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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.