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gradio
requests
# Core LangChain and LangGraph Framework
# These are the fundamental building blocks for your agent.
langchain
langgraph

# LangChain Community and Integration Packages
# These packages allow LangChain to connect to various models, services, and data sources.
langchain-community
langchain-google-genai   # For Google Gemini models
langchain-groq           # For Groq models
langchain-huggingface    # For Hugging Face models and embeddings

# Vector Store and Embeddings
# Used for creating and searching your local knowledge base of Q&A examples.
faiss-cpu                # For the FAISS vector store (CPU version is best for HF Spaces)
sentence-transformers    # The model used to generate text embeddings

# Tool-Specific Dependencies
# Each tool that connects to an external service needs its own client library.
tavily-python            # For the Tavily web search tool
wikipedia                # For the Wikipedia search tool
arxiv                    # For the Arxiv scientific paper search tool

# Utility Libraries
python-dotenv            # For loading API keys from a .env file
requests                 # For making HTTP requests (used in the describe_image tool)
Pillow                   # For image processing (used in the describe_image tool)
cachetools               # For in-memory caching of API results to improve speed

# This is often installed as a dependency of other HF packages, but it's good
# practice to list it explicitly as HuggingFaceEndpoint is used.
huggingface_hub
yt-dlp
speechrecognition
pydub
google-cloud-speech
ffmpeg