add CLAUDE.md and flow diagram

CLAUDE.md

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+# CLAUDE.md
+
+This file provides guidance to Claude Code (claude.ai/code) when working with code in this repository.
+
+## Running the Application
+
+```bash
+# Quick start (from project root)
+./run.sh
+
+# Manual start
+cd backend && uv run uvicorn app:app --reload --port 8000
+```
+
+App runs at http://localhost:8000. Requires `ANTHROPIC_API_KEY` in a `.env` file at the project root.
+
+Install dependencies: `uv sync`
+
+**Always use `uv` for all dependency management — never `pip` directly.**
+- Add a package: `uv add <package>`
+- Remove a package: `uv remove <package>`
+
+## Architecture
+
+This is a full-stack RAG chatbot. The **backend** is a FastAPI app served from the `backend/` directory; it also serves the **frontend** (`frontend/`) as static files mounted at `/`. There is no build step for the frontend.
+
+### Query pipeline (the core flow)
+
+1. `app.py` — receives `POST /api/query`, creates a session if needed, delegates to `RAGSystem`
+2. `rag_system.py` — orchestrates the pipeline: fetches conversation history, calls `AIGenerator`
+3. `ai_generator.py` — makes the first Claude API call with `tool_choice: auto` and the search tool definition. If Claude invokes the tool, `_handle_tool_execution()` runs it and makes a second Claude call (without tools) to produce the final answer
+4. `search_tools.py` — `CourseSearchTool` wraps `VectorStore.search()` and formats results for Claude; `ToolManager` registers tools and exposes them as Anthropic tool definitions
+5. `vector_store.py` — two ChromaDB collections: `course_catalog` (one doc per course, for fuzzy name resolution) and `course_content` (chunked lesson text, for semantic search). Embeddings use `all-MiniLM-L6-v2`
+6. `session_manager.py` — in-memory session store; keeps last 2 exchanges (configurable via `MAX_HISTORY`) formatted as a string injected into the system prompt
+
+### Document ingestion
+
+`document_processor.py` parses `.txt`/`.pdf`/`.docx` files from `docs/` at startup. Expected file format:
+```
+Course Title: <title>
+Course Link: <url>
+Course Instructor: <name>
+Lesson 0: <lesson title>
+Lesson Link: <url>
+<lesson content...>
+Lesson 1: <lesson title>
+...
+```
+
+Chunks are sentence-aware with configurable size (800 chars) and overlap (100 chars).
+
+### Configuration
+
+All tunable parameters live in `backend/config.py` (`Config` dataclass):
+- `ANTHROPIC_MODEL` — Claude model to use
+- `EMBEDDING_MODEL` — sentence-transformers model
+- `CHUNK_SIZE`, `CHUNK_OVERLAP`, `MAX_RESULTS`, `MAX_HISTORY`
+- `CHROMA_PATH` — where ChromaDB persists data (`./chroma_db` relative to `backend/`)
+
+### Key design decisions
+- The server must be started from the `backend/` directory (paths like `../docs` and `../frontend` are relative to that working directory)
+- Course deduplication is by title — re-ingesting the same course title is a no-op
+- Tool sources (`last_sources`) are stored on the tool instance and reset after each query cycle
+- The second Claude call omits tools to prevent recursive tool use

flow-diagram.md

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+# RAG Chatbot — Request Flow Diagram
+
+```mermaid
+sequenceDiagram
+    actor User
+    participant FE as Frontend<br/>(script.js)
+    participant API as FastAPI<br/>(app.py)
+    participant RAG as RAGSystem<br/>(rag_system.py)
+    participant SM as SessionManager<br/>(session_manager.py)
+    participant AI as AIGenerator<br/>(ai_generator.py)
+    participant TM as ToolManager<br/>(search_tools.py)
+    participant VS as VectorStore<br/>(vector_store.py)
+    participant DB as ChromaDB
+    participant Claude as Claude API
+
+    User->>FE: Types message + hits Enter/Send
+    FE->>FE: Disable input, show loading spinner
+    FE->>API: POST /api/query<br/>{query, session_id}
+
+    API->>SM: create_session() if no session_id
+    SM-->>API: "session_1"
+    API->>RAG: query(query, session_id)
+
+    RAG->>SM: get_conversation_history(session_id)
+    SM-->>RAG: last 2 exchanges (or null)
+
+    RAG->>AI: generate_response(prompt, history, tools)
+
+    AI->>Claude: messages.create()<br/>system prompt + tool definitions<br/>tool_choice: auto
+    Claude-->>AI: stop_reason = "tool_use"<br/>search_course_content(query, course_name, lesson_number)
+
+    AI->>TM: execute_tool("search_course_content", ...)
+    TM->>VS: search(query, course_name, lesson_number)
+
+    VS->>DB: query course_catalog<br/>(resolve course name to exact title)
+    DB-->>VS: matched course title
+
+    VS->>DB: query course_content<br/>(embedding similarity + where filter)
+    DB-->>VS: top 5 chunks + metadata
+
+    VS-->>TM: SearchResults
+    TM->>TM: format results + store sources
+    TM-->>AI: formatted text chunks
+
+    AI->>Claude: messages.create()<br/>[user → tool_use → tool_result]<br/>(no tools this time)
+    Claude-->>AI: final answer text
+
+    AI-->>RAG: response string
+    RAG->>TM: get_last_sources() + reset_sources()
+    RAG->>SM: add_exchange(session_id, query, response)
+    RAG-->>API: (answer, sources)
+
+    API-->>FE: {answer, sources, session_id}
+
+    FE->>FE: Remove spinner
+    FE->>FE: Render answer as Markdown
+    FE->>FE: Show sources in collapsible details
+    FE->>FE: Save session_id, re-enable input
+    FE-->>User: Displays response
+```