ChatBot
by 080bct12alex
Overview
Develops a versatile and interactive AI chatbot using LangGraph, featuring advanced concepts like memory, persistence, tool integration (search, calculator, stock price), multi-party communication (MCP), and retrieval-augmented generation (RAG) with a Streamlit user interface and user management.
Installation
streamlit run with_rag/app.pyEnvironment Variables
- GOOGLE_API_KEY
- LANGCHAIN_TRACING_V2
- LANGCHAIN_ENDPOINT
- LANGCHAIN_API_KEY
- LANGCHAIN_PROJECT
Security Notes
CRITICAL: The Alpha Vantage API key is hardcoded in `agent.py` (`apikey=8S6VBWTFZH9U6HDA`). CRITICAL: The cookie encryption password for `EncryptedCookieManager` is hardcoded in `app.py` (`password="7b9561efc4a6acf95c78285418225434533f70dd609026c8ff9ba1c50a5be6c6"`). These hardcoded secrets pose significant security risks, allowing unauthorized access to API services and potential decryption of user session data. While user authentication with bcrypt is implemented for passwords, the overall system is highly vulnerable due to these critical hardcoded secrets.
Similar Servers
Docker_MCPGUIApp
A conversational AI chatbot leveraging Docker's Model and Component Protocol (MCP) to integrate with LLMs and perform various tool-augmented searches (web, academic papers).
fastchat-mcp
A Python client integrating Language Models (LLMs) with Model Context Protocol (MCP) servers, enabling natural language interaction with external tools, resources, and prompts via terminal or a FastAPI/WebSocket API.
ChatBot_Development
A LangGraph-based AI chatbot with a Streamlit UI, featuring conversation memory, tool integration (search, calculator, stock price), RAG capabilities for document analysis, Multi-Agent Collaboration (MCP), user authentication, and persistent storage.
mcp-explore
A Streamlit chat application integrating multiple MCP servers (local and remote) to orchestrate LLM tool calls.