An intelligent assistant specialized in Python, powered by RAG (Retrieval-Augmented Generation) technology. Ask your Python questions and get accurate answers with code examples and documented references.
- 💬 Conversational Interface: Chat naturally with the assistant
- 📚 Knowledge Base: Access to comprehensive Python documentation
- 🔍 Intelligent Search: Retrieves relevant information from vector database
- 📝 Code Examples: Answers accompanied by practical examples
- 🎯 Cited Sources: Traceability of provided information
- ⚙️ Configurable Parameters: Adjust temperature and number of documents
- Type your Python question in the text field
- Click "Send" or press Enter
- The assistant searches its knowledge base
- Receive a detailed answer with examples and sources
- "How to create a list comprehension?"
- "What's the difference between a list and a tuple?"
- "How to handle exceptions in Python?"
- "Explain decorators to me"
- "How to read a CSV file?"
- Streamlit: User interface
- LangChain: Framework for LLM applications
- ChromaDB: Vector database
- Sentence Transformers: Embedding generation
- Groq API: Language model (GPT)
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Temperature (0.0 - 1.0): Controls response creativity
- 0.0 = More precise and deterministic responses
- 1.0 = More creative and varied responses
-
Top K documents (1 - 10): Number of documents consulted
- Higher numbers provide broader context
- Recommended: 3-5 for good balance
User Question
↓
Convert to embedding
↓
Search in ChromaDB
↓
Retrieve relevant documents
↓
Generate response (LLM + context)
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Display with sources
- No user data is stored permanently
- Conversations are not saved between sessions
- Use the "Clear History" button to delete the current session
Contributions are welcome! Feel free to:
- Report bugs
- Suggest new features
- Improve documentation
For any questions or suggestions, feel free to open an issue on the GitHub repository.
Built with ❤️ using Streamlit and LangChain