: + break + + # --- Intermediate call: tools still available for chaining --- + intermediate_params = { + **self.base_params, + "messages": messages, + "system": base_params["system"], + "tools": base_params["tools"], + "tool_choice": base_params["tool_choice"], + } + current_response = self.client.messages.create(**intermediate_params) + + # Stop condition (a): Claude answered without requesting another tool + if current_response.stop_reason != "tool_use": + return current_response.content[0].text + + # --- Forced final call: always strip tools --- + final_params = { + **self.base_params, + "messages": messages, + "system": base_params["system"], + } + final_response = self.client.messages.create(**final_params) + return final_response.content[0].text diff --git a/backend/backend-tool-refactor.md b/backend/backend-tool-refactor.md new file mode 100644 index 000000000..1e6653064 --- /dev/null +++ b/backend/backend-tool-refactor.md @@ -0,0 +1,30 @@ +Refactor @backend/ai_generator.py to support sequential tool calling where Claude can make up 2 tool calls in separate API rounds. + + +Current behavior: +- Claude makes 1 tool call → tools are removed from API params → final response +- If Claude wants another tool call after seeing results, it can't (gets empty response) + + +Desired behavior: +- Each tool call should be a separate API request where Claude can reason about previous results +- Support for complex queries requiring multiple searches for comparisons, multi-part questions, or when information from different courses/lessons is needed + +Example Flow: +1. User: "Search for a course that discusses the same topic as lesson 4 of course X" +2. Claude: get course outline for course X → gets title of lesson 4 +3. Claude: uses the title to search for a course that discusses the same topic → returns course information +4. Claude: provides complete answer + +Requirements: +- Maximum 2 sequential rounds per user query +- Terminate when:(a) 2 rounds completed, (b) Claude's response has no tool_use blocks, or (c) tool call fails +- Preserve conversation context between rounds +- Handle tool execution errors gracefully + +Notes: +- update the system prompt in @backend/ai_generator.py +- update the test @backend/tests/test_ai_generator.py +- Write tests that verify the external behavior (API calls made, tools executed, results returned) rather than internal state details. + +Use two parallel subagents to brainstorm possible plans. Do not implement any code. \ No newline at end of file diff --git a/backend/rag_system.py b/backend/rag_system.py index 50d848c8e..443649f0e 100644 --- a/backend/rag_system.py +++ b/backend/rag_system.py @@ -4,7 +4,7 @@ from vector_store import VectorStore from ai_generator import AIGenerator from session_manager import SessionManager -from search_tools import ToolManager, CourseSearchTool +from search_tools import ToolManager, CourseSearchTool, CourseOutlineTool from models import Course, Lesson, CourseChunk class RAGSystem: @@ -23,6 +23,8 @@ def __init__(self, config): self.tool_manager = ToolManager() self.search_tool = CourseSearchTool(self.vector_store) self.tool_manager.register_tool(self.search_tool) + self.outline_tool = CourseOutlineTool(self.vector_store) + self.tool_manager.register_tool(self.outline_tool) def add_course_document(self, file_path: str) -> Tuple[Course, int]: """ diff --git a/backend/search_tools.py b/backend/search_tools.py index 21f466c16..38d715fca 100644 --- a/backend/search_tools.py +++ b/backend/search_tools.py @@ -118,6 +118,42 @@ def _format_results(self, results: SearchResults) -> str: return "\n\n".join(formatted) +class CourseOutlineTool(Tool): + """Tool for retrieving a course outline (title, link, and full lesson list)""" + + def __init__(self, vector_store: VectorStore): + self.store = vector_store + + def get_tool_definition(self) -> Dict[str, Any]: + return { + "name": "get_course_outline", + "description": "Return the complete outline of a course: its title, link, and all lesson numbers and titles", + "input_schema": { + "type": "object", + "properties": { + "course_name": { + "type": "string", + "description": "Course name or partial name (e.g. 'MCP', 'Introduction to Claude')" + } + }, + "required": ["course_name"] + } + } + + def execute(self, course_name: str) -> str: + outline = self.store.get_course_outline(course_name) + if not outline: + return f"No course found matching '{course_name}'." + lines = [ + f"Course: {outline['title']}", + f"Link: {outline['course_link']}", + "Lessons:" + ] + for lesson in outline['lessons']: + lines.append(f" Lesson {lesson['lesson_number']}: {lesson['lesson_title']}") + return "\n".join(lines) + + class ToolManager: """Manages available tools for the AI""" diff --git a/backend/tests/__init__.py b/backend/tests/__init__.py new file mode 100644 index 000000000..e69de29bb diff --git a/backend/tests/conftest.py b/backend/tests/conftest.py new file mode 100644 index 000000000..4f03cbc58 --- /dev/null +++ b/backend/tests/conftest.py @@ -0,0 +1,91 @@ +""" +Shared pytest configuration and fixtures for all test modules. +Adds the backend directory to sys.path so modules can be imported +without package-prefix notation (matching how the app itself imports them). +""" +import sys +import os +from unittest.mock import MagicMock + +# Make backend/ importable as the root package +sys.path.insert(0, os.path.dirname(os.path.dirname(os.path.abspath(__file__)))) + +import pytest +from vector_store import SearchResults + + +# --------------------------------------------------------------------------- +# SearchResults factories +# --------------------------------------------------------------------------- + +def make_search_results(documents=None, metadata=None, distances=None): + """Return a successful SearchResults with the given content.""" + docs = documents or [] + meta = metadata or [] + dist = distances or ([0.1] * len(docs)) + return SearchResults(documents=docs, metadata=meta, distances=dist, error=None) + + +def make_error_results(error_msg="Search error: connection failed"): + """Return a SearchResults that carries an error.""" + return SearchResults.empty(error_msg) + + +# --------------------------------------------------------------------------- +# Anthropic message response factories +# --------------------------------------------------------------------------- + +def make_text_response(text="Here is the answer."): + """Mock a Claude response that returns text directly (no tool use).""" + content_block = MagicMock() + content_block.type = "text" + content_block.text = text + + response = MagicMock() + response.stop_reason = "end_turn" + response.content = [content_block] + return response + + +def make_tool_use_response( + tool_name="search_course_content", + tool_id="toolu_abc123", + tool_input=None, +): + """Mock a Claude response that requests a tool call.""" + tool_input = tool_input or {"query": "what is RAG?"} + + tool_block = MagicMock() + tool_block.type = "tool_use" + tool_block.name = tool_name + tool_block.id = tool_id + tool_block.input = tool_input + + response = MagicMock() + response.stop_reason = "tool_use" + response.content = [tool_block] + return response + + +# --------------------------------------------------------------------------- +# Expose factories as fixtures so tests can request them +# --------------------------------------------------------------------------- + +@pytest.fixture +def search_results_factory(): + return make_search_results + + +@pytest.fixture +def error_results_factory(): + return make_error_results + + +@pytest.fixture +def text_response_factory(): + return make_text_response + + +@pytest.fixture +def tool_use_response_factory(): + return make_tool_use_response diff --git a/backend/tests/test_ai_generator.py b/backend/tests/test_ai_generator.py new file mode 100644 index 000000000..5e7901f84 --- /dev/null +++ b/backend/tests/test_ai_generator.py @@ -0,0 +1,399 @@ +""" +Tests that AIGenerator correctly invokes tools via the sequential tool-calling loop. + +Covers: +- Direct text answers when Claude doesn't call a tool +- Tool manager is called when Claude returns stop_reason="tool_use" +- Correct tool name and inputs are forwarded to the tool manager +- A second API call is made after tool execution, carrying the tool result +- The final forced call does NOT include the tools parameter +- tools + tool_choice are set on the first call when tools are provided +- Edge case: stop_reason="tool_use" but no tool_manager provided +- Sequential tool calling: 2 chained rounds, forced stop, error string, exception handling +""" +import pytest +from unittest.mock import MagicMock, patch, call +from ai_generator import AIGenerator +from tests.conftest import make_text_response, make_tool_use_response + + +# --------------------------------------------------------------------------- +# Fixture: AIGenerator with a mocked Anthropic client +# --------------------------------------------------------------------------- + +@pytest.fixture +def generator_and_client(): + """ + Returns (AIGenerator, mock_client) where mock_client is the mock + anthropic.Anthropic() instance injected into the generator. + """ + with patch("ai_generator.anthropic.Anthropic") as mock_class: + mock_client = MagicMock() + mock_class.return_value = mock_client + gen = AIGenerator(api_key="test-key", model="claude-test") + return gen, mock_client + + +# --------------------------------------------------------------------------- +# Direct (no-tool) responses +# --------------------------------------------------------------------------- + +class TestDirectResponse: + def test_returns_text_when_no_tool_use(self, generator_and_client): + gen, client = generator_and_client + client.messages.create.return_value = make_text_response("Paris is the capital of France.") + + result = gen.generate_response(query="What is the capital of France?") + + assert result == "Paris is the capital of France." + + def test_single_api_call_when_no_tool_use(self, generator_and_client): + gen, client = generator_and_client + client.messages.create.return_value = make_text_response() + + gen.generate_response(query="Hello") + + assert client.messages.create.call_count == 1 + + def test_tools_not_in_api_call_when_none_provided(self, generator_and_client): + gen, client = generator_and_client + client.messages.create.return_value = make_text_response() + + gen.generate_response(query="Hello", tools=None) + + api_call_kwargs = client.messages.create.call_args[1] + assert "tools" not in api_call_kwargs + assert "tool_choice" not in api_call_kwargs + + def test_conversation_history_added_to_system_prompt(self, generator_and_client): + gen, client = generator_and_client + client.messages.create.return_value = make_text_response() + + gen.generate_response(query="Follow-up", conversation_history="User: Hi\nAssistant: Hello") + + system_content = client.messages.create.call_args[1]["system"] + assert "User: Hi" in system_content + assert "Assistant: Hello" in system_content + + +# --------------------------------------------------------------------------- +# Tool use: first call triggers tool, second call produces answer +# --------------------------------------------------------------------------- + +class TestToolUseFlow: + def _setup_two_call_sequence(self, client, tool_input=None): + """Configure client to return tool_use on first call, text on second.""" + tool_response = make_tool_use_response( + tool_name="search_course_content", + tool_id="toolu_123", + tool_input=tool_input or {"query": "what is RAG?"}, + ) + final_response = make_text_response("RAG combines retrieval with generation.") + client.messages.create.side_effect = [tool_response, final_response] + + def test_two_api_calls_made_on_tool_use(self, generator_and_client): + gen, client = generator_and_client + self._setup_two_call_sequence(client) + tool_manager = MagicMock() + tool_manager.execute_tool.return_value = "Relevant chunk content." + + gen.generate_response( + query="What is RAG?", + tools=[{"name": "search_course_content"}], + tool_manager=tool_manager, + ) + + assert client.messages.create.call_count == 2 + + def test_tool_manager_called_with_correct_tool_name(self, generator_and_client): + gen, client = generator_and_client + self._setup_two_call_sequence(client, tool_input={"query": "what is RAG?"}) + tool_manager = MagicMock() + tool_manager.execute_tool.return_value = "some content" + + gen.generate_response( + query="What is RAG?", + tools=[{"name": "search_course_content"}], + tool_manager=tool_manager, + ) + + tool_manager.execute_tool.assert_called_once_with( + "search_course_content", query="what is RAG?" + ) + + def test_final_response_text_returned(self, generator_and_client): + gen, client = generator_and_client + self._setup_two_call_sequence(client) + tool_manager = MagicMock() + tool_manager.execute_tool.return_value = "Chunk text." + + result = gen.generate_response( + query="What is RAG?", + tools=[{"name": "search_course_content"}], + tool_manager=tool_manager, + ) + + assert result == "RAG combines retrieval with generation." + + def test_tool_result_injected_into_second_call_messages(self, generator_and_client): + gen, client = generator_and_client + self._setup_two_call_sequence(client) + tool_manager = MagicMock() + tool_manager.execute_tool.return_value = "Retrieved content here." + + gen.generate_response( + query="What is RAG?", + tools=[{"name": "search_course_content"}], + tool_manager=tool_manager, + ) + + second_call_kwargs = client.messages.create.call_args_list[1][1] + messages = second_call_kwargs["messages"] + # Find the tool_result message specifically (role=user, content is a list of tool_result dicts) + tool_result_message = next( + m for m in messages + if isinstance(m.get("content"), list) + and m["content"] + and isinstance(m["content"][0], dict) + and m["content"][0].get("type") == "tool_result" + ) + assert tool_result_message["role"] == "user" + result_block = tool_result_message["content"][0] + assert result_block["type"] == "tool_result" + assert result_block["content"] == "Retrieved content here." + assert result_block["tool_use_id"] == "toolu_123" + + def test_second_call_includes_tools_for_possible_chaining(self, generator_and_client): + """ + With the sequential loop, the second API call is an intermediate call that + still includes tools — Claude can decide to chain a second tool call or + answer directly. If Claude answers directly, the loop exits early (no forced + final call). The forced-final-call-without-tools case is covered by + TestSequentialToolUse.test_forced_final_call_excludes_tools. + """ + gen, client = generator_and_client + self._setup_two_call_sequence(client) + tool_manager = MagicMock() + tool_manager.execute_tool.return_value = "content" + + gen.generate_response( + query="What is RAG?", + tools=[{"name": "search_course_content"}], + tool_manager=tool_manager, + ) + + second_call_kwargs = client.messages.create.call_args_list[1][1] + assert "tools" in second_call_kwargs + assert "tool_choice" in second_call_kwargs + + +# --------------------------------------------------------------------------- +# First-call API parameter validation +# --------------------------------------------------------------------------- + +class TestFirstCallParameters: + def test_tools_included_in_first_call_when_provided(self, generator_and_client): + gen, client = generator_and_client + client.messages.create.return_value = make_text_response() + tools = [{"name": "search_course_content", "description": "search"}] + + gen.generate_response(query="test", tools=tools) + + first_call_kwargs = client.messages.create.call_args[1] + assert first_call_kwargs["tools"] == tools + + def test_tool_choice_auto_set_when_tools_provided(self, generator_and_client): + gen, client = generator_and_client + client.messages.create.return_value = make_text_response() + + gen.generate_response(query="test", tools=[{"name": "some_tool"}]) + + first_call_kwargs = client.messages.create.call_args[1] + assert first_call_kwargs["tool_choice"] == {"type": "auto"} + + def test_user_query_in_messages(self, generator_and_client): + gen, client = generator_and_client + client.messages.create.return_value = make_text_response() + + gen.generate_response(query="What is attention?") + + first_call_kwargs = client.messages.create.call_args[1] + assert first_call_kwargs["messages"][0]["role"] == "user" + assert first_call_kwargs["messages"][0]["content"] == "What is attention?" + + +# --------------------------------------------------------------------------- +# Edge case: tool_use response but no tool_manager +# --------------------------------------------------------------------------- + +class TestMissingToolManager: + def test_returns_graceful_message_when_tool_manager_missing(self, generator_and_client): + """ + If Claude returns stop_reason='tool_use' but no tool_manager is provided, + the generator must return a safe error message rather than crashing. + + Previously the code used a single `and` condition, causing it to fall + through to response.content[0].text on a tool_use block (no .text attribute) + — an AttributeError in production. The fix splits into nested ifs so the + missing-tool_manager case is handled explicitly. + """ + gen, client = generator_and_client + client.messages.create.return_value = make_tool_use_response() + + result = gen.generate_response( + query="What is RAG?", + tools=[{"name": "search_course_content"}], + tool_manager=None, + ) + + assert "tool execution is not available" in result + + +# --------------------------------------------------------------------------- +# Sequential tool calling (up to MAX_ROUNDS = 2) +# --------------------------------------------------------------------------- + +class TestSequentialToolUse: + """ + These tests treat the generator as a black box and assert on observable + outcomes: number of API calls, number of tool executions, return value, + and which calls include/exclude the tools parameter. + """ + + TOOLS = [{"name": "search_course_content"}, {"name": "get_course_outline"}] + + def test_two_tool_calls_three_api_calls(self, generator_and_client): + """Scenario C: Claude chains 2 tool calls then answers — 3 API calls total.""" + gen, client = generator_and_client + tool_manager = MagicMock() + tool_manager.execute_tool.side_effect = ["outline result", "search result"] + + client.messages.create.side_effect = [ + make_tool_use_response("get_course_outline", "id1", {"course_name": "Python 101"}), + make_tool_use_response("search_course_content","id2", {"query": "decorators"}), + make_text_response("Here is the comparison."), + ] + + result = gen.generate_response(query="Compare topics", tools=self.TOOLS, tool_manager=tool_manager) + + assert client.messages.create.call_count == 3 + assert tool_manager.execute_tool.call_count == 2 + assert result == "Here is the comparison." + + def test_intermediate_call_includes_tools(self, generator_and_client): + """The second API call (between round 1 and round 2) must include tools.""" + gen, client = generator_and_client + tool_manager = MagicMock() + tool_manager.execute_tool.side_effect = ["result1", "result2"] + + client.messages.create.side_effect = [ + make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), + make_tool_use_response("search_course_content","id2", {"query": "topic"}), + make_text_response("Final answer."), + ] + + gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + + second_call_kwargs = client.messages.create.call_args_list[1][1] + assert "tools" in second_call_kwargs + assert "tool_choice" in second_call_kwargs + + def test_forced_final_call_excludes_tools(self, generator_and_client): + """The third (forced) API call must NOT include tools regardless of how the loop exited.""" + gen, client = generator_and_client + tool_manager = MagicMock() + tool_manager.execute_tool.side_effect = ["result1", "result2"] + + client.messages.create.side_effect = [ + make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), + make_tool_use_response("search_course_content","id2", {"query": "topic"}), + make_text_response("Forced final answer."), + ] + + gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + + third_call_kwargs = client.messages.create.call_args_list[2][1] + assert "tools" not in third_call_kwargs + assert "tool_choice" not in third_call_kwargs + + def test_early_exit_when_claude_answers_mid_loop(self, generator_and_client): + """ + Scenario: Claude calls a tool in round 1, then returns text in the intermediate + call (round 2 start). The loop should return immediately — no forced final call. + Total: 2 API calls, 1 tool execution. + """ + gen, client = generator_and_client + tool_manager = MagicMock() + tool_manager.execute_tool.return_value = "outline content" + + client.messages.create.side_effect = [ + make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), + make_text_response("I have enough info to answer now."), + ] + + result = gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + + assert client.messages.create.call_count == 2 + assert tool_manager.execute_tool.call_count == 1 + assert result == "I have enough info to answer now." + + def test_tool_error_string_passed_to_claude_loop_continues(self, generator_and_client): + """ + Scenario E: Tool returns an error string (not an exception). + The error string is valid tool result content — loop continues and Claude + gets to reason about the failure. + """ + gen, client = generator_and_client + tool_manager = MagicMock() + tool_manager.execute_tool.return_value = "Error: course not found" + + client.messages.create.side_effect = [ + make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), + make_text_response("I could not find the course."), + ] + + result = gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + + assert client.messages.create.call_count == 2 + assert tool_manager.execute_tool.call_count == 1 + # Error string is present in the messages sent to the final call + final_call_messages = client.messages.create.call_args_list[1][1]["messages"] + tool_result_msg = next( + m for m in final_call_messages + if isinstance(m.get("content"), list) + and m["content"] + and isinstance(m["content"][0], dict) + and m["content"][0].get("type") == "tool_result" + ) + assert tool_result_msg["content"][0]["content"] == "Error: course not found" + assert result == "I could not find the course." + + def test_tool_exception_exits_loop_gracefully(self, generator_and_client): + """ + Scenario F: Tool raises an exception. Loop must exit cleanly to a forced + final call. No exception propagates to the caller. + """ + gen, client = generator_and_client + tool_manager = MagicMock() + tool_manager.execute_tool.side_effect = RuntimeError("DB connection failed") + + client.messages.create.side_effect = [ + make_tool_use_response("search_course_content", "id1", {"query": "X"}), + make_text_response("I encountered an error searching for that."), + ] + + result = gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + + assert client.messages.create.call_count == 2 + assert tool_manager.execute_tool.call_count == 1 + # Exception is caught and turned into a tool_result message + final_call_messages = client.messages.create.call_args_list[1][1]["messages"] + tool_result_msg = next( + m for m in final_call_messages + if isinstance(m.get("content"), list) + and m["content"] + and isinstance(m["content"][0], dict) + and m["content"][0].get("type") == "tool_result" + ) + assert "Tool execution failed" in tool_result_msg["content"][0]["content"] + assert result == "I encountered an error searching for that." diff --git a/backend/tests/test_course_search_tool.py b/backend/tests/test_course_search_tool.py new file mode 100644 index 000000000..22f8f0ea6 --- /dev/null +++ b/backend/tests/test_course_search_tool.py @@ -0,0 +1,254 @@ +""" +Tests for CourseSearchTool.execute() + +Covers: +- Error propagation from the vector store +- Empty-result messages (with and without filter annotations) +- Correct result formatting (headers, content) +- Source tracking and deduplication +- Parameter passthrough to VectorStore.search() +""" +import pytest +from unittest.mock import MagicMock, call +from search_tools import CourseSearchTool +from vector_store import SearchResults +from tests.conftest import make_search_results, make_error_results + + +# --------------------------------------------------------------------------- +# Helpers +# --------------------------------------------------------------------------- + +def make_store(search_return=None): + """Return a mock VectorStore with search() pre-configured.""" + store = MagicMock() + store.search.return_value = search_return or SearchResults( + documents=[], metadata=[], distances=[], error=None + ) + store.get_lesson_link.return_value = "https://example.com/lesson" + return store + + +# --------------------------------------------------------------------------- +# Error handling +# --------------------------------------------------------------------------- + +class TestErrorHandling: + def test_returns_error_string_from_store(self): + """Tool must pass the raw error string back so Claude can report it.""" + store = make_store(make_error_results("Search error: db timeout")) + tool = CourseSearchTool(store) + + result = tool.execute(query="what is RAG?") + + assert result == "Search error: db timeout" + + def test_error_result_prevents_formatting(self): + """When an error is present, _format_results must never be called.""" + store = make_store(make_error_results("Search error: embedding failed")) + tool = CourseSearchTool(store) + tool._format_results = MagicMock() + + tool.execute(query="something") + + tool._format_results.assert_not_called() + + +# --------------------------------------------------------------------------- +# Empty results +# --------------------------------------------------------------------------- + +class TestEmptyResults: + def test_no_content_found_message_baseline(self): + store = make_store() # empty results, no error + tool = CourseSearchTool(store) + + result = tool.execute(query="what is RAG?") + + assert result == "No relevant content found." + + def test_no_content_includes_course_name(self): + store = make_store() + tool = CourseSearchTool(store) + + result = tool.execute(query="what is RAG?", course_name="AI Fundamentals") + + assert "No relevant content found" in result + assert "AI Fundamentals" in result + + def test_no_content_includes_lesson_number(self): + store = make_store() + tool = CourseSearchTool(store) + + result = tool.execute(query="what is RAG?", lesson_number=3) + + assert "No relevant content found" in result + assert "3" in result + + def test_no_content_with_both_filters(self): + store = make_store() + tool = CourseSearchTool(store) + + result = tool.execute(query="embeddings", course_name="MCP Course", lesson_number=2) + + assert "MCP Course" in result + assert "2" in result + + +# --------------------------------------------------------------------------- +# Successful result formatting +# --------------------------------------------------------------------------- + +class TestResultFormatting: + def test_result_header_contains_course_title(self): + store = make_store(make_search_results( + documents=["Embeddings are dense vectors."], + metadata=[{"course_title": "Vector DB Deep Dive", "lesson_number": 1}], + )) + tool = CourseSearchTool(store) + + result = tool.execute(query="what are embeddings?") + + assert "[Vector DB Deep Dive - Lesson 1]" in result + + def test_result_body_contains_document_text(self): + store = make_store(make_search_results( + documents=["RAG retrieves relevant chunks before generation."], + metadata=[{"course_title": "RAG Course", "lesson_number": 2}], + )) + tool = CourseSearchTool(store) + + result = tool.execute(query="what is RAG?") + + assert "RAG retrieves relevant chunks before generation." in result + + def test_header_omits_lesson_when_none(self): + """If lesson_number is None in metadata, the header should not show 'Lesson'.""" + store = make_store(make_search_results( + documents=["Course intro text."], + metadata=[{"course_title": "Intro Course", "lesson_number": None}], + )) + tool = CourseSearchTool(store) + + result = tool.execute(query="intro") + + assert "[Intro Course]" in result + assert "Lesson" not in result + + def test_multiple_results_separated_by_blank_lines(self): + store = make_store(make_search_results( + documents=["Chunk A.", "Chunk B."], + metadata=[ + {"course_title": "Course X", "lesson_number": 1}, + {"course_title": "Course X", "lesson_number": 2}, + ], + )) + tool = CourseSearchTool(store) + + result = tool.execute(query="something") + + assert "Chunk A." in result + assert "Chunk B." in result + # Results are joined with double newlines + assert "\n\n" in result + + +# --------------------------------------------------------------------------- +# Source tracking +# --------------------------------------------------------------------------- + +class TestSourceTracking: + def test_last_sources_populated_after_search(self): + store = make_store(make_search_results( + documents=["content"], + metadata=[{"course_title": "AI Course", "lesson_number": 1}], + )) + store.get_lesson_link.return_value = "https://example.com/lesson1" + tool = CourseSearchTool(store) + + tool.execute(query="something") + + assert len(tool.last_sources) == 1 + assert tool.last_sources[0]["label"] == "AI Course - Lesson 1" + assert tool.last_sources[0]["url"] == "https://example.com/lesson1" + + def test_sources_deduplicated_for_same_lesson(self): + """Two chunks from the same lesson should produce only one source entry.""" + store = make_store(make_search_results( + documents=["chunk 1", "chunk 2"], + metadata=[ + {"course_title": "AI Course", "lesson_number": 1}, + {"course_title": "AI Course", "lesson_number": 1}, + ], + )) + tool = CourseSearchTool(store) + + tool.execute(query="something") + + assert len(tool.last_sources) == 1 + + def test_sources_empty_on_error(self): + """An errored search must not populate last_sources.""" + store = make_store(make_error_results()) + tool = CourseSearchTool(store) + + tool.execute(query="something") + + assert tool.last_sources == [] + + def test_sources_empty_on_empty_results(self): + """No results means no sources.""" + store = make_store() + tool = CourseSearchTool(store) + + tool.execute(query="something") + + assert tool.last_sources == [] + + +# --------------------------------------------------------------------------- +# Parameter passthrough +# --------------------------------------------------------------------------- + +class TestParameterPassthrough: + def test_query_passed_to_store(self): + store = make_store() + tool = CourseSearchTool(store) + + tool.execute(query="what is transformer architecture?") + + store.search.assert_called_once_with( + query="what is transformer architecture?", + course_name=None, + lesson_number=None, + ) + + def test_course_name_passed_to_store(self): + store = make_store() + tool = CourseSearchTool(store) + + tool.execute(query="test", course_name="MCP") + + store.search.assert_called_once_with( + query="test", course_name="MCP", lesson_number=None + ) + + def test_lesson_number_passed_to_store(self): + store = make_store() + tool = CourseSearchTool(store) + + tool.execute(query="test", lesson_number=5) + + store.search.assert_called_once_with( + query="test", course_name=None, lesson_number=5 + ) + + def test_all_params_passed_together(self): + store = make_store() + tool = CourseSearchTool(store) + + tool.execute(query="embeddings", course_name="Vector DB", lesson_number=3) + + store.search.assert_called_once_with( + query="embeddings", course_name="Vector DB", lesson_number=3 + ) diff --git a/backend/tests/test_rag_system.py b/backend/tests/test_rag_system.py new file mode 100644 index 000000000..93e191ec4 --- /dev/null +++ b/backend/tests/test_rag_system.py @@ -0,0 +1,208 @@ +""" +Tests for RAGSystem's handling of content-related queries. + +Covers: +- Tools are forwarded to the AI generator on every query +- Sources are returned from the last tool search +- Sources are reset (cleared) after each query so they don't bleed into the next +- Conversation history is passed to the generator when a session exists +- No history is passed for new / unknown sessions +- End-to-end content query flow: Claude calls the search tool, result is synthesized +""" +import pytest +from unittest.mock import MagicMock, patch, call +from tests.conftest import make_text_response, make_tool_use_response + + +# --------------------------------------------------------------------------- +# RAGSystem fixture — all heavy dependencies mocked at class level +# --------------------------------------------------------------------------- + +@pytest.fixture +def rag(): + """ + Returns a RAGSystem with VectorStore, AIGenerator, and DocumentProcessor + replaced by MagicMocks so no disk I/O or API calls occur. + """ + from config import Config + + config = Config( + ANTHROPIC_API_KEY="test-key", + ANTHROPIC_MODEL="claude-test", + CHROMA_PATH="./test_chroma", + ) + + with patch("rag_system.VectorStore"), \ + patch("rag_system.AIGenerator"), \ + patch("rag_system.DocumentProcessor"): + from rag_system import RAGSystem + system = RAGSystem(config) + + return system + + +# --------------------------------------------------------------------------- +# Tool forwarding +# --------------------------------------------------------------------------- + +class TestToolForwarding: + def test_tools_passed_to_ai_generator(self, rag): + """generate_response must receive the registered tool definitions.""" + rag.ai_generator.generate_response.return_value = "Direct answer." + + rag.query("What is RAG?") + + call_kwargs = rag.ai_generator.generate_response.call_args[1] + assert call_kwargs["tools"] is not None + assert len(call_kwargs["tools"]) > 0 + + def test_tool_manager_passed_to_ai_generator(self, rag): + """The tool_manager must be passed so the generator can execute tool calls.""" + rag.ai_generator.generate_response.return_value = "answer" + + rag.query("What is RAG?") + + call_kwargs = rag.ai_generator.generate_response.call_args[1] + assert call_kwargs["tool_manager"] is rag.tool_manager + + def test_search_course_content_tool_registered(self, rag): + """CourseSearchTool must be present in the tool definitions.""" + tool_names = [t["name"] for t in rag.tool_manager.get_tool_definitions()] + assert "search_course_content" in tool_names + + def test_get_course_outline_tool_registered(self, rag): + """CourseOutlineTool must also be present in the tool definitions.""" + tool_names = [t["name"] for t in rag.tool_manager.get_tool_definitions()] + assert "get_course_outline" in tool_names + + +# --------------------------------------------------------------------------- +# Source management +# --------------------------------------------------------------------------- + +class TestSourceManagement: + def test_sources_returned_from_last_search(self, rag): + """query() must return whatever sources the search tool recorded.""" + rag.ai_generator.generate_response.return_value = "answer" + expected_sources = [{"label": "AI Course - Lesson 1", "url": "https://example.com"}] + rag.search_tool.last_sources = expected_sources + + _, sources = rag.query("What is attention?") + + assert sources == expected_sources + + def test_sources_reset_after_query(self, rag): + """After returning sources, they must be cleared for the next query.""" + rag.ai_generator.generate_response.return_value = "answer" + rag.search_tool.last_sources = [{"label": "Some Course", "url": None}] + + rag.query("First query") + # Simulate a second query where the search tool found nothing + rag.search_tool.last_sources = [] + _, sources = rag.query("Second query — no search") + + assert sources == [] + + def test_empty_sources_when_no_tool_called(self, rag): + """If Claude answered directly (no search), sources list must be empty.""" + rag.ai_generator.generate_response.return_value = "Direct answer." + # last_sources was never set (starts as []) + + _, sources = rag.query("What is 2 + 2?") + + assert sources == [] + + +# --------------------------------------------------------------------------- +# Conversation history +# --------------------------------------------------------------------------- + +class TestConversationHistory: + def test_history_passed_when_session_exists(self, rag): + """For a known session with history, generate_response must receive it.""" + session_id = rag.session_manager.create_session() + rag.session_manager.add_exchange(session_id, "Hi", "Hello!") + rag.ai_generator.generate_response.return_value = "answer" + + rag.query("Follow-up question", session_id=session_id) + + call_kwargs = rag.ai_generator.generate_response.call_args[1] + history = call_kwargs["conversation_history"] + assert history is not None + assert "Hi" in history + assert "Hello!" in history + + def test_no_history_for_new_session(self, rag): + """A brand-new session has no history; None must be passed.""" + session_id = rag.session_manager.create_session() + rag.ai_generator.generate_response.return_value = "answer" + + rag.query("First message", session_id=session_id) + + call_kwargs = rag.ai_generator.generate_response.call_args[1] + assert call_kwargs["conversation_history"] is None + + def test_no_history_when_no_session_id(self, rag): + """Queries without a session_id must pass history=None.""" + rag.ai_generator.generate_response.return_value = "answer" + + rag.query("Stateless question", session_id=None) + + call_kwargs = rag.ai_generator.generate_response.call_args[1] + assert call_kwargs["conversation_history"] is None + + def test_exchange_stored_after_query(self, rag): + """The query/response pair must be saved to session history.""" + session_id = rag.session_manager.create_session() + rag.ai_generator.generate_response.return_value = "RAG is useful." + + rag.query("Tell me about RAG.", session_id=session_id) + + history = rag.session_manager.get_conversation_history(session_id) + assert "Tell me about RAG." in history + assert "RAG is useful." in history + + +# --------------------------------------------------------------------------- +# End-to-end content query flow +# --------------------------------------------------------------------------- + +class TestContentQueryFlow: + def test_content_query_uses_search_and_synthesizes_answer(self, rag): + """ + Simulates the full path for a content question: + 1. AI decides to call search_course_content + 2. Tool executes and returns chunks + 3. AI synthesizes a final answer + + All external calls (Anthropic API, ChromaDB) are mocked. + """ + # Simulate the AI generator going through the tool-use loop internally + # and returning the final synthesized answer + rag.ai_generator.generate_response.return_value = ( + "RAG stands for Retrieval-Augmented Generation." + ) + # Simulate search tool populating sources + rag.search_tool.last_sources = [ + {"label": "RAG Course - Lesson 1", "url": "https://example.com/rag/1"} + ] + + response, sources = rag.query("What does RAG stand for?") + + assert "RAG" in response + assert len(sources) == 1 + assert sources[0]["label"] == "RAG Course - Lesson 1" + + def test_query_response_and_sources_independent_across_calls(self, rag): + """Sources from query N must not leak into query N+1.""" + rag.ai_generator.generate_response.return_value = "answer" + + # First query leaves sources + rag.search_tool.last_sources = [{"label": "Course A - Lesson 1", "url": None}] + rag.query("First question") + + # Second query — no search performed + rag.search_tool.last_sources = [] + _, sources = rag.query("Second question") + + assert sources == [] diff --git a/backend/tests/test_vector_store.py b/backend/tests/test_vector_store.py new file mode 100644 index 000000000..4780c6f0f --- /dev/null +++ b/backend/tests/test_vector_store.py @@ -0,0 +1,241 @@ +""" +Integration tests for VectorStore using a real (temporary) ChromaDB instance. + +Unlike the other test files that mock VectorStore entirely, these tests exercise +the actual ChromaDB layer. This is where bugs like MAX_RESULTS = 0 become visible: +a misconfigured value won't raise an error — it will silently return empty results, +which only an end-to-end test can catch. + +NOTE: First run downloads the sentence-transformer model if not already cached. +Subsequent runs are fast. +""" +import pytest +from vector_store import VectorStore +from models import Course, Lesson, CourseChunk +from config import Config + + +# --------------------------------------------------------------------------- +# Fixtures +# --------------------------------------------------------------------------- + +@pytest.fixture +def store(tmp_path): + """Real VectorStore backed by a temporary ChromaDB directory.""" + return VectorStore( + chroma_path=str(tmp_path / "test_chroma"), + embedding_model="all-MiniLM-L6-v2", + max_results=Config.MAX_RESULTS, + ) + + +@pytest.fixture +def sample_course(): + """A minimal course with two lessons for use in multiple tests.""" + return Course( + title="Introduction to RAG", + course_link="https://example.com/rag", + instructor="Test Instructor", + lessons=[ + Lesson(lesson_number=0, title="Overview", lesson_link="https://example.com/rag/0"), + Lesson(lesson_number=1, title="Embeddings and Vector Search", lesson_link="https://example.com/rag/1"), + ], + ) + + +@pytest.fixture +def sample_chunks(sample_course): + """Content chunks for sample_course, more than MAX_RESULTS to test the cap.""" + return [ + CourseChunk( + content=f"RAG lesson content chunk number {i}. Retrieval augmented generation.", + course_title=sample_course.title, + lesson_number=1, + chunk_index=i, + ) + for i in range(Config.MAX_RESULTS + 3) + ] + + +# --------------------------------------------------------------------------- +# 1. Config validation — catches silent misconfigurations +# --------------------------------------------------------------------------- + +class TestConfigValidation: + def test_max_results_is_positive(self): + """MAX_RESULTS = 0 causes ChromaDB to return nothing; must be > 0.""" + assert Config.MAX_RESULTS > 0 + + def test_chunk_size_is_positive(self): + assert Config.CHUNK_SIZE > 0 + + def test_chunk_overlap_less_than_chunk_size(self): + """Overlap >= chunk size would cause infinite chunking loops.""" + assert Config.CHUNK_OVERLAP < Config.CHUNK_SIZE + + def test_embedding_model_is_set(self): + assert Config.EMBEDDING_MODEL != "" + + def test_anthropic_model_is_set(self): + assert Config.ANTHROPIC_MODEL != "" + + +# --------------------------------------------------------------------------- +# 2. Initialization — collections are created on startup +# --------------------------------------------------------------------------- + +class TestInitialization: + def test_course_catalog_collection_created(self, store): + assert store.course_catalog is not None + + def test_course_content_collection_created(self, store): + assert store.course_content is not None + + def test_new_store_has_zero_courses(self, store): + assert store.get_course_count() == 0 + + def test_new_store_has_empty_titles_list(self, store): + assert store.get_existing_course_titles() == [] + + +# --------------------------------------------------------------------------- +# 3. Data ingestion and retrieval +# --------------------------------------------------------------------------- + +class TestDataIngestion: + def test_add_course_increments_count(self, store, sample_course): + store.add_course_metadata(sample_course) + assert store.get_course_count() == 1 + + def test_added_course_appears_in_titles(self, store, sample_course): + store.add_course_metadata(sample_course) + assert sample_course.title in store.get_existing_course_titles() + + def test_course_link_retrievable_by_exact_title(self, store, sample_course): + store.add_course_metadata(sample_course) + assert store.get_course_link(sample_course.title) == sample_course.course_link + + def test_lesson_link_retrievable(self, store, sample_course): + store.add_course_metadata(sample_course) + url = store.get_lesson_link(sample_course.title, lesson_number=1) + assert url == "https://example.com/rag/1" + + def test_unknown_course_link_returns_none(self, store): + result = store.get_course_link("Nonexistent Course Title") + assert result is None + + def test_multiple_courses_counted_correctly(self, store, sample_course): + course2 = Course( + title="Advanced Prompt Engineering", + course_link="https://example.com/pe", + instructor="Another Instructor", + lessons=[Lesson(lesson_number=0, title="Intro", lesson_link="https://example.com/pe/0")], + ) + store.add_course_metadata(sample_course) + store.add_course_metadata(course2) + assert store.get_course_count() == 2 + + +# --------------------------------------------------------------------------- +# 4. Search — the MAX_RESULTS = 0 guard +# --------------------------------------------------------------------------- + +class TestSearch: + def test_search_returns_results_for_relevant_query(self, store, sample_course, sample_chunks): + """ + The critical integration test. With real content indexed, a relevant + query must return results. If MAX_RESULTS = 0, this fails even though + no error is raised — ChromaDB just returns nothing. + """ + store.add_course_content(sample_chunks) + results = store.search(query="RAG retrieval augmented generation") + assert not results.is_empty() + + def test_search_result_count_respects_max_results(self, store, sample_course, sample_chunks): + """Number of results returned must never exceed MAX_RESULTS.""" + store.add_course_content(sample_chunks) + results = store.search(query="RAG retrieval") + assert len(results.documents) <= Config.MAX_RESULTS + + def test_search_result_metadata_contains_course_title(self, store, sample_course, sample_chunks): + store.add_course_content(sample_chunks) + results = store.search(query="RAG retrieval") + assert all( + m.get("course_title") == sample_course.title + for m in results.metadata + ) + + def test_search_with_course_filter_returns_only_matching_course(self, store, sample_course, sample_chunks): + other_chunks = [ + CourseChunk( + content="Machine learning neural networks deep learning.", + course_title="Deep Learning Fundamentals", + lesson_number=1, + chunk_index=0, + ) + ] + store.add_course_content(sample_chunks) + store.add_course_content(other_chunks) + + results = store.search(query="neural networks", course_name="Introduction to RAG") + # All returned results must be from the filtered course + assert all(m["course_title"] == sample_course.title for m in results.metadata) + + def test_search_returns_no_error_on_success(self, store, sample_chunks): + store.add_course_content(sample_chunks) + results = store.search(query="RAG retrieval") + assert results.error is None + + def test_search_empty_catalog_returns_empty_results(self, store): + """With no content indexed, search should return empty (not crash).""" + results = store.search(query="anything") + assert results.is_empty() + + +# --------------------------------------------------------------------------- +# 5. Course outline (our new get_course_outline method) +# --------------------------------------------------------------------------- + +class TestCourseOutline: + def test_outline_contains_correct_title(self, store, sample_course): + store.add_course_metadata(sample_course) + outline = store.get_course_outline(sample_course.title) + assert outline["title"] == sample_course.title + + def test_outline_contains_correct_course_link(self, store, sample_course): + store.add_course_metadata(sample_course) + outline = store.get_course_outline(sample_course.title) + assert outline["course_link"] == sample_course.course_link + + def test_outline_contains_all_lessons(self, store, sample_course): + store.add_course_metadata(sample_course) + outline = store.get_course_outline(sample_course.title) + assert len(outline["lessons"]) == len(sample_course.lessons) + + def test_outline_lessons_have_number_and_title(self, store, sample_course): + store.add_course_metadata(sample_course) + outline = store.get_course_outline(sample_course.title) + for lesson in outline["lessons"]: + assert "lesson_number" in lesson + assert "lesson_title" in lesson + + def test_outline_fuzzy_matches_partial_name(self, store, sample_course): + """Partial names (e.g. 'RAG') should resolve to the right course.""" + store.add_course_metadata(sample_course) + outline = store.get_course_outline("RAG") + assert outline is not None + assert outline["title"] == sample_course.title + + def test_outline_returns_none_for_empty_catalog(self, store): + """With no courses indexed, any lookup should return None.""" + result = store.get_course_outline("Introduction to RAG") + assert result is None + + def test_get_all_courses_metadata_returns_parsed_lessons(self, store, sample_course): + store.add_course_metadata(sample_course) + all_meta = store.get_all_courses_metadata() + assert len(all_meta) == 1 + # lessons_json should be parsed into a list + assert "lessons" in all_meta[0] + assert isinstance(all_meta[0]["lessons"], list) + assert "lessons_json" not in all_meta[0] diff --git a/backend/vector_store.py b/backend/vector_store.py index 390abe71c..fe2aff3bb 100644 --- a/backend/vector_store.py +++ b/backend/vector_store.py @@ -233,6 +233,29 @@ def get_all_courses_metadata(self) -> List[Dict[str, Any]]: print(f"Error getting courses metadata: {e}") return [] + def get_course_outline(self, course_name: str) -> Optional[Dict[str, Any]]: + """Get structured outline (title, link, lessons) for a course by name (fuzzy match)""" + import json + resolved_title = self._resolve_course_name(course_name) + if not resolved_title: + return None + try: + results = self.course_catalog.get(ids=[resolved_title]) + if results and 'metadatas' in results and results['metadatas']: + metadata = results['metadatas'][0] + lessons = json.loads(metadata.get('lessons_json', '[]')) + return { + 'title': metadata.get('title'), + 'course_link': metadata.get('course_link'), + 'lessons': [ + {'lesson_number': l['lesson_number'], 'lesson_title': l['lesson_title']} + for l in lessons + ] + } + except Exception as e: + print(f"Error getting course outline: {e}") + return None + def get_course_link(self, course_title: str) -> Optional[str]: """Get course link for a given course title""" try: diff --git a/notes.md b/notes.md index 1c355ed96..654354b88 100644 --- a/notes.md +++ b/notes.md @@ -19,6 +19,16 @@ By default Claude Code can read files, run bash commands, search code, etc. MCP 2. Claude Code connects to it via the `/mcp` command or settings 3. The server exposes tools that Claude can call just like any built-in tool +## run.sh vs Manual uvicorn Command + +Both `./run.sh` and `cd backend && uv run uvicorn app:app --reload --port 8000` start the same server. The difference is that `run.sh` adds safety checks before launching: + +1. Creates the `/docs` directory if it doesn't exist (`mkdir -p docs`) +2. Validates that the `backend/` directory exists and exits with an error if not +3. Prints a reminder to check your `ANTHROPIC_API_KEY` + +Then it runs the identical `uvicorn` command. Use `./run.sh` for day-to-day startup; use the manual command only if the script fails or you need to customize flags. + ## Setting Up a Custom Skill (/log command) Custom slash commands in Claude Code are called **skills** and must follow a specific folder structure to be recognized. @@ -36,3 +46,73 @@ Custom slash commands in Claude Code are called **skills** and must follow a spe - `.claude/commands/log.md` — the old format, no longer supported **Important:** Claude Code only scans for skills on startup — a full restart is required after creating a new skill for it to be recognized. + +## Adding a Second Tool to the RAG System (CourseOutlineTool) + +New tools in this RAG system must implement the `Tool` ABC defined in `search_tools.py` (two methods: `get_tool_definition()` and `execute()`), then be registered with `ToolManager.register_tool()` in `rag_system.py`. + +**What was built:** `CourseOutlineTool` — answers "what lessons does course X have?" queries without doing a content search. It takes a course name (partial matches work), fuzzy-resolves it via `VectorStore._resolve_course_name()`, then fetches structured metadata (title, course link, lesson numbers and titles) from the `course_catalog` ChromaDB collection. + +**Key design points:** +- Course metadata is already stored in `course_catalog` with a `lessons_json` field (a JSON string of `[{lesson_number, lesson_title, lesson_link}]`) — no re-indexing needed +- `VectorStore.get_course_outline()` was added as a public method that resolves the name and parses `lessons_json` into a clean dict +- The system prompt in `ai_generator.py` was updated to distinguish the two tools: use `get_course_outline` for structure/outline queries, `search_course_content` for content queries +- The tool is registered alongside `CourseSearchTool` in `RAGSystem.__init__()` + +## tools vs tool_manager in the Anthropic Tool-Calling Flow + +These are two separate things that work together when Claude uses a tool. + +**`tools`** is a plain list of JSON schema definitions sent to the Anthropic API. It tells Claude what tools exist, what they do, and what inputs they accept. Claude reads these and decides on its own whether to call one. Produced by `ToolManager.get_tool_definitions()` in `search_tools.py`. + +**`tool_manager`** is the Python `ToolManager` object that holds the actual tool instances and executes them. When Claude replies with `stop_reason = "tool_use"`, `AIGenerator` calls `tool_manager.execute_tool(name, **inputs)`, which routes to the right tool's `execute()` method and returns real results. + +**Why they're separate:** Claude only ever sees the JSON schema (`tools`) — it has no access to your Python code. The five-step loop is: +1. Send Claude the tool schemas +2. Claude replies: "call tool X with these inputs" +3. Your code runs `tool_manager.execute_tool(...)` locally +4. You send Claude the result +5. Claude synthesizes the final answer + +Both `tools` and `tool_manager` pre-existed the test files added today — the tests only verify their behavior. + +## Defensive Gap: stop_reason="tool_use" Without a tool_manager + +In `ai_generator.py`, the condition that routes to tool execution is: + +```python +if response.stop_reason == "tool_use" and tool_manager: + return self._handle_tool_execution(...) +return response.content[0].text # ← danger zone +``` + +If Claude decides to use a tool but `tool_manager` is None, the `and` makes the whole condition False and the code falls through to `.text` on a tool-use content block — which has no `.text` attribute in real Anthropic responses → `AttributeError` crash. + +**Why it doesn't crash in production:** `RAGSystem.query()` always passes both `tools` and `tool_manager` together, so the None path is never reached through the browser UI. + +**Why the test missed it:** `MagicMock()` auto-creates any attribute accessed on it, so `mock_block.text` returns another MagicMock instead of raising `AttributeError`. The test expected a crash but got silent success. + +**The fix:** Split the `and` into nested `if` statements so the missing-tool_manager case returns a graceful error message instead of crashing. Update the test to assert the error message rather than expecting `AttributeError`. + +## Plan A: Sequential Tool Calling via Loop in `_handle_tool_execution` + +The approach to support up to 2 chained tool calls per query (Plan A) keeps the existing method name and converts its body into a bounded loop. + +**Key design decisions:** +- `MAX_ROUNDS = 2` as a class constant on `AIGenerator` — policy decision, not a runtime param +- `_handle_tool_execution` signature stays the same; `base_params` already contains `tools` and `tool_choice` from `generate_response` +- Each loop iteration: execute tools → append assistant + tool_result messages → check stop conditions +- **3 stop conditions:** (a) Claude returns no tool_use mid-loop → early return from inside loop; (b) tool raises exception → break to forced final call; (c) MAX_ROUNDS exhausted → break to forced final call +- Intermediate calls include `tools` so Claude can chain; the forced final call always strips them +- Tool returning an error *string* is NOT an error — it's valid content Claude can reason about; only exceptions trigger early exit +- System prompt updated: remove "one tool call max", add guidance that chaining is allowed when the second call depends on the first + +**API call counts by scenario:** + +| Scenario | API calls | Tool calls | +|---|---|---| +| Direct answer | 1 | 0 | +| 1 tool → answer | 2 | 1 | +| 2 tools → answer | 3 | 2 | +| Tool error string | 2 | 1 | +| Tool exception | 2 | 1 | From 4d82e4f4bfad7ba1b245002798e8447d813b1424 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Mon, 18 May 2026 10:11:41 -0700 Subject: [PATCH 07/12] Add pytest allowlist entries and notes on semantic search and settings.local.json - Allow two specific pytest bash commands in settings.local.json permissions - Document semantic vs. fuzzy course name resolution in notes.md - Explain why settings.local.json should be committed separately from feature changes Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- .claude/settings.local.json | 5 ++++- notes.md | 17 +++++++++++++++++ 2 files changed, 21 insertions(+), 1 deletion(-) diff --git a/.claude/settings.local.json b/.claude/settings.local.json index 87fefe214..e0077272f 100644 --- a/.claude/settings.local.json +++ b/.claude/settings.local.json @@ -3,7 +3,10 @@ "allow": [ "mcp__playwright__browser_navigate", "mcp__playwright__browser_take_screenshot", - "mcp__playwright__browser_evaluate" + "mcp__playwright__browser_evaluate", + "Bash(UV_LINK_MODE=copy uv run --with pytest pytest tests/test_vector_store.py -v)", + "Bash(UV_LINK_MODE=copy uv run --with pytest pytest tests/ -v)", + "Bash(git add *)" ] } } diff --git a/notes.md b/notes.md index 654354b88..199ab3f2e 100644 --- a/notes.md +++ b/notes.md @@ -116,3 +116,20 @@ The approach to support up to 2 chained tool calls per query (Plan A) keeps the | 2 tools → answer | 3 | 2 | | Tool error string | 2 | 1 | | Tool exception | 2 | 1 | + +## Semantic vs. Fuzzy Course Name Resolution + +`_resolve_course_name()` in `vector_store.py` is sometimes called "fuzzy matching" but it's actually **semantic/vector search** — more powerful than traditional fuzzy string matching (e.g. Levenshtein distance). + +**How it works:** +1. Your input (e.g. `"RAG"`) is converted to an embedding vector by `sentence-transformers` +2. ChromaDB finds the course title vector with the highest cosine similarity +3. That title is returned — even if the input words don't appear in the title at all + +So `"retrieval augmented generation course"` resolves to `"Introduction to RAG"` purely on semantic similarity, not string overlap. + +**Important limitation:** There is no similarity threshold — it always returns the closest match even for completely unrelated queries. This is why `test_get_course_outline_returns_none_for_empty_catalog` tests the empty-catalog case (guaranteed None) rather than an "unrelated query" case (which would still return *something*). + +## Why .claude/settings.local.json Is Not Committed with Feature Changes + +`.claude/settings.local.json` holds local IDE preferences, permissions, and hook settings personal to one machine. Even though it is a tracked file, it should not be bundled into feature commits — doing so would add noise and could overwrite another developer's local configuration. It is staged and committed separately, only when its changes are intentional. From 3fe8058b414c9179cbc26999a5cef0888a228f25 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Mon, 18 May 2026 11:04:40 -0700 Subject: [PATCH 08/12] Add API endpoint tests, pytest config, and shared fixtures - Add backend/tests/test_api.py with 14 tests covering POST /api/query, GET /api/courses, and DELETE /api/session using an inline test app that mirrors app.py routes without the static file mount - Add mock_rag_system fixture to conftest.py for reuse across API tests - Add [tool.pytest.ini_options] to pyproject.toml (testpaths, pythonpath, addopts) so pytest can be run from the project root without manual config - Add [dependency-groups] dev with pytest>=8.0 and httpx>=0.27 Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- backend/tests/conftest.py | 25 ++++++ backend/tests/test_api.py | 156 ++++++++++++++++++++++++++++++++++++++ pyproject.toml | 11 +++ uv.lock | 48 +++++++++++- 4 files changed, 239 insertions(+), 1 deletion(-) create mode 100644 backend/tests/test_api.py diff --git a/backend/tests/conftest.py b/backend/tests/conftest.py index 4f03cbc58..15f87995b 100644 --- a/backend/tests/conftest.py +++ b/backend/tests/conftest.py @@ -89,3 +89,28 @@ def text_response_factory(): @pytest.fixture def tool_use_response_factory(): return make_tool_use_response + + +# --------------------------------------------------------------------------- +# RAGSystem mock for API endpoint tests +# --------------------------------------------------------------------------- + +@pytest.fixture +def mock_rag_system(): + """ + Fully configured mock RAGSystem for API endpoint tests. + + Provides realistic default return values so tests can assert on + response shape without wiring up ChromaDB or the Anthropic API. + """ + mock = MagicMock() + mock.session_manager.create_session.return_value = "session-abc123" + mock.query.return_value = ( + "RAG stands for Retrieval-Augmented Generation.", + [{"label": "AI Course - Lesson 1", "url": "https://example.com/1"}], + ) + mock.get_course_analytics.return_value = { + "total_courses": 2, + "course_titles": ["Python 101", "AI Fundamentals"], + } + return mock diff --git a/backend/tests/test_api.py b/backend/tests/test_api.py new file mode 100644 index 000000000..7c24ab5bf --- /dev/null +++ b/backend/tests/test_api.py @@ -0,0 +1,156 @@ +""" +Tests for the FastAPI API endpoints (/api/query, /api/courses, /api/session). + +app.py mounts static files from ../frontend and instantiates RAGSystem at +module level — both fail in the test environment. Instead, this file builds +a minimal test app that mirrors the same routes and Pydantic models, backed +by the mock_rag_system fixture from conftest.py. +""" +import pytest +from fastapi import FastAPI, HTTPException +from fastapi.testclient import TestClient +from pydantic import BaseModel +from typing import List, Optional + + +# --------------------------------------------------------------------------- +# Minimal test app — same routes and models as app.py, no static files +# --------------------------------------------------------------------------- + +def _build_test_app(rag_system) -> FastAPI: + """Return a FastAPI app with the same routes as app.py.""" + app = FastAPI() + + class QueryRequest(BaseModel): + query: str + session_id: Optional[str] = None + + class QueryResponse(BaseModel): + answer: str + sources: List[dict] + session_id: str + + class CourseStats(BaseModel): + total_courses: int + course_titles: List[str] + + @app.post("/api/query", response_model=QueryResponse) + async def query_documents(request: QueryRequest): + try: + session_id = request.session_id + if not session_id: + session_id = rag_system.session_manager.create_session() + answer, sources = rag_system.query(request.query, session_id) + return QueryResponse(answer=answer, sources=sources, session_id=session_id) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + @app.get("/api/courses", response_model=CourseStats) + async def get_course_stats(): + try: + analytics = rag_system.get_course_analytics() + return CourseStats( + total_courses=analytics["total_courses"], + course_titles=analytics["course_titles"], + ) + except Exception as e: + raise HTTPException(status_code=500, detail=str(e)) + + @app.delete("/api/session/{session_id}") + async def clear_session(session_id: str): + rag_system.session_manager.clear_session(session_id) + return {"status": "cleared"} + + return app + + +@pytest.fixture +def client(mock_rag_system): + with TestClient(_build_test_app(mock_rag_system)) as c: + yield c + + +# --------------------------------------------------------------------------- +# POST /api/query +# --------------------------------------------------------------------------- + +class TestQueryEndpoint: + def test_returns_200_with_valid_body(self, client): + resp = client.post("/api/query", json={"query": "What is RAG?"}) + assert resp.status_code == 200 + + def test_response_contains_required_fields(self, client): + resp = client.post("/api/query", json={"query": "What is RAG?"}) + data = resp.json() + assert "answer" in data + assert "sources" in data + assert "session_id" in data + + def test_answer_and_sources_come_from_rag(self, client): + resp = client.post("/api/query", json={"query": "What is RAG?"}) + data = resp.json() + assert "RAG" in data["answer"] + assert data["sources"][0]["label"] == "AI Course - Lesson 1" + + def test_creates_session_when_none_provided(self, client, mock_rag_system): + resp = client.post("/api/query", json={"query": "Hello"}) + assert resp.json()["session_id"] == "session-abc123" + mock_rag_system.session_manager.create_session.assert_called_once() + + def test_uses_provided_session_id(self, client, mock_rag_system): + resp = client.post("/api/query", json={"query": "Hello", "session_id": "existing"}) + assert resp.json()["session_id"] == "existing" + mock_rag_system.session_manager.create_session.assert_not_called() + + def test_query_forwarded_to_rag(self, client, mock_rag_system): + client.post("/api/query", json={"query": "Tell me about transformers"}) + call_args = mock_rag_system.query.call_args + assert "Tell me about transformers" in call_args[0][0] + + def test_returns_422_for_missing_query_field(self, client): + resp = client.post("/api/query", json={}) + assert resp.status_code == 422 + + def test_returns_500_when_rag_raises(self, client, mock_rag_system): + mock_rag_system.query.side_effect = RuntimeError("DB failure") + resp = client.post("/api/query", json={"query": "crash"}) + assert resp.status_code == 500 + + +# --------------------------------------------------------------------------- +# GET /api/courses +# --------------------------------------------------------------------------- + +class TestCoursesEndpoint: + def test_returns_200(self, client): + resp = client.get("/api/courses") + assert resp.status_code == 200 + + def test_response_contains_total_courses(self, client): + resp = client.get("/api/courses") + assert resp.json()["total_courses"] == 2 + + def test_response_contains_course_titles(self, client): + titles = client.get("/api/courses").json()["course_titles"] + assert "Python 101" in titles + assert "AI Fundamentals" in titles + + def test_returns_500_when_analytics_raises(self, client, mock_rag_system): + mock_rag_system.get_course_analytics.side_effect = RuntimeError("DB error") + resp = client.get("/api/courses") + assert resp.status_code == 500 + + +# --------------------------------------------------------------------------- +# DELETE /api/session/{session_id} +# --------------------------------------------------------------------------- + +class TestSessionEndpoint: + def test_returns_200_with_cleared_status(self, client): + resp = client.delete("/api/session/abc-123") + assert resp.status_code == 200 + assert resp.json() == {"status": "cleared"} + + def test_calls_clear_session_with_correct_id(self, client, mock_rag_system): + client.delete("/api/session/my-session-42") + mock_rag_system.session_manager.clear_session.assert_called_once_with("my-session-42") diff --git a/pyproject.toml b/pyproject.toml index 3f05e2de0..d3244a62b 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -13,3 +13,14 @@ dependencies = [ "python-multipart==0.0.20", "python-dotenv==1.1.1", ] + +[dependency-groups] +dev = [ + "pytest>=8.0", + "httpx>=0.27", +] + +[tool.pytest.ini_options] +testpaths = ["backend/tests"] +pythonpath = ["backend"] +addopts = 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name = "pygments" }, +] +sdist = { url = "https://files.pythonhosted.org/packages/7d/0d/549bd94f1a0a402dc8cf64563a117c0f3765662e2e668477624baeec44d5/pytest-9.0.3.tar.gz", hash = "sha256:b86ada508af81d19edeb213c681b1d48246c1a91d304c6c81a427674c17eb91c", size = 1572165, upload-time = "2026-04-07T17:16:18.027Z" } +wheels = [ + { url = "https://files.pythonhosted.org/packages/d4/24/a372aaf5c9b7208e7112038812994107bc65a84cd00e0354a88c2c77a617/pytest-9.0.3-py3-none-any.whl", hash = "sha256:2c5efc453d45394fdd706ade797c0a81091eccd1d6e4bccfcd476e2b8e0ab5d9", size = 375249, upload-time = "2026-04-07T17:16:16.13Z" }, +] + [[package]] name = "python-dateutil" version = "2.9.0.post0" @@ -1561,6 +1595,12 @@ dependencies = [ { name = "uvicorn" }, ] +[package.dev-dependencies] +dev = [ + { name = "httpx" }, + { name = "pytest" }, +] + [package.metadata] requires-dist = [ { name = "anthropic", specifier = "==0.58.2" }, @@ -1572,6 +1612,12 @@ requires-dist = [ { name = "uvicorn", specifier = "==0.35.0" }, ] +[package.metadata.requires-dev] +dev = [ + { name = "httpx", specifier = ">=0.27" }, + { name = "pytest", specifier = ">=8.0" }, +] + [[package]] name = "sympy" version = "1.14.0" From cb9ee32e9a4615aca89fe9ee9f0350d1712dacbc Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Mon, 18 May 2026 11:04:42 -0700 Subject: [PATCH 09/12] Add dark/light mode toggle with full light theme color system - Add fixed top-right toggle button (sun/moon SVG icons) with smooth rotate/scale transition animation and full keyboard/ARIA support - Theme preference persisted to localStorage, falls back to prefers-color-scheme on first visit - Add [data-theme="light"] CSS variable overrides for all palette tokens (background, surface, text, border, shadow, focus-ring) - Introduce semantic CSS variables for previously hardcoded colors (--link-color, --code-bg, --welcome-shadow, --error/success tokens) and override them in the light theme with WCAG AA-compliant values - Add 0.3s transitions on body and key layout elements for smooth theme switch - Fix blockquote using undefined var(--primary); corrected to var(--primary-color) - Document all changes in frontend-changes.md Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> --- frontend-changes.md | 76 +++++++++++++++++++++++ frontend/index.html | 21 ++++++- frontend/script.js | 29 ++++++++- frontend/style.css | 143 ++++++++++++++++++++++++++++++++++++++++---- 4 files changed, 254 insertions(+), 15 deletions(-) create mode 100644 frontend-changes.md diff --git a/frontend-changes.md b/frontend-changes.md new file mode 100644 index 000000000..7ecbdd940 --- /dev/null +++ b/frontend-changes.md @@ -0,0 +1,76 @@ +# Frontend Changes + +## Dark/Light Mode Toggle Button + +### Feature +A theme toggle button positioned fixed in the top-right corner of the viewport, allowing users to switch between dark and light modes. + +### Files Modified + +#### `frontend/index.html` +- Added `<button id="themeToggle">` as a fixed-position element outside `.container`, before the main layout +- Button contains two inline SVGs: a sun icon (shown in dark mode) and a moon icon (shown in light mode), both with `aria-hidden="true"` +- Button has `aria-label` attribute (dynamically updated by JS) and `title` for tooltip +- Bumped cache-buster version on `style.css` and `script.js` links to `v=10` + +#### `frontend/style.css` +- Added `[data-theme="light"]` CSS variable overrides for the full light palette (background, surface, text, border colours) +- Added `.theme-toggle` button styles: fixed position top-right, circular, 40×40 px, uses existing design tokens (`--surface`, `--border-color`, `--focus-ring`) +- Added hover (scale + primary colour), focus (3 px ring matching `--focus-ring`), and active (scale-down) states +- Sun/moon icon transition: `opacity` and `transform` (rotate + scale) with 0.3–0.4 s ease, so the outgoing icon rotates away and the incoming icon rotates in +- Added `transition: background-color/color/border-color 0.3s ease` to key layout elements (sidebar, chat container, inputs, messages, buttons) so the whole UI transitions smoothly on theme switch +- Added `transition: background-color/color` to `body` as a base fallback + +#### `frontend/script.js` +- Added `initTheme()`: reads `localStorage` for a saved preference, falls back to `prefers-color-scheme` media query +- Added `applyTheme(theme)`: sets/removes `data-theme` attribute on `<html>`, updates `aria-label` on the button, and persists the choice to `localStorage` +- Added `toggleTheme()`: reads current state and calls `applyTheme` with the opposite value +- Wired `toggleTheme` to the toggle button's `click` event in `setupEventListeners()` +- Called `initTheme()` at the top of the `DOMContentLoaded` handler so the correct theme is applied before first paint + +### Accessibility +- Button uses `aria-label` (updated dynamically to reflect the *target* state, e.g. "Switch to dark mode") +- SVG icons carry `aria-hidden="true"` so screen readers only announce the button label +- Focus ring uses the existing `--focus-ring` variable (3 px blue outline) +- Keyboard-navigable: standard `<button>` element responds to Enter and Space natively + +--- + +## Light Theme — Complete Color System + +### Feature +Completed the light theme by variabilizing all previously hardcoded colors so every element responds correctly to theme switching. All light-theme values were chosen to meet WCAG AA contrast ratios (≥ 4.5:1 for normal text). + +### Files Modified + +#### `frontend/style.css` + +**New semantic CSS variables added to `:root`** (dark-theme defaults): +| Variable | Dark value | Purpose | +|---|---|---| +| `--link-color` | `#60a5fa` | Source citation link text | +| `--link-hover` | `#93c5fd` | Source link hover state | +| `--code-bg` | `rgba(0,0,0,0.25)` | Inline code and pre-block backgrounds | +| `--welcome-shadow` | `0 4px 16px rgba(0,0,0,0.25)` | Welcome message card shadow | +| `--error-bg/color/border` | red-tinted alpha values + `#f87171` | Error feedback banner | +| `--success-bg/color/border` | green-tinted alpha values + `#4ade80` | Success feedback banner | + +**Light-theme overrides added to `[data-theme="light"]`**: +| Variable | Light value | Contrast note | +|---|---|---| +| `--border-color` | `#cbd5e1` | Slightly darker than before for visible borders | +| `--focus-ring` | `rgba(37,99,235,0.25)` | Slightly more opaque on light backgrounds | +| `--link-color` | `#1d4ed8` | ≈ 5.9:1 on white — passes AA | +| `--link-hover` | `#1e40af` | Darker on hover for clear feedback | +| `--code-bg` | `rgba(15,23,42,0.06)` | Subtle tint, dark-on-light direction | +| `--welcome-shadow` | `0 4px 16px rgba(0,0,0,0.06)` | Lighter shadow on light backgrounds | +| `--error-color` | `#b91c1c` | ≈ 6.7:1 on white — passes AA | +| `--success-color` | `#15803d` | ≈ 5.1:1 on white — passes AA | + +**CSS rules updated to use variables** (previously hardcoded): +- `.sources-content a` and `:hover` → `var(--link-color)` / `var(--link-hover)` +- `.message-content code` and `pre` backgrounds → `var(--code-bg)` +- `.message.welcome-message .message-content` shadow → `var(--welcome-shadow)` +- `.error-message` and `.success-message` → `var(--error-bg/color/border)` and `var(--success-bg/color/border)` + +**Bug fix**: `.message-content blockquote` referenced `var(--primary)` (undefined) — corrected to `var(--primary-color)`. diff --git a/frontend/index.html b/frontend/index.html index 30692e0f8..33d0a309a 100644 --- a/frontend/index.html +++ b/frontend/index.html @@ -7,9 +7,26 @@ <meta http-equiv="Pragma" content="no-cache"> <meta http-equiv="Expires" content="0"> <title>Course Materials Assistant - + + +

Course Materials Assistant

@@ -81,6 +98,6 @@

Course Materials Assistant

- + \ No newline at end of file diff --git a/frontend/script.js b/frontend/script.js index 339e1d776..58fddf0b8 100644 --- a/frontend/script.js +++ b/frontend/script.js @@ -15,12 +15,38 @@ document.addEventListener('DOMContentLoaded', () => { sendButton = document.getElementById('sendButton'); totalCourses = document.getElementById('totalCourses'); courseTitles = document.getElementById('courseTitles'); - + + initTheme(); setupEventListeners(); createNewSession(); loadCourseStats(); }); +// Theme Management +function initTheme() { + const saved = localStorage.getItem('theme'); + const prefersDark = window.matchMedia('(prefers-color-scheme: dark)').matches; + const theme = saved || (prefersDark ? 'dark' : 'light'); + applyTheme(theme); +} + +function applyTheme(theme) { + const toggle = document.getElementById('themeToggle'); + if (theme === 'light') { + document.documentElement.setAttribute('data-theme', 'light'); + toggle.setAttribute('aria-label', 'Switch to dark mode'); + } else { + document.documentElement.removeAttribute('data-theme'); + toggle.setAttribute('aria-label', 'Switch to light mode'); + } + localStorage.setItem('theme', theme); +} + +function toggleTheme() { + const isLight = document.documentElement.getAttribute('data-theme') === 'light'; + applyTheme(isLight ? 'dark' : 'light'); +} + // Event Listeners function setupEventListeners() { // Chat functionality @@ -30,6 +56,7 @@ function setupEventListeners() { }); document.getElementById('newChatBtn').addEventListener('click', createNewSession); + document.getElementById('themeToggle').addEventListener('click', toggleTheme); // Suggested questions document.querySelectorAll('.suggested-item').forEach(button => { diff --git a/frontend/style.css b/frontend/style.css index 24b12ecd0..4271bfadf 100644 --- a/frontend/style.css +++ b/frontend/style.css @@ -22,6 +22,44 @@ --focus-ring: rgba(37, 99, 235, 0.2); --welcome-bg: #1e3a5f; --welcome-border: #2563eb; + /* Semantic tokens for theme-sensitive hardcoded colors */ + --link-color: #60a5fa; + --link-hover: #93c5fd; + --code-bg: rgba(0, 0, 0, 0.25); + --welcome-shadow: 0 4px 16px rgba(0, 0, 0, 0.25); + --error-bg: rgba(239, 68, 68, 0.1); + --error-color: #f87171; + --error-border: rgba(239, 68, 68, 0.2); + --success-bg: rgba(34, 197, 94, 0.1); + --success-color: #4ade80; + --success-border: rgba(34, 197, 94, 0.2); +} + +/* Light Theme Variables */ +[data-theme="light"] { + --background: #f8fafc; + --surface: #ffffff; + --surface-hover: #f1f5f9; + --text-primary: #0f172a; + --text-secondary: #64748b; + --border-color: #cbd5e1; + --user-message: #2563eb; + --assistant-message: #f1f5f9; + --shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.08); + --focus-ring: rgba(37, 99, 235, 0.25); + --welcome-bg: #eff6ff; + --welcome-border: #3b82f6; + /* Semantic token overrides — WCAG AA contrast on light backgrounds */ + --link-color: #1d4ed8; + --link-hover: #1e40af; + --code-bg: rgba(15, 23, 42, 0.06); + --welcome-shadow: 0 4px 16px rgba(0, 0, 0, 0.06); + --error-bg: rgba(220, 38, 38, 0.07); + --error-color: #b91c1c; + --error-border: rgba(220, 38, 38, 0.2); + --success-bg: rgba(22, 163, 74, 0.07); + --success-color: #15803d; + --success-border: rgba(22, 163, 74, 0.2); } /* Base Styles */ @@ -34,6 +72,71 @@ body { overflow: hidden; margin: 0; padding: 0; + transition: background-color 0.3s ease, color 0.3s ease; +} + +/* Theme Toggle Button */ +.theme-toggle { + position: fixed; + top: 1rem; + right: 1rem; + width: 40px; + height: 40px; + border-radius: 50%; + background: var(--surface); + border: 1px solid var(--border-color); + color: var(--text-secondary); + cursor: pointer; + display: flex; + align-items: center; + justify-content: center; + z-index: 200; + transition: background 0.3s ease, color 0.2s ease, border-color 0.3s ease, transform 0.2s ease, box-shadow 0.2s ease; +} + +.theme-toggle:hover { + background: var(--surface-hover); + color: var(--primary-color); + transform: scale(1.08); + box-shadow: var(--shadow); +} + +.theme-toggle:focus { + outline: none; + box-shadow: 0 0 0 3px var(--focus-ring); +} + +.theme-toggle:active { + transform: scale(0.95); +} + +/* Icon transitions */ +.theme-toggle .icon-sun, +.theme-toggle .icon-moon { + position: absolute; + transition: opacity 0.3s ease, transform 0.4s ease; +} + +/* Dark mode (default): show sun icon, hide moon */ +.theme-toggle .icon-sun { + opacity: 1; + transform: rotate(0deg) scale(1); +} + +.theme-toggle .icon-moon { + opacity: 0; + transform: rotate(90deg) scale(0.5); +} + +/* Light mode: show moon icon, hide sun */ +[data-theme="light"] .theme-toggle .icon-sun { + opacity: 0; + transform: rotate(-90deg) scale(0.5); +} + +[data-theme="light"] .theme-toggle .icon-moon { + opacity: 1; + transform: rotate(0deg) scale(1); } /* Container - Full Screen */ @@ -75,6 +178,22 @@ header h1 { background: var(--background); } +/* Smooth transitions for theme switch on key elements */ +.sidebar, +.chat-main, +.chat-container, +.chat-messages, +.chat-input-container, +#chatInput, +#sendButton, +.message-content, +.stat-item, +.suggested-item, +.new-chat-btn, +.theme-toggle { + transition: background-color 0.3s ease, color 0.3s ease, border-color 0.3s ease; +} + /* Left Sidebar */ .sidebar { width: 320px; @@ -269,14 +388,14 @@ header h1 { } .sources-content a { - color: #60a5fa; + color: var(--link-color); text-decoration: underline; text-underline-offset: 2px; transition: color 0.2s ease; } .sources-content a:hover { - color: #93c5fd; + color: var(--link-hover); } /* Markdown formatting styles */ @@ -311,7 +430,7 @@ header h1 { } .message-content code { - background-color: rgba(0, 0, 0, 0.2); + background-color: var(--code-bg); padding: 0.125rem 0.25rem; border-radius: 3px; font-family: 'Fira Code', 'Consolas', monospace; @@ -319,7 +438,7 @@ header h1 { } .message-content pre { - background-color: rgba(0, 0, 0, 0.2); + background-color: var(--code-bg); padding: 0.75rem; border-radius: 4px; overflow-x: auto; @@ -332,7 +451,7 @@ header h1 { } .message-content blockquote { - border-left: 3px solid var(--primary); + border-left: 3px solid var(--primary-color); padding-left: 1rem; margin: 0.5rem 0; color: var(--text-secondary); @@ -342,7 +461,7 @@ header h1 { .message.welcome-message .message-content { background: var(--surface); border: 2px solid var(--border-color); - box-shadow: 0 4px 16px rgba(0, 0, 0, 0.2); + box-shadow: var(--welcome-shadow); position: relative; } @@ -461,21 +580,21 @@ header h1 { /* Error Message */ .error-message { - background: rgba(239, 68, 68, 0.1); - color: #f87171; + background: var(--error-bg); + color: var(--error-color); padding: 0.75rem 1.25rem; border-radius: 8px; - border: 1px solid rgba(239, 68, 68, 0.2); + border: 1px solid var(--error-border); margin: 0.5rem 0; } /* Success Message */ .success-message { - background: rgba(34, 197, 94, 0.1); - color: #4ade80; + background: var(--success-bg); + color: var(--success-color); padding: 0.75rem 1.25rem; border-radius: 8px; - border: 1px solid rgba(34, 197, 94, 0.2); + border: 1px solid var(--success-border); margin: 0.5rem 0; } From a5379ffb5c236e92697664ec44dc9b1e38b9b262 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Mon, 18 May 2026 11:04:54 -0700 Subject: [PATCH 10/12] Add Black formatting and dev quality scripts - Add black>=25.1.0 as a dev dependency in pyproject.toml with [tool.black] config (line-length 88, py313) - Run black across all 14 backend Python files for consistent formatting - Add scripts/format.sh (auto-fix) and scripts/check_quality.sh (CI-safe check) - Document quality workflow in CLAUDE.md Co-Authored-By: Claude Sonnet 4.6 --- CLAUDE.md | 20 ++ backend/ai_generator.py | 40 ++-- backend/app.py | 40 ++-- backend/config.py | 19 +- backend/document_processor.py | 151 +++++++------- backend/models.py | 20 +- backend/rag_system.py | 97 +++++---- backend/search_tools.py | 91 ++++---- backend/session_manager.py | 33 +-- backend/tests/conftest.py | 5 +- backend/tests/test_ai_generator.py | 69 ++++-- backend/tests/test_course_search_tool.py | 84 +++++--- backend/tests/test_rag_system.py | 20 +- backend/tests/test_vector_store.py | 55 +++-- backend/vector_store.py | 255 +++++++++++++---------- pyproject.toml | 9 + scripts/check_quality.sh | 10 + scripts/format.sh | 5 + uv.lock | 88 +++++++- 19 files changed, 714 insertions(+), 397 deletions(-) create mode 100644 scripts/check_quality.sh create mode 100644 scripts/format.sh diff --git a/CLAUDE.md b/CLAUDE.md index 8d4608416..e1dc3030c 100644 --- a/CLAUDE.md +++ b/CLAUDE.md @@ -64,6 +64,26 @@ Lesson 1: ... ``` +## Code Quality + +### Formatting — Black + +All Python code is formatted with [Black](https://black.readthedocs.io/). Configuration lives in `pyproject.toml` under `[tool.black]` (line length 88, target Python 3.13). + +```bash +# Auto-format all backend Python files +bash scripts/format.sh +# or directly: +uv run black backend/ + +# Check formatting without changing files (CI-safe) +bash scripts/check_quality.sh +# or directly: +uv run black --check backend/ +``` + +Always run `bash scripts/format.sh` before committing Python changes. PRs with unformatted code will fail the quality check. + ### Configuration (`backend/config.py`) | Setting | Default | Purpose | diff --git a/backend/ai_generator.py b/backend/ai_generator.py index 52d20b7df..9d5359160 100644 --- a/backend/ai_generator.py +++ b/backend/ai_generator.py @@ -1,6 +1,7 @@ import anthropic from typing import List, Optional, Dict, Any + class AIGenerator: """Handles interactions with Anthropic's Claude API for generating responses""" @@ -42,16 +43,15 @@ def __init__(self, api_key: str, model: str): self.model = model # Pre-build base API parameters - self.base_params = { - "model": self.model, - "temperature": 0, - "max_tokens": 800 - } - - def generate_response(self, query: str, - conversation_history: Optional[str] = None, - tools: Optional[List] = None, - tool_manager=None) -> str: + self.base_params = {"model": self.model, "temperature": 0, "max_tokens": 800} + + def generate_response( + self, + query: str, + conversation_history: Optional[str] = None, + tools: Optional[List] = None, + tool_manager=None, + ) -> str: """ Generate AI response with optional tool usage and conversation context. @@ -76,7 +76,7 @@ def generate_response(self, query: str, api_params = { **self.base_params, "messages": [{"role": "user", "content": query}], - "system": system_content + "system": system_content, } # Add tools if available @@ -96,7 +96,9 @@ def generate_response(self, query: str, # Return direct response return response.content[0].text - def _handle_tool_execution(self, initial_response, base_params: Dict[str, Any], tool_manager): + def _handle_tool_execution( + self, initial_response, base_params: Dict[str, Any], tool_manager + ): """ Handle sequential tool calls up to MAX_ROUNDS, then force a final text response. @@ -130,18 +132,20 @@ def _handle_tool_execution(self, initial_response, base_params: Dict[str, Any], except Exception as e: result = f"Tool execution failed: {e}" had_error = True - tool_results.append({ - "type": "tool_result", - "tool_use_id": block.id, - "content": result, - }) + tool_results.append( + { + "type": "tool_result", + "tool_use_id": block.id, + "content": result, + } + ) # --- Append this round to the message thread --- messages.append({"role": "assistant", "content": current_response.content}) if tool_results: messages.append({"role": "user", "content": tool_results}) - is_last_round = (round_num == self.MAX_ROUNDS - 1) + is_last_round = round_num == self.MAX_ROUNDS - 1 # Stop conditions (b) exception or (c) rounds exhausted if had_error or is_last_round: diff --git a/backend/app.py b/backend/app.py index 7e105d1d0..c24be7b0c 100644 --- a/backend/app.py +++ b/backend/app.py @@ -1,4 +1,5 @@ import warnings + warnings.filterwarnings("ignore", message="resource_tracker: There appear to be.*") from fastapi import FastAPI, HTTPException @@ -16,10 +17,7 @@ app = FastAPI(title="Course Materials RAG System", root_path="") # Add trusted host middleware for proxy -app.add_middleware( - TrustedHostMiddleware, - allowed_hosts=["*"] -) +app.add_middleware(TrustedHostMiddleware, allowed_hosts=["*"]) # Enable CORS with proper settings for proxy app.add_middleware( @@ -34,25 +32,33 @@ # Initialize RAG system rag_system = RAGSystem(config) + # Pydantic models for request/response class QueryRequest(BaseModel): """Request model for course queries""" + query: str session_id: Optional[str] = None + class QueryResponse(BaseModel): """Response model for course queries""" + answer: str sources: List[dict] session_id: str + class CourseStats(BaseModel): """Response model for course statistics""" + total_courses: int course_titles: List[str] + # API Endpoints + @app.post("/api/query", response_model=QueryResponse) async def query_documents(request: QueryRequest): """Process a query and return response with sources""" @@ -61,18 +67,15 @@ async def query_documents(request: QueryRequest): session_id = request.session_id if not session_id: session_id = rag_system.session_manager.create_session() - + # Process query using RAG system answer, sources = rag_system.query(request.query, session_id) - - return QueryResponse( - answer=answer, - sources=sources, - session_id=session_id - ) + + return QueryResponse(answer=answer, sources=sources, session_id=session_id) except Exception as e: raise HTTPException(status_code=500, detail=str(e)) + @app.get("/api/courses", response_model=CourseStats) async def get_course_stats(): """Get course analytics and statistics""" @@ -80,17 +83,19 @@ async def get_course_stats(): analytics = rag_system.get_course_analytics() return CourseStats( total_courses=analytics["total_courses"], - course_titles=analytics["course_titles"] + course_titles=analytics["course_titles"], ) except Exception as e: raise HTTPException(status_code=500, detail=str(e)) + @app.delete("/api/session/{session_id}") async def clear_session(session_id: str): """Clear conversation history for a session""" rag_system.session_manager.clear_session(session_id) return {"status": "cleared"} + @app.on_event("startup") async def startup_event(): """Load initial documents on startup""" @@ -98,11 +103,14 @@ async def startup_event(): if os.path.exists(docs_path): print("Loading initial documents...") try: - courses, chunks = rag_system.add_course_folder(docs_path, clear_existing=False) + courses, chunks = rag_system.add_course_folder( + docs_path, clear_existing=False + ) print(f"Loaded {courses} courses with {chunks} chunks") except Exception as e: print(f"Error loading documents: {e}") + # Custom static file handler with no-cache headers for development from fastapi.staticfiles import StaticFiles from fastapi.responses import FileResponse @@ -119,7 +127,7 @@ async def get_response(self, path: str, scope): response.headers["Pragma"] = "no-cache" response.headers["Expires"] = "0" return response - - + + # Serve static files for the frontend -app.mount("/", StaticFiles(directory="../frontend", html=True), name="static") \ No newline at end of file +app.mount("/", StaticFiles(directory="../frontend", html=True), name="static") diff --git a/backend/config.py b/backend/config.py index d9f6392ef..7379e7133 100644 --- a/backend/config.py +++ b/backend/config.py @@ -5,25 +5,26 @@ # Load environment variables from .env file load_dotenv() + @dataclass class Config: """Configuration settings for the RAG system""" + # Anthropic API settings ANTHROPIC_API_KEY: str = os.getenv("ANTHROPIC_API_KEY", "") ANTHROPIC_MODEL: str = "claude-sonnet-4-20250514" - + # Embedding model settings EMBEDDING_MODEL: str = "all-MiniLM-L6-v2" - + # Document processing settings - CHUNK_SIZE: int = 800 # Size of text chunks for vector storage - CHUNK_OVERLAP: int = 100 # Characters to overlap between chunks - MAX_RESULTS: int = 5 # Maximum search results to return - MAX_HISTORY: int = 2 # Number of conversation messages to remember - + CHUNK_SIZE: int = 800 # Size of text chunks for vector storage + CHUNK_OVERLAP: int = 100 # Characters to overlap between chunks + MAX_RESULTS: int = 5 # Maximum search results to return + MAX_HISTORY: int = 2 # Number of conversation messages to remember + # Database paths CHROMA_PATH: str = "./chroma_db" # ChromaDB storage location -config = Config() - +config = Config() diff --git a/backend/document_processor.py b/backend/document_processor.py index 266e85904..32c6648ae 100644 --- a/backend/document_processor.py +++ b/backend/document_processor.py @@ -3,81 +3,84 @@ from typing import List, Tuple from models import Course, Lesson, CourseChunk + class DocumentProcessor: """Processes course documents and extracts structured information""" - + def __init__(self, chunk_size: int, chunk_overlap: int): self.chunk_size = chunk_size self.chunk_overlap = chunk_overlap - + def read_file(self, file_path: str) -> str: """Read content from file with UTF-8 encoding""" try: - with open(file_path, 'r', encoding='utf-8') as file: + with open(file_path, "r", encoding="utf-8") as file: return file.read() except UnicodeDecodeError: # If UTF-8 fails, try with error handling - with open(file_path, 'r', encoding='utf-8', errors='ignore') as file: + with open(file_path, "r", encoding="utf-8", errors="ignore") as file: return file.read() - - def chunk_text(self, text: str) -> List[str]: """Split text into sentence-based chunks with overlap using config settings""" - + # Clean up the text - text = re.sub(r'\s+', ' ', text.strip()) # Normalize whitespace - + text = re.sub(r"\s+", " ", text.strip()) # Normalize whitespace + # Better sentence splitting that handles abbreviations # This regex looks for periods followed by whitespace and capital letters # but ignores common abbreviations - sentence_endings = re.compile(r'(? self.chunk_size and current_chunk: break - + current_chunk.append(sentence) current_size += total_addition - + # Add chunk if we have content if current_chunk: - chunks.append(' '.join(current_chunk)) - + chunks.append(" ".join(current_chunk)) + # Calculate overlap for next chunk - if hasattr(self, 'chunk_overlap') and self.chunk_overlap > 0: + if hasattr(self, "chunk_overlap") and self.chunk_overlap > 0: # Find how many sentences to overlap overlap_size = 0 overlap_sentences = 0 - + # Count backwards from end of current chunk for k in range(len(current_chunk) - 1, -1, -1): - sentence_len = len(current_chunk[k]) + (1 if k < len(current_chunk) - 1 else 0) + sentence_len = len(current_chunk[k]) + ( + 1 if k < len(current_chunk) - 1 else 0 + ) if overlap_size + sentence_len <= self.chunk_overlap: overlap_size += sentence_len overlap_sentences += 1 else: break - + # Move start position considering overlap next_start = i + len(current_chunk) - overlap_sentences i = max(next_start, i + 1) # Ensure we make progress @@ -87,14 +90,12 @@ def chunk_text(self, text: str) -> List[str]: else: # No sentences fit, move to next i += 1 - - return chunks - - + return chunks - - def process_course_document(self, file_path: str) -> Tuple[Course, List[CourseChunk]]: + def process_course_document( + self, file_path: str + ) -> Tuple[Course, List[CourseChunk]]: """ Process a course document with expected format: Line 1: Course Title: [title] @@ -104,47 +105,51 @@ def process_course_document(self, file_path: str) -> Tuple[Course, List[CourseCh """ content = self.read_file(file_path) filename = os.path.basename(file_path) - - lines = content.strip().split('\n') - + + lines = content.strip().split("\n") + # Extract course metadata from first three lines course_title = filename # Default fallback course_link = None instructor_name = "Unknown" - + # Parse course title from first line if len(lines) >= 1 and lines[0].strip(): - title_match = re.match(r'^Course Title:\s*(.+)$', lines[0].strip(), re.IGNORECASE) + title_match = re.match( + r"^Course Title:\s*(.+)$", lines[0].strip(), re.IGNORECASE + ) if title_match: course_title = title_match.group(1).strip() else: course_title = lines[0].strip() - + # Parse remaining lines for course metadata for i in range(1, min(len(lines), 4)): # Check first 4 lines for metadata line = lines[i].strip() if not line: continue - + # Try to match course link - link_match = re.match(r'^Course Link:\s*(.+)$', line, re.IGNORECASE) + link_match = re.match(r"^Course Link:\s*(.+)$", line, re.IGNORECASE) if link_match: course_link = link_match.group(1).strip() continue - + # Try to match instructor - instructor_match = re.match(r'^Course Instructor:\s*(.+)$', line, re.IGNORECASE) + instructor_match = re.match( + r"^Course Instructor:\s*(.+)$", line, re.IGNORECASE + ) if instructor_match: instructor_name = instructor_match.group(1).strip() continue - + # Create course object with title as ID course = Course( title=course_title, course_link=course_link, - instructor=instructor_name if instructor_name != "Unknown" else None + instructor=instructor_name if instructor_name != "Unknown" else None, ) - + # Process lessons and create chunks course_chunks = [] current_lesson = None @@ -152,108 +157,114 @@ def process_course_document(self, file_path: str) -> Tuple[Course, List[CourseCh lesson_link = None lesson_content = [] chunk_counter = 0 - + # Start processing from line 4 (after metadata) start_index = 3 if len(lines) > 3 and not lines[3].strip(): start_index = 4 # Skip empty line after instructor - + i = start_index while i < len(lines): line = lines[i] - + # Check for lesson markers (e.g., "Lesson 0: Introduction") - lesson_match = re.match(r'^Lesson\s+(\d+):\s*(.+)$', line.strip(), re.IGNORECASE) - + lesson_match = re.match( + r"^Lesson\s+(\d+):\s*(.+)$", line.strip(), re.IGNORECASE + ) + if lesson_match: # Process previous lesson if it exists if current_lesson is not None and lesson_content: - lesson_text = '\n'.join(lesson_content).strip() + lesson_text = "\n".join(lesson_content).strip() if lesson_text: # Add lesson to course lesson = Lesson( lesson_number=current_lesson, title=lesson_title, - lesson_link=lesson_link + lesson_link=lesson_link, ) course.lessons.append(lesson) - + # Create chunks for this lesson chunks = self.chunk_text(lesson_text) for idx, chunk in enumerate(chunks): # For the first chunk of each lesson, add lesson context if idx == 0: - chunk_with_context = f"Lesson {current_lesson} content: {chunk}" + chunk_with_context = ( + f"Lesson {current_lesson} content: {chunk}" + ) else: chunk_with_context = chunk - + course_chunk = CourseChunk( content=chunk_with_context, course_title=course.title, lesson_number=current_lesson, - chunk_index=chunk_counter + chunk_index=chunk_counter, ) course_chunks.append(course_chunk) chunk_counter += 1 - + # Start new lesson current_lesson = int(lesson_match.group(1)) lesson_title = lesson_match.group(2).strip() lesson_link = None - + # Check if next line is a lesson link if i + 1 < len(lines): next_line = lines[i + 1].strip() - link_match = re.match(r'^Lesson Link:\s*(.+)$', next_line, re.IGNORECASE) + link_match = re.match( + r"^Lesson Link:\s*(.+)$", next_line, re.IGNORECASE + ) if link_match: lesson_link = link_match.group(1).strip() i += 1 # Skip the link line so it's not added to content - + lesson_content = [] else: # Add line to current lesson content lesson_content.append(line) - + i += 1 - + # Process the last lesson if current_lesson is not None and lesson_content: - lesson_text = '\n'.join(lesson_content).strip() + lesson_text = "\n".join(lesson_content).strip() if lesson_text: lesson = Lesson( lesson_number=current_lesson, title=lesson_title, - lesson_link=lesson_link + lesson_link=lesson_link, ) course.lessons.append(lesson) - + chunks = self.chunk_text(lesson_text) for idx, chunk in enumerate(chunks): # For any chunk of each lesson, add lesson context & course title - + chunk_with_context = f"Course {course_title} Lesson {current_lesson} content: {chunk}" - + course_chunk = CourseChunk( content=chunk_with_context, course_title=course.title, lesson_number=current_lesson, - chunk_index=chunk_counter + chunk_index=chunk_counter, ) course_chunks.append(course_chunk) chunk_counter += 1 - + # If no lessons found, treat entire content as one document if not course_chunks and len(lines) > 2: - remaining_content = '\n'.join(lines[start_index:]).strip() + remaining_content = "\n".join(lines[start_index:]).strip() if remaining_content: chunks = self.chunk_text(remaining_content) for chunk in chunks: course_chunk = CourseChunk( content=chunk, course_title=course.title, - chunk_index=chunk_counter + chunk_index=chunk_counter, ) course_chunks.append(course_chunk) chunk_counter += 1 - + return course, course_chunks diff --git a/backend/models.py b/backend/models.py index 7f7126fa3..12ae8113e 100644 --- a/backend/models.py +++ b/backend/models.py @@ -1,22 +1,28 @@ from typing import List, Dict, Optional from pydantic import BaseModel + class Lesson(BaseModel): """Represents a lesson within a course""" + lesson_number: int # Sequential lesson number (1, 2, 3, etc.) - title: str # Lesson title + title: str # Lesson title lesson_link: Optional[str] = None # URL link to the lesson + class Course(BaseModel): """Represents a complete course with its lessons""" - title: str # Full course title (used as unique identifier) + + title: str # Full course title (used as unique identifier) course_link: Optional[str] = None # URL link to the course instructor: Optional[str] = None # Course instructor name (optional metadata) - lessons: List[Lesson] = [] # List of lessons in this course + lessons: List[Lesson] = [] # List of lessons in this course + class CourseChunk(BaseModel): """Represents a text chunk from a course for vector storage""" - content: str # The actual text content - course_title: str # Which course this chunk belongs to - lesson_number: Optional[int] = None # Which lesson this chunk is from - chunk_index: int # Position of this chunk in the document \ No newline at end of file + + content: str # The actual text content + course_title: str # Which course this chunk belongs to + lesson_number: Optional[int] = None # Which lesson this chunk is from + chunk_index: int # Position of this chunk in the document diff --git a/backend/rag_system.py b/backend/rag_system.py index 443649f0e..ae43567ce 100644 --- a/backend/rag_system.py +++ b/backend/rag_system.py @@ -7,143 +7,162 @@ from search_tools import ToolManager, CourseSearchTool, CourseOutlineTool from models import Course, Lesson, CourseChunk + class RAGSystem: """Main orchestrator for the Retrieval-Augmented Generation system""" - + def __init__(self, config): self.config = config - + # Initialize core components - self.document_processor = DocumentProcessor(config.CHUNK_SIZE, config.CHUNK_OVERLAP) - self.vector_store = VectorStore(config.CHROMA_PATH, config.EMBEDDING_MODEL, config.MAX_RESULTS) - self.ai_generator = AIGenerator(config.ANTHROPIC_API_KEY, config.ANTHROPIC_MODEL) + self.document_processor = DocumentProcessor( + config.CHUNK_SIZE, config.CHUNK_OVERLAP + ) + self.vector_store = VectorStore( + config.CHROMA_PATH, config.EMBEDDING_MODEL, config.MAX_RESULTS + ) + self.ai_generator = AIGenerator( + config.ANTHROPIC_API_KEY, config.ANTHROPIC_MODEL + ) self.session_manager = SessionManager(config.MAX_HISTORY) - + # Initialize search tools self.tool_manager = ToolManager() self.search_tool = CourseSearchTool(self.vector_store) self.tool_manager.register_tool(self.search_tool) self.outline_tool = CourseOutlineTool(self.vector_store) self.tool_manager.register_tool(self.outline_tool) - + def add_course_document(self, file_path: str) -> Tuple[Course, int]: """ Add a single course document to the knowledge base. - + Args: file_path: Path to the course document - + Returns: Tuple of (Course object, number of chunks created) """ try: # Process the document - course, course_chunks = self.document_processor.process_course_document(file_path) - + course, course_chunks = self.document_processor.process_course_document( + file_path + ) + # Add course metadata to vector store for semantic search self.vector_store.add_course_metadata(course) - + # Add course content chunks to vector store self.vector_store.add_course_content(course_chunks) - + return course, len(course_chunks) except Exception as e: print(f"Error processing course document {file_path}: {e}") return None, 0 - - def add_course_folder(self, folder_path: str, clear_existing: bool = False) -> Tuple[int, int]: + + def add_course_folder( + self, folder_path: str, clear_existing: bool = False + ) -> Tuple[int, int]: """ Add all course documents from a folder. - + Args: folder_path: Path to folder containing course documents clear_existing: Whether to clear existing data first - + Returns: Tuple of (total courses added, total chunks created) """ total_courses = 0 total_chunks = 0 - + # Clear existing data if requested if clear_existing: print("Clearing existing data for fresh rebuild...") self.vector_store.clear_all_data() - + if not os.path.exists(folder_path): print(f"Folder {folder_path} does not exist") return 0, 0 - + # Get existing course titles to avoid re-processing existing_course_titles = set(self.vector_store.get_existing_course_titles()) - + # Process each file in the folder for file_name in os.listdir(folder_path): file_path = os.path.join(folder_path, file_name) - if os.path.isfile(file_path) and file_name.lower().endswith(('.pdf', '.docx', '.txt')): + if os.path.isfile(file_path) and file_name.lower().endswith( + (".pdf", ".docx", ".txt") + ): try: # Check if this course might already exist # We'll process the document to get the course ID, but only add if new - course, course_chunks = self.document_processor.process_course_document(file_path) - + course, course_chunks = ( + self.document_processor.process_course_document(file_path) + ) + if course and course.title not in existing_course_titles: # This is a new course - add it to the vector store self.vector_store.add_course_metadata(course) self.vector_store.add_course_content(course_chunks) total_courses += 1 total_chunks += len(course_chunks) - print(f"Added new course: {course.title} ({len(course_chunks)} chunks)") + print( + f"Added new course: {course.title} ({len(course_chunks)} chunks)" + ) existing_course_titles.add(course.title) elif course: print(f"Course already exists: {course.title} - skipping") except Exception as e: print(f"Error processing {file_name}: {e}") - + return total_courses, total_chunks - - def query(self, query: str, session_id: Optional[str] = None) -> Tuple[str, List[str]]: + + def query( + self, query: str, session_id: Optional[str] = None + ) -> Tuple[str, List[str]]: """ Process a user query using the RAG system with tool-based search. - + Args: query: User's question session_id: Optional session ID for conversation context - + Returns: Tuple of (response, sources list - empty for tool-based approach) """ # Create prompt for the AI with clear instructions prompt = f"""Answer this question about course materials: {query}""" - + # Get conversation history if session exists history = None if session_id: history = self.session_manager.get_conversation_history(session_id) - + # Generate response using AI with tools response = self.ai_generator.generate_response( query=prompt, conversation_history=history, tools=self.tool_manager.get_tool_definitions(), - tool_manager=self.tool_manager + tool_manager=self.tool_manager, ) - + # Get sources from the search tool sources = self.tool_manager.get_last_sources() # Reset sources after retrieving them self.tool_manager.reset_sources() - + # Update conversation history if session_id: self.session_manager.add_exchange(session_id, query, response) - + # Return response with sources from tool searches return response, sources - + def get_course_analytics(self) -> Dict: """Get analytics about the course catalog""" return { "total_courses": self.vector_store.get_course_count(), - "course_titles": self.vector_store.get_existing_course_titles() - } \ No newline at end of file + "course_titles": self.vector_store.get_existing_course_titles(), + } diff --git a/backend/search_tools.py b/backend/search_tools.py index 38d715fca..205c79821 100644 --- a/backend/search_tools.py +++ b/backend/search_tools.py @@ -5,12 +5,12 @@ class Tool(ABC): """Abstract base class for all tools""" - + @abstractmethod def get_tool_definition(self) -> Dict[str, Any]: """Return Anthropic tool definition for this tool""" pass - + @abstractmethod def execute(self, **kwargs) -> str: """Execute the tool with given parameters""" @@ -19,11 +19,11 @@ def execute(self, **kwargs) -> str: class CourseSearchTool(Tool): """Tool for searching course content with semantic course name matching""" - + def __init__(self, vector_store: VectorStore): self.store = vector_store self.last_sources = [] # Track sources from last search - + def get_tool_definition(self) -> Dict[str, Any]: """Return Anthropic tool definition for this tool""" return { @@ -33,46 +33,49 @@ def get_tool_definition(self) -> Dict[str, Any]: "type": "object", "properties": { "query": { - "type": "string", - "description": "What to search for in the course content" + "type": "string", + "description": "What to search for in the course content", }, "course_name": { "type": "string", - "description": "Course title (partial matches work, e.g. 'MCP', 'Introduction')" + "description": "Course title (partial matches work, e.g. 'MCP', 'Introduction')", }, "lesson_number": { "type": "integer", - "description": "Specific lesson number to search within (e.g. 1, 2, 3)" - } + "description": "Specific lesson number to search within (e.g. 1, 2, 3)", + }, }, - "required": ["query"] - } + "required": ["query"], + }, } - - def execute(self, query: str, course_name: Optional[str] = None, lesson_number: Optional[int] = None) -> str: + + def execute( + self, + query: str, + course_name: Optional[str] = None, + lesson_number: Optional[int] = None, + ) -> str: """ Execute the search tool with given parameters. - + Args: query: What to search for course_name: Optional course filter lesson_number: Optional lesson filter - + Returns: Formatted search results or error message """ - + # Use the vector store's unified search interface results = self.store.search( - query=query, - course_name=course_name, - lesson_number=lesson_number + query=query, course_name=course_name, lesson_number=lesson_number ) - + # Handle errors if results.error: return results.error - + # Handle empty results if results.is_empty(): filter_info = "" @@ -81,10 +84,10 @@ def execute(self, query: str, course_name: Optional[str] = None, lesson_number: if lesson_number: filter_info += f" in lesson {lesson_number}" return f"No relevant content found{filter_info}." - + # Format and return results return self._format_results(results) - + def _format_results(self, results: SearchResults) -> str: """Format search results with course and lesson context""" formatted = [] @@ -92,8 +95,8 @@ def _format_results(self, results: SearchResults) -> str: seen = set() # Deduplicate sources for doc, meta in zip(results.documents, results.metadata): - course_title = meta.get('course_title', 'unknown') - lesson_num = meta.get('lesson_number') + course_title = meta.get("course_title", "unknown") + lesson_num = meta.get("lesson_number") # Build context header header = f"[{course_title}" @@ -108,7 +111,11 @@ def _format_results(self, results: SearchResults) -> str: label = course_title if lesson_num is not None: label += f" - Lesson {lesson_num}" - url = self.store.get_lesson_link(course_title, lesson_num) if lesson_num is not None else None + url = ( + self.store.get_lesson_link(course_title, lesson_num) + if lesson_num is not None + else None + ) sources.append({"label": label, "url": url}) formatted.append(f"{header}\n{doc}") @@ -118,6 +125,7 @@ def _format_results(self, results: SearchResults) -> str: return "\n\n".join(formatted) + class CourseOutlineTool(Tool): """Tool for retrieving a course outline (title, link, and full lesson list)""" @@ -133,11 +141,11 @@ def get_tool_definition(self) -> Dict[str, Any]: "properties": { "course_name": { "type": "string", - "description": "Course name or partial name (e.g. 'MCP', 'Introduction to Claude')" + "description": "Course name or partial name (e.g. 'MCP', 'Introduction to Claude')", } }, - "required": ["course_name"] - } + "required": ["course_name"], + }, } def execute(self, course_name: str) -> str: @@ -147,19 +155,21 @@ def execute(self, course_name: str) -> str: lines = [ f"Course: {outline['title']}", f"Link: {outline['course_link']}", - "Lessons:" + "Lessons:", ] - for lesson in outline['lessons']: - lines.append(f" Lesson {lesson['lesson_number']}: {lesson['lesson_title']}") + for lesson in outline["lessons"]: + lines.append( + f" Lesson {lesson['lesson_number']}: {lesson['lesson_title']}" + ) return "\n".join(lines) class ToolManager: """Manages available tools for the AI""" - + def __init__(self): self.tools = {} - + def register_tool(self, tool: Tool): """Register any tool that implements the Tool interface""" tool_def = tool.get_tool_definition() @@ -168,28 +178,27 @@ def register_tool(self, tool: Tool): raise ValueError("Tool must have a 'name' in its definition") self.tools[tool_name] = tool - def get_tool_definitions(self) -> list: """Get all tool definitions for Anthropic tool calling""" return [tool.get_tool_definition() for tool in self.tools.values()] - + def execute_tool(self, tool_name: str, **kwargs) -> str: """Execute a tool by name with given parameters""" if tool_name not in self.tools: return f"Tool '{tool_name}' not found" - + return self.tools[tool_name].execute(**kwargs) - + def get_last_sources(self) -> list: """Get sources from the last search operation""" # Check all tools for last_sources attribute for tool in self.tools.values(): - if hasattr(tool, 'last_sources') and tool.last_sources: + if hasattr(tool, "last_sources") and tool.last_sources: return tool.last_sources return [] def reset_sources(self): """Reset sources from all tools that track sources""" for tool in self.tools.values(): - if hasattr(tool, 'last_sources'): - tool.last_sources = [] \ No newline at end of file + if hasattr(tool, "last_sources"): + tool.last_sources = [] diff --git a/backend/session_manager.py b/backend/session_manager.py index a5a96b1a1..9e17f346b 100644 --- a/backend/session_manager.py +++ b/backend/session_manager.py @@ -1,61 +1,66 @@ from typing import Dict, List, Optional from dataclasses import dataclass + @dataclass class Message: """Represents a single message in a conversation""" - role: str # "user" or "assistant" + + role: str # "user" or "assistant" content: str # The message content + class SessionManager: """Manages conversation sessions and message history""" - + def __init__(self, max_history: int = 5): self.max_history = max_history self.sessions: Dict[str, List[Message]] = {} self.session_counter = 0 - + def create_session(self) -> str: """Create a new conversation session""" self.session_counter += 1 session_id = f"session_{self.session_counter}" self.sessions[session_id] = [] return session_id - + def add_message(self, session_id: str, role: str, content: str): """Add a message to the conversation history""" if session_id not in self.sessions: self.sessions[session_id] = [] - + message = Message(role=role, content=content) self.sessions[session_id].append(message) - + # Keep conversation history within limits if len(self.sessions[session_id]) > self.max_history * 2: - self.sessions[session_id] = self.sessions[session_id][-self.max_history * 2:] - + self.sessions[session_id] = self.sessions[session_id][ + -self.max_history * 2 : + ] + def add_exchange(self, session_id: str, user_message: str, assistant_message: str): """Add a complete question-answer exchange""" self.add_message(session_id, "user", user_message) self.add_message(session_id, "assistant", assistant_message) - + def get_conversation_history(self, session_id: Optional[str]) -> Optional[str]: """Get formatted conversation history for a session""" if not session_id or session_id not in self.sessions: return None - + messages = self.sessions[session_id] if not messages: return None - + # Format messages for context formatted_messages = [] for msg in messages: formatted_messages.append(f"{msg.role.title()}: {msg.content}") - + return "\n".join(formatted_messages) - + def clear_session(self, session_id: str): """Clear all messages from a session""" if session_id in self.sessions: - self.sessions[session_id] = [] \ No newline at end of file + self.sessions[session_id] = [] diff --git a/backend/tests/conftest.py b/backend/tests/conftest.py index 4f03cbc58..a0c9d81d1 100644 --- a/backend/tests/conftest.py +++ b/backend/tests/conftest.py @@ -3,6 +3,7 @@ Adds the backend directory to sys.path so modules can be imported without package-prefix notation (matching how the app itself imports them). """ + import sys import os from unittest.mock import MagicMock @@ -13,11 +14,11 @@ import pytest from vector_store import SearchResults - # --------------------------------------------------------------------------- # SearchResults factories # --------------------------------------------------------------------------- + def make_search_results(documents=None, metadata=None, distances=None): """Return a successful SearchResults with the given content.""" docs = documents or [] @@ -35,6 +36,7 @@ def make_error_results(error_msg="Search error: connection failed"): # Anthropic message response factories # --------------------------------------------------------------------------- + def make_text_response(text="Here is the answer."): """Mock a Claude response that returns text directly (no tool use).""" content_block = MagicMock() @@ -71,6 +73,7 @@ def make_tool_use_response( # Expose factories as fixtures so tests can request them # --------------------------------------------------------------------------- + @pytest.fixture def search_results_factory(): return make_search_results diff --git a/backend/tests/test_ai_generator.py b/backend/tests/test_ai_generator.py index 5e7901f84..2f6c00c5a 100644 --- a/backend/tests/test_ai_generator.py +++ b/backend/tests/test_ai_generator.py @@ -11,16 +11,17 @@ - Edge case: stop_reason="tool_use" but no tool_manager provided - Sequential tool calling: 2 chained rounds, forced stop, error string, exception handling """ + import pytest from unittest.mock import MagicMock, patch, call from ai_generator import AIGenerator from tests.conftest import make_text_response, make_tool_use_response - # --------------------------------------------------------------------------- # Fixture: AIGenerator with a mocked Anthropic client # --------------------------------------------------------------------------- + @pytest.fixture def generator_and_client(): """ @@ -38,10 +39,13 @@ def generator_and_client(): # Direct (no-tool) responses # --------------------------------------------------------------------------- + class TestDirectResponse: def test_returns_text_when_no_tool_use(self, generator_and_client): gen, client = generator_and_client - client.messages.create.return_value = make_text_response("Paris is the capital of France.") + client.messages.create.return_value = make_text_response( + "Paris is the capital of France." + ) result = gen.generate_response(query="What is the capital of France?") @@ -69,7 +73,9 @@ def test_conversation_history_added_to_system_prompt(self, generator_and_client) gen, client = generator_and_client client.messages.create.return_value = make_text_response() - gen.generate_response(query="Follow-up", conversation_history="User: Hi\nAssistant: Hello") + gen.generate_response( + query="Follow-up", conversation_history="User: Hi\nAssistant: Hello" + ) system_content = client.messages.create.call_args[1]["system"] assert "User: Hi" in system_content @@ -80,6 +86,7 @@ def test_conversation_history_added_to_system_prompt(self, generator_and_client) # Tool use: first call triggers tool, second call produces answer # --------------------------------------------------------------------------- + class TestToolUseFlow: def _setup_two_call_sequence(self, client, tool_input=None): """Configure client to return tool_use on first call, text on second.""" @@ -151,7 +158,8 @@ def test_tool_result_injected_into_second_call_messages(self, generator_and_clie messages = second_call_kwargs["messages"] # Find the tool_result message specifically (role=user, content is a list of tool_result dicts) tool_result_message = next( - m for m in messages + m + for m in messages if isinstance(m.get("content"), list) and m["content"] and isinstance(m["content"][0], dict) @@ -163,7 +171,9 @@ def test_tool_result_injected_into_second_call_messages(self, generator_and_clie assert result_block["content"] == "Retrieved content here." assert result_block["tool_use_id"] == "toolu_123" - def test_second_call_includes_tools_for_possible_chaining(self, generator_and_client): + def test_second_call_includes_tools_for_possible_chaining( + self, generator_and_client + ): """ With the sequential loop, the second API call is an intermediate call that still includes tools — Claude can decide to chain a second tool call or @@ -191,6 +201,7 @@ def test_second_call_includes_tools_for_possible_chaining(self, generator_and_cl # First-call API parameter validation # --------------------------------------------------------------------------- + class TestFirstCallParameters: def test_tools_included_in_first_call_when_provided(self, generator_and_client): gen, client = generator_and_client @@ -226,8 +237,11 @@ def test_user_query_in_messages(self, generator_and_client): # Edge case: tool_use response but no tool_manager # --------------------------------------------------------------------------- + class TestMissingToolManager: - def test_returns_graceful_message_when_tool_manager_missing(self, generator_and_client): + def test_returns_graceful_message_when_tool_manager_missing( + self, generator_and_client + ): """ If Claude returns stop_reason='tool_use' but no tool_manager is provided, the generator must return a safe error message rather than crashing. @@ -253,6 +267,7 @@ def test_returns_graceful_message_when_tool_manager_missing(self, generator_and_ # Sequential tool calling (up to MAX_ROUNDS = 2) # --------------------------------------------------------------------------- + class TestSequentialToolUse: """ These tests treat the generator as a black box and assert on observable @@ -269,12 +284,18 @@ def test_two_tool_calls_three_api_calls(self, generator_and_client): tool_manager.execute_tool.side_effect = ["outline result", "search result"] client.messages.create.side_effect = [ - make_tool_use_response("get_course_outline", "id1", {"course_name": "Python 101"}), - make_tool_use_response("search_course_content","id2", {"query": "decorators"}), + make_tool_use_response( + "get_course_outline", "id1", {"course_name": "Python 101"} + ), + make_tool_use_response( + "search_course_content", "id2", {"query": "decorators"} + ), make_text_response("Here is the comparison."), ] - result = gen.generate_response(query="Compare topics", tools=self.TOOLS, tool_manager=tool_manager) + result = gen.generate_response( + query="Compare topics", tools=self.TOOLS, tool_manager=tool_manager + ) assert client.messages.create.call_count == 3 assert tool_manager.execute_tool.call_count == 2 @@ -287,8 +308,8 @@ def test_intermediate_call_includes_tools(self, generator_and_client): tool_manager.execute_tool.side_effect = ["result1", "result2"] client.messages.create.side_effect = [ - make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), - make_tool_use_response("search_course_content","id2", {"query": "topic"}), + make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), + make_tool_use_response("search_course_content", "id2", {"query": "topic"}), make_text_response("Final answer."), ] @@ -305,8 +326,8 @@ def test_forced_final_call_excludes_tools(self, generator_and_client): tool_manager.execute_tool.side_effect = ["result1", "result2"] client.messages.create.side_effect = [ - make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), - make_tool_use_response("search_course_content","id2", {"query": "topic"}), + make_tool_use_response("get_course_outline", "id1", {"course_name": "X"}), + make_tool_use_response("search_course_content", "id2", {"query": "topic"}), make_text_response("Forced final answer."), ] @@ -331,13 +352,17 @@ def test_early_exit_when_claude_answers_mid_loop(self, generator_and_client): make_text_response("I have enough info to answer now."), ] - result = gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + result = gen.generate_response( + query="test", tools=self.TOOLS, tool_manager=tool_manager + ) assert client.messages.create.call_count == 2 assert tool_manager.execute_tool.call_count == 1 assert result == "I have enough info to answer now." - def test_tool_error_string_passed_to_claude_loop_continues(self, generator_and_client): + def test_tool_error_string_passed_to_claude_loop_continues( + self, generator_and_client + ): """ Scenario E: Tool returns an error string (not an exception). The error string is valid tool result content — loop continues and Claude @@ -352,14 +377,17 @@ def test_tool_error_string_passed_to_claude_loop_continues(self, generator_and_c make_text_response("I could not find the course."), ] - result = gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + result = gen.generate_response( + query="test", tools=self.TOOLS, tool_manager=tool_manager + ) assert client.messages.create.call_count == 2 assert tool_manager.execute_tool.call_count == 1 # Error string is present in the messages sent to the final call final_call_messages = client.messages.create.call_args_list[1][1]["messages"] tool_result_msg = next( - m for m in final_call_messages + m + for m in final_call_messages if isinstance(m.get("content"), list) and m["content"] and isinstance(m["content"][0], dict) @@ -382,14 +410,17 @@ def test_tool_exception_exits_loop_gracefully(self, generator_and_client): make_text_response("I encountered an error searching for that."), ] - result = gen.generate_response(query="test", tools=self.TOOLS, tool_manager=tool_manager) + result = gen.generate_response( + query="test", tools=self.TOOLS, tool_manager=tool_manager + ) assert client.messages.create.call_count == 2 assert tool_manager.execute_tool.call_count == 1 # Exception is caught and turned into a tool_result message final_call_messages = client.messages.create.call_args_list[1][1]["messages"] tool_result_msg = next( - m for m in final_call_messages + m + for m in final_call_messages if isinstance(m.get("content"), list) and m["content"] and isinstance(m["content"][0], dict) diff --git a/backend/tests/test_course_search_tool.py b/backend/tests/test_course_search_tool.py index 22f8f0ea6..5f88aaeb7 100644 --- a/backend/tests/test_course_search_tool.py +++ b/backend/tests/test_course_search_tool.py @@ -8,17 +8,18 @@ - Source tracking and deduplication - Parameter passthrough to VectorStore.search() """ + import pytest from unittest.mock import MagicMock, call from search_tools import CourseSearchTool from vector_store import SearchResults from tests.conftest import make_search_results, make_error_results - # --------------------------------------------------------------------------- # Helpers # --------------------------------------------------------------------------- + def make_store(search_return=None): """Return a mock VectorStore with search() pre-configured.""" store = MagicMock() @@ -33,6 +34,7 @@ def make_store(search_return=None): # Error handling # --------------------------------------------------------------------------- + class TestErrorHandling: def test_returns_error_string_from_store(self): """Tool must pass the raw error string back so Claude can report it.""" @@ -58,6 +60,7 @@ def test_error_result_prevents_formatting(self): # Empty results # --------------------------------------------------------------------------- + class TestEmptyResults: def test_no_content_found_message_baseline(self): store = make_store() # empty results, no error @@ -89,7 +92,9 @@ def test_no_content_with_both_filters(self): store = make_store() tool = CourseSearchTool(store) - result = tool.execute(query="embeddings", course_name="MCP Course", lesson_number=2) + result = tool.execute( + query="embeddings", course_name="MCP Course", lesson_number=2 + ) assert "MCP Course" in result assert "2" in result @@ -99,12 +104,15 @@ def test_no_content_with_both_filters(self): # Successful result formatting # --------------------------------------------------------------------------- + class TestResultFormatting: def test_result_header_contains_course_title(self): - store = make_store(make_search_results( - documents=["Embeddings are dense vectors."], - metadata=[{"course_title": "Vector DB Deep Dive", "lesson_number": 1}], - )) + store = make_store( + make_search_results( + documents=["Embeddings are dense vectors."], + metadata=[{"course_title": "Vector DB Deep Dive", "lesson_number": 1}], + ) + ) tool = CourseSearchTool(store) result = tool.execute(query="what are embeddings?") @@ -112,10 +120,12 @@ def test_result_header_contains_course_title(self): assert "[Vector DB Deep Dive - Lesson 1]" in result def test_result_body_contains_document_text(self): - store = make_store(make_search_results( - documents=["RAG retrieves relevant chunks before generation."], - metadata=[{"course_title": "RAG Course", "lesson_number": 2}], - )) + store = make_store( + make_search_results( + documents=["RAG retrieves relevant chunks before generation."], + metadata=[{"course_title": "RAG Course", "lesson_number": 2}], + ) + ) tool = CourseSearchTool(store) result = tool.execute(query="what is RAG?") @@ -124,10 +134,12 @@ def test_result_body_contains_document_text(self): def test_header_omits_lesson_when_none(self): """If lesson_number is None in metadata, the header should not show 'Lesson'.""" - store = make_store(make_search_results( - documents=["Course intro text."], - metadata=[{"course_title": "Intro Course", "lesson_number": None}], - )) + store = make_store( + make_search_results( + documents=["Course intro text."], + metadata=[{"course_title": "Intro Course", "lesson_number": None}], + ) + ) tool = CourseSearchTool(store) result = tool.execute(query="intro") @@ -136,13 +148,15 @@ def test_header_omits_lesson_when_none(self): assert "Lesson" not in result def test_multiple_results_separated_by_blank_lines(self): - store = make_store(make_search_results( - documents=["Chunk A.", "Chunk B."], - metadata=[ - {"course_title": "Course X", "lesson_number": 1}, - {"course_title": "Course X", "lesson_number": 2}, - ], - )) + store = make_store( + make_search_results( + documents=["Chunk A.", "Chunk B."], + metadata=[ + {"course_title": "Course X", "lesson_number": 1}, + {"course_title": "Course X", "lesson_number": 2}, + ], + ) + ) tool = CourseSearchTool(store) result = tool.execute(query="something") @@ -157,12 +171,15 @@ def test_multiple_results_separated_by_blank_lines(self): # Source tracking # --------------------------------------------------------------------------- + class TestSourceTracking: def test_last_sources_populated_after_search(self): - store = make_store(make_search_results( - documents=["content"], - metadata=[{"course_title": "AI Course", "lesson_number": 1}], - )) + store = make_store( + make_search_results( + documents=["content"], + metadata=[{"course_title": "AI Course", "lesson_number": 1}], + ) + ) store.get_lesson_link.return_value = "https://example.com/lesson1" tool = CourseSearchTool(store) @@ -174,13 +191,15 @@ def test_last_sources_populated_after_search(self): def test_sources_deduplicated_for_same_lesson(self): """Two chunks from the same lesson should produce only one source entry.""" - store = make_store(make_search_results( - documents=["chunk 1", "chunk 2"], - metadata=[ - {"course_title": "AI Course", "lesson_number": 1}, - {"course_title": "AI Course", "lesson_number": 1}, - ], - )) + store = make_store( + make_search_results( + documents=["chunk 1", "chunk 2"], + metadata=[ + {"course_title": "AI Course", "lesson_number": 1}, + {"course_title": "AI Course", "lesson_number": 1}, + ], + ) + ) tool = CourseSearchTool(store) tool.execute(query="something") @@ -210,6 +229,7 @@ def test_sources_empty_on_empty_results(self): # Parameter passthrough # --------------------------------------------------------------------------- + class TestParameterPassthrough: def test_query_passed_to_store(self): store = make_store() diff --git a/backend/tests/test_rag_system.py b/backend/tests/test_rag_system.py index 93e191ec4..2674ba834 100644 --- a/backend/tests/test_rag_system.py +++ b/backend/tests/test_rag_system.py @@ -9,15 +9,16 @@ - No history is passed for new / unknown sessions - End-to-end content query flow: Claude calls the search tool, result is synthesized """ + import pytest from unittest.mock import MagicMock, patch, call from tests.conftest import make_text_response, make_tool_use_response - # --------------------------------------------------------------------------- # RAGSystem fixture — all heavy dependencies mocked at class level # --------------------------------------------------------------------------- + @pytest.fixture def rag(): """ @@ -32,10 +33,13 @@ def rag(): CHROMA_PATH="./test_chroma", ) - with patch("rag_system.VectorStore"), \ - patch("rag_system.AIGenerator"), \ - patch("rag_system.DocumentProcessor"): + with ( + patch("rag_system.VectorStore"), + patch("rag_system.AIGenerator"), + patch("rag_system.DocumentProcessor"), + ): from rag_system import RAGSystem + system = RAGSystem(config) return system @@ -45,6 +49,7 @@ def rag(): # Tool forwarding # --------------------------------------------------------------------------- + class TestToolForwarding: def test_tools_passed_to_ai_generator(self, rag): """generate_response must receive the registered tool definitions.""" @@ -80,11 +85,14 @@ def test_get_course_outline_tool_registered(self, rag): # Source management # --------------------------------------------------------------------------- + class TestSourceManagement: def test_sources_returned_from_last_search(self, rag): """query() must return whatever sources the search tool recorded.""" rag.ai_generator.generate_response.return_value = "answer" - expected_sources = [{"label": "AI Course - Lesson 1", "url": "https://example.com"}] + expected_sources = [ + {"label": "AI Course - Lesson 1", "url": "https://example.com"} + ] rag.search_tool.last_sources = expected_sources _, sources = rag.query("What is attention?") @@ -117,6 +125,7 @@ def test_empty_sources_when_no_tool_called(self, rag): # Conversation history # --------------------------------------------------------------------------- + class TestConversationHistory: def test_history_passed_when_session_exists(self, rag): """For a known session with history, generate_response must receive it.""" @@ -167,6 +176,7 @@ def test_exchange_stored_after_query(self, rag): # End-to-end content query flow # --------------------------------------------------------------------------- + class TestContentQueryFlow: def test_content_query_uses_search_and_synthesizes_answer(self, rag): """ diff --git a/backend/tests/test_vector_store.py b/backend/tests/test_vector_store.py index 4780c6f0f..22cf4fedf 100644 --- a/backend/tests/test_vector_store.py +++ b/backend/tests/test_vector_store.py @@ -9,16 +9,17 @@ NOTE: First run downloads the sentence-transformer model if not already cached. Subsequent runs are fast. """ + import pytest from vector_store import VectorStore from models import Course, Lesson, CourseChunk from config import Config - # --------------------------------------------------------------------------- # Fixtures # --------------------------------------------------------------------------- + @pytest.fixture def store(tmp_path): """Real VectorStore backed by a temporary ChromaDB directory.""" @@ -37,8 +38,16 @@ def sample_course(): course_link="https://example.com/rag", instructor="Test Instructor", lessons=[ - Lesson(lesson_number=0, title="Overview", lesson_link="https://example.com/rag/0"), - Lesson(lesson_number=1, title="Embeddings and Vector Search", lesson_link="https://example.com/rag/1"), + Lesson( + lesson_number=0, + title="Overview", + lesson_link="https://example.com/rag/0", + ), + Lesson( + lesson_number=1, + title="Embeddings and Vector Search", + lesson_link="https://example.com/rag/1", + ), ], ) @@ -61,6 +70,7 @@ def sample_chunks(sample_course): # 1. Config validation — catches silent misconfigurations # --------------------------------------------------------------------------- + class TestConfigValidation: def test_max_results_is_positive(self): """MAX_RESULTS = 0 causes ChromaDB to return nothing; must be > 0.""" @@ -84,6 +94,7 @@ def test_anthropic_model_is_set(self): # 2. Initialization — collections are created on startup # --------------------------------------------------------------------------- + class TestInitialization: def test_course_catalog_collection_created(self, store): assert store.course_catalog is not None @@ -102,6 +113,7 @@ def test_new_store_has_empty_titles_list(self, store): # 3. Data ingestion and retrieval # --------------------------------------------------------------------------- + class TestDataIngestion: def test_add_course_increments_count(self, store, sample_course): store.add_course_metadata(sample_course) @@ -129,7 +141,13 @@ def test_multiple_courses_counted_correctly(self, store, sample_course): title="Advanced Prompt Engineering", course_link="https://example.com/pe", instructor="Another Instructor", - lessons=[Lesson(lesson_number=0, title="Intro", lesson_link="https://example.com/pe/0")], + lessons=[ + Lesson( + lesson_number=0, + title="Intro", + lesson_link="https://example.com/pe/0", + ) + ], ) store.add_course_metadata(sample_course) store.add_course_metadata(course2) @@ -140,8 +158,11 @@ def test_multiple_courses_counted_correctly(self, store, sample_course): # 4. Search — the MAX_RESULTS = 0 guard # --------------------------------------------------------------------------- + class TestSearch: - def test_search_returns_results_for_relevant_query(self, store, sample_course, sample_chunks): + def test_search_returns_results_for_relevant_query( + self, store, sample_course, sample_chunks + ): """ The critical integration test. With real content indexed, a relevant query must return results. If MAX_RESULTS = 0, this fails even though @@ -151,21 +172,26 @@ def test_search_returns_results_for_relevant_query(self, store, sample_course, s results = store.search(query="RAG retrieval augmented generation") assert not results.is_empty() - def test_search_result_count_respects_max_results(self, store, sample_course, sample_chunks): + def test_search_result_count_respects_max_results( + self, store, sample_course, sample_chunks + ): """Number of results returned must never exceed MAX_RESULTS.""" store.add_course_content(sample_chunks) results = store.search(query="RAG retrieval") assert len(results.documents) <= Config.MAX_RESULTS - def test_search_result_metadata_contains_course_title(self, store, sample_course, sample_chunks): + def test_search_result_metadata_contains_course_title( + self, store, sample_course, sample_chunks + ): store.add_course_content(sample_chunks) results = store.search(query="RAG retrieval") assert all( - m.get("course_title") == sample_course.title - for m in results.metadata + m.get("course_title") == sample_course.title for m in results.metadata ) - def test_search_with_course_filter_returns_only_matching_course(self, store, sample_course, sample_chunks): + def test_search_with_course_filter_returns_only_matching_course( + self, store, sample_course, sample_chunks + ): other_chunks = [ CourseChunk( content="Machine learning neural networks deep learning.", @@ -177,7 +203,9 @@ def test_search_with_course_filter_returns_only_matching_course(self, store, sam store.add_course_content(sample_chunks) store.add_course_content(other_chunks) - results = store.search(query="neural networks", course_name="Introduction to RAG") + results = store.search( + query="neural networks", course_name="Introduction to RAG" + ) # All returned results must be from the filtered course assert all(m["course_title"] == sample_course.title for m in results.metadata) @@ -196,6 +224,7 @@ def test_search_empty_catalog_returns_empty_results(self, store): # 5. Course outline (our new get_course_outline method) # --------------------------------------------------------------------------- + class TestCourseOutline: def test_outline_contains_correct_title(self, store, sample_course): store.add_course_metadata(sample_course) @@ -231,7 +260,9 @@ def test_outline_returns_none_for_empty_catalog(self, store): result = store.get_course_outline("Introduction to RAG") assert result is None - def test_get_all_courses_metadata_returns_parsed_lessons(self, store, sample_course): + def test_get_all_courses_metadata_returns_parsed_lessons( + self, store, sample_course + ): store.add_course_metadata(sample_course) all_meta = store.get_all_courses_metadata() assert len(all_meta) == 1 diff --git a/backend/vector_store.py b/backend/vector_store.py index fe2aff3bb..324901b61 100644 --- a/backend/vector_store.py +++ b/backend/vector_store.py @@ -5,73 +5,88 @@ from models import Course, CourseChunk from sentence_transformers import SentenceTransformer + @dataclass class SearchResults: """Container for search results with metadata""" + documents: List[str] metadata: List[Dict[str, Any]] distances: List[float] error: Optional[str] = None - + @classmethod - def from_chroma(cls, chroma_results: Dict) -> 'SearchResults': + def from_chroma(cls, chroma_results: Dict) -> "SearchResults": """Create SearchResults from ChromaDB query results""" return cls( - documents=chroma_results['documents'][0] if chroma_results['documents'] else [], - metadata=chroma_results['metadatas'][0] if chroma_results['metadatas'] else [], - distances=chroma_results['distances'][0] if chroma_results['distances'] else [] + documents=( + chroma_results["documents"][0] if chroma_results["documents"] else [] + ), + metadata=( + chroma_results["metadatas"][0] if chroma_results["metadatas"] else [] + ), + distances=( + chroma_results["distances"][0] if chroma_results["distances"] else [] + ), ) - + @classmethod - def empty(cls, error_msg: str) -> 'SearchResults': + def empty(cls, error_msg: str) -> "SearchResults": """Create empty results with error message""" return cls(documents=[], metadata=[], distances=[], error=error_msg) - + def is_empty(self) -> bool: """Check if results are empty""" return len(self.documents) == 0 + class VectorStore: """Vector storage using ChromaDB for course content and metadata""" - + def __init__(self, chroma_path: str, embedding_model: str, max_results: int = 5): self.max_results = max_results # Initialize ChromaDB client self.client = chromadb.PersistentClient( - path=chroma_path, - settings=Settings(anonymized_telemetry=False) + path=chroma_path, settings=Settings(anonymized_telemetry=False) ) - + # Set up sentence transformer embedding function - self.embedding_function = chromadb.utils.embedding_functions.SentenceTransformerEmbeddingFunction( - model_name=embedding_model + self.embedding_function = ( + chromadb.utils.embedding_functions.SentenceTransformerEmbeddingFunction( + model_name=embedding_model + ) ) - + # Create collections for different types of data - self.course_catalog = self._create_collection("course_catalog") # Course titles/instructors - self.course_content = self._create_collection("course_content") # Actual course material - + self.course_catalog = self._create_collection( + "course_catalog" + ) # Course titles/instructors + self.course_content = self._create_collection( + "course_content" + ) # Actual course material + def _create_collection(self, name: str): """Create or get a ChromaDB collection""" return self.client.get_or_create_collection( - name=name, - embedding_function=self.embedding_function + name=name, embedding_function=self.embedding_function ) - - def search(self, - query: str, - course_name: Optional[str] = None, - lesson_number: Optional[int] = None, - limit: Optional[int] = None) -> SearchResults: + + def search( + self, + query: str, + course_name: Optional[str] = None, + lesson_number: Optional[int] = None, + limit: Optional[int] = None, + ) -> SearchResults: """ Main search interface that handles course resolution and content search. - + Args: query: What to search for in course content course_name: Optional course name/title to filter by lesson_number: Optional lesson number to filter by limit: Maximum results to return - + Returns: SearchResults object with documents and metadata """ @@ -81,104 +96,111 @@ def search(self, course_title = self._resolve_course_name(course_name) if not course_title: return SearchResults.empty(f"No course found matching '{course_name}'") - + # Step 2: Build filter for content search filter_dict = self._build_filter(course_title, lesson_number) - + # Step 3: Search course content # Use provided limit or fall back to configured max_results search_limit = limit if limit is not None else self.max_results - + try: results = self.course_content.query( - query_texts=[query], - n_results=search_limit, - where=filter_dict + query_texts=[query], n_results=search_limit, where=filter_dict ) return SearchResults.from_chroma(results) except Exception as e: return SearchResults.empty(f"Search error: {str(e)}") - + def _resolve_course_name(self, course_name: str) -> Optional[str]: """Use vector search to find best matching course by name""" try: - results = self.course_catalog.query( - query_texts=[course_name], - n_results=1 - ) - - if results['documents'][0] and results['metadatas'][0]: + results = self.course_catalog.query(query_texts=[course_name], n_results=1) + + if results["documents"][0] and results["metadatas"][0]: # Return the title (which is now the ID) - return results['metadatas'][0][0]['title'] + return results["metadatas"][0][0]["title"] except Exception as e: print(f"Error resolving course name: {e}") - + return None - - def _build_filter(self, course_title: Optional[str], lesson_number: Optional[int]) -> Optional[Dict]: + + def _build_filter( + self, course_title: Optional[str], lesson_number: Optional[int] + ) -> Optional[Dict]: """Build ChromaDB filter from search parameters""" if not course_title and lesson_number is None: return None - + # Handle different filter combinations if course_title and lesson_number is not None: - return {"$and": [ - {"course_title": course_title}, - {"lesson_number": lesson_number} - ]} - + return { + "$and": [ + {"course_title": course_title}, + {"lesson_number": lesson_number}, + ] + } + if course_title: return {"course_title": course_title} - + return {"lesson_number": lesson_number} - + def add_course_metadata(self, course: Course): """Add course information to the catalog for semantic search""" import json course_text = course.title - + # Build lessons metadata and serialize as JSON string lessons_metadata = [] for lesson in course.lessons: - lessons_metadata.append({ - "lesson_number": lesson.lesson_number, - "lesson_title": lesson.title, - "lesson_link": lesson.lesson_link - }) - + lessons_metadata.append( + { + "lesson_number": lesson.lesson_number, + "lesson_title": lesson.title, + "lesson_link": lesson.lesson_link, + } + ) + self.course_catalog.add( documents=[course_text], - metadatas=[{ - "title": course.title, - "instructor": course.instructor, - "course_link": course.course_link, - "lessons_json": json.dumps(lessons_metadata), # Serialize as JSON string - "lesson_count": len(course.lessons) - }], - ids=[course.title] + metadatas=[ + { + "title": course.title, + "instructor": course.instructor, + "course_link": course.course_link, + "lessons_json": json.dumps( + lessons_metadata + ), # Serialize as JSON string + "lesson_count": len(course.lessons), + } + ], + ids=[course.title], ) - + def add_course_content(self, chunks: List[CourseChunk]): """Add course content chunks to the vector store""" if not chunks: return - + documents = [chunk.content for chunk in chunks] - metadatas = [{ - "course_title": chunk.course_title, - "lesson_number": chunk.lesson_number, - "chunk_index": chunk.chunk_index - } for chunk in chunks] + metadatas = [ + { + "course_title": chunk.course_title, + "lesson_number": chunk.lesson_number, + "chunk_index": chunk.chunk_index, + } + for chunk in chunks + ] # Use title with chunk index for unique IDs - ids = [f"{chunk.course_title.replace(' ', '_')}_{chunk.chunk_index}" for chunk in chunks] - - self.course_content.add( - documents=documents, - metadatas=metadatas, - ids=ids - ) - + ids = [ + f"{chunk.course_title.replace(' ', '_')}_{chunk.chunk_index}" + for chunk in chunks + ] + + self.course_content.add(documents=documents, metadatas=metadatas, ids=ids) + def clear_all_data(self): """Clear all data from both collections""" try: @@ -189,43 +211,46 @@ def clear_all_data(self): self.course_content = self._create_collection("course_content") except Exception as e: print(f"Error clearing data: {e}") - + def get_existing_course_titles(self) -> List[str]: """Get all existing course titles from the vector store""" try: # Get all documents from the catalog results = self.course_catalog.get() - if results and 'ids' in results: - return results['ids'] + if results and "ids" in results: + return results["ids"] return [] except Exception as e: print(f"Error getting existing course titles: {e}") return [] - + def get_course_count(self) -> int: """Get the total number of courses in the vector store""" try: results = self.course_catalog.get() - if results and 'ids' in results: - return len(results['ids']) + if results and "ids" in results: + return len(results["ids"]) return 0 except Exception as e: print(f"Error getting course count: {e}") return 0 - + def get_all_courses_metadata(self) -> List[Dict[str, Any]]: """Get metadata for all courses in the vector store""" import json + try: results = self.course_catalog.get() - if results and 'metadatas' in results: + if results and "metadatas" in results: # Parse lessons JSON for each course parsed_metadata = [] - for metadata in results['metadatas']: + for metadata in results["metadatas"]: course_meta = metadata.copy() - if 'lessons_json' in course_meta: - course_meta['lessons'] = json.loads(course_meta['lessons_json']) - del course_meta['lessons_json'] # Remove the JSON string version + if "lessons_json" in course_meta: + course_meta["lessons"] = json.loads(course_meta["lessons_json"]) + del course_meta[ + "lessons_json" + ] # Remove the JSON string version parsed_metadata.append(course_meta) return parsed_metadata return [] @@ -236,21 +261,25 @@ def get_all_courses_metadata(self) -> List[Dict[str, Any]]: def get_course_outline(self, course_name: str) -> Optional[Dict[str, Any]]: """Get structured outline (title, link, lessons) for a course by name (fuzzy match)""" import json + resolved_title = self._resolve_course_name(course_name) if not resolved_title: return None try: results = self.course_catalog.get(ids=[resolved_title]) - if results and 'metadatas' in results and results['metadatas']: - metadata = results['metadatas'][0] - lessons = json.loads(metadata.get('lessons_json', '[]')) + if results and "metadatas" in results and results["metadatas"]: + metadata = results["metadatas"][0] + lessons = json.loads(metadata.get("lessons_json", "[]")) return { - 'title': metadata.get('title'), - 'course_link': metadata.get('course_link'), - 'lessons': [ - {'lesson_number': l['lesson_number'], 'lesson_title': l['lesson_title']} + "title": metadata.get("title"), + "course_link": metadata.get("course_link"), + "lessons": [ + { + "lesson_number": l["lesson_number"], + "lesson_title": l["lesson_title"], + } for l in lessons - ] + ], } except Exception as e: print(f"Error getting course outline: {e}") @@ -261,30 +290,30 @@ def get_course_link(self, course_title: str) -> Optional[str]: try: # Get course by ID (title is the ID) results = self.course_catalog.get(ids=[course_title]) - if results and 'metadatas' in results and results['metadatas']: - metadata = results['metadatas'][0] - return metadata.get('course_link') + if results and "metadatas" in results and results["metadatas"]: + metadata = results["metadatas"][0] + return metadata.get("course_link") return None except Exception as e: print(f"Error getting course link: {e}") return None - + def get_lesson_link(self, course_title: str, lesson_number: int) -> Optional[str]: """Get lesson link for a given course title and lesson number""" import json + try: # Get course by ID (title is the ID) results = self.course_catalog.get(ids=[course_title]) - if results and 'metadatas' in results and results['metadatas']: - metadata = results['metadatas'][0] - lessons_json = metadata.get('lessons_json') + if results and "metadatas" in results and results["metadatas"]: + metadata = results["metadatas"][0] + lessons_json = metadata.get("lessons_json") if lessons_json: lessons = json.loads(lessons_json) # Find the lesson with matching number for lesson in lessons: - if lesson.get('lesson_number') == lesson_number: - return lesson.get('lesson_link') + if lesson.get("lesson_number") == lesson_number: + return lesson.get("lesson_link") return None except Exception as e: print(f"Error getting lesson link: {e}") - \ No newline at end of file diff --git a/pyproject.toml b/pyproject.toml index 3f05e2de0..b7e2e4a6d 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -13,3 +13,12 @@ dependencies = [ "python-multipart==0.0.20", "python-dotenv==1.1.1", ] + +[dependency-groups] +dev = [ + "black>=25.1.0", +] + +[tool.black] +line-length = 88 +target-version = ["py313"] diff --git a/scripts/check_quality.sh b/scripts/check_quality.sh new file mode 100644 index 000000000..d10b1610a --- /dev/null +++ b/scripts/check_quality.sh @@ -0,0 +1,10 @@ +#!/usr/bin/env bash +# Run all quality checks (non-destructive — exits non-zero if anything fails) +set -e +cd "$(dirname "$0")/.." + +echo "==> black (format check)" +uv run black --check backend/ + +echo "" +echo "All quality checks passed." diff --git a/scripts/format.sh b/scripts/format.sh new file mode 100644 index 000000000..8747cbb2c --- /dev/null +++ b/scripts/format.sh @@ -0,0 +1,5 @@ +#!/usr/bin/env bash +# 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+[package.metadata.requires-dev] +dev = [{ name = "black", specifier = ">=25.1.0" }] + [[package]] name = "sympy" version = "1.14.0" From ef1403ad31d783c58018c4aeb148c99f50e337b5 Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Mon, 18 May 2026 12:26:42 -0700 Subject: [PATCH 11/12] "Claude PR Assistant workflow" --- .github/workflows/claude.yml | 50 ++++++++++++++++++++++++++++++++++++ 1 file changed, 50 insertions(+) create mode 100644 .github/workflows/claude.yml diff --git a/.github/workflows/claude.yml b/.github/workflows/claude.yml new file mode 100644 index 000000000..6b15fac7a --- /dev/null +++ b/.github/workflows/claude.yml @@ -0,0 +1,50 @@ +name: Claude Code + +on: + issue_comment: + types: [created] + pull_request_review_comment: + types: [created] + issues: + types: [opened, assigned] + pull_request_review: + types: [submitted] + +jobs: + claude: + if: | + (github.event_name == 'issue_comment' && contains(github.event.comment.body, '@claude')) || + (github.event_name == 'pull_request_review_comment' && contains(github.event.comment.body, '@claude')) || + (github.event_name == 'pull_request_review' && contains(github.event.review.body, '@claude')) || + (github.event_name == 'issues' && (contains(github.event.issue.body, '@claude') || contains(github.event.issue.title, '@claude'))) + runs-on: ubuntu-latest + permissions: + contents: read + pull-requests: read + issues: read + id-token: write + actions: read # Required for Claude to read CI results on PRs + steps: + - name: Checkout repository + uses: actions/checkout@v4 + with: + fetch-depth: 1 + + - name: Run Claude Code + id: claude + uses: anthropics/claude-code-action@v1 + with: + claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }} + + # This is an optional setting that allows Claude to read CI results on PRs + additional_permissions: | + actions: read + + # Optional: Give a custom prompt to Claude. If this is not specified, Claude will perform the instructions specified in the comment that tagged it. + # prompt: 'Update the pull request description to include a summary of changes.' + + # Optional: Add claude_args to customize behavior and configuration + # See https://github.com/anthropics/claude-code-action/blob/main/docs/usage.md + # or https://code.claude.com/docs/en/cli-reference for available options + # claude_args: '--allowed-tools Bash(gh pr *)' + From 42bc927ce60b6b8e5fbbe4ad3eb63143737d7bbe Mon Sep 17 00:00:00 2001 From: gsuarez90 <60275264+gsuarez90@users.noreply.github.com> Date: Mon, 18 May 2026 12:26:43 -0700 Subject: [PATCH 12/12] "Claude Code Review workflow" --- .github/workflows/claude-code-review.yml | 44 ++++++++++++++++++++++++ 1 file changed, 44 insertions(+) create mode 100644 .github/workflows/claude-code-review.yml diff --git a/.github/workflows/claude-code-review.yml b/.github/workflows/claude-code-review.yml new file mode 100644 index 000000000..b5e8cfd4d --- /dev/null +++ b/.github/workflows/claude-code-review.yml @@ -0,0 +1,44 @@ +name: Claude Code Review + +on: + pull_request: + types: [opened, synchronize, ready_for_review, reopened] + # Optional: Only run on specific file changes + # paths: + # - "src/**/*.ts" + # - "src/**/*.tsx" + # - "src/**/*.js" + # - "src/**/*.jsx" + +jobs: + claude-review: + # Optional: Filter by PR author + # if: | + # github.event.pull_request.user.login == 'external-contributor' || + # github.event.pull_request.user.login == 'new-developer' || + # github.event.pull_request.author_association == 'FIRST_TIME_CONTRIBUTOR' + + runs-on: ubuntu-latest + permissions: + contents: read + pull-requests: read + issues: read + id-token: write + + steps: + - name: Checkout repository + uses: actions/checkout@v4 + with: + fetch-depth: 1 + + - name: Run Claude Code Review + id: claude-review + uses: anthropics/claude-code-action@v1 + with: + claude_code_oauth_token: ${{ secrets.CLAUDE_CODE_OAUTH_TOKEN }} + plugin_marketplaces: 'https://github.com/anthropics/claude-code.git' + plugins: 'code-review@claude-code-plugins' + prompt: '/code-review:code-review ${{ github.repository }}/pull/${{ github.event.pull_request.number }}' + # See https://github.com/anthropics/claude-code-action/blob/main/docs/usage.md + # or https://code.claude.com/docs/en/cli-reference for available options +