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innovation_pathfinder_ai/structured_tools/code_structure_documentation.md

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-## Functionality Breakdown
-
-### Internal Knowledge Exploration
-
-- **memory_search**: Searches a Chroma vector store containing past findings, utilizing sentence embeddings to identify relevant information.
-  
-- **knowledgeBase_search**: Similar to `memory_search`, but specifically explores a collection within Chroma potentially holding research papers or relevant information chunks.
-
-### External Information Retrieval
-
-- **arxiv_search**: Retrieves scientific research papers from the Arxiv database based on user queries, stores metadata, and formats papers for display.
-
-- **get_arxiv_paper**: Downloads full PDF content of a specific Arxiv paper based on its ID and saves it to a designated directory.
-
-- **wikipedia_search**: Queries Wikipedia for relevant summaries based on user input, formats and stores retrieved summaries.
-
-- **google_search**: Performs a Google Search using user queries, retrieves relevant results, and stores them for later use.
-
-### Data Storage and Management
-
-- **Chroma Vector Store**: Stores text content embeddings for similarity search (`memory_search`) and Arxiv paper embeddings (`embed_arvix_paper`).
-
-- **Global `all_sources` Variable**: Accumulates retrieved information from various sources (Arxiv, Wikipedia, Google Search).
-
-## Additional Notes
-
-- These tools are integrated with a larger LangChain framework, as indicated by the `@tool` decorator.
-  
-- Configuration files (`config.ini`) define details like vector store location and collection names.
-
-## Getting Started
-
-1. Install the LangChain framework and required libraries.
-  
-2. Configure access to the Chroma vector store (likely involves environment variables or configuration files).
-
-3. Refer to the InnovationPathfinderAI project documentation for detailed integration instructions.
-
-## Disclaimer
-
-This documentation provides an overview of the tools' functionalities.