https://github.com/spyker77/agentic-rag
[WIP] Dirty code, only for local experiments with agents and RAG
https://github.com/spyker77/agentic-rag
crewai langchain langgraph llamaindex ollama smolagents
Last synced: about 1 month ago
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[WIP] Dirty code, only for local experiments with agents and RAG
- Host: GitHub
- URL: https://github.com/spyker77/agentic-rag
- Owner: spyker77
- License: mit
- Created: 2025-03-25T07:21:19.000Z (about 1 month ago)
- Default Branch: main
- Last Pushed: 2025-03-25T11:19:53.000Z (about 1 month ago)
- Last Synced: 2025-03-25T12:25:31.504Z (about 1 month ago)
- Topics: crewai, langchain, langgraph, llamaindex, ollama, smolagents
- Language: Python
- Homepage:
- Size: 753 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
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README
# Agentic RAG Playground
A playground repository exploring different frameworks and approaches for building Retrieval Augmented Generation (RAG) systems with agentic capabilities.
## Overview
This repository demonstrates various implementations of RAG systems using different frameworks and approaches. It serves as a learning playground and reference for AI engineers interested in exploring the landscape of RAG and agent-based architectures.
The code is intentionally experimental in nature, showcasing different implementation patterns rather than providing a single production-ready solution.
## Frameworks Explored
- **LangChain**: Implementation of retrieval chains and document processing
- **LangGraph**: Graph-based agent workflows with state management
- **LlamaIndex**: Vector store indexing and query engines
- **CrewAI**: Multi-agent systems with specialized roles and coordination
- **SmolAgents**: Lightweight agent framework with custom tools
## Key Components
### RAG Implementations
- Basic RAG with LangChain and LlamaIndex
- Document chunking and embedding strategies
- Vector store creation and similarity search
### Agent Architectures
- Single-agent RAG with tool use
- Multi-agent systems with coordination
- Graph-based agent workflows
### Advanced Techniques
- `misc/dvts.py`: Diverse Verifier Tree Search for complex reasoning
- `misc/rag.py`: Production-grade RAG with HNSW vector search
- `misc/perplexity.py`: Real-time search with dynamic index management
- `misc/optimizations.py`: High-performance LLM serving optimizations
### Resume Agent
A more structured implementation of a LangGraph-based agent designed to answer questions about a resume:
- Graph-based agent workflow
- RAG chain for document retrieval
- Custom tools for resume search
## Getting Started
### Prerequisites
- Python 3.12+
- Local LLM server (Ollama recommended)
### Installation
```bash
# Clone the repository
git clone https://github.com/spyker77/agentic-rag.git
cd agentic-rag
# Install dependencies
uv sync
```
### Running Demos
```bash
python -m demos.crewai
python -m demos.langchain
python -m demos.langgraph
python -m demos.llamaindex_agent
python -m demos.llamaindex_rag
python -m demos.smolagents
python -m src.resume_agent.main
```
## Project Structure
```bash
.
├── data/ # Sample data including resume
├── misc/ # Advanced techniques and optimizations
│ ├── dvts.py # Diverse Verifier Tree Search
│ ├── optimizations.py # LLM serving optimizations
│ ├── perplexity.py # Real-time search system
│ └── rag.py # Advanced RAG implementation
├── src/ # Source code
│ └── resume_agent/ # Structured LangGraph agent implementation
├── demos/ # Demos with different frameworks
```
## Disclaimer
This repository is intended as an experimental playground for learning and exploration. The code is not optimized for production use and may contain experimental patterns and approaches.
## License
MIT