Agentic RAG using Crew AI.

Agentic RAG using Crew AI

This project is an Agentic RAG system leveraging CrewAI for agent orchestration, FAISS for efficient vector search, Sentence Transformers for embeddings, LangChain for document processing, and Ollama for local language model inference, enabling query answering from uploaded documents with a fallback to web searches via Firecrawl.

Tell Me Chatbot is a Mental Well-being chatbot serving as a proxy to provide initial therapeutic care to Clients. The core of the bot is LLM's giving choice to the developers to use local models like llama2 or even utilize GPT 4. The experiment is utilize methods like RAG, Langchain and Crew AI Agents to provide a comprehensive platform for care.

An Agentic RAG-based AI chatbot that uses CrewAI agents, Groq LLM, and LlamaIndex-powered retrieval from ChromaDB to answer class 12 Biology queries, along with top 3 YouTube video suggestions. Built with FastAPI, Streamlit, and Docker for seamless backend, frontend, and deployment integration.

An insurance AI agent built with crewAI and FastAPI. It uses specialized agent crews to provide quotes and answer policy questions using a Retrieval-Augmented Generation (RAG) system.

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Agentic RAG using Crew AI

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Multi-Agentic-RAG-using-Crew-AI

AI Agentic RAG application using Crew AI, LangChain, Web scrapping and FAISS

Agent-based symptom checker using Crew AI and RAG in Python.

Agent based RAG application is created using Crew AI and Langchain

AI Agentic RAG application with Streamlit UI using Crew AI, LangChain, Web scrapping and FAISS

GCRBOT – Multi-agent AI assistant for GCR students using Crew AI, Weaviate, and RAG-based knowledge retrieval

Lots and lots of LLM agent and RAG demos using crew-ai, langchain & llama-index.

Minimal project playing around with Crew AI for creating an agentic Magic the Gathering judge. Meant as an exercise in RAG and tool use with web APIs.

This is a multi-agent ai system based on Crew AI Framework & Graph of Thought Prompting Strategy.It uses rag retrival and external web search along with a crew of five agents and provides response along with confidence score and reffaral links.

this project is about to implement rag application using Docling Data Pipeline & Storage LlamaIndex + PGVector/PostgreSQL RAG Methodology Contextual RAG (Anthropic-style) Embedding / LLM / Re-ranking Models Locally hosted models via Ollama Agentic Framework Crew.AI Prompt Optimization Arize Phoenix Prompt Playground Evaluation RAGAs

This is a Smart Client Email Generator Pro - an AI-powered Streamlit app that analyzes client requests, profiles their technical sophistication & communication style, then generates personalized business emails using RAG with PDF knowledge bases and OpenAI models and using Crew AI multi-agent platform.

This is a full-stack financial analysis tool using a crew of autonomous AI agents (CrewAI, Google Gemini) to analyze documents, conduct live market research, and generate comprehensive reports. The Streamlit frontend calls a FastAPI backend, which uses LangChain and a vector database for RAG, demonstrating an end-to-end intelligent workflow.