#117 · Primary category： LLM Application Frameworks
langfun
OO for LLMs
Project last updated：08/29/26
GitHub Stars
914
Forks
80
Contributors
14
License
Apache-2.0
Why we included this project
Langfun gives Python developers a different way to work with LLMs. Instead of stitching together prompt strings and parsing whatever comes back, you define your expected output as a PyGlove object and let the library call a model to fill in the fields. That keeps results structured and checkable. One API covers Gemini, GPT, Claude, and Llama, so you can switch providers without touching call sites. It fits workflows that need typed, dependable output, such as batch jobs, pipelines, or agent loops, and it supports prompts that mix text and images. If you already use PyGlove or just want LLM output that behaves like a normal Python type, this is worth a close look.
Articles for this project
No articles for this project yet.
To suggest a topic or contribute an article, contact us.
Related projects in this category
langchain
The agent engineering platform.
dify
Build Agentic workflows, RAG pipelines, with rich AI model and tool support on one collaborative workspace. Deploy on cloud, VPC, or self-hosted, so teams move from prototype to production without rebuilding the stack.
headroom
Compress tool outputs, logs, files, and RAG chunks before they reach the LLM. 20% fewer tokens for coding agents, 60-95% fewer tokens for JSON, same answers. Library, proxy, MCP server.
litellm
The fastest, litest AI Gateway. Rust core with Python SDK. Call 100+ LLM APIs in OpenAI (or native) format with cost tracking, guardrails, load balancing, and logging [Bedrock, Azure, OpenAI, Anthropic, OpenAI, VertexAI, vLLM, Nvidia NIM]
llama_index
LlamaIndex is the leading document agent and OCR platform