Frameworks together enable end-to-end Agentic AI systems — from LLM orchestration, memory, multi-agent collaboration, RAG, observability, automation, APIs, to cloud-scale deployment.
- Purpose: Core framework for building LLM-powered applications, chains, tools, and RAG systems
- 🌐 Website: https://www.langchain.com
- 📘 Docs: https://python.langchain.com/docs
- Purpose: Declarative way to build composable LLM pipelines
- 🌐 Website: https://www.langchain.com
- 📘 Docs: https://python.langchain.com/docs/expression_language
- Purpose: Graph-based agent workflows, state & memory management, multi-agent systems
- 🌐 Website: https://langchain-ai.github.io/langgraph
- 📘 Docs: https://langchain-ai.github.io/langgraph/concepts
- Purpose: Tracing, debugging, evaluation, and monitoring of LLM & agent workflows
- 🌐 Website: https://smith.langchain.com
- 📘 Docs: https://docs.smith.langchain.com
- Purpose: Multi-agent collaboration framework with role-based agents
- 🌐 Website: https://www.crewai.com
- 📘 Docs: https://docs.crewai.com
- Purpose: Autonomous multi-agent conversations and task execution
- 🌐 Website: https://microsoft.github.io/autogen
- 📘 Docs: https://microsoft.github.io/autogen/docs
- Purpose: Lightweight agent framework with RAG, observability, and agent UIs
- 🌐 Website: https://www.agno.com/
- 📘 Docs: https://docs.agno.com/
- https://docs.phidata.com/introduction
- https://docs.phidata.com/reference/agents/python
- https://github.com/agno-agi/phidata
- Purpose: LlamaIndex delivers industry-leading document parsing and AI agent frameworks. Transform complex documents into automated workflows
- 🌐 Website: https://www.llamaindex.ai/
- 📘 Docs: https://developers.llamaindex.ai/python/framework/
- https://github.com/run-llama/llama_index
- Production-grade framework for RAG + agentic pipeline building with search and reasoning components.
- 🌐 Official Website: https://www.deepset.ai/
- 📘 Documentation: https://docs.deepset.ai/
- A methodology/framework for chaining reasoning and actions in language models.
- 🌐 ReAct Paper & Community Examples:
- https://arxiv.org/abs/2210.03629
- 📘 Implementations: Provided in LangChain / community repos
- Purpose: Low-code / no-code UI for building LangChain-based LLM apps
- 🌐 Website: https://www.langflow.org
- 📘 Docs: https://docs.langflow.org
- Purpose: Workflow automation + AI agents + RAG + tool integrations
- 🌐 Website: https://n8n.io
- 📘 Docs: https://docs.n8n.io
- Purpose: Standardized protocol for connecting LLMs with tools, resources, and data
- 🌐 Website: https://modelcontextprotocol.io
- 📘 Docs: https://modelcontextprotocol.io/docs
- Purpose: High-performance APIs for serving agents and LLM pipelines
- 🌐 Website: https://fastapi.tiangolo.com
- 📘 Docs: https://fastapi.tiangolo.com/tutorial
- Purpose: Flask is a lightweight WSGI web application framework. It is designed to make getting started quick and easy, with the ability to scale up to complex applications.
- 🌐 Website: https://flask.palletsprojects.com/en/stable/api/
- 📘 Docs: https://flask.palletsprojects.com/en/stable/api/
- https://github.com/flask-api/flask-api
- The Apache HTTP Server Project is an effort to develop and maintain an open-source HTTP server for modern operating systems including UNIX and Windows.
- https://github.com/apache/httpd
- https://httpd.apache.org/
- https://httpd.apache.org/docs/
- https://www.youtube.com/watch?v=NACRKwkXKO0
- Purpose: Model serving & deployment for LLMs and AI agents
- 🌐 Website: https://www.bentoml.com
- 📘 Docs: https://docs.bentoml.com
- Purpose: UI for LLMs, GenAI demos, and agent interaction
- 🌐 Website: https://www.gradio.app
- 📘 Docs: https://www.gradio.app/docs
- Purpose: Rapid frontend for AI/ML & GenAI applications
- 🌐 Website: https://streamlit.io
- 📘 Docs: https://docs.streamlit.io
- FAISS → https://github.com/facebookresearch/faiss
- ChromaDB → https://www.trychroma.com
- Docs: FAISS: https://faiss.ai & Chroma: https://docs.trychroma.com
- Pinecone https://www.pinecone.io/
- AstraDb https://docs.datastax.com/en/astra-db-serverless/get-started/quickstart.html
- OpenAI – https://platform.openai.com/docs
- Anthropic (Claude) – https://docs.anthropic.com
- Google Gemini – https://ai.google.dev/docs
- Grok (xAI) – https://x.ai
- Groq AI - https://console.groq.com/docs/quickstart
- Docker – https://docs.docker.com
- AWS (EC2, S3, ECR, Bedrock) – https://docs.aws.amazon.com
- GitHub Actions – https://docs.github.com/actions
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