Your DeepSeek web account, now an OpenAI-compatible API

What it does deepseek2api is a Python adapter that logs into DeepSeek’s consumer web interface with real account credentials and re-exposes the chat backend as an OpenAI-compatible REST API. It translates your /v1/chat/completions requests into DeepSeek web sessions, then streams the responses back with token counts and model IDs attached. In short, it lets you treat a web login like an API key.

The interesting bit The project uses DeepSeek’s own web app as its backend infrastructure. Because a single account only supports one concurrent output stream, the server rotates through a pool of logins to load-balance traffic across your personal accounts. It also scrubs the native DeepSeek conversation history after each API exchange, which keeps the web account’s inbox tidy and reduces server-side clutter.

Key highlights

• OpenAI-compatible surface: supports /v1/chat/completions and /v1/models, including deepseek-chat, deepseek-reasoner (R1), and search-enabled variants.
• Credential pooling: accepts an array of email or mobile/password pairs and round-robins them, since one account handles only one stream at a time.
• Session hygiene: automatically deletes the underlying DeepSeek conversation after the chat finishes.
• Token accounting: returns usage fields (prompt_tokens, completion_tokens) in OpenAI format, even though the figures originate from the unofficial interface.
• Tool calls and streaming: advertises support for function calling and SSE streaming through the translated endpoint.

Caveats

• The README explicitly warns that reverse APIs are unstable and that accounts risk being banned; the authors label this as research-grade, self-use software.
• Multi-turn conversations are implemented by merging message history into a single prompt, which the README admits can degrade capability and is capped by single-round token limits.
• Vercel’s free tier is effectively incompatible because its 10-second response timeout is shorter than DeepSeek’s typical generation time.

Verdict Useful if you want to pipe DeepSeek’s models into existing OpenAI clients without official API access. Avoid it if you need reliability, predictable rate limits, or a clean terms-of-service story.