This workflow automates the process of uploading documents to Google Drive, extracting and splitting their content, creating embeddings with OpenAI, storing these embeddings in a Pinecone vector database, and enabling instant retrieval through an AI-powered chat agent. Designed for seamless knowledge management, it helps users automate document handling and quickly query information via natural language chat. The setup involves monitoring a specific Google Drive folder for new files, downloading them automatically, processing their text, creating semantic embeddings, and storing the data in Pinecone. When a user sends a chat message, the system retrieves relevant information from Pinecone and responds intelligently using GPT-4.
**Steps overview:**
1. Google Drive Trigger monitors a folder for new files.
2. The file is downloaded from Google Drive.
3. Text content of the file is split into manageable chunks.
4. Embeddings are generated for each chunk using OpenAI.
5. Embeddings are stored in Pinecone for fast retrieval.
6. The chat trigger listens for user queries.
7. Relevant data is fetched from Pinecone based on the query.
8. GPT-4 processes the data and generates a response.
**Use cases:** Automate documentation workflows, build intelligent chatbots that reference large documents, or create knowledge bases that can be queried naturally, saving time and improving efficiency.
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