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api.md

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+# RAG Pipeline API Documentation
+
+## Overview
+FastAPI-based RAG (Retrieval-Augmented Generation) pipeline with OpenRouter GLM integration for intelligent tool calling.
+
+## Base URL
+```
+http://localhost:8000
+```
+
+## Endpoints
+
+### `/chat` - Main Chat Endpoint
+**Method:** `POST`  
+**Description:** Intelligent chat with RAG tool calling. GLM automatically determines when to use RAG vs. general conversation.
+
+#### Request Body
+```json
+{
+  "messages": [
+    {
+      "role": "user|assistant|system",
+      "content": "string"
+    }
+  ]
+}
+```
+
+#### Response Format
+```json
+{
+  "response": "string",
+  "tool_calls": [
+    {
+      "name": "rag_qa",
+      "arguments": "{\"question\": \"string\", \"dataset\": \"string\"}"
+    }
+  ] | null
+}
+```
+
+#### Examples
+
+**1. General Greeting (No RAG):**
+```bash
+curl -X POST http://localhost:8000/chat \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"hi"}]}'
+```
+
+**Response:**
+```json
+{
+  "response": "Hi! I'm Rohit's AI assistant. I can help you learn about his professional background, skills, and experience. What would you like to know about Rohit?",
+  "tool_calls": null
+}
+```
+
+**2. Portfolio Question (RAG Enabled):**
+```bash
+curl -X POST http://localhost:8000/chat \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"What is your current role?"}]}'
+```
+
+**Response:**
+```json
+{
+  "response": "Based on the portfolio information, Rohit is currently working as a Tech Lead at FleetEnable, where he leads UI development for a logistics SaaS product focused on drayage and freight management...",
+  "tool_calls": [
+    {
+      "name": "rag_qa", 
+      "arguments": "{\"question\": \"What is your current role?\"}"
+    }
+  ]
+}
+```
+
+### `/health` - Health Check
+**Method:** `GET`  
+**Description:** Check API and dataset loading status.
+
+#### Response
+```json
+{
+  "status": "healthy",
+  "datasets_loaded": 1,
+  "available_datasets": ["developer-portfolio"]
+}
+```
+
+### `/datasets` - List Available Datasets
+**Method:** `GET`  
+**Description:** Get list of available datasets.
+
+#### Response
+```json
+{
+  "datasets": ["developer-portfolio"]
+}
+```
+
+## Features
+
+### 🧠 Intelligent Tool Calling
+- **Automatic Detection:** GLM determines when questions need RAG vs. general conversation
+- **Context-Aware:** Uses portfolio information for relevant questions
+- **Natural Responses:** Synthesizes RAG results into conversational answers
+
+### 🎯 Third-Person AI Assistant
+- **Portfolio Focus:** Responds about Rohit's experience (not "my" experience)
+- **Professional Tone:** Maintains proper third-person references
+- **Context Integration:** Combines multiple data points coherently
+
+### ⚡ Performance Optimizations
+- **On-Demand Loading:** Datasets load only when RAG is needed
+- **Clean Output:** No verbose ML logging for general conversations
+- **Fast Responses:** Sub-second for greetings, ~20s for first RAG query
+
+## Available Datasets
+
+### `developer-portfolio`
+- **Content:** Work experience, skills, projects, achievements
+- **Topics:** FleetEnable, Coditude, technologies, leadership
+- **Size:** 19 documents with full metadata
+
+## Error Handling
+
+### Common Responses
+- **Datasets Loading:** "RAG Pipeline is running but datasets are still loading..."
+- **Dataset Not Found:** "Dataset 'xyz' not available. Available datasets: [...]"
+- **API Errors:** HTTP 500 with error details
+
+### Status Codes
+- `200` - Success
+- `400` - Bad Request (invalid JSON, missing fields)
+- `500` - Internal Server Error
+
+## Environment Variables
+
+Create `.env` file:
+```bash
+OPENROUTER_API_KEY=sk-or-v1-your-key-here
+PORT=8000
+TOKENIZERS_PARALLELISM=false
+```
+
+## Development
+
+### Running Locally
+```bash
+# Install dependencies
+pip install -r requirements.txt
+
+# Start server
+python -m uvicorn app.main:app --host 0.0.0.0 --port 8000 --reload
+
+# Or use script
+./start.sh
+```
+
+### Testing
+```bash
+# Health check
+curl http://localhost:8000/health
+
+# Chat test
+curl -X POST http://localhost:8000/chat \
+  -H "Content-Type: application/json" \
+  -d '{"messages":[{"role":"user","content":"hi"}]}'
+```
+
+## Deployment
+
+### Docker
+```bash
+# Build
+docker build -t rag-pipeline .
+
+# Run
+docker run -p 8000:8000 rag-pipeline
+```
+
+### Hugging Face Spaces
+1. Push code to repository
+2. Connect Space to repository
+3. Set environment variables in Space settings
+4. Automatic deployment from `main` branch
+
+## Architecture
+
+```
+OpenRouter GLM-4.5-air (Parent AI)
+├── Tool Calling Logic
+│   ├── Automatically detects RAG-worthy questions
+│   └── Falls back to general knowledge
+├── RAG Tool Function
+│   ├── Dataset selection (developer-portfolio)
+│   ├── Document retrieval
+│   └── Context formatting
+└── Response Generation
+    ├── Tool results integration
+    └── Natural language responses
+```
+
+## Changelog
+
+### v2.0 - Current
+- ��� OpenRouter GLM integration with tool calling
+- ✅ Intelligent RAG vs. conversation detection
+- ✅ Third-person AI assistant for Rohit's portfolio
+- ✅ On-demand dataset loading
+- ✅ Removed `/answer` endpoint (use `/chat` only)
+- ✅ Environment variable configuration
+- ✅ Performance optimizations
+
+### v1.0 - Legacy
+- Google Gemini integration
+- Multiple endpoints (`/answer`, `/chat`)
+- Background dataset loading
+- First-person responses

pytest.ini

@@ -3,8 +3,4 @@ testpaths = .
 python_files = test_*.py
 python_classes = Test*
 python_functions = test_*
-addopts = -v --tb=short
-markers =
-    slow: marks tests as slow (deselect with '-m "not slow"')
-    integration: marks tests as integration tests
-    unit: marks tests as unit tests
+addopts = -v --tb=short