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  "full_text": "I made a multi-agent workflow that should be a decent initial reference for anyone building report generation + form filling use cases! \n\nStep 1: Index a knowledge base, creating tools/RAG endpoints to query this KB\nStep 2: Input a template (in this case it's an RFP)\nStep 3: Parse out the template into a set of k:v pairs that you need to fill out\nStep 4: Fill out k:v pairs by having a research agent query the knowledge base repeatedly\nStep 5: Generate the final report! \n\nLong context LLMs are great for this. Also because this is a long-running process, certain features like streaming + human-in-the-loop become super useful.\n\nCookbook: https://t.co/CFYq8PlMe6\n\nA secret weapon to any agentic document workflow is of course llamaparse: https://t.co/XYZmx5TFz8",
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    "full_text": "Multi-agent system for RFP Response Generation 🔥✍️\n\nWe’re excited to release a brand-new guide showing you how to build an agentic workflow that can take in an input Request for Proposal (RFP) template and generate a full response to the RFP, grounded in your knowledge base and adhering to the relevant guidelines.\n\nThis is much more than a standard RAG or ReAct agent architecture, and requires the careful orchestration of a set of steps + components.\n\n1. Parse the input RFP template using LlamaParse, extract out a set of questions that you would need answered.\n2. For each question, use a Research agent (ReAct loop) with access to a set of tools in the knowledge base to retrieve relevant information and generate an answer\n3. Aggregate question/answer pairs into a single file\n4. Generate the final report with the RFP template and QA pairs as input.\n\nBonuses 💫: it’s fully async, and you get back event and final response streaming!\n\nNotebook: https://t.co/5XCkFeUQen\n\nLlamaParse signup: https://t.co/yQGTiRSNvj",
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