Agents
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Explore diverse AI agent implementations using LangGraph for reasoning, RAG, chatbots, and structured output generation.
About
This repository offers a comprehensive exploration of cutting-edge AI agent architectures, leveraging LangGraph to build complex agentic workflows. Implementations range from reasoning agents to retrieval-augmented systems, showcasing innovative approaches to AI reasoning, retrieval, interaction, and structured data processing. Explore ReAct agents, RAG systems (Corrective, Self, Agentic), chatbots, microagents, and database integrations.
Key Features
- ReAct agents with custom tools and LangGraph integration
- Corrective, Self, and Agentic RAG implementations
- LangGraph-based chatbots with conversational context management
- Structured output generation from agent workflows
- Database integration for querying and managing structured data
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Use Cases
- Building intelligent chatbots with reasoning capabilities
- Enhancing retrieval accuracy through iterative refinement
- Automating workflows with agentic reasoning and decision-making