Open Responses – Drop-In OpenAI Responses API Alternative for Any LLM

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Open Responses – Drop-In OpenAI Responses API Alternative for Any LLM

Hello HN! I just open-sourced Open Responses , a self-hosted implementation of OpenAI’s new Responses API that works with any LLM backend. It lets you self-host your own server compatible with the official API, but you’re free to plug in Claude, Qwen, R1, or other models. It’s a drop-in replacement. The motivation: I wanted to use the awesome new agents SDK & the Responses API from OpenAI but with other models, including locally. To try it out, just run: npx -y open-responses init # or uvx/pipx This is an early release, and I’d really love feedback and help from the community to make it better. Docs: https://docs.julep.ai/responses Repo: https://github.com/julep-ai/open-responses Why: - Use any model - Self-hosted and Private - Drop-in compatibility - Easy to deploy via docker-compose or our CLI - Built-in support for tools Whenever the model wants to use a tool (like web_search), the server automatically executes those with open & pluggable alternatives (e.g. Brave Search API). For example, once you have the service up, to use Agents SDK with Claude, you can do: from openai import AsyncOpenAI from agents import set_default_openai_client # Create and configure the OpenAI client custom_client = AsyncOpenAI(base_url="http://localhost:8080/", api_key="your_api_key") set_default_openai_client(custom_client) from agents import Agent, Runner agent = Agent( name="Test Agent", instructions="You are a helpful assistant.", model="claude-3.5-sonnet", ) result = await Runner.run(agent, "Hello! Are you working correctly?") This will route the call to Claude (through its API) and return the summary, just as if OpenAI’s API handled it! Roadmap: - Full support for streaming, and voice agents. - Add file search integration using pgvector. - Support more models out-of-the-box. - Helm chart for Kubernetes. Please give feedback! I’d love to know what features or improvements are most important. For example, is fine-tuning or vector DB integration something you’d want? Does this sound useful for your projects? Thanks for reading, and I hope some of you will try it out or even contribute!