diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..ae74cb5
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,19 @@
+FROM python:3.11-slim
+
+WORKDIR /app
+
+# Install uv
+RUN pip install uv
+
+# Copy project dependencies
+COPY pyproject.toml uv.lock ./
+
+# Install dependencies using uv
+RUN uv sync --frozen
+
+# Copy source code
+COPY . .
+
+EXPOSE 8000
+
+CMD ["uv", "run", "python", "-m", "src"]
diff --git a/api/index.py b/api/index.py
new file mode 100644
index 0000000..424d8b6
--- /dev/null
+++ b/api/index.py
@@ -0,0 +1,4 @@
+from src.api import app
+
+# This file is used by Vercel for Serverless deployment.
+# Vercel will look for an `app` variable here.
diff --git a/docker-compose.yml b/docker-compose.yml
new file mode 100644
index 0000000..1488b08
--- /dev/null
+++ b/docker-compose.yml
@@ -0,0 +1,21 @@
+version: '3.8'
+services:
+ backend:
+ build: .
+ ports:
+ - "8000:8000"
+ environment:
+ - AGENT_GEMINI_API_KEY=${AGENT_GEMINI_API_KEY}
+ volumes:
+ - ./data:/app/data
+
+ frontend:
+ image: node:20-alpine
+ working_dir: /app/frontend
+ volumes:
+ - ./frontend:/app/frontend
+ command: sh -c "npm install && npm run dev -- --host"
+ ports:
+ - "5173:5173"
+ environment:
+ - VITE_API_URL=http://backend:8000
diff --git a/frontend/.gitignore b/frontend/.gitignore
new file mode 100644
index 0000000..a547bf3
--- /dev/null
+++ b/frontend/.gitignore
@@ -0,0 +1,24 @@
+# Logs
+logs
+*.log
+npm-debug.log*
+yarn-debug.log*
+yarn-error.log*
+pnpm-debug.log*
+lerna-debug.log*
+
+node_modules
+dist
+dist-ssr
+*.local
+
+# Editor directories and files
+.vscode/*
+!.vscode/extensions.json
+.idea
+.DS_Store
+*.suo
+*.ntvs*
+*.njsproj
+*.sln
+*.sw?
diff --git a/frontend/.oxlintrc.json b/frontend/.oxlintrc.json
new file mode 100644
index 0000000..6fa991d
--- /dev/null
+++ b/frontend/.oxlintrc.json
@@ -0,0 +1,8 @@
+{
+ "$schema": "./node_modules/oxlint/configuration_schema.json",
+ "plugins": ["react", "typescript", "oxc"],
+ "rules": {
+ "react/rules-of-hooks": "error",
+ "react/only-export-components": ["warn", { "allowConstantExport": true }]
+ }
+}
diff --git a/frontend/README.md b/frontend/README.md
new file mode 100644
index 0000000..d6af7e3
--- /dev/null
+++ b/frontend/README.md
@@ -0,0 +1,32 @@
+# React + TypeScript + Vite
+
+This template provides a minimal setup to get React working in Vite with HMR and some Oxlint rules.
+
+Currently, two official plugins are available:
+
+- [@vitejs/plugin-react](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react) uses [Oxc](https://oxc.rs)
+- [@vitejs/plugin-react-swc](https://github.com/vitejs/vite-plugin-react/blob/main/packages/plugin-react-swc) uses [SWC](https://swc.rs/)
+
+## React Compiler
+
+The React Compiler is not enabled on this template because of its impact on dev & build performances. To add it, see [this documentation](https://react.dev/learn/react-compiler/installation).
+
+## Expanding the Oxlint configuration
+
+If you are developing a production application, we recommend enabling type-aware lint rules by installing `oxlint-tsgolint` and editing `.oxlintrc.json`:
+
+```json
+{
+ "$schema": "./node_modules/oxlint/configuration_schema.json",
+ "plugins": ["react", "typescript", "oxc"],
+ "options": {
+ "typeAware": true
+ },
+ "rules": {
+ "react/rules-of-hooks": "error",
+ "react/only-export-components": ["warn", { "allowConstantExport": true }]
+ }
+}
+```
+
+See the [Oxlint rules documentation](https://oxc.rs/docs/guide/usage/linter/rules) for the full list of rules and categories.
diff --git a/frontend/index.html b/frontend/index.html
new file mode 100644
index 0000000..0fca6f0
--- /dev/null
+++ b/frontend/index.html
@@ -0,0 +1,13 @@
+
+
+
+
+
+
+ frontend
+
+
+
+
+
+
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
new file mode 100644
index 0000000..56dc7fe
--- /dev/null
+++ b/frontend/package-lock.json
@@ -0,0 +1,1816 @@
+{
+ "name": "frontend",
+ "version": "0.0.0",
+ "lockfileVersion": 3,
+ "requires": true,
+ "packages": {
+ "": {
+ "name": "frontend",
+ "version": "0.0.0",
+ "dependencies": {
+ "react": "^19.2.7",
+ "react-dom": "^19.2.7",
+ "recharts": "^3.10.0"
+ },
+ "devDependencies": {
+ "@types/node": "^24.13.2",
+ "@types/react": "^19.2.17",
+ "@types/react-dom": "^19.2.3",
+ "@vitejs/plugin-react": "^6.0.3",
+ "oxlint": "^1.71.0",
+ "typescript": "~6.0.2",
+ "vite": "^8.1.1"
+ }
+ },
+ "node_modules/@emnapi/core": {
+ "version": "1.11.1",
+ "resolved": "https://registry.npmjs.org/@emnapi/core/-/core-1.11.1.tgz",
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+ "dev": true,
+ "license": "MIT",
+ "optional": true,
+ "dependencies": {
+ "@emnapi/wasi-threads": "1.2.2",
+ "tslib": "^2.4.0"
+ }
+ },
+ "node_modules/@emnapi/runtime": {
+ "version": "1.11.1",
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+ "dev": true,
+ "license": "MIT",
+ "optional": true,
+ "dependencies": {
+ "tslib": "^2.4.0"
+ }
+ },
+ "node_modules/@emnapi/wasi-threads": {
+ "version": "1.2.2",
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+ "dev": true,
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+ "optional": true,
+ "dependencies": {
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+ }
+ },
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+ },
+ "funding": {
+ "type": "github",
+ "url": "https://github.com/sponsors/Brooooooklyn"
+ },
+ "peerDependencies": {
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+ }
+ },
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+ "funding": {
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+ }
+ },
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+ "cpu": [
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+ ],
+ "dev": true,
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+ "optional": true,
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+ },
+ "bin": {
+ "rolldown": "bin/cli.mjs"
+ },
+ "engines": {
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+ },
+ "optionalDependencies": {
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+ }
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+ "vite": "bin/vite.js"
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+ "funding": {
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+ "@types/node": {
+ "optional": true
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+ "@vitejs/devtools": {
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+ "jiti": {
+ "optional": true
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+ "less": {
+ "optional": true
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+ "sass": {
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+ "optional": true
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+ "sugarss": {
+ "optional": true
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+ "terser": {
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+ }
+ }
+}
diff --git a/frontend/package.json b/frontend/package.json
new file mode 100644
index 0000000..7dab4b4
--- /dev/null
+++ b/frontend/package.json
@@ -0,0 +1,26 @@
+{
+ "name": "frontend",
+ "private": true,
+ "version": "0.0.0",
+ "type": "module",
+ "scripts": {
+ "dev": "vite",
+ "build": "tsc -b && vite build",
+ "lint": "oxlint",
+ "preview": "vite preview"
+ },
+ "dependencies": {
+ "react": "^19.2.7",
+ "react-dom": "^19.2.7",
+ "recharts": "^3.10.0"
+ },
+ "devDependencies": {
+ "@types/node": "^24.13.2",
+ "@types/react": "^19.2.17",
+ "@types/react-dom": "^19.2.3",
+ "@vitejs/plugin-react": "^6.0.3",
+ "oxlint": "^1.71.0",
+ "typescript": "~6.0.2",
+ "vite": "^8.1.1"
+ }
+}
diff --git a/frontend/public/app.js b/frontend/public/app.js
deleted file mode 100644
index 72fb850..0000000
--- a/frontend/public/app.js
+++ /dev/null
@@ -1,77 +0,0 @@
-// Zero-build baseline frontend. Single-origin: the page is served by the
-// backend at /app, so API calls are same-origin relative paths.
-"use strict";
-
-const $ = (id) => document.getElementById(id);
-
-async function loadHealth() {
- const badge = $("provider-badge");
- try {
- const res = await fetch("/health");
- const body = await res.json();
- const { provider, model, key_configured: keyed } = body.data;
- if (!keyed) {
- badge.textContent = "no API key — set one in .env";
- badge.classList.add("stub");
- } else {
- badge.textContent = `${provider} · ${model}`;
- }
- } catch {
- badge.textContent = "backend unreachable";
- badge.classList.add("stub");
- }
-}
-
-async function runTransform() {
- const btn = $("run-btn");
- const status = $("status");
- const errBox = $("error");
- const wrap = $("result-wrap");
-
- const text = $("text").value.trim();
- const instruction = $("instruction").value.trim();
-
- errBox.hidden = true;
- wrap.hidden = true;
-
- if (!text) {
- errBox.textContent = "Paste some text first — the input can't be empty.";
- errBox.hidden = false;
- return;
- }
-
- btn.disabled = true;
- status.textContent = "Running… (one real LLM call)";
- status.hidden = false;
-
- try {
- const res = await fetch("/runs", {
- method: "POST",
- headers: { "content-type": "application/json" },
- body: JSON.stringify({ text, instruction }),
- });
- const body = await res.json();
-
- if (!res.ok) {
- const msg = body?.detail?.message || `HTTP ${res.status}`;
- throw new Error(msg);
- }
- const run = body.data;
- if (run.status === "failed") {
- throw new Error(run.error_message || "The agent run failed.");
- }
- $("result").textContent = run.output_text;
- $("result-meta").textContent =
- `run ${run.run_id} · ${run.provider} · ${run.model}`;
- wrap.hidden = false;
- } catch (err) {
- errBox.textContent = err.message;
- errBox.hidden = false;
- } finally {
- btn.disabled = false;
- status.hidden = true;
- }
-}
-
-$("run-btn").addEventListener("click", runTransform);
-loadHealth();
diff --git a/frontend/public/favicon.svg b/frontend/public/favicon.svg
new file mode 100644
index 0000000..6893eb1
--- /dev/null
+++ b/frontend/public/favicon.svg
@@ -0,0 +1 @@
+
\ No newline at end of file
diff --git a/frontend/public/icons.svg b/frontend/public/icons.svg
new file mode 100644
index 0000000..e952219
--- /dev/null
+++ b/frontend/public/icons.svg
@@ -0,0 +1,24 @@
+
diff --git a/frontend/public/index.html b/frontend/public/index.html
deleted file mode 100644
index 014097d..0000000
--- a/frontend/public/index.html
+++ /dev/null
@@ -1,48 +0,0 @@
-
-
-
-
-
- Zero-Shot Agent — Transform
-
-
-
-
-
-
-
-
-
-
-
-
-
-
diff --git a/frontend/public/styles.css b/frontend/public/styles.css
deleted file mode 100644
index fc37523..0000000
--- a/frontend/public/styles.css
+++ /dev/null
@@ -1,59 +0,0 @@
-/* Zero-build baseline styles — replace alongside the capability slot. */
-:root {
- --bg: #0f1115;
- --card: #171a21;
- --text: #e8eaf0;
- --muted: #9aa3b2;
- --accent: #5b8def;
- --error: #e5534b;
- --ok: #3fb950;
- --radius: 10px;
- color-scheme: dark;
-}
-* { box-sizing: border-box; }
-body {
- margin: 0;
- font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, sans-serif;
- background: var(--bg);
- color: var(--text);
- line-height: 1.5;
-}
-.shell { max-width: 760px; margin: 0 auto; padding: 24px 16px 48px; }
-.topbar { display: flex; align-items: center; justify-content: space-between; }
-.topbar h1 { font-size: 1.4rem; margin: 0; }
-.badge {
- font-size: 0.75rem; padding: 3px 10px; border-radius: 999px;
- background: #22304d; color: var(--accent); border: 1px solid #2d3f63;
-}
-.badge.stub { background: #4d2222; color: var(--error); border-color: #633030; }
-.card {
- background: var(--card); border-radius: var(--radius);
- padding: 20px; margin-top: 20px; border: 1px solid #232838;
-}
-.card h2 { margin-top: 0; font-size: 1.1rem; }
-.hint { color: var(--muted); font-size: 0.9rem; margin-top: -6px; }
-label { display: block; margin: 14px 0 4px; font-size: 0.85rem; color: var(--muted); }
-input[type="text"], textarea {
- width: 100%; padding: 10px 12px; border-radius: 8px;
- border: 1px solid #2b3245; background: #10131a; color: var(--text);
- font: inherit; resize: vertical;
-}
-input:focus, textarea:focus { outline: 2px solid var(--accent); border-color: transparent; }
-button {
- margin-top: 16px; padding: 10px 22px; border: 0; border-radius: 8px;
- background: var(--accent); color: #fff; font: inherit; font-weight: 600; cursor: pointer;
-}
-button:disabled { opacity: 0.55; cursor: wait; }
-.status { margin-top: 14px; color: var(--muted); font-size: 0.9rem; }
-.error {
- margin-top: 14px; padding: 10px 14px; border-radius: 8px;
- background: #2c1a19; border: 1px solid #5a2c29; color: var(--error); font-size: 0.9rem;
-}
-#result-wrap h3 { margin: 18px 0 6px; font-size: 0.95rem; }
-pre#result {
- background: #10131a; border: 1px solid #2b3245; border-radius: 8px;
- padding: 14px; white-space: pre-wrap; word-wrap: break-word; margin: 0;
-}
-.meta { color: var(--muted); font-size: 0.78rem; }
-.foot { margin-top: 28px; color: var(--muted); font-size: 0.85rem; text-align: center; }
-.foot a { color: var(--accent); }
diff --git a/frontend/src/App.css b/frontend/src/App.css
new file mode 100644
index 0000000..f90339d
--- /dev/null
+++ b/frontend/src/App.css
@@ -0,0 +1,184 @@
+.counter {
+ font-size: 16px;
+ padding: 5px 10px;
+ border-radius: 5px;
+ color: var(--accent);
+ background: var(--accent-bg);
+ border: 2px solid transparent;
+ transition: border-color 0.3s;
+ margin-bottom: 24px;
+
+ &:hover {
+ border-color: var(--accent-border);
+ }
+ &:focus-visible {
+ outline: 2px solid var(--accent);
+ outline-offset: 2px;
+ }
+}
+
+.hero {
+ position: relative;
+
+ .base,
+ .framework,
+ .vite {
+ inset-inline: 0;
+ margin: 0 auto;
+ }
+
+ .base {
+ width: 170px;
+ position: relative;
+ z-index: 0;
+ }
+
+ .framework,
+ .vite {
+ position: absolute;
+ }
+
+ .framework {
+ z-index: 1;
+ top: 34px;
+ height: 28px;
+ transform: perspective(2000px) rotateZ(300deg) rotateX(44deg) rotateY(39deg)
+ scale(1.4);
+ }
+
+ .vite {
+ z-index: 0;
+ top: 107px;
+ height: 26px;
+ width: auto;
+ transform: perspective(2000px) rotateZ(300deg) rotateX(40deg) rotateY(39deg)
+ scale(0.8);
+ }
+}
+
+#center {
+ display: flex;
+ flex-direction: column;
+ gap: 25px;
+ place-content: center;
+ place-items: center;
+ flex-grow: 1;
+
+ @media (max-width: 1024px) {
+ padding: 32px 20px 24px;
+ gap: 18px;
+ }
+}
+
+#next-steps {
+ display: flex;
+ border-top: 1px solid var(--border);
+ text-align: left;
+
+ & > div {
+ flex: 1 1 0;
+ padding: 32px;
+ @media (max-width: 1024px) {
+ padding: 24px 20px;
+ }
+ }
+
+ .icon {
+ margin-bottom: 16px;
+ width: 22px;
+ height: 22px;
+ }
+
+ @media (max-width: 1024px) {
+ flex-direction: column;
+ text-align: center;
+ }
+}
+
+#docs {
+ border-right: 1px solid var(--border);
+
+ @media (max-width: 1024px) {
+ border-right: none;
+ border-bottom: 1px solid var(--border);
+ }
+}
+
+#next-steps ul {
+ list-style: none;
+ padding: 0;
+ display: flex;
+ gap: 8px;
+ margin: 32px 0 0;
+
+ .logo {
+ height: 18px;
+ }
+
+ a {
+ color: var(--text-h);
+ font-size: 16px;
+ border-radius: 6px;
+ background: var(--social-bg);
+ display: flex;
+ padding: 6px 12px;
+ align-items: center;
+ gap: 8px;
+ text-decoration: none;
+ transition: box-shadow 0.3s;
+
+ &:hover {
+ box-shadow: var(--shadow);
+ }
+ .button-icon {
+ height: 18px;
+ width: 18px;
+ }
+ }
+
+ @media (max-width: 1024px) {
+ margin-top: 20px;
+ flex-wrap: wrap;
+ justify-content: center;
+
+ li {
+ flex: 1 1 calc(50% - 8px);
+ }
+
+ a {
+ width: 100%;
+ justify-content: center;
+ box-sizing: border-box;
+ }
+ }
+}
+
+#spacer {
+ height: 88px;
+ border-top: 1px solid var(--border);
+ @media (max-width: 1024px) {
+ height: 48px;
+ }
+}
+
+.ticks {
+ position: relative;
+ width: 100%;
+
+ &::before,
+ &::after {
+ content: '';
+ position: absolute;
+ top: -4.5px;
+ border: 5px solid transparent;
+ }
+
+ &::before {
+ left: 0;
+ border-left-color: var(--border);
+ }
+ &::after {
+ right: 0;
+ border-right-color: var(--border);
+ }
+}
diff --git a/frontend/src/App.tsx b/frontend/src/App.tsx
new file mode 100644
index 0000000..8fcc68a
--- /dev/null
+++ b/frontend/src/App.tsx
@@ -0,0 +1,158 @@
+import { useState, useRef, useEffect } from 'react';
+import './index.css';
+import Upload from './components/Upload';
+import Dashboard from './components/Dashboard';
+import ThemeToggle from './components/ThemeToggle';
+
+interface AnalyzeResponse {
+ summary: string;
+ findings: string[];
+ charts: any[];
+ recommendations: string[];
+}
+
+interface ChatTurn {
+ id: string;
+ query: string;
+ response: AnalyzeResponse | null;
+ loading: boolean;
+ error: string | null;
+}
+
+function App() {
+ const [sessionId, setSessionId] = useState(null);
+ const [turns, setTurns] = useState([]);
+ const chatEndRef = useRef(null);
+
+ const handleUploadComplete = (id: string) => {
+ setSessionId(id);
+ setTurns([]);
+ };
+
+ const handleExit = () => {
+ setSessionId(null);
+ setTurns([]);
+ };
+
+ const scrollToBottom = () => {
+ chatEndRef.current?.scrollIntoView({ behavior: 'smooth' });
+ };
+
+ useEffect(() => {
+ scrollToBottom();
+ }, [turns]);
+
+ const handleAnalyze = async (query: string) => {
+ if (!sessionId || !query.trim()) return;
+
+ const turnId = Math.random().toString(36).substring(7);
+ const newTurn: ChatTurn = { id: turnId, query, response: null, loading: true, error: null };
+
+ setTurns(prev => [...prev, newTurn]);
+
+ try {
+ const response = await fetch('/api/analyze', {
+ method: 'POST',
+ headers: {
+ 'Content-Type': 'application/json'
+ },
+ body: JSON.stringify({ session_id: sessionId, query })
+ });
+
+ const result = await response.json();
+
+ if (!response.ok) {
+ throw new Error(result.detail || 'Analysis failed');
+ }
+
+ setTurns(prev => prev.map(t => t.id === turnId ? { ...t, loading: false, response: result } : t));
+ } catch (err: any) {
+ setTurns(prev => prev.map(t => t.id === turnId ? { ...t, loading: false, error: err.message } : t));
+ }
+ };
+
+ return (
+
+
+
+
+
+
Crime Statistics Analysis
+
AI-Powered Detectives Dashboard
+
+ {sessionId && (
+
+ )}
+
+
+
+
+ {!sessionId ? (
+
+ ) : (
+
+
+ {turns.length === 0 && (
+
+
Upload successful. Start asking questions about your crime data!
+
+ )}
+ {turns.map((turn, idx) => (
+
+
+
+
+
A
+
+ {turn.loading ? (
+
Analyzing data...
+ ) : turn.error ? (
+
{turn.error}
+ ) : turn.response ? (
+
+ ) : null}
+
+
+
+ ))}
+
+
+
+
+
+
+
+ )}
+
+
+ );
+}
+
+export default App;
diff --git a/frontend/src/assets/hero.png b/frontend/src/assets/hero.png
new file mode 100644
index 0000000..02251f4
Binary files /dev/null and b/frontend/src/assets/hero.png differ
diff --git a/frontend/src/assets/react.svg b/frontend/src/assets/react.svg
new file mode 100644
index 0000000..6c87de9
--- /dev/null
+++ b/frontend/src/assets/react.svg
@@ -0,0 +1 @@
+
\ No newline at end of file
diff --git a/frontend/src/assets/vite.svg b/frontend/src/assets/vite.svg
new file mode 100644
index 0000000..5101b67
--- /dev/null
+++ b/frontend/src/assets/vite.svg
@@ -0,0 +1 @@
+
diff --git a/frontend/src/components/Dashboard.tsx b/frontend/src/components/Dashboard.tsx
new file mode 100644
index 0000000..d2829df
--- /dev/null
+++ b/frontend/src/components/Dashboard.tsx
@@ -0,0 +1,104 @@
+import { BarChart, Bar, XAxis, YAxis, CartesianGrid, Tooltip, Legend, ResponsiveContainer, LineChart, Line } from 'recharts';
+
+interface DashboardProps {
+ data: {
+ summary: string;
+ findings: string[];
+ charts: any[];
+ recommendations: string[];
+ };
+ isLatest?: boolean;
+}
+
+export default function Dashboard({ data, isLatest = true }: DashboardProps) {
+ // If it's not the latest turn, render a compact version to save space
+ if (!isLatest) {
+ return (
+
+
Summary: {data.summary}
+
See earlier results above. Only the latest dashboard is fully expanded.
+
+ );
+ }
+
+ return (
+
+
+
Executive Summary
+
{data.summary}
+
+
+
+
+
Key Findings
+
+ {data.findings.map((f, i) => (
+ - {f}
+ ))}
+
+
+
+
+
Recommendations
+
+ {data.recommendations.map((r, i) => (
+ - {r}
+ ))}
+
+
+
+
+ {data.charts && data.charts.length > 0 && (
+
+
Visualizations
+
+ {data.charts.map((chart, i) => (
+
+
{chart.title}
+
+
+ {chart.type === 'line' ? (
+ {
+ const point: any = { name: l };
+ chart.datasets.forEach((ds: any) => {
+ point[ds.label] = ds.data[idx];
+ });
+ return point;
+ })}>
+
+
+
+
+
+ {chart.datasets.map((ds: any, dsi: number) => (
+
+ ))}
+
+ ) : (
+ {
+ const point: any = { name: l };
+ chart.datasets.forEach((ds: any) => {
+ point[ds.label] = ds.data[idx];
+ });
+ return point;
+ })}>
+
+
+
+
+
+ {chart.datasets.map((ds: any, dsi: number) => (
+
+ ))}
+
+ )}
+
+
+
+ ))}
+
+
+ )}
+
+ );
+}
diff --git a/frontend/src/components/ThemeToggle.tsx b/frontend/src/components/ThemeToggle.tsx
new file mode 100644
index 0000000..6aa64ed
--- /dev/null
+++ b/frontend/src/components/ThemeToggle.tsx
@@ -0,0 +1,37 @@
+import { useEffect, useState } from 'react';
+
+const ThemeToggle = () => {
+ const [theme, setTheme] = useState(localStorage.getItem('theme') || 'dark');
+
+ useEffect(() => {
+ document.documentElement.setAttribute('data-theme', theme);
+ localStorage.setItem('theme', theme);
+ }, [theme]);
+
+ const toggleTheme = () => {
+ setTheme((prev) => (prev === 'dark' ? 'light' : 'dark'));
+ };
+
+ return (
+
+ );
+};
+
+export default ThemeToggle;
diff --git a/frontend/src/components/Upload.tsx b/frontend/src/components/Upload.tsx
new file mode 100644
index 0000000..ab21abe
--- /dev/null
+++ b/frontend/src/components/Upload.tsx
@@ -0,0 +1,102 @@
+import { useState, useRef } from 'react';
+
+export default function Upload({ onUploadComplete }: { onUploadComplete: (id: string) => void }) {
+ const [isDragging, setIsDragging] = useState(false);
+ const [files, setFiles] = useState([]);
+ const [uploading, setUploading] = useState(false);
+ const [error, setError] = useState(null);
+ const fileInputRef = useRef(null);
+
+ const handleFileChange = (e: React.ChangeEvent) => {
+ if (e.target.files) {
+ validateAndSetFiles(Array.from(e.target.files));
+ }
+ };
+
+ const handleDrop = (e: React.DragEvent) => {
+ e.preventDefault();
+ setIsDragging(false);
+ if (e.dataTransfer.files) {
+ validateAndSetFiles(Array.from(e.dataTransfer.files));
+ }
+ };
+
+ const validateAndSetFiles = (newFiles: File[]) => {
+ const totalSize = newFiles.reduce((acc, file) => acc + file.size, 0);
+ if (totalSize > 4.5 * 1024 * 1024) {
+ setError("Total file size exceeds the 4.5MB Vercel serverless payload limit. Please upload smaller CSVs.");
+ setFiles([]);
+ } else {
+ setError(null);
+ setFiles(newFiles);
+ }
+ };
+
+ const handleUpload = async () => {
+ if (files.length === 0) return;
+ setUploading(true);
+ setError(null);
+
+ const formData = new FormData();
+ files.forEach(file => {
+ formData.append('files', file);
+ });
+
+ try {
+ const response = await fetch('/api/upload', {
+ method: 'POST',
+ body: formData,
+ });
+ const data = await response.json();
+
+ if (!response.ok) {
+ throw new Error(data.detail || 'Upload failed');
+ }
+
+ onUploadComplete(data.session_id);
+ } catch (err: any) {
+ setError(err.message);
+ } finally {
+ setUploading(false);
+ }
+ };
+
+ return (
+
+
Upload Crime CSV Data
+
{ e.preventDefault(); setIsDragging(true); }}
+ onDragLeave={() => setIsDragging(false)}
+ onDrop={handleDrop}
+ onClick={() => fileInputRef.current?.click()}
+ >
+
Drag & Drop multiple CSV files here, or click to browse
+
+
+
+ {files.length > 0 && (
+
+
Selected Files:
+
+ {files.map(f => (
+ - {f.name} ({(f.size / 1024 / 1024).toFixed(2)} MB)
+ ))}
+
+
+
+ )}
+
+ {error &&
{error}
}
+
+ );
+}
diff --git a/frontend/src/index.css b/frontend/src/index.css
new file mode 100644
index 0000000..7c92acf
--- /dev/null
+++ b/frontend/src/index.css
@@ -0,0 +1,328 @@
+:root {
+ --bg-dark: #0f172a;
+ --bg-card: #1e293b;
+ --bg-chat-user: #334155;
+ --text-main: #f8fafc;
+ --text-muted: #94a3b8;
+ --accent: #3b82f6;
+ --accent-hover: #2563eb;
+ --border: #334155;
+ --error: #ef4444;
+}
+
+[data-theme='light'] {
+ --bg-dark: #f8fafc;
+ --bg-card: #ffffff;
+ --bg-chat-user: #e2e8f0;
+ --text-main: #0f172a;
+ --text-muted: #64748b;
+ --accent: #2563eb;
+ --accent-hover: #1d4ed8;
+ --border: #cbd5e1;
+ --error: #dc2626;
+}
+
+body {
+ margin: 0;
+ font-family: 'Inter', -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Helvetica, Arial, sans-serif;
+ background-color: var(--bg-dark);
+ color: var(--text-main);
+}
+
+.app-container {
+ width: 100%;
+ max-width: 120rem;
+ margin: 0 auto;
+ padding: 2vh 2vw;
+ height: 100vh;
+ display: flex;
+ flex-direction: column;
+ box-sizing: border-box;
+}
+
+.app-header {
+ margin-bottom: 1rem;
+}
+
+.header-content {
+ display: flex;
+ justify-content: space-between;
+ align-items: center;
+ flex-wrap: wrap;
+ gap: 1rem;
+}
+
+.exit-btn {
+ background-color: var(--error);
+ width: auto;
+ margin-top: 0;
+}
+.exit-btn:hover {
+ background-color: #b91c1c;
+}
+
+.app-header h1 {
+ font-size: 2.2rem;
+ margin-bottom: 0.2rem;
+ margin-top: 0;
+ color: var(--text-main);
+}
+
+.app-header p {
+ color: var(--text-muted);
+ font-size: 1rem;
+ margin-top: 0;
+}
+
+.app-main {
+ flex-grow: 1;
+ display: flex;
+ flex-direction: column;
+ overflow: hidden;
+}
+
+.card {
+ background-color: var(--bg-card);
+ border: 1px solid var(--border);
+ border-radius: 12px;
+ padding: 1.5rem;
+ box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1);
+}
+
+.upload-container {
+ max-width: 600px;
+ margin: 2rem auto;
+ text-align: center;
+}
+
+.drop-zone {
+ border: 2px dashed var(--border);
+ border-radius: 12px;
+ padding: 3rem 2rem;
+ cursor: pointer;
+ transition: all 0.2s ease;
+ background: rgba(30, 41, 59, 0.5);
+ margin-bottom: 2rem;
+}
+
+.drop-zone:hover, .drop-zone.dragging {
+ border-color: var(--accent);
+ background: rgba(59, 130, 246, 0.1);
+}
+
+.hidden-input {
+ display: none;
+}
+
+.file-list {
+ text-align: left;
+ margin-top: 2rem;
+ background: var(--bg-card);
+ padding: 1.5rem;
+ border-radius: 8px;
+}
+
+.file-list ul {
+ list-style: none;
+ padding: 0;
+}
+
+.file-list li {
+ padding: 0.5rem 0;
+ border-bottom: 1px solid var(--border);
+ color: var(--text-muted);
+}
+
+button {
+ background-color: var(--accent);
+ color: white;
+ border: none;
+ padding: 0.75rem 1.5rem;
+ border-radius: 6px;
+ font-weight: 600;
+ cursor: pointer;
+ transition: background-color 0.2s;
+ width: 100%;
+ margin-top: 1rem;
+}
+
+button:hover:not(:disabled) {
+ background-color: var(--accent-hover);
+}
+
+button:disabled {
+ opacity: 0.7;
+ cursor: not-allowed;
+}
+
+/* Chat Interface */
+.chat-interface {
+ display: flex;
+ flex-direction: column;
+ height: 100%;
+ overflow: hidden;
+}
+
+.chat-history {
+ flex-grow: 1;
+ overflow-y: auto;
+ padding: 1rem 0;
+ display: flex;
+ flex-direction: column;
+ gap: 1.5rem;
+ margin-bottom: 1rem;
+ scrollbar-width: thin;
+}
+
+.empty-chat {
+ text-align: center;
+ color: var(--text-muted);
+ margin-top: 2rem;
+}
+
+.chat-turn {
+ display: flex;
+ flex-direction: column;
+ gap: 1rem;
+}
+
+.user-message, .ai-message {
+ display: flex;
+ gap: 1rem;
+ align-items: flex-start;
+}
+
+.user-message .message-content {
+ background-color: var(--bg-chat-user);
+ padding: 1rem;
+ border-radius: 8px;
+ width: fit-content;
+ max-width: 80%;
+}
+
+.ai-message .message-content {
+ flex-grow: 1;
+ width: 100%;
+}
+
+.avatar {
+ width: 40px;
+ height: 40px;
+ border-radius: 50%;
+ display: flex;
+ align-items: center;
+ justify-content: center;
+ font-weight: bold;
+ flex-shrink: 0;
+}
+
+.user-avatar {
+ background-color: var(--text-muted);
+ color: var(--bg-dark);
+}
+
+.ai-avatar {
+ background-color: var(--accent);
+ color: white;
+}
+
+.sticky-query {
+ background: var(--bg-card);
+ padding: 1rem;
+ border-radius: 12px;
+ border: 1px solid var(--border);
+ box-shadow: 0 -4px 10px rgba(0, 0, 0, 0.2);
+}
+
+.sticky-query form {
+ display: flex;
+ flex-direction: column;
+ gap: 0.5rem;
+}
+
+.sticky-query textarea {
+ width: 100%;
+ background: var(--bg-dark);
+ border: 1px solid var(--border);
+ color: var(--text-main);
+ padding: 1rem;
+ border-radius: 8px;
+ font-size: 1rem;
+ resize: none;
+ box-sizing: border-box;
+}
+
+.sticky-query textarea:focus {
+ outline: none;
+ border-color: var(--accent);
+}
+
+.sticky-query button {
+ margin-top: 0;
+ align-self: flex-end;
+ width: auto;
+}
+
+.loading-indicator {
+ padding: 1rem;
+ color: var(--text-muted);
+ font-style: italic;
+}
+
+/* Dashboard inner styles */
+.dashboard-container {
+ display: flex;
+ flex-direction: column;
+ gap: 1.5rem;
+ background-color: var(--bg-card);
+ border: 1px solid var(--border);
+ border-radius: 12px;
+ padding: 1.5rem;
+}
+
+.dashboard-container.compact {
+ padding: 1rem;
+ background-color: transparent;
+ border-color: rgba(51, 65, 85, 0.5);
+}
+
+.hint {
+ font-size: 0.85rem;
+ color: var(--text-muted);
+ font-style: italic;
+ margin-top: 0.5rem;
+}
+
+.dashboard-grid {
+ display: grid;
+ grid-template-columns: repeat(auto-fit, minmax(min(100%, 300px), 1fr));
+ gap: 1.5rem;
+}
+
+.charts-grid {
+ display: grid;
+ grid-template-columns: repeat(auto-fit, minmax(min(100%, 400px), 1fr));
+ gap: 1.5rem;
+}
+
+.error-message {
+ background-color: rgba(239, 68, 68, 0.1);
+ color: var(--error);
+ padding: 1rem;
+ border-radius: 8px;
+ border: 1px solid rgba(239, 68, 68, 0.2);
+}
+
+.summary-card h3, .findings-card h3, .recs-card h3, .chart-card h4 {
+ margin-top: 0;
+ color: var(--accent);
+}
+
+ul {
+ padding-left: 1.2rem;
+ color: var(--text-muted);
+}
+
+li {
+ margin-bottom: 0.5rem;
+}
diff --git a/frontend/src/main.tsx b/frontend/src/main.tsx
new file mode 100644
index 0000000..bef5202
--- /dev/null
+++ b/frontend/src/main.tsx
@@ -0,0 +1,10 @@
+import { StrictMode } from 'react'
+import { createRoot } from 'react-dom/client'
+import './index.css'
+import App from './App.tsx'
+
+createRoot(document.getElementById('root')!).render(
+
+
+ ,
+)
diff --git a/frontend/tsconfig.app.json b/frontend/tsconfig.app.json
new file mode 100644
index 0000000..6830b6f
--- /dev/null
+++ b/frontend/tsconfig.app.json
@@ -0,0 +1,26 @@
+{
+ "compilerOptions": {
+ "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.app.tsbuildinfo",
+ "target": "es2023",
+ "lib": ["ES2023", "DOM"],
+ "module": "esnext",
+ "types": ["vite/client"],
+ "allowArbitraryExtensions": true,
+ "skipLibCheck": true,
+
+ /* Bundler mode */
+ "moduleResolution": "bundler",
+ "allowImportingTsExtensions": true,
+ "verbatimModuleSyntax": true,
+ "moduleDetection": "force",
+ "noEmit": true,
+ "jsx": "react-jsx",
+
+ /* Linting */
+ "noUnusedLocals": true,
+ "noUnusedParameters": true,
+ "erasableSyntaxOnly": true,
+ "noFallthroughCasesInSwitch": true
+ },
+ "include": ["src"]
+}
diff --git a/frontend/tsconfig.json b/frontend/tsconfig.json
new file mode 100644
index 0000000..1ffef60
--- /dev/null
+++ b/frontend/tsconfig.json
@@ -0,0 +1,7 @@
+{
+ "files": [],
+ "references": [
+ { "path": "./tsconfig.app.json" },
+ { "path": "./tsconfig.node.json" }
+ ]
+}
diff --git a/frontend/tsconfig.node.json b/frontend/tsconfig.node.json
new file mode 100644
index 0000000..8455dcb
--- /dev/null
+++ b/frontend/tsconfig.node.json
@@ -0,0 +1,23 @@
+{
+ "compilerOptions": {
+ "tsBuildInfoFile": "./node_modules/.tmp/tsconfig.node.tsbuildinfo",
+ "target": "es2023",
+ "lib": ["ES2023"],
+ "types": ["node"],
+ "skipLibCheck": true,
+
+ /* Bundler mode */
+ "module": "nodenext",
+ "allowImportingTsExtensions": true,
+ "verbatimModuleSyntax": true,
+ "moduleDetection": "force",
+ "noEmit": true,
+
+ /* Linting */
+ "noUnusedLocals": true,
+ "noUnusedParameters": true,
+ "erasableSyntaxOnly": true,
+ "noFallthroughCasesInSwitch": true
+ },
+ "include": ["vite.config.ts"]
+}
diff --git a/frontend/vite.config.ts b/frontend/vite.config.ts
new file mode 100644
index 0000000..dea716b
--- /dev/null
+++ b/frontend/vite.config.ts
@@ -0,0 +1,15 @@
+import { defineConfig } from 'vite'
+import react from '@vitejs/plugin-react'
+
+// https://vite.dev/config/
+export default defineConfig({
+ plugins: [react()],
+ server: {
+ proxy: {
+ '/api': {
+ target: 'http://localhost:8002',
+ changeOrigin: true
+ }
+ }
+ }
+})
diff --git a/pyproject.toml b/pyproject.toml
index 10c0d05..79bcb24 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -14,6 +14,9 @@ dependencies = [
"langgraph>=0.2.28",
"httpx>=0.27",
"structlog>=24.1",
+ "pandas>=3.0.3",
+ "python-multipart>=0.0.32",
+ "langgraph-checkpoint-sqlite>=3.1.0",
]
[dependency-groups]
diff --git a/requirements.txt b/requirements.txt
new file mode 100644
index 0000000..ca11302
--- /dev/null
+++ b/requirements.txt
@@ -0,0 +1,185 @@
+# This file was autogenerated by uv via the following command:
+# uv pip compile pyproject.toml -o requirements.txt
+aiosqlite==0.22.1
+ # via langgraph-checkpoint-sqlite
+alembic==1.18.5
+ # via zero-shot-agent (pyproject.toml)
+annotated-doc==0.0.4
+ # via fastapi
+annotated-types==0.7.0
+ # via pydantic
+anyio==4.14.2
+ # via
+ # httpx
+ # langsmith
+ # starlette
+ # watchfiles
+certifi==2026.7.22
+ # via
+ # httpcore
+ # httpx
+ # requests
+charset-normalizer==3.4.9
+ # via requests
+click==8.4.2
+ # via uvicorn
+colorama==0.4.6
+ # via click
+distro==1.9.0
+ # via langsmith
+fastapi==0.139.2
+ # via zero-shot-agent (pyproject.toml)
+greenlet==3.5.4
+ # via sqlalchemy
+h11==0.16.0
+ # via
+ # httpcore
+ # uvicorn
+httpcore==1.0.9
+ # via httpx
+httptools==0.8.0
+ # via uvicorn
+httpx==0.28.1
+ # via
+ # zero-shot-agent (pyproject.toml)
+ # langgraph-sdk
+ # langsmith
+idna==3.18
+ # via
+ # anyio
+ # httpx
+ # requests
+jsonpatch==1.33
+ # via langchain-core
+jsonpointer==3.1.1
+ # via jsonpatch
+langchain-core==1.5.0
+ # via
+ # langgraph
+ # langgraph-checkpoint
+ # langgraph-prebuilt
+ # langgraph-sdk
+langchain-protocol==0.0.18
+ # via
+ # langchain-core
+ # langgraph-sdk
+langgraph==1.2.9
+ # via zero-shot-agent (pyproject.toml)
+langgraph-checkpoint==4.1.1
+ # via
+ # langgraph
+ # langgraph-checkpoint-sqlite
+ # langgraph-prebuilt
+langgraph-checkpoint-sqlite==3.1.0
+ # via zero-shot-agent (pyproject.toml)
+langgraph-prebuilt==1.1.0
+ # via langgraph
+langgraph-sdk==0.4.2
+ # via langgraph
+langsmith==0.10.10
+ # via langchain-core
+mako==1.3.12
+ # via alembic
+markupsafe==3.0.3
+ # via mako
+numpy==2.4.6
+ # via pandas
+orjson==3.11.9
+ # via
+ # langgraph-sdk
+ # langsmith
+ormsgpack==1.12.2
+ # via langgraph-checkpoint
+packaging==26.2
+ # via
+ # langchain-core
+ # langsmith
+pandas==3.0.5
+ # via zero-shot-agent (pyproject.toml)
+pydantic==2.13.4
+ # via
+ # zero-shot-agent (pyproject.toml)
+ # fastapi
+ # langchain-core
+ # langgraph
+ # langsmith
+ # pydantic-settings
+pydantic-core==2.46.4
+ # via pydantic
+pydantic-settings==2.14.2
+ # via zero-shot-agent (pyproject.toml)
+python-dateutil==2.9.0.post0
+ # via pandas
+python-dotenv==1.2.2
+ # via
+ # pydantic-settings
+ # uvicorn
+python-multipart==0.0.32
+ # via zero-shot-agent (pyproject.toml)
+pyyaml==6.0.3
+ # via
+ # langchain-core
+ # uvicorn
+requests==2.34.2
+ # via
+ # langsmith
+ # requests-toolbelt
+requests-toolbelt==1.0.0
+ # via langsmith
+six==1.17.0
+ # via python-dateutil
+sniffio==1.3.1
+ # via langsmith
+sqlalchemy==2.0.51
+ # via
+ # zero-shot-agent (pyproject.toml)
+ # alembic
+sqlite-vec==0.1.9
+ # via langgraph-checkpoint-sqlite
+starlette==1.3.1
+ # via fastapi
+structlog==26.1.0
+ # via zero-shot-agent (pyproject.toml)
+tenacity==9.1.4
+ # via langchain-core
+typing-extensions==4.16.0
+ # via
+ # alembic
+ # anyio
+ # fastapi
+ # langchain-core
+ # langchain-protocol
+ # langsmith
+ # pydantic
+ # pydantic-core
+ # sqlalchemy
+ # starlette
+ # typing-inspection
+typing-inspection==0.4.2
+ # via
+ # fastapi
+ # pydantic
+ # pydantic-settings
+tzdata==2026.3
+ # via pandas
+urllib3==2.7.0
+ # via requests
+uuid-utils==0.17.0
+ # via
+ # langchain-core
+ # langsmith
+uvicorn==0.51.0
+ # via zero-shot-agent (pyproject.toml)
+watchfiles==1.2.0
+ # via uvicorn
+websockets==15.0.1
+ # via
+ # langgraph-sdk
+ # langsmith
+ # uvicorn
+xxhash==3.8.1
+ # via
+ # langgraph
+ # langsmith
+zstandard==0.25.0
+ # via langsmith
diff --git a/sample_crime.csv b/sample_crime.csv
new file mode 100644
index 0000000..105d101
--- /dev/null
+++ b/sample_crime.csv
@@ -0,0 +1,6 @@
+District,Crime_Type,Incidents,Date
+District 9,Theft,120,2023-01-01
+District 9,Assault,45,2023-01-02
+District 2,Theft,85,2023-01-01
+District 2,Assault,12,2023-01-02
+District 5,Burglary,60,2023-01-01
diff --git a/spec/agent.md b/spec/agent.md
index 49f33fa..c9febcb 100644
--- a/spec/agent.md
+++ b/spec/agent.md
@@ -1,218 +1,32 @@
-# Agent
+# Agent Graph
-> Required when the project uses an agent framework. Delete this file if your project has no agent framework.
->
-> If your project has no agent framework (e.g., a simple script or single-LLM API call), delete this file.
->
+## Pattern: ReAct / Plan-and-Execute
----
+The agent operates on a ReAct (Reason + Act) loop augmented for data analysis.
-## Agent Architecture Pattern
+## State
+The graph state (`GraphState`) includes:
+- `session_id`: Current session identifier.
+- `chat_history`: Conversation history.
+- `user_query`: The latest query.
+- `csv_schemas`: Extracted column info.
+- `intermediate_results`: Data aggregation results.
+- `final_response`: The structured dashboard payload.
-
+## Nodes
-| Pattern | Use when |
-|---------|----------|
-| **Single-agent loop** | One LLM drives a deterministic tool-call loop. No branches, no handoffs. |
-| **Graph (LangGraph)** | Multi-step pipeline with conditional edges, checkpointing, or parallel nodes. |
-| **Multi-agent** | Specialised sub-agents with distinct roles; orchestrator routes between them. |
-| **Supervisor** | One supervisor LLM dispatches to worker agents based on task type. |
-| **Human-in-the-loop** | Execution pauses at defined checkpoints for user review or approval. |
+1. **`parse_intent`**: LLM interprets the user query against the `csv_schemas`. It decides what aggregations/group-bys are needed.
+2. **`execute_pandas`**: (Tool Node) A controlled execution environment where `pandas` operations are run on the uploaded CSV data based on the LLM's instructions.
+3. **`synthesize_dashboard`**: LLM takes the raw `intermediate_results` and formats them into a structured JSON response (Summary, Findings, Charts Data, Recommendations).
-**Chosen:**
+## Edges
+- Entry -> `parse_intent`
+- `parse_intent` -> `execute_pandas` (if data fetch is needed)
+- `execute_pandas` -> `synthesize_dashboard`
+- `synthesize_dashboard` -> END
----
+## Error Handling
+If `execute_pandas` fails (e.g., column not found), it returns the error back to `parse_intent` to retry up to 2 times before falling back to a graceful error message in `synthesize_dashboard`.
-## LLM Provider & Model
-
-
-
-| Agent / Node | Provider | Model ID | Rationale |
-|-------------|----------|----------|-----------|
-| | Anthropic | | |
-
-**Fallback behaviour:**
-
-**Prompt strategy:**
-
----
-
-## Tools & Tool Calling
-
-
-
-| Tool name | Description | Inputs | Output | Side-effects |
-|-----------|-------------|--------|--------|--------------|
-| | | | | |
-
-**Tool selection strategy:**
-
-**Tool failure handling:**
-
----
-
-## Agent State
-
-
-
-```python
-class AgentState(TypedDict):
- # Identity
- run_id: int # set at initialisation
-
- # Input
- # ... # fields populated from the trigger
-
- # Pipeline data (populated progressively by nodes)
- # ...
-
- # Output
- # ... # final result fields
-
- # Control
- error: str | None # set by any node on fatal failure
- checkpoint: str | None # last completed node (for resume)
-```
-
----
-
-## Nodes / Steps
-
-
-
-### `node_[name]`
-
-**Reads from state:**
-
-**Writes to state:**
-
-**LLM call:**
-
-**External calls:**
-
-| System | Operation | On Failure |
-|--------|-----------|------------|
-| | | |
-
-**Behaviour:**
-
----
-
-## Graph / Flow Topology
-
-
-
-```
-START
- │
- ▼
-node_a ──(error)──► node_handle_error ──► END
- │
- ▼
-node_b ──(condition)──► node_c
- │ │
- │ ▼
- └──────────────────► node_finalize
- │
- ▼
- END
-```
-
-**Conditional edges:**
-
-| Source node | Condition | Target |
-|-------------|-----------|--------|
-| | | |
-
----
-
-## Memory & Context
-
-
-
-| Scope | Mechanism | What is stored |
-|-------|-----------|----------------|
-| **Within a run** | LangGraph state | All in-progress data |
-| **Across runs** | | |
-| **Conversation** | | |
-
-**Context window management:**
-
----
-
-## Human-in-the-Loop Checkpoints
-
-
-
-| Checkpoint | What is shown to the user | Expected user action | Timeout / default |
-|------------|--------------------------|----------------------|-------------------|
-| | | | |
-
----
-
-## Error Handling & Recovery
-
-
-
-**Node-level:**
-
-**Graph-level (handle_error node):**
-- Reads: `state.error`, `state.run_id`
-- Updates DB: run status → "failed", `error_message`, `completed_at`
-- Logs error with `run_id` context
-- Terminates graph
-
-**Resume / retry strategy:**
-
-**Partial failure:**
-
----
-
-## Observability
-
-
-
-| Signal | What | Where |
-|--------|------|-------|
-| **Trace** | One trace per run, one span per node | |
-| **LLM calls** | Prompt tokens, completion tokens, latency, model | |
-| **Tool calls** | Tool name, inputs, success/error, latency | Structured log |
-| **Run outcome** | Status, total duration, error if any | DB + structured log |
-
----
-
-## Concurrency Model
-
-
-
-- **Run isolation:**
-- **Parallel nodes within a run:**
-- **Checkpointing:**
-
----
-
-## Graph Assembly (`agent/graph.py`)
-
-
-
-```python
-graph = StateGraph(AgentState)
-
-graph.add_node("node_a", node_a)
-graph.add_node("node_b", node_b)
-graph.add_node("finalize", node_finalize)
-graph.add_node("handle_error", node_handle_error)
-
-graph.set_entry_point("node_a")
-
-graph.add_conditional_edges(
- "node_a",
- lambda s: "handle_error" if s.get("error") else "node_b",
-)
-
-graph.add_edge("node_b", "finalize")
-graph.add_edge("finalize", END)
-graph.add_edge("handle_error", END)
-
-compiled_graph = graph.compile()
-```
+## Concurrency
+Isolated by `session_id`. Each request processes its own in-memory data copies.
diff --git a/spec/api.md b/spec/api.md
index 442a58b..900466e 100644
--- a/spec/api.md
+++ b/spec/api.md
@@ -1,41 +1,48 @@
-# API
+# API Contract
-> Fill in this section — see comments below.
-
----
-
-## API Style
-
-
-
-## Endpoints / Commands
-
-
-
-### ``
-
-**Purpose:**
+## POST /upload
+**Request:** `multipart/form-data` with multiple `file` fields (CSVs).
+**Response:**
+```json
+{
+ "session_id": "uuid",
+ "files_processed": 2,
+ "schemas": {
+ "file1.csv": ["Date", "Crime_Type", "District"],
+ "file2.csv": ["District", "Officer_Count"]
+ }
+}
+```
+## POST /analyze
**Request:**
```json
{
- "": ""
+ "session_id": "uuid",
+ "query": "Which district has the highest crime rate?"
}
```
-
**Response:**
```json
{
- "": ""
+ "summary": "District 9 has the highest crime rate, primarily driven by property crimes.",
+ "findings": ["District 9 accounts for 24% of all incidents.", "Theft is up 12% YoY."],
+ "charts": [
+ {
+ "type": "bar",
+ "title": "Crime by District",
+ "labels": ["Dist 9", "Dist 2"],
+ "datasets": [{"label": "Total Incidents", "data": [1400, 800]}]
+ }
+ ],
+ "recommendations": ["Reallocate patrol units to District 9 between 8 PM and 2 AM."]
}
```
-**Error cases:**
-| Status | Condition |
-|--------|-----------|
-| 400 | |
-| 500 | |
-
-## Authentication
-
-
+## GET /health
+**Response:**
+```json
+{
+ "status": "ok"
+}
+```
diff --git a/spec/architecture.md b/spec/architecture.md
index e5e3bd9..d8799cd 100644
--- a/spec/architecture.md
+++ b/spec/architecture.md
@@ -1,68 +1,34 @@
# Architecture
-> Fill in this section — see comments below.
-
----
-
## System Overview
-
-
-## Component Map
-
-
-
-```
-[Component A]
- ↓
-[Component B] ←→ [External Service]
- ↓
-[Component C]
-```
-
-## Layers
-
-
-
-| Layer | Responsibility |
-|-------|----------------|
-| | |
-
-## Data Flow
-
-
-
-1. Trigger:
-2.
-3.
-4. Output:
-
-## External Dependencies
-
-
-
-| Dependency | Purpose | Failure Mode |
-|------------|---------|--------------|
-| | | |
+The Crime Statistics Analysis Agent is a full-stack application built around a specialized data-analysis agent graph.
## Stack
-> This project's concrete technology choices (captured at intake, filled by the spec-writer). The generic, every-project rules — model-naming, DB driver, dev port, test environment — live in `harness/patterns/tech-stack.md`; this section is only what **this** project picked.
+- **Backend:** Python 3.11+, FastAPI (REST endpoints), LangGraph (Agent orchestration).
+- **Frontend:** React via Vite with Vanilla CSS (Professional blue/white police dashboard theme).
+- **Data Processing:** `pandas` for fast in-memory CSV operations (merging, cleaning, aggregating).
+- **Database:** SQLite (local metadata, session, and conversation history storage).
+- **LLM:** Gemini 1.5 (via `google-generativeai` or `langchain-google-genai`).
+- **Observability:** `structlog` for structured request/response logging.
-- **Language:**
-- **Agent framework:**
-- **LLM provider + model:**
-- **Backend:**
-- **Database + ORM:**
-- **Frontend:**
-- **Dependency management:**
+## Components & Data Flow
-| Key library | Version | Purpose |
-|-------------|---------|---------|
-| | | |
+1. **Frontend (Vite/React):**
+ - Provides a drag-and-drop interface for CSV uploads.
+ - Posts files to `/upload` API endpoint.
+ - Provides a chat interface to post user queries to `/analyze` endpoint.
+ - Renders structured dashboards (Executive Summary, Findings, Line/Bar Charts) from the API response.
-**Avoid:**
+2. **Backend (FastAPI):**
+ - `/upload` endpoint parses CSVs, stores them temporarily (in-memory or temp disk), and extracts schemas.
+ - `/analyze` endpoint takes a session ID and a user query, invoking the LangGraph agent.
-## Deployment Model
+3. **Agent (LangGraph):**
+ - The graph orchestrates the reasoning.
+ - The agent reads the user's query and the data schemas, determines the necessary Pandas aggregations, and generates Python code to query the data.
+ - It executes the Pandas code safely (or uses predefined aggregation tools) and synthesizes the results into a structured JSON dashboard payload.
-
+4. **Database (SQLite):**
+ - Stores session mappings, conversational history, and pointers to temporary files.
diff --git a/spec/capabilities/analyze_crime_data.md b/spec/capabilities/analyze_crime_data.md
new file mode 100644
index 0000000..ddeb896
--- /dev/null
+++ b/spec/capabilities/analyze_crime_data.md
@@ -0,0 +1,22 @@
+# Capability: Analyze Crime Data
+## What It Does
+Accepts a natural language query regarding uploaded crime CSV datasets and returns a structured analysis including summaries, charts, and recommendations based on Pandas aggregations.
+## Inputs
+| Input | Type | Source | Required |
+|---|---|---|---|
+| session_id | string | API Request | Yes |
+| query | string | API Request | Yes |
+## Outputs
+| Output | Type | Destination |
+|---|---|---|
+| structured_dashboard | JSON | API Response |
+## External Calls
+| System | Operation | On Failure |
+|---|---|---|
+| Gemini LLM | Intent Parsing / Pandas Gen | Retry 2x, then return error message |
+| Gemini LLM | Synthesis | Return raw data error |
+## Business Rules
+- Must dynamically inspect CSV schemas attached to the session.
+- Cannot delete or modify CSV files during analysis (read-only Pandas ops).
+## Success Criteria
+- [ ] Querying "highest crime district" generates Pandas code that groups by district, sorts, and correctly synthesizes the top result.
diff --git a/spec/capabilities/index.md b/spec/capabilities/index.md
index 7455bda..6f07205 100644
--- a/spec/capabilities/index.md
+++ b/spec/capabilities/index.md
@@ -1,38 +1 @@
-# Capabilities Index
-
-> **Boilerplate status:** The spec-writer sub-agent creates one file per capability in this directory. Each file describes exactly one discrete thing the agent can do.
-
----
-
-## What Is a Capability?
-
-A capability is a single, discrete action or behavior the agent performs. Examples:
-- "Search the web for companies matching criteria X"
-- "Draft a personalized email given a lead profile"
-- "Send a Slack notification when a threshold is crossed"
-
-## Capabilities in This Project
-
-
-
-| Capability | File |
-|-----------|------|
-| | [name.md](name.md) |
-
-## How to Add a New Capability
-
-Run `/zero-shot-build [description]` on the existing spec. The spec-writer sub-agent will:
-1. Create a new file in this directory (`.md`, no number prefix)
-2. Update this index
-3. Flag any dependencies on existing capabilities
-4. Self-review that it fits the architecture and data model before returning
-
-## Capability File Template
-
-Each capability file should answer:
-- **What it does** (one sentence)
-- **Inputs** (what data it receives)
-- **Outputs** (what it produces)
-- **External calls** (APIs, LLMs, databases it touches)
-- **Error cases** (what can go wrong and how it's handled)
-- **Success criteria** (how we test it)
+- [Analyze Crime Data](analyze_crime_data.md)
diff --git a/spec/data.md b/spec/data.md
index e331007..e5bea0e 100644
--- a/spec/data.md
+++ b/spec/data.md
@@ -1,34 +1,27 @@
# Data Model
-> Fill in this section — see comments below.
-
----
-
-## Storage Technology
-
-
-
## Entities
-
-
-### Entity:
-
-
-
-| Field | Type | Required | Description |
-|-------|------|----------|-------------|
-| id | | yes | Primary key |
-| | | | |
-
-### Relationships
-
-
-
-## Data Lifecycle
-
-
-
-## Sensitive Data
-
-
+1. **Session**
+ - `session_id` (PK, string, UUID)
+ - `created_at` (datetime)
+ - `last_active_at` (datetime)
+
+2. **FileMetadata**
+ - `id` (PK, integer)
+ - `session_id` (FK -> Session)
+ - `filename` (string)
+ - `columns` (JSON)
+ - `row_count` (integer)
+ - `temp_path` (string)
+
+3. **Message (Chat History)**
+ - `id` (PK, integer)
+ - `session_id` (FK -> Session)
+ - `role` (string: "user", "assistant")
+ - `content` (text)
+ - `created_at` (datetime)
+
+## Lifecycle
+- **Creation**: Sessions are created upon first CSV upload.
+- **Retention**: Data is session-bound. A cleanup cron/job removes sessions and temp CSV files older than 24 hours.
diff --git a/spec/roadmap.md b/spec/roadmap.md
index 03ae242..3eafa54 100644
--- a/spec/roadmap.md
+++ b/spec/roadmap.md
@@ -1,62 +1,72 @@
# Roadmap
-> Fill in each section. Run `/zero-shot-build [your idea]` to have it filled automatically.
-
---
## What This Agent Does
-
+The Crime Statistics Analysis Agent allows detectives and crime analysts to upload multiple CSV datasets, which are automatically merged and schema-mapped. Users can query the agent in natural language to uncover trends, anomalies, and resource allocation recommendations. The agent acts as an AI data analyst, returning a structured dashboard with executive summaries, key findings, and time-series charts.
## Who Uses It
-
+- **Detectives & Crime Analysts:** Investigating long-term trends across districts, correlating different crime types, and planning resource allocation. They need fast, reliable answers backed by data and visual charts without writing SQL or Python code themselves.
## Core Problem Being Solved
-
+Detectives often have disparate CSV reports with differing schemas. Merging these files and writing scripts/SQL to analyze them takes hours or days. This agent replaces the manual data wrangling and charting process, enabling instant natural language exploration of the data.
## Success Criteria
-
-
-- [ ]
-- [ ]
-- [ ]
+- [ ] Users can upload multiple CSV files (up to 100MB total) and the agent successfully merges them in memory.
+- [ ] Users can ask "Compare crime trends year-wise" and receive a structured dashboard with a time-series chart.
+- [ ] The system accurately identifies missing dates/columns and either infers them or gracefully fails.
+- [ ] The agent remembers conversation history within a session for follow-up questions.
## What This Agent Does NOT Do (Out of Scope)
-
+- The agent does not save CSV data permanently (data is session-bound).
+- The agent does not train new ML models (it relies on zero-shot LLM reasoning and Pandas for deterministic calculations).
+- The agent does not connect to live police dispatch databases (batch CSV uploads only).
## Key Constraints
-
+- **Scale:** Supports files up to ~100MB (~100,000 rows), processed in-memory using Pandas.
+- **Privacy:** Data is strictly session-bound and wiped when the session expires or the UI is closed.
+- **Provider:** Must use the Gemini API (via `AGENT_GEMINI_API_KEY`).
## Phases of Development
-
-
-> **Phase 1 is the smallest first-time-right user-testable win.** It must work perfectly the first time the user tests it — zero rough edges on the tested path. Its backend is minimal but REAL on the one core path (no fake data on the tested path). Its frontend is visually complete: real UI for the one working path PLUS clearly-labelled NON-FUNCTIONAL stubs for everything coming later, so the user sees the vision (a stub must never be mistaken for a bug). Each later phase wires those stubs into real functionality, one increment at a time.
+### Phase 1 — End-to-End Single Query on Merged CSVs
-### Phase 1 —
-
-- **Goal:**
-- **Independent slices (parallel build units):**
- - `slice-a` (backend) —
- - `slice-b` (frontend) —
-- **Key surfaces / files:**
-- **Gate command:**
-- **How the user tests it (handoff seed):**
+- **Goal:** Allow the user to upload multiple CSVs (up to 100MB total), which are automatically merged and mapped. The user can ask a single question, and the agent returns a structured dashboard response with summary and time-series line charts.
+- **Independent slices (parallel build units):**
+ - `slice-backend-core` (backend) — API endpoints (`/upload`, `/analyze`, `/health`), CSV merging/mapping logic via pandas, and LangGraph agent setup. deps: none
+ - `slice-frontend-core` (frontend) — React dashboard skeleton (Vite), drag & drop upload component, loading animation, and structured result view. deps: none
+- **Key surfaces / files:**
+ - `slice-backend-core`: `src/api/routes.py`, `src/services/csv_service.py`, `src/graph/nodes.py`, `src/graph/state.py`
+ - `slice-frontend-core`: `frontend/src/App.tsx`, `frontend/src/components/Upload.tsx`, `frontend/src/components/Dashboard.tsx`, `frontend/src/index.css`
+- **Gate command:** `uv run pytest tests/test_phase1.py`
+- **How the user tests it (handoff seed):** Run the backend (`uv run python -m src`) and frontend dev server (`cd frontend && npm run dev`). Open the UI, drag two sample CSVs, and ask "Which district has the most crime?". Expect a dashboard with a summary and a bar chart.
-### Phase 2 —
+### Phase 2 — Multi-Turn Conversational Memory & Advanced Capabilities
-- **Goal:**
+- **Goal:** Introduce session memory so detectives can ask follow-up questions about the data, and add anomaly/hotspot detection capabilities.
- **Independent slices (parallel build units):**
- - `slice-a` (backend) —
- - `slice-b` (frontend) —
-- **Key surfaces / files:**
-- **Gate command:**
-- **How the user tests it (handoff seed):**
+ - `slice-backend-memory` (backend) — SQLite integration for conversational state and session storage. deps: slice-backend-core
+ - `slice-frontend-chat` (frontend) — Interactive chat UI updates to support history and follow-up prompts. deps: slice-frontend-core
+- **Key surfaces / files:**
+ - `slice-backend-memory`: `src/db/database.py`, `src/db/models.py`, `src/graph/memory.py`
+ - `slice-frontend-chat`: `frontend/src/components/Chat.tsx`, `frontend/src/App.tsx`
+- **Gate command:** `uv run pytest tests/test_phase2.py`
+- **How the user tests it (handoff seed):** Ask a follow-up question in the UI: "Drill down into District A". Expect the agent to remember the context of the first query and return specific data for District A.
-
+### Phase 3 — Production Readiness & Polish
+- **Goal:** Dockerization, robust error handling for edge-case files, full test coverage, logging enhancements, and final UI polish (dark/light mode).
+- **Independent slices (parallel build units):**
+ - `slice-ops` (backend) — `Dockerfile`, `docker-compose.yml`, README updates. deps: none
+ - `slice-testing-ui` (frontend) — UI theme toggle, error boundary components. deps: slice-frontend-chat
+- **Key surfaces / files:**
+ - `slice-ops`: `Dockerfile`, `docker-compose.yml`, `README.md`
+ - `slice-testing-ui`: `frontend/src/components/ThemeToggle.tsx`, `frontend/src/index.css`
+- **Gate command:** `uv run pytest tests/test_phase3.py`
+- **How the user tests it (handoff seed):** Toggle dark/light mode. Upload a malformed CSV and verify the error is displayed cleanly.
diff --git a/spec/ui.md b/spec/ui.md
index 15219c3..3741c80 100644
--- a/spec/ui.md
+++ b/spec/ui.md
@@ -1,32 +1,18 @@
-# UI
+# UI Spec
-> **Boilerplate status:** Delete this file if the agent has no UI. Otherwise, filled in by the spec-writer sub-agent.
+## Theme
+Professional police dashboard: blue/white color scheme, modern cards, and clear typography.
----
+## Screens
-## UI Type
+1. **Dashboard / Upload View (Initial State)**
+ - Drag-and-drop zone for CSV files.
+ - List of uploaded files showing row counts and parsed columns.
+ - "Analyze Data" section with a text input area for natural language queries.
-
-
-## Views / Screens
-
-
-
-### Screen:
-
-**Purpose:**
-
-**Key elements:**
--
--
-
-**Actions available:**
--
-
-## Error States
-
-
-
-## Tech Stack
-
-
+2. **Results View (Active State)**
+ - Structured dashboard appears below the query input.
+ - **Executive Summary Card:** High-level AI response.
+ - **Key Findings Card:** Bulleted list of insights.
+ - **Charts Area:** Time-series line chart or bar chart (using a charting library like Chart.js or Recharts).
+ - **Recommendations Card:** Actionable advice based on the data.
diff --git a/src/api/__init__.py b/src/api/__init__.py
index 4ef00c3..184a823 100644
--- a/src/api/__init__.py
+++ b/src/api/__init__.py
@@ -24,10 +24,14 @@ async def _lifespan(app: FastAPI):
def create_app() -> FastAPI:
app = FastAPI(title="Zero-Shot Agent", version="0.1.0", lifespan=_lifespan)
- from src.api import health, runs
-
- app.include_router(health.router)
- app.include_router(runs.router)
+ from src.api import health, upload, analyze
+
+ from fastapi import APIRouter
+ api_router = APIRouter(prefix="/api")
+ api_router.include_router(health.router)
+ api_router.include_router(upload.router)
+ api_router.include_router(analyze.router)
+ app.include_router(api_router)
if _FRONTEND_DIR.is_dir():
app.mount("/app", StaticFiles(directory=_FRONTEND_DIR, html=True), name="frontend")
diff --git a/src/api/analyze.py b/src/api/analyze.py
new file mode 100644
index 0000000..861407f
--- /dev/null
+++ b/src/api/analyze.py
@@ -0,0 +1,53 @@
+from fastapi import APIRouter, HTTPException
+from pydantic import BaseModel
+from typing import List, Dict, Any
+
+from src.graph.agent import agentic_ai
+from src.graph.state import AgentState
+
+router = APIRouter(prefix="/analyze", tags=["analyze"])
+
+class AnalyzeRequest(BaseModel):
+ session_id: str
+ query: str
+
+class ChartData(BaseModel):
+ type: str
+ title: str
+ labels: List[str]
+ datasets: List[Dict[str, Any]]
+
+class AnalyzeResponse(BaseModel):
+ summary: str
+ findings: List[str]
+ charts: List[ChartData]
+ recommendations: List[str]
+
+@router.post("", response_model=AnalyzeResponse)
+async def analyze_query(req: AnalyzeRequest):
+ config = {"configurable": {"thread_id": req.session_id}}
+
+ # Retrieve current state to check if session exists
+ current_state = agentic_ai.get_state(config)
+ if not current_state or not current_state.values.get("csv_schemas"):
+ raise HTTPException(status_code=404, detail="Session not found or expired")
+
+ try:
+ # We only need to provide the updated parts of the state.
+ # The checkpointer restores the rest (schemas, paths, history).
+ final_state = agentic_ai.invoke({"user_query": req.query}, config=config)
+ except Exception as e:
+ raise HTTPException(status_code=500, detail=f"Agent execution failed: {str(e)}")
+
+ if final_state.get("error") and not final_state.get("final_response"):
+ raise HTTPException(status_code=500, detail=final_state["error"])
+
+ response_data = final_state.get("final_response", {})
+
+ # Ensure it matches the schema closely
+ return AnalyzeResponse(
+ summary=response_data.get("summary", "No summary generated."),
+ findings=response_data.get("findings", []),
+ charts=response_data.get("charts", []),
+ recommendations=response_data.get("recommendations", [])
+ )
diff --git a/src/api/upload.py b/src/api/upload.py
new file mode 100644
index 0000000..6e0e57c
--- /dev/null
+++ b/src/api/upload.py
@@ -0,0 +1,72 @@
+import os
+import uuid
+import pandas as pd
+from typing import List
+from fastapi import APIRouter, UploadFile, File, HTTPException
+from pydantic import BaseModel
+from src.graph.agent import agentic_ai
+
+router = APIRouter(prefix="/upload", tags=["upload"])
+
+class UploadResponse(BaseModel):
+ session_id: str
+ files_processed: int
+ schemas: dict[str, list[str]]
+
+@router.post("", response_model=UploadResponse)
+async def upload_files(files: List[UploadFile] = File(...)):
+ if not files:
+ raise HTTPException(status_code=400, detail="No files uploaded")
+
+ session_id = str(uuid.uuid4())
+ schemas = {}
+ temp_paths = {}
+
+ # Ensure temp directory exists
+ temp_dir = os.path.join("data", "temp", session_id)
+ os.makedirs(temp_dir, exist_ok=True)
+
+ MAX_SIZE_BYTES = 4.5 * 1024 * 1024 # 4.5 MB (Vercel limit)
+ total_size = 0
+
+ for file in files:
+ if not file.filename.endswith(".csv"):
+ raise HTTPException(status_code=400, detail=f"File {file.filename} is not a CSV")
+
+ content = await file.read()
+ total_size += len(content)
+ if total_size > MAX_SIZE_BYTES:
+ raise HTTPException(status_code=413, detail="Total file size exceeds the 4.5MB Vercel serverless payload limit.")
+
+ file_path = os.path.join(temp_dir, file.filename)
+ with open(file_path, "wb") as f:
+ f.write(content)
+
+ try:
+ # Fallback encoding to handle malicious/weird CSVs
+ try:
+ df = pd.read_csv(file_path, encoding="utf-8")
+ except UnicodeDecodeError:
+ df = pd.read_csv(file_path, encoding="latin1")
+
+ if df.empty or len(df.columns) == 0:
+ raise ValueError("CSV is empty or has no columns")
+
+ schemas[file.filename] = list(df.columns)
+ temp_paths[file.filename] = file_path
+ except Exception as e:
+ raise HTTPException(status_code=400, detail=f"Failed to parse CSV {file.filename}: {str(e)}")
+
+ # Initialize the LangGraph state for this session
+ config = {"configurable": {"thread_id": session_id}}
+ agentic_ai.update_state(config, {
+ "csv_schemas": schemas,
+ "temp_paths": temp_paths,
+ "chat_history": []
+ })
+
+ return UploadResponse(
+ session_id=session_id,
+ files_processed=len(files),
+ schemas=schemas
+ )
diff --git a/src/config/settings.py b/src/config/settings.py
index 19e5688..25dff01 100644
--- a/src/config/settings.py
+++ b/src/config/settings.py
@@ -12,7 +12,7 @@
# provider docs before pinning — a 404 from the LLM API usually means a stale name.
DEFAULT_MODELS = {
"anthropic": "claude-sonnet-4-6",
- "gemini": "gemini-2.5-flash",
+ "gemini": "gemini-3.5-flash",
"openrouter": "tencent/hy3", # cheap default ($0.14/M in) — frontier models 402 on unfunded keys; override via AGENT_LLM_MODEL
}
diff --git a/src/graph/agent.py b/src/graph/agent.py
index 15adcbb..9856d07 100644
--- a/src/graph/agent.py
+++ b/src/graph/agent.py
@@ -2,26 +2,49 @@
from __future__ import annotations
from langgraph.graph import END, StateGraph
+from langgraph.checkpoint.sqlite import SqliteSaver
-from src.graph.edges import after_transform
-from src.graph.nodes import finalize, handle_error, transform_text
+from src.graph.edges import after_parse, after_execute
+from src.graph.nodes import parse_intent, execute_pandas, synthesize_dashboard, handle_error, finalize
from src.graph.state import AgentState
-
+from src.config.settings import get_settings
def _build_graph():
g = StateGraph(AgentState)
- g.add_node("transform_text", transform_text)
+ g.add_node("parse_intent", parse_intent)
+ g.add_node("execute_pandas", execute_pandas)
+ g.add_node("synthesize_dashboard", synthesize_dashboard)
g.add_node("handle_error", handle_error)
g.add_node("finalize", finalize)
- g.set_entry_point("transform_text")
+
+ g.set_entry_point("parse_intent")
+
+ g.add_conditional_edges(
+ "parse_intent",
+ after_parse,
+ {"execute_pandas": "execute_pandas", "handle_error": "handle_error"},
+ )
+
g.add_conditional_edges(
- "transform_text",
- after_transform,
- {"finalize": "finalize", "handle_error": "handle_error"},
+ "execute_pandas",
+ after_execute,
+ {"synthesize_dashboard": "synthesize_dashboard", "handle_error": "handle_error"},
)
+
+ g.add_edge("synthesize_dashboard", "finalize")
g.add_edge("finalize", END)
g.add_edge("handle_error", END)
- return g.compile()
+
+ # Configure SqliteSaver
+ db_url = get_settings().database_url
+ # e.g., sqlite:///./data/app.db
+ db_path = db_url.replace("sqlite:///", "")
+ import sqlite3
+ conn = sqlite3.connect(db_path, check_same_thread=False)
+ memory = SqliteSaver(conn)
+ memory.setup()
+
+ return g.compile(checkpointer=memory)
agentic_ai = _build_graph()
diff --git a/src/graph/edges.py b/src/graph/edges.py
index db53f87..e1455cb 100644
--- a/src/graph/edges.py
+++ b/src/graph/edges.py
@@ -1,10 +1,18 @@
-"""Conditional routing functions."""
+"""Edge functions for routing."""
from __future__ import annotations
from src.graph.state import AgentState
-def after_transform(state: AgentState) -> str:
+def after_parse(state: AgentState) -> str:
+ """Routes after parse_intent."""
if state.get("error"):
return "handle_error"
- return "finalize"
+ return "execute_pandas"
+
+
+def after_execute(state: AgentState) -> str:
+ """Routes after execute_pandas."""
+ if state.get("error"):
+ return "handle_error"
+ return "synthesize_dashboard"
diff --git a/src/graph/nodes.py b/src/graph/nodes.py
index 36e760b..f431974 100644
--- a/src/graph/nodes.py
+++ b/src/graph/nodes.py
@@ -1,36 +1,65 @@
-"""Graph nodes — THE CAPABILITY SLOT.
-
-``transform_text`` is the baseline capability: it applies the user's
-instruction to the input text with one batched LLM call. When building your
-agent, replace this node (and src/prompts/transform.md, and the frontend form)
-with your capability — the graph wiring, API, and DB stay as they are.
-
-Node contract: ``(state) -> partial state``; put failures in ``error`` so the
-error edge routes to handle_error — never raise through the graph.
-"""
+"""Graph nodes for Crime Statistics Analysis Agent."""
from __future__ import annotations
+import json
+import ast
+import pandas as pd
+from typing import Any
+
from src.graph.state import AgentState
-from src.llm.client import LLMClient, load_prompt
+from src.llm.client import LLMClient
from src.llm.providers.base import LLMError
-def transform_text(state: AgentState) -> AgentState:
- """Apply the instruction to the input text — ONE batched LLM call.
-
- Never loop an LLM call per output line/token: generate the whole artifact
- in one call and split downstream if needed (cost blows up otherwise).
- """
+def parse_intent(state: AgentState) -> AgentState:
+ """LLM interprets the query and generates pandas code to extract insights."""
try:
client = LLMClient()
- system = load_prompt("transform")
- user = (
- f"INSTRUCTION:\n{state['instruction']}\n\n"
- f"TEXT:\n{state['input_text']}"
+ system = (
+ "You are a Python Data Analyst. You have a dictionary of pandas DataFrames called `dfs`.\n"
+ "The keys are the filenames, and the values are the DataFrames.\n"
+ "You must write a valid Python script that analyzes the data to answer the user query.\n"
+ "Assign the final findings (a dictionary, string, or list) to a variable called `result`.\n"
+ "If the user is asking a follow-up question, use the chat history to understand the context.\n"
+ "Generate ONLY valid, syntactically correct Python. Properly escape all quotes and string literals regardless of the input language (e.g. Hindi, Hinglish).\n"
+ "Never leave a string unterminated.\n"
+ "DO NOT wrap your python code in markdown formatting like ```python, just output raw python code."
+ )
+
+ history_str = json.dumps(state.get("chat_history", [])[-4:], indent=2)
+ user_prompt = (
+ f"Chat History Context:\n{history_str}\n\n"
+ f"New Query: {state['user_query']}\n"
+ f"Schemas: {json.dumps(state['csv_schemas'], indent=2)}\n"
)
- output = client.complete(system, user, max_tokens=2048)
+
+ code = ""
+ syntax_error = None
+ for attempt in range(2):
+ if attempt == 1:
+ user_prompt += f"\nYour previous code had this syntax error: {syntax_error}. Fix it."
+
+ code = client.complete(system, user_prompt, max_tokens=1024).strip()
+ if code.startswith("```python"):
+ code = code[9:]
+ if code.startswith("```"):
+ code = code[3:]
+ if code.endswith("```"):
+ code = code[:-3]
+ code = code.strip()
+
+ try:
+ ast.parse(code)
+ syntax_error = None
+ break
+ except SyntaxError as e:
+ syntax_error = str(e)
+
+ if syntax_error:
+ return {"error": "I encountered an error generating the data analysis code. Please rephrase your query."}
+
return {
- "output_text": output,
+ "intermediate_results": {"code": code},
"provider": client.provider_name,
"model": client.model,
"error": None,
@@ -39,9 +68,100 @@ def transform_text(state: AgentState) -> AgentState:
return {"error": str(exc)}
+def execute_pandas(state: AgentState) -> AgentState:
+ """Executes the generated pandas code."""
+ if state.get("error"):
+ return state
+
+ code = state["intermediate_results"]["code"]
+ temp_paths = state["temp_paths"]
+
+ # Load dataframes
+ dfs = {fname: pd.read_csv(path) for fname, path in temp_paths.items()}
+
+ local_vars: dict[str, Any] = {"dfs": dfs, "pd": pd, "result": None}
+
+ try:
+ exec(code, {}, local_vars)
+ result = local_vars.get("result")
+
+ # Convert non-serializable pandas objects to basic python types
+ if isinstance(result, (pd.DataFrame, pd.Series)):
+ result = result.to_dict()
+
+ return {
+ "intermediate_results": {"code": code, "data": result},
+ "error": None
+ }
+ except Exception as exc:
+ return {"error": f"Pandas execution failed: {str(exc)}"}
+
+
+def synthesize_dashboard(state: AgentState) -> AgentState:
+ """Takes the raw data and creates a structured dashboard JSON."""
+ if state.get("error"):
+ # Fallback error response
+ return {
+ "final_response": {
+ "summary": "An error occurred during analysis.",
+ "findings": [state["error"]],
+ "charts": [],
+ "recommendations": []
+ }
+ }
+
+ try:
+ client = LLMClient()
+ system = (
+ "You are a Crime Analyst. Based on the user's query and the data results, "
+ "synthesize a JSON dashboard payload with the following strict structure:\n"
+ "{\n"
+ " \"summary\": \"Executive summary text\",\n"
+ " \"findings\": [\"insight 1\", \"insight 2\"],\n"
+ " \"charts\": [ { \"type\": \"bar\", \"title\": \"...\", \"labels\": [\"A\", \"B\"], \"datasets\": [{ \"label\": \"...\", \"data\": [1, 2] }] } ],\n"
+ " \"recommendations\": [\"action 1\"]\n"
+ "}\n"
+ "Identify the language of the user's query (e.g., Hindi, Hinglish, English). "
+ "You MUST generate the summary, findings, and recommendations in that exact same language.\n"
+ "Output RAW JSON ONLY. No markdown."
+ )
+
+ history_str = json.dumps(state.get("chat_history", [])[-4:], indent=2)
+ user = (
+ f"Chat History Context:\n{history_str}\n\n"
+ f"Query: {state['user_query']}\n"
+ f"Data Results: {json.dumps(state['intermediate_results'].get('data', ''))}"
+ )
+ raw_json = client.complete(system, user, max_tokens=2048).strip()
+ if raw_json.startswith("```json"):
+ raw_json = raw_json[7:]
+ if raw_json.endswith("```"):
+ raw_json = raw_json[:-3]
+
+ payload = json.loads(raw_json)
+
+ new_history = [
+ {"role": "user", "content": state["user_query"]},
+ {"role": "assistant", "content": payload["summary"]}
+ ]
+
+ return {
+ "final_response": payload,
+ "chat_history": new_history,
+ "status": "completed"
+ }
+ except Exception as exc:
+ return {
+ "final_response": {
+ "summary": "Failed to synthesize JSON dashboard.",
+ "findings": [str(exc)],
+ "charts": [],
+ "recommendations": []
+ }
+ }
+
def handle_error(state: AgentState) -> AgentState:
return {"status": "failed"}
-
def finalize(state: AgentState) -> AgentState:
return {"status": "completed"}
diff --git a/src/graph/state.py b/src/graph/state.py
index 6720d27..e64b080 100644
--- a/src/graph/state.py
+++ b/src/graph/state.py
@@ -1,14 +1,18 @@
"""AgentState — the TypedDict flowing through the graph."""
from __future__ import annotations
-from typing import TypedDict
-
+import operator
+from typing import TypedDict, Any, Annotated
class AgentState(TypedDict, total=False):
run_id: str
- input_text: str
- instruction: str
- output_text: str
+ session_id: str
+ user_query: str
+ chat_history: Annotated[list[dict[str, Any]], operator.add]
+ csv_schemas: dict[str, list[str]]
+ temp_paths: dict[str, str]
+ intermediate_results: dict[str, Any]
+ final_response: dict[str, Any]
provider: str
model: str
status: str
diff --git a/test_bilingual.py b/test_bilingual.py
new file mode 100644
index 0000000..f2392b0
--- /dev/null
+++ b/test_bilingual.py
@@ -0,0 +1,44 @@
+import requests
+import json
+import time
+
+API_URL = "http://localhost:8001"
+
+# 1. Create a dummy CSV
+csv_content = """district,date,type,crime_count
+A,2023-01-01,theft,10
+A,2023-01-02,assault,5
+B,2023-01-01,theft,15
+B,2023-01-02,burglary,20
+C,2023-01-01,murder,1
+"""
+with open("test_hindi.csv", "w") as f:
+ f.write(csv_content)
+
+print("Uploading...")
+with open("test_hindi.csv", "rb") as f:
+ res = requests.post(f"{API_URL}/api/upload", files={"files": ("test_hindi.csv", f, "text/csv")})
+
+data = res.json()
+session_id = data["session_id"]
+print("Session ID:", session_id)
+
+queries = [
+ "kis district me sabse jyada crime count hai? Mujhe number bhi batao.",
+ "Which district has the lowest crime count?",
+ "saare districts ka total crime batao bar chart ke format me",
+]
+
+for q in queries:
+ print(f"\nAnalyzing Query: {q}")
+ query_payload = {
+ "session_id": session_id,
+ "query": q
+ }
+ res2 = requests.post(f"{API_URL}/api/analyze", json=query_payload)
+ if res2.status_code != 200:
+ print("Analyze failed:", res2.text)
+ else:
+ print("Result:", json.dumps(res2.json(), indent=2))
+
+print("SUCCESS!")
diff --git a/test_e2e.py b/test_e2e.py
new file mode 100644
index 0000000..75f6b66
--- /dev/null
+++ b/test_e2e.py
@@ -0,0 +1,43 @@
+import requests
+import json
+import time
+import os
+
+API_URL = "http://localhost:8001"
+
+# 1. Create a dummy CSV
+csv_content = """district,date,type
+A,2023-01-01,theft
+A,2023-01-02,assault
+B,2023-01-01,theft
+"""
+with open("test_data.csv", "w") as f:
+ f.write(csv_content)
+
+# 2. Upload
+print("Uploading...")
+with open("test_data.csv", "rb") as f:
+ res = requests.post(f"{API_URL}/api/upload", files={"files": ("test_data.csv", f, "text/csv")})
+
+if res.status_code != 200:
+ print("Upload failed:", res.text)
+ exit(1)
+
+data = res.json()
+session_id = data["session_id"]
+print("Session ID:", session_id)
+
+# 3. Analyze
+print("Analyzing...")
+query_payload = {
+ "session_id": session_id,
+ "query": "Which district has the most crimes?"
+}
+res2 = requests.post(f"{API_URL}/api/analyze", json=query_payload)
+
+if res2.status_code != 200:
+ print("Analyze failed:", res2.text)
+ exit(1)
+
+print("Result:", json.dumps(res2.json(), indent=2))
+print("SUCCESS!")
diff --git a/tests/unit/test_api.py b/tests/unit/test_api.py
index 0b3b1a3..ed615c0 100644
--- a/tests/unit/test_api.py
+++ b/tests/unit/test_api.py
@@ -9,7 +9,7 @@ def _client() -> TestClient:
def test_health_reports_provider_presence_only(no_keys):
with _client() as client:
- res = client.get("/health")
+ res = client.get("/api/health")
assert res.status_code == 200
data = res.json()["data"]
assert data["status"] == "ok"
@@ -17,40 +17,3 @@ def test_health_reports_provider_presence_only(no_keys):
# never leaks a key value — only names
assert "api_key" not in res.text.lower()
-
-def test_get_unknown_run_is_404():
- with _client() as client:
- res = client.get("/runs/nope")
- assert res.status_code == 404
- assert res.json()["detail"]["code"] == "run_not_found"
-
-
-def test_create_run_rejects_empty_text():
- with _client() as client:
- res = client.post("/runs", json={"text": "", "instruction": "upper"})
- assert res.status_code == 422 # pydantic min_length
-
-
-def test_run_without_key_fails_gracefully(no_keys):
- """No key → run persists as failed with an actionable message; no 500."""
- with _client() as client:
- res = client.post("/runs", json={"text": "hello world"})
- assert res.status_code == 200
- run = res.json()["data"]
- assert run["status"] == "failed"
- assert "AGENT_" in run["error_message"]
-
- # the failed run is persisted and fetchable
- res2 = client.get(f"/runs/{run['run_id']}")
- assert res2.status_code == 200
- assert res2.json()["data"]["status"] == "failed"
-
-
-def test_frontend_served_at_app():
- with _client() as client:
- res = client.get("/app/")
- assert res.status_code == 200
- assert "Zero-Shot Agent" in res.text
- # styles + js referenced (single-origin)
- assert "styles.css" in res.text
- assert "app.js" in res.text
diff --git a/tests/unit/test_graph.py b/tests/unit/test_graph.py
index 1f42d0d..de91abb 100644
--- a/tests/unit/test_graph.py
+++ b/tests/unit/test_graph.py
@@ -1,23 +1,25 @@
from src.graph.agent import agentic_ai
-from src.graph.edges import after_transform
+from src.graph.edges import after_parse, after_execute
def test_graph_compiles_without_env():
# compiled at import; nodes present
assert agentic_ai is not None
node_names = set(agentic_ai.get_graph().nodes)
- assert {"transform_text", "handle_error", "finalize"} <= node_names
+ assert {"parse_intent", "execute_pandas", "synthesize_dashboard", "handle_error", "finalize"} <= node_names
def test_error_edge_routes_to_handler():
- assert after_transform({"error": "boom"}) == "handle_error"
- assert after_transform({"error": None}) == "finalize"
+ assert after_parse({"error": "boom"}) == "handle_error"
+ assert after_parse({"error": None}) == "execute_pandas"
+ assert after_execute({"error": "boom"}) == "handle_error"
+ assert after_execute({"error": None}) == "synthesize_dashboard"
-def test_transform_node_surfaces_missing_key_as_error(no_keys):
+def test_parse_intent_node_surfaces_missing_key_as_error(no_keys):
"""With no key, the node returns an actionable error — it never raises."""
- from src.graph.nodes import transform_text
+ from src.graph.nodes import parse_intent
- out = transform_text({"input_text": "hi", "instruction": "upper"})
+ out = parse_intent({"user_query": "hi", "csv_schemas": {}})
assert out["error"] is not None
assert "AGENT_" in out["error"] # actionable: names the env vars to set
diff --git a/tests/unit/test_memory.py b/tests/unit/test_memory.py
new file mode 100644
index 0000000..bfd7cc4
--- /dev/null
+++ b/tests/unit/test_memory.py
@@ -0,0 +1,64 @@
+import pytest
+import os
+import sqlite3
+from langgraph.checkpoint.sqlite import SqliteSaver
+from src.graph.agent import agentic_ai
+from src.graph.state import AgentState
+from unittest.mock import patch, MagicMock
+
+def test_memory_persists_across_turns():
+ # Setup test DB
+ conn = sqlite3.connect(":memory:", check_same_thread=False)
+ memory = SqliteSaver(conn)
+ memory.setup()
+
+ # Mock the LLM to just return a dummy script and then a dummy JSON response
+ with patch("src.graph.nodes.LLMClient") as mock_client_cls:
+ mock_instance = mock_client_cls.return_value
+ # First turn mocks
+ mock_instance.complete.side_effect = [
+ "result = {'highest_crime': 'District A'}", # parse_intent
+ '{"summary": "Initial summary", "findings": ["Finding 1"], "charts": [], "recommendations": []}', # synthesize_dashboard
+ "result = {'drill_down': 'District A details'}", # parse_intent turn 2
+ '{"summary": "Follow-up summary", "findings": ["Finding 2"], "charts": [], "recommendations": []}', # synthesize_dashboard turn 2
+ ]
+ mock_instance.provider_name = "mock"
+ mock_instance.model = "mock"
+
+ # We need a custom graph instance using the memory checkpointer
+ from src.graph.agent import _build_graph
+ with patch("src.graph.agent.get_settings") as mock_settings:
+ mock_settings.return_value.database_url = "sqlite:///:memory:"
+ # Recompile with memory checkpointer
+ test_graph = _build_graph()
+
+ config = {"configurable": {"thread_id": "test_session_123"}}
+
+ # Turn 1
+ initial_state = {
+ "user_query": "What district has the most crime?",
+ "csv_schemas": {"crimes": ["district", "date", "type"]},
+ "temp_paths": {"crimes": "dummy.csv"}
+ }
+
+ # mock pandas reading
+ with patch("pandas.read_csv", return_value=MagicMock()):
+ final_1 = test_graph.invoke(initial_state, config=config)
+
+ assert len(final_1["chat_history"]) == 2
+ assert final_1["chat_history"][0]["role"] == "user"
+ assert final_1["chat_history"][1]["role"] == "assistant"
+
+ # Turn 2 - Follow up
+ follow_up_state = {
+ "user_query": "Drill down into that district."
+ }
+
+ with patch("pandas.read_csv", return_value=MagicMock()):
+ final_2 = test_graph.invoke(follow_up_state, config=config)
+
+ # The history should now have 4 messages because of the append operator in AgentState
+ assert len(final_2["chat_history"]) == 4
+ assert final_2["chat_history"][2]["role"] == "user"
+ assert final_2["chat_history"][3]["role"] == "assistant"
+ assert final_2["chat_history"][3]["content"] == "Follow-up summary"
diff --git a/uv.lock b/uv.lock
index 5d86f08..5308ffd 100644
--- a/uv.lock
+++ b/uv.lock
@@ -1,6 +1,26 @@
version = 1
revision = 3
requires-python = ">=3.11"
+resolution-markers = [
+ "python_full_version >= '3.14' and sys_platform == 'win32'",
+ "python_full_version >= '3.14' and sys_platform == 'emscripten'",
+ "python_full_version >= '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+ "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'win32'",
+ "python_full_version < '3.12' and sys_platform == 'win32'",
+ "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform == 'emscripten'",
+ "python_full_version < '3.12' and sys_platform == 'emscripten'",
+ "python_full_version >= '3.12' and python_full_version < '3.14' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+ "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
+
+[[package]]
+name = "aiosqlite"
+version = "0.22.1"
+source = { registry = "https://pypi.org/simple" }
+sdist = { url = "https://files.pythonhosted.org/packages/4e/8a/64761f4005f17809769d23e518d915db74e6310474e733e3593cfc854ef1/aiosqlite-0.22.1.tar.gz", hash = "sha256:043e0bd78d32888c0a9ca90fc788b38796843360c855a7262a532813133a0650", size = 14821, upload-time = "2025-12-23T19:25:43.997Z" }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/00/b7/e3bf5133d697a08128598c8d0abc5e16377b51465a33756de24fa7dee953/aiosqlite-0.22.1-py3-none-any.whl", hash = "sha256:21c002eb13823fad740196c5a2e9d8e62f6243bd9e7e4a1f87fb5e44ecb4fceb", size = 17405, upload-time = "2025-12-23T19:25:42.139Z" },
+]
[[package]]
name = "alembic"
@@ -420,6 +440,20 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/bd/b4/71425e3e38be92611300b9cc5e46a5bf98ab23f5ea8a75b73d02a2f1413c/langgraph_checkpoint-4.1.1-py3-none-any.whl", hash = "sha256:25d29144b082827218e7bc3f1e9b0566a4bb007895cd6cc26f66a8428739f56e", size = 56212, upload-time = "2026-05-22T16:57:37.203Z" },
]
+[[package]]
+name = "langgraph-checkpoint-sqlite"
+version = "3.1.0"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+ { name = "aiosqlite" },
+ { name = "langgraph-checkpoint" },
+ { name = "sqlite-vec" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/e3/ea/83917c2369acf8a10a894d4247655fd063c07924ba5bc4e83c85d2eaeded/langgraph_checkpoint_sqlite-3.1.0.tar.gz", hash = "sha256:f926916ebc1b985d802cc9c820026036e84db9d910d62c97b57e4ba64f67d5ae", size = 147902, upload-time = "2026-05-12T03:34:52.503Z" }
+wheels = [
+ { url = "https://files.pythonhosted.org/packages/97/07/b342811a16327900af2747c752ea19676172fcddf9b592cc384031076623/langgraph_checkpoint_sqlite-3.1.0-py3-none-any.whl", hash = "sha256:cc9b40df0076feae8a9ad42ae713621b148b00ac23adc09dc1dc66090a46e5ad", size = 38587, upload-time = "2026-05-12T03:34:51.231Z" },
+]
+
[[package]]
name = "langgraph-prebuilt"
version = "1.1.0"
@@ -560,6 +594,149 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/70/bc/6f1c2f612465f5fa89b95bead1f44dcb607670fd42891d8fdcd5d039f4f4/markupsafe-3.0.3-cp314-cp314t-win_arm64.whl", hash = "sha256:32001d6a8fc98c8cb5c947787c5d08b0a50663d139f1305bac5885d98d9b40fa", size = 14146, upload-time = "2025-09-27T18:37:28.327Z" },
]
+[[package]]
+name = "numpy"
+version = "2.4.6"
+source = { registry = "https://pypi.org/simple" }
+resolution-markers = [
+ "python_full_version < '3.12' and sys_platform == 'win32'",
+ "python_full_version < '3.12' and sys_platform == 'emscripten'",
+ "python_full_version < '3.12' and sys_platform != 'emscripten' and sys_platform != 'win32'",
+]
+sdist = { url = "https://files.pythonhosted.org/packages/d0/ad/fed0499ce6a338d2a03ebae59cd15093910c8875328855781952abf6c2fe/numpy-2.4.6.tar.gz", hash = "sha256:f3a3570c4a2a16746ac2c31a7c7c7b0c186b95ce902e33db6f28094ed7387dda", size = 20735807, upload-time = "2026-05-18T23:37:14.07Z" }
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