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225 lines
5.2 KiB
Markdown
225 lines
5.2 KiB
Markdown
# LangChain + Llama Stack Document Processing
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1. **`langchain-llama-stack.py`** - Interactive CLI version
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---
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## 📋 Prerequisites
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### System Requirements
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- Python 3.12+
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- Llama Stack server running on `http://localhost:8321/`
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- Ollama or compatible model server
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### Environment Setup
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```bash
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# Create and activate virtual environment
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python3.12 -m venv llama-env-py312
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source llama-env-py312/bin/activate
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# Install dependencies
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pip install llama-stack-client langchain langchain-core langchain-community beautifulsoup4 markdownify readability-lxml requests langchain_openai
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```
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---
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## 🚀 Quick Start
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### Start Llama Stack Server
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Before running either version, ensure your Llama Stack server is running:
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```bash
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# Start Llama Stack server (example)
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llama stack run your-config --port 8321
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```
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---
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## 📖 Option 1: Interactive CLI Version (`langchain-llama-stack.py`)
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### Features
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- ✅ Interactive command-line interface
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- ✅ Document loading from URLs and PDFs
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- ✅ AI-powered summarization and fact extraction
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- ✅ Question-answering based on document content
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- ✅ Session-based document storage
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### How to Run
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```bash
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# Run the interactive CLI
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cd /docs/notebooks/langchain/
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python langchain-llama-stack.py
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```
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### Usage Commands
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Once running, you can use these interactive commands:
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```
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🎯 Interactive Document Processing Demo
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Commands:
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load <url_or_path> - Process a document
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ask <question> - Ask about the document
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summary - Show document summary
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facts - Show extracted facts
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help - Show commands
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quit - Exit demo
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```
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### Example Session
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```
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> load https://en.wikipedia.org/wiki/Artificial_intelligence
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📄 Loading document from: https://en.wikipedia.org/wiki/Artificial_intelligence
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✅ Loaded 45,832 characters
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📝 Generating summary...
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🔍 Extracting key facts...
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✅ Processing complete!
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> summary
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📝 Summary:
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Artificial intelligence (AI) is the simulation of human intelligence...
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> ask What are the main types of AI?
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💬 Q: What are the main types of AI?
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📝 A: Based on the document, the main types of AI include...
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> facts
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🔍 Key Facts:
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- AI was founded as an academic discipline in 1956
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- Machine learning is a subset of AI...
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> quit
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👋 Thanks for exploring LangChain chains!
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```
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#### Using curl:
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```bash
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# Check service status
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curl http://localhost:8000/
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# Process a document
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curl -X POST http://localhost:8000/process \
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-H 'Content-Type: application/json' \
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-d '{"source": "https://en.wikipedia.org/wiki/Machine_learning"}'
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# Ask a question
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curl -X POST http://localhost:8000/ask \
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-H 'Content-Type: application/json' \
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-d '{"question": "What is machine learning?"}'
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# Get summary
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curl http://localhost:8000/summary
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# Get facts
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curl http://localhost:8000/facts
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# List all processed documents
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curl http://localhost:8000/docs
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```
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#### Using Python requests:
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```python
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import requests
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# Process a document
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response = requests.post(
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"http://localhost:8000/process",
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json={"source": "https://en.wikipedia.org/wiki/Deep_learning"},
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)
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print(response.json())
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# Ask a question
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response = requests.post(
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"http://localhost:8000/ask", json={"question": "What are neural networks?"}
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)
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print(response.json())
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# Get facts
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response = requests.get("http://localhost:8000/facts")
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print(response.json())
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```
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---
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## 🔧 Configuration
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### Model Configuration
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Both versions use these models by default:
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- **Model ID**: `llama3.2:3b`
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- **Llama Stack URL**: `http://localhost:8321/`
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To change the model, edit the `model_id` parameter in the respective files.
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### Supported Document Types
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- ✅ **URLs**: Any web page (extracted using readability)
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- ✅ **PDF files**: Local or remote PDF documents
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- ❌ Plain text files (can be added if needed)
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---
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## 🛠️ Troubleshooting
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### Common Issues
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#### 1. Connection Refused to Llama Stack
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**Error**: `Connection refused to http://localhost:8321/`
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**Solution**:
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- Ensure Llama Stack server is running
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- Check if port 8321 is correct
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- Verify network connectivity
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#### 2. Model Not Found
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**Error**: `Model not found: llama3.2:3b`
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**Solution**:
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- Check available models: `curl http://localhost:8321/models/list`
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- Update `model_id` in the code to match available models
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#### 4. Missing Dependencies
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### Debug Mode
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To enable verbose logging, add this to the beginning of either file:
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```python
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import logging
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logging.basicConfig(level=logging.DEBUG)
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```
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---
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## 📊 Performance Notes
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### CLI Version
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- **Pros**: Simple to use, interactive, good for testing
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- **Cons**: Single-threaded, session-based only
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- **Best for**: Development, testing, manual document analysis
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---
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## 🛑 Stopping Services
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### CLI Version
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- Press `Ctrl+C` or type `quit` in the interactive prompt
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---
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## 📝 Examples
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### CLI Workflow
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1. Start: `python langchain-llama-stack.py`
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2. Load document: `load https://arxiv.org/pdf/2103.00020.pdf`
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3. Get summary: `summary`
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4. Ask questions: `ask What are the main contributions?`
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5. Exit: `quit`
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---
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## 🤝 Contributing
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To extend functionality:
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1. Add new prompt templates for different analysis types
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2. Support additional document formats
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3. Add caching for processed documents
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4. Implement user authentication for API version
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---
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## 📜 License
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This project is for educational and research purposes.
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