DeepSeek Opens Full-Stack App API for One-to-One App Replication
DeepSeek has opened its full-stack application API, letting developers enable parameters to obtain complete conversational capabilities including web search, deep-thinking search, file input and link reading, with tool calls and context assembly handled server-side. Voice and underlying capabilities (Search, Fetch, OCR, ASR, TTS) are also available as standalone endpoints, and an open-source frontend demo supports importing chat history, enabling one-to-one replication of the full DeepSeek App.
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IT之家 November 13 news: This evening (the 13th), DeepSeek announced the official opening of its full-suite application API: by enabling the corresponding parameters in the existing API, you can obtain conversational features such as deep-thinking search and file input; voice and related underlying capabilities have also been opened as independent interfaces (including OCR, ASR, TTS, etc.), supporting individual or combined invocation.
Developers can easily implement complex conversational features in their own applications, and even replicate the complete DeepSeek App 1.
This update directly integrates the various interactive features of the DeepSeek App into the existing API. After enabling the corresponding parameters, the related tool calls and context assembly are all handled automatically by the server.
Currently, the V4.1-Flash model (deepseek-flash) supports the following capabilities under the Messages, Responses, and Chat Completions interfaces:
- Web search: In non-thinking mode, after enabling the deepseek_web_search tool, the model can automatically initiate web or image searches based on the question and answer with citations;
- Deep-thinking search: In thinking mode, after enabling the deepseek_web_search tool, the model can autonomously search the web and read links during multi-step reasoning;
- File input: Supports uploading files in PDF, Office, image, and other formats, completing plain-text extraction or mixed text-image parsing, and then splicing them into the conversation context for the model to answer;
- Link reading: After enabling the deepseek_read_url tool, the model can automatically recognize links in user messages, fetch the web page content, and answer in combination with the context;
- Model security: After enabling the security verification parameter, DeepSeek will provide basic risk control, reviewing model input and output, and returning a refusal identifier when a risk is hit. If you provide application services externally, be sure to enable this parameter and assume obligations such as content security review, large-model registration, and AI labeling.
In addition, to make it easier for developers to integrate their own workflows more flexibly, the above underlying capabilities and voice capabilities are all supported as independent interfaces for separate invocation, including: Search, Fetch, OCR, ASR, TTS.
Using the above interfaces, developers can implement features basically consistent with the DeepSeek App. To intuitively demonstrate this effect, DeepSeek has built and open-sourced a lightweight front-end Demo based on the new API, which supports directly importing DeepSeek conversation history.
- Demo experience entry: https://cdn.deepseek.com/chat-demo
- Sample code entry: https://github.com/deepseek-ai/chat-demo

According to IT之家, when users call the DeepSeek API to use extended capabilities, in addition to Token fees, they will also be charged for the invocation of related tools.
- Text / image search: 5 yuan / thousand calls
- Web page fetching: 5 yuan / thousand calls
- Text recognition: 1.5 yuan / thousand pages
- Speech recognition: limited-time 50% off, 0.39 yuan / hour after discount
- Speech synthesis: limited-time 50% off, 1.5 yuan / ten thousand characters after discount
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