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Python Libraries for LLM Applications: LangChain, LlamaIndex, DSPy & More

Python libraries for building LLM apps: models and serving, orchestration and agents, structured output, SDKs and evaluation.

29 topics•6 categories•Updated October 2026

Models, Fine-tuning & Serving

5 entries

Load, adapt and serve models.

01Hugging Face TransformersPretrained models for text, vision, audio and multimodal tasks. 02PEFTParameter-efficient fine-tuning methods. 03Sentence TransformersEmbedding and reranking models. 04vLLMHigh-throughput LLM inference and serving engine. 05UnslothFaster fine-tuning for LLMs; blocks automated checks.

Orchestration, RAG & Agents

9 entries

Frameworks for chains, retrieval and agents.

06LangChainFramework for LLM applications and agents. 07LangGraphStateful, graph-based agent orchestration. 08LlamaIndexData framework for RAG and agents. 09HaystackOpen-source framework for RAG and agent pipelines. 10CrewAIMulti-agent orchestration framework. 11Pydantic AIAgent framework from the Pydantic team; the docs now live at pydantic.dev. 12smolagentsLightweight agent library from Hugging Face. 13OpenAI Agents SDKOpenAI framework for multi-agent workflows. 14AutoGPTPlatform for autonomous AI agents; very active in October 2026.

Prompting, Structured Output & Gateways

3 entries

Control and route model calls.

15DSPyProgramming, not prompting, language models. 16InstructorStructured outputs from LLMs using Pydantic. 17LiteLLMOne interface and gateway for many LLM providers.

Vendor SDKs & Vector Stores

5 entries

Client libraries and storage.

18OpenAI Python SDKOfficial OpenAI client library. 19Anthropic Python SDKOfficial Anthropic client library. 20Google Gen AI Python SDKOfficial Google client library for Gemini models. 21Ollama Python libraryClient for running models locally with Ollama. 22ChromaOpen-source embedding database.

Evaluation

1 entries

Test LLM applications.

23DeepEvalEvaluation framework for LLM applications; very active in October 2026.

Related Pages

6 entries

Neighbouring pages on this site.

24PythonPython hub. 25Large Language ModelsLLM hub. 26AI Agent FrameworksAgent frameworks. 27Vector DatabasesVector databases. 28LLMOpsLLM operations. 29Python Frameworks for AIAI frameworks for Python.

Frequently Asked Questions

Which Python library should I use to build an LLM app?

Use a vendor SDK for direct model calls, LangChain, LlamaIndex or Haystack for retrieval and chains, LangGraph, CrewAI or Pydantic AI for agents, and DSPy or Instructor for structured, programmatic prompting.

How do I serve an open model?

vLLM is a common high-throughput serving engine, while Ollama is convenient for running models locally.

How do I evaluate an LLM application?

Use an evaluation framework such as DeepEval to test outputs against metrics and datasets before and after changes.

How current is this page?

Links were checked in October 2026. Sites that block automated checks are kept and may need a manual click. Last-commit dates are from GitHub in October 2026 and show activity only; check each project's release notes before adopting it. The page was previously also stored under a file name with spaces; that copy is now a redirect.