opencode-llm-proxy

One local endpoint. Every model you have access to. Any API format.

opencode-llm-proxy is an OpenCode plugin that starts a local HTTP server on http://127.0.0.1:4010. It translates between the API format your tool speaks and whichever LLM provider OpenCode has configured — so you never reconfigure the same models twice.

Your tool (OpenAI / Anthropic / Gemini SDK)
         │
         ▼  http://127.0.0.1:4010
  opencode-llm-proxy
         │
         ▼  OpenCode SDK
  GitHub Copilot · Anthropic · Gemini · Ollama · OpenRouter · Bedrock · …

Supported API formats — all with streaming:

Format	Endpoint
OpenAI Chat Completions	POST /v1/chat/completions
OpenAI Responses API	POST /v1/responses
Anthropic Messages API	POST /v1/messages
Google Gemini	POST /v1beta/models/:model:generateContent

---

Why

Most LLM tools speak exactly one API dialect. OpenCode already manages connections to every provider you use. This proxy bridges the two — your tools keep working as-is, and you change which model they use in one place.

Common situations it solves:

• You have a GitHub Copilot subscription. Open WebUI, Chatbox, or a VS Code extension only accepts an OpenAI-compatible URL. Point them at the proxy — done.
• You run Ollama locally. Your Python scripts use the OpenAI SDK. Set base_url to the proxy and use your Ollama model IDs directly.
• You want to swap models without code changes. Your app talks to the proxy; you change the model in OpenCode config.
• You want to share your models on a LAN. Expose the proxy on 0.0.0.0 and give teammates the URL.
• You use the Anthropic SDK but want to route through GitHub Copilot or Bedrock. No code change in the SDK — just point it at the proxy.

---

Quickstart

npm install opencode-llm-proxy

Add to opencode.json:

{
  "plugin": ["opencode-llm-proxy"]
}

Start OpenCode — the proxy starts automatically:

opencode

Send a request:

curl http://127.0.0.1:4010/v1/chat/completions \
  -H "Content-Type: application/json" \
  -d '{
    "model": "github-copilot/claude-sonnet-4.6",
    "messages": [{"role": "user", "content": "Hello!"}]
  }'

---

Install

npm plugin (recommended)

npm install opencode-llm-proxy

Add to your global ~/.config/opencode/opencode.json (works everywhere) or a project-level opencode.json:

{
  "plugin": ["opencode-llm-proxy"]
}

Copy the file

Global — loaded for every OpenCode session:

curl -o ~/.config/opencode/plugins/llm-proxy.js \
  https://raw.githubusercontent.com/KochC/opencode-llm-proxy/main/index.js

Per-project — loaded only in this directory:

mkdir -p .opencode/plugins
curl -o .opencode/plugins/llm-proxy.js \
  https://raw.githubusercontent.com/KochC/opencode-llm-proxy/main/index.js

---

Configuration

Variable	Default	Description
OPENCODE_LLM_PROXY_HOST	127.0.0.1	Bind address. 0.0.0.0 to expose on LAN or Docker.
OPENCODE_LLM_PROXY_PORT	4010	TCP port.
OPENCODE_LLM_PROXY_TOKEN	(unset)	Bearer token required on every request. Unset = no auth.
OPENCODE_LLM_PROXY_CORS_ORIGIN	*	Access-Control-Allow-Origin value for browser clients.

OPENCODE_LLM_PROXY_HOST=0.0.0.0 \
OPENCODE_LLM_PROXY_TOKEN=my-secret \
opencode

---

Using with SDKs and tools

OpenAI SDK (JS/TS)

import OpenAI from "openai"

const client = new OpenAI({
  baseURL: "http://127.0.0.1:4010/v1",
  apiKey: "unused",
})

const response = await client.chat.completions.create({
  model: "github-copilot/claude-sonnet-4.6",
  messages: [{ role: "user", content: "Explain recursion." }],
})

OpenAI SDK (Python)

from openai import OpenAI

client = OpenAI(base_url="http://127.0.0.1:4010/v1", api_key="unused")

response = client.chat.completions.create(
    model="ollama/qwen2.5-coder",
    messages=[{"role": "user", "content": "Write a Python function to reverse a string."}],
)
print(response.choices[0].message.content)

Anthropic SDK (Python)

import anthropic

client = anthropic.Anthropic(
    base_url="http://127.0.0.1:4010",
    api_key="unused",
)

message = client.messages.create(
    model="anthropic/claude-3-5-sonnet",
    max_tokens=1024,
    messages=[{"role": "user", "content": "What is the Pythagorean theorem?"}],
)
print(message.content[0].text)

Anthropic SDK (JS/TS)

import Anthropic from "@anthropic-ai/sdk"

const client = new Anthropic({
  baseURL: "http://127.0.0.1:4010",
  apiKey: "unused",
})

const message = await client.messages.create({
  model: "anthropic/claude-opus-4",
  max_tokens: 1024,
  messages: [{ role: "user", content: "Explain async/await." }],
})

Google Generative AI SDK (JS/TS)

import { GoogleGenerativeAI } from "@google/generative-ai"

const genAI = new GoogleGenerativeAI("unused", {
  baseUrl: "http://127.0.0.1:4010",
})

const model = genAI.getGenerativeModel({ model: "google/gemini-2.0-flash" })
const result = await model.generateContent("What is machine learning?")
console.log(result.response.text())

LangChain (Python)

from langchain_openai import ChatOpenAI

llm = ChatOpenAI(
    model="anthropic/claude-3-5-sonnet",
    openai_api_base="http://127.0.0.1:4010/v1",
    openai_api_key="unused",
)

response = llm.invoke("What are the SOLID principles?")
print(response.content)

Open WebUI

1. Settings → Connections → OpenAI API
2. Set API Base URL to http://127.0.0.1:4010/v1
3. Leave API Key blank (or set to your OPENCODE_LLM_PROXY_TOKEN)
4. Save — all your OpenCode models appear in the model picker

Running Open WebUI in Docker? Use http://host.docker.internal:4010/v1 and set OPENCODE_LLM_PROXY_HOST=0.0.0.0.

Chatbox

Settings → AI Provider → OpenAI API → set API Host to http://127.0.0.1:4010.

Continue (VS Code / JetBrains)

In ~/.continue/config.json:

{
  "models": [
    {
      "title": "Claude via OpenCode",
      "provider": "openai",
      "model": "anthropic/claude-3-5-sonnet",
      "apiBase": "http://127.0.0.1:4010/v1",
      "apiKey": "unused"
    }
  ]
}

Zed

In ~/.config/zed/settings.json:

{
  "language_models": {
    "openai": {
      "api_url": "http://127.0.0.1:4010/v1",
      "available_models": [
        {
          "name": "github-copilot/claude-sonnet-4.6",
          "display_name": "Claude (OpenCode)",
          "max_tokens": 8096
        }
      ]
    }
  }
}

---

Finding model IDs

curl http://127.0.0.1:4010/v1/models | jq '.data[].id'
# "github-copilot/claude-sonnet-4.6"
# "anthropic/claude-3-5-sonnet"
# "ollama/qwen2.5-coder"
# ...

Use provider/model for clarity. Bare model IDs (e.g. gpt-4o) work if unambiguous across your providers.

To force a specific provider without changing the model string, add:

x-opencode-provider: anthropic

---

API reference

GET /health

{ "healthy": true, "service": "opencode-openai-proxy" }

GET /v1/models

Returns all models from all configured providers in OpenAI list format.

POST /v1/chat/completions

OpenAI Chat Completions. Required fields: model, messages. Optional: stream, temperature, max_tokens.

POST /v1/responses

OpenAI Responses API. Required fields: model, input. Optional: instructions, stream, max_output_tokens.

POST /v1/messages

Anthropic Messages API. Required fields: model, messages. Optional: system, max_tokens, stream.

Errors are returned in Anthropic format: { "type": "error", "error": { "type": "...", "message": "..." } }.

POST /v1beta/models/:model:generateContent

Google Gemini non-streaming. Model name in URL path. Required field: contents. Optional: systemInstruction, generationConfig.

POST /v1beta/models/:model:streamGenerateContent

Same as above, returns newline-delimited JSON stream.

---

How it works

Each request:

1. Is authenticated if OPENCODE_LLM_PROXY_TOKEN is set
2. Has its model resolved — provider/model, bare model ID, or Gemini URL path
3. Creates a temporary OpenCode session (visible in the session list)
4. Sends the prompt via client.session.prompt / client.session.promptAsync
5. Returns the response in the same format as the request

Streaming uses OpenCode's client.event.subscribe() SSE stream. Text deltas are forwarded in real time.

---

Limitations

• Text only — image, audio, and file inputs are ignored
• No tool/function calling — all OpenCode tools are disabled for proxy sessions
• No cross-request session state — send full conversation history on every request
• Temperature and max tokens are advisory (passed as system prompt hints)

---

License

MIT