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Developing applications powered by Large Language Models (LLMs) can be costly, especially during the development phase. Each API call to services like OpenAI or Anthropic consumes tokens, and these costs can accumulate rapidly during iterative development and debugging.
I developed to address this issue. It's a local API proxy that routes your LLM requests to GitHub Copilot, maximizing your free quota usage and minimizing your API costs.
Existing Alternatives and Their Limitations
Some developers turn to local solutions like Ollama, which allows running open-source models such as LLaMA and Mistral locally. While this approach offers privacy and cost benefits, it comes with certain limitations:
- Hardware Requirements: Running these models efficiently requires above-average hardware, such as modern Apple Silicon or high-end GPUs.
- Model Availability: Ollama primarily supports open-source models. Mainstream models like GPT-4, Claude, or Gemini are not available through this platform.
- Performance Variability: The performance and quality of open-source models can be inconsistent compared to their proprietary counterparts.
- Management Overhead: Handling model downloads and dependencies can be cumbersome.
- Seamless API Proxying: Transparently routes your OpenAI-compatible API requests to , allowing you to use GitHub Copilot as a drop-in replacement for expensive LLM APIs during development.
- Supported Endpoints: Handles key endpoints such as /chat/completions for conversational AI and /models for model discovery, ensuring compatibility with most OpenAI-based tools and SDKs.
- Intuitive Admin UI:
- GitHub Authentication: Securely log in with your GitHub account to generate and manage Copilot tokens directly from the interface.
- Manual Token Management: Easily add, remove, or update tokens as needed, giving you full control over your Copilot access.
- Multi-Token Support: Manage several tokens at once, allowing you to distribute requests across them and make the most of your available free quota.
- Usage Analytics: Visualize chat message and code completion statistics to monitor your development activity and optimize token utilization.
- Developing with frameworks like or to prototype and test LLM-powered workflows without incurring API costs.
- Using the for your daily tasks, such as generating commit messages or summarizing code changes.
- Chatting with GitHub Copilot through outside VSCode.
While Copilot Proxy is excellent for development purposes, it's not intended for production use. Copilot doesn't support features like function calls, tools, or streaming outputs that are available in full-fledged APIs. However, for local testing and development cycles, it serves as a cost-effective solution.
Try It Out
If you're building LLM-powered applications and want to optimize your development process without incurring high costs, give Copilot Proxy a try.