OAIProxy
A self-maintained VS Code extension to use OpenAI/Ollama/Anthropic/Gemini API providers in GitHub Copilot Chat, with presets for OpenAI, Anthropic, Fireworks, Kimi, DeepSeek, Z.AI GLM, Xiaomi MiMo, and MiniMax 🔥
English | 简体中文
Features
- Multi-API support: OpenAI/Ollama/Anthropic/Gemini APIs, with OpenAI-compatible presets for Fireworks, Kimi, DeepSeek, Z.AI GLM, Xiaomi MiMo, MiniMax, ModelScope, SiliconFlow, and more
- Vision models: Full support for image understanding capabilities
- Vision Bridge: Use images in chat with text-only models — OAIProxy automatically describes images via a configured vision model with LRU caching
- Think tag support: Seamless display of model thinking/reasoning blocks across all providers (OpenAI, Ollama, Gemini, Anthropic)
- Thinking Effort control: VS Code's built-in per-model Thinking Effort dropdown in the model picker — customize reasoning effort on the fly
- Advanced configuration: Flexible chat request options with thinking/reasoning control
- Multi-provider management: Configure models from multiple providers simultaneously with automatic API key management
- Provider usage checks: Check Fireworks month-to-date serverless tokens, DeepSeek/Kimi credit balance, MiniMax token-plan remaining quota, and OpenAI/Anthropic month-to-date cost usage from a standalone Provider Usage Check table; Z.AI and MiMo are shown as unavailable until public API-key usage endpoints are documented
- Multi-config per model: Define different settings for the same model (e.g., GLM-4.6 with/without thinking)
- Visual configuration UI: Intuitive interface for managing providers and models
- Auto-retry: Handles API errors (429, 500, 502, 503, 504) with exponential backoff
- Request cancellation: Stop in-progress chat requests instantly — cancellation is wired to HTTP
AbortController across all API modes
- Token usage: Real-time token counting and provider API key management from status bar
- Git integration: Generate commit messages directly from source control with OpenAI/OpenAI Responses/Ollama/Anthropic models
- Import/export: Easily share and backup configurations
- Tools optimization: Optimize agent
read_file tool handling for supported streamed tool calls, avoiding small chunks for large files.
- Structured logging: File-based request/debug logs with rotation, configurable levels (
off/debug/info/warn/error)
Requirements
- VS Code 1.120.0 or higher.
- OpenAI-compatible provider API key.
Quick Start
- Install the OAIProxy VSIX package (
lqdflying.oaiproxy).
- Open VS Code Settings and configure
oaicopilot.baseUrl and oaicopilot.models.
- Open GitHub Copilot Chat interface.
- Click the model picker and select "Manage Models...".
- Choose "OAIProxy" provider.
- Enter your API key — it will be saved locally.
- Select the models you want to add to the model picker.
Compatibility note: OAIProxy keeps the existing oaicopilot.* settings keys, so your JSON model configuration stays valid. Because the extension ID changed to lqdflying.oaiproxy, VS Code may require entering API keys once under the new extension.
Settings Example
"oaicopilot.baseUrl": "https://api-inference.modelscope.cn/v1",
"oaicopilot.models": [
{
"id": "Qwen/Qwen3-Coder-480B-A35B-Instruct",
"owned_by": "modelscope",
"context_length": 256000,
"max_tokens": 8192
}
]
Set max_input_tokens when a provider needs a safety margin below its official context window. OAIProxy advertises that smaller input budget to VS Code and blocks oversized requests before contacting the provider; it does not send max_input_tokens upstream.
Configuration UI
The extension provides a visual configuration interface for managing providers, models, and API keys without editing JSON files manually. Open via the Command Palette (OAIProxy: Open Configuration UI) or click the OAIProxy status bar item.
The Provider Management form includes presets for OpenAI, Anthropic, Fireworks, Kimi, DeepSeek, Z.AI GLM, Xiaomi MiMo, and MiniMax. Selecting a preset fills the provider ID, base URL, and API mode; you still choose the model ID from the provider's current documentation or model list. Example snippets are in examples/openai-responses.jsonc, examples/openai-chat-completions.jsonc, examples/anthropic.jsonc, examples/fireworks.jsonc, examples/zai-glm.jsonc, examples/mimo.jsonc, examples/minimax-openai.jsonc, and examples/minimax-anthropic.jsonc.
The standalone Provider Usage Check table lists configured supported providers dynamically and reports credit, token, token-plan, or cost usage. Fireworks account discovery and month-to-date serverless token checks reuse the normal Fireworks provider key. OpenAI and Anthropic usage/admin keys are stored separately from chat API keys. Z.AI and MiMo entries are shown with unavailable reasons because their current public docs do not expose API-key usage or balance endpoints.
→ Full Configuration Guide
Multi-API Mode
Supports five API protocols: openai (Chat Completions), openai-responses (Responses), ollama, anthropic, and gemini. Specify per-model via the apiMode parameter.
Fireworks, Kimi, DeepSeek, Z.AI GLM, and Xiaomi MiMo use the existing openai mode because their hosted APIs are OpenAI-compatible. MiniMax supports both openai and anthropic modes; MiniMax recommends the Anthropic-compatible M3 endpoint for thinking and interleaved-thinking workflows.
→ Full Multi-API Guide
Fireworks AI
Fireworks is a first-class provider using https://api.fireworks.ai/inference/v1 and full model IDs such as accounts/fireworks/models/deepseek-v4-pro, accounts/fireworks/models/kimi-k2p7-code, and accounts/fireworks/models/glm-5p2. Quick Setup keeps these Fireworks-hosted cards separate from the original DeepSeek, Kimi, and Z.AI cards.
Fireworks prompt caching is enabled by default upstream. OAIProxy adds a stable user affinity value to improve cache routing and reads cached-token telemetry from OpenAI-compatible usage responses. The Fireworks usage check discovers accounts through the public accounts API and reports month-to-date serverless input/output tokens; the HTTP endpoint does not expose rated cost totals.
Z.AI GLM-5.2
Use glm-5.2 as the model ID with the Z.AI GLM Coding Plan endpoint (https://api.z.ai/api/coding/paas/v4). Z.AI's docs list GLM-5.2 as a text model with a 1,000,000-token context window, 131,072 max output tokens, thinking/reasoning support, reasoning effort, and tool use. The Quick Setup preset enables thinking, sets reasoning_effort: "max", and sets thinking.clear_thinking: false to preserve returned reasoning content in follow-up requests.
MiniMax M3
Use MiniMax-M3 as the model ID. MiniMax's M3 docs list a 1,000,000-token context window, tool use, coding/agentic workflows, adaptive thinking, and native image/video input. OAIProxy supports M3 through the existing MiniMax OpenAI-compatible preset (https://api.minimax.io/v1) and MiniMax Anthropic-compatible preset (https://api.minimax.io/anthropic).
For OpenAI mode, use max_completion_tokens, thinking: { "type": "adaptive" }, and extra.reasoning_split: true to stream thinking separately. For Anthropic mode, use max_tokens and thinking: { "type": "adaptive" }. Set vision: true for M3 so OAIProxy forwards image and supported video LanguageModelDataParts directly instead of routing image inputs through Vision Bridge.
Vision Bridge
Use images with text-only models. OAIProxy automatically describes images via a configured vision-capable model before forwarding as text, with LRU caching (50 entries, ~500KB).
→ Vision Bridge Guide
Multi-Provider Guide
Configure models from multiple providers simultaneously. Use owned_by to group models by provider, with automatic per-provider API key management stored as oaicopilot.apiKey.<provider>.
→ Multi-Provider Guide
Multi-config for the same model
Define multiple configurations for the same model ID via configId (e.g., glm-4.6::thinking and glm-4.6::no-thinking), each with independent settings.
→ Multi-config Guide
Thinking Effort Control
VS Code 1.120+ exposes a per-model Thinking Effort dropdown in the model picker. Enable it with supports_reasoning_effort: true. DeepSeek models default to high/max; Claude Sonnet 4.6 is detected automatically and maps to Anthropic output_config.effort.
→ Thinking Effort Guide
Specify custom HTTP headers per model provider (API versioning, additional auth, debugging tokens). Merged with default headers on each request.
→ Custom Headers Guide
Custom Request Body Parameters
Use the extra field to inject arbitrary JSON parameters into the API request body for all API modes. Override standard parameters or add provider-specific features.
→ Custom Request Body Guide
Prompt / KV Cache
OAIProxy surfaces provider cache-hit usage in structured logs and applies safe cache request shaping where supported. OpenAI endpoints get a stable prompt_cache_key by default, Fireworks gets a stable user affinity value, and Anthropic-compatible cache_control writes are opt-in via prompt_cache.anthropic.enabled or explicit VS Code cache_control message parts. DeepSeek, Xiaomi MiMo, MiniMax OpenAI mode, and Gemini continue to use provider automatic/implicit caching.
OpenAI previous_response_id is kept for conversation state only; OpenAI still bills previous input tokens in the response chain. Use oaicopilot.logLevel: "info" or "debug" and inspect cache.usage log entries to verify actual cache reads/hits.
Model Parameters
Full reference of all 30+ configurable model parameters (id, owned_by, temperature, reasoning_effort, vision, toolCalling, apiMode, etc.).
→ Model Parameters Reference
Logging
OAIProxy always writes extension lifecycle events (install, update, activate) to the VS Code Output panel. Open Output: Show Output and select OAIProxy.
For request/debug logs, add this to VS Code User Settings JSON:
"oaicopilot.logLevel": "debug"
Valid values are off, debug, info, warn, and error. File logs are written to ~/.copilot/oaiproxy/logs/ with daily rotation (logs older than 7 days are automatically cleaned up). Sensitive header values (Authorization, x-api-key, x-goog-api-key) are automatically redacted from log output.
Thanks to
Thanks to all the people who contribute.
Support & License
