apideepseek 0.1.2

High-performance async Python client for the private DeepSeek API

apideepseek

apideepseek is an async Python client for the private DeepSeek API. It supports token or email/password authentication, streaming responses, multi-turn conversations, image uploads, generic file uploads, model modes, and account registration.

Russian documentation: docs/ru/README.md

Installation

pip install apideepseek

Building from source requires a C++17 compiler with AVX2 support and pybind11 for the PoW extension. See docs/en/pow.md.

Quick Start

import asyncio
from apideepseek import DeepSeekClient

async def main():
    async with DeepSeekClient(token="YOUR_TOKEN") as client:
        result = await client.ask("Hello!")
        print(result.text)

asyncio.run(main())

Email/password login also works:

async with DeepSeekClient(email="[e-mail]", password="password123") as client:
    result = await client.ask("Hello!")
    print(result.text)

Model Modes

Mode	Use When	Code
Fast/default	Normal text chat and most file questions	ModelType.DEFAULT
Expert	Harder reasoning or expert answers	ModelType.EXPERT
Vision/recognition	Questions about images	ModelType.VISION

from apideepseek import DeepSeekClient, ModelType

async with DeepSeekClient(token="...", model=ModelType.DEFAULT) as client:
    fast = await client.ask("Short answer: what is asyncio?")
    expert = await client.ask("Analyze this deeply", model=ModelType.EXPERT)

Attach Files to a Prompt

Use file= for one file and files= for several files. Paths are uploaded automatically before the prompt is sent.

from pathlib import Path
from apideepseek import DeepSeekClient

async with DeepSeekClient(token="...") as client:
    result = await client.ask(
        "Summarize this file",
        file=Path("notes.txt"),
    )
    print(result.text)

You can attach source code the same way:

result = await client.ask(
    "Review this function and explain what it returns",
    file=Path("sample_code.py"),
)

Attach several files:

result = await client.ask(
    "Compare the JSON config with the CSV data",
    files=[Path("config.json"), Path("data.csv")],
)

Upload once and reuse the file object:

uploaded = await client.upload_file(Path("report.pdf"))
first = await client.ask("Summarize the report", file=uploaded)
second = await client.ask("List the key risks", file=uploaded)

Raw bytes work too, but you must provide a filename so DeepSeek can detect the format:

data = Path("contract.docx").read_bytes()
uploaded = await client.upload_file(data, filename="contract.docx")
result = await client.ask("Extract the main obligations", file=uploaded)

Common formats are passed through the same upload endpoint: TXT, Python/source code, JSON, CSV, PDF, DOCX, and other formats DeepSeek accepts. If DeepSeek rejects a file as empty or unsupported, EmptyUploadedFileError or DeepSeekError is raised.

Attach Images

Images can be attached through image= or through the generic file= parameter. Use image=/upload_image() when you want local PNG/JPEG validation and image dimensions.

from pathlib import Path
from apideepseek import DeepSeekClient, ModelType

async with DeepSeekClient(token="...") as client:
    result = await client.ask(
        "What is shown in this image?",
        image=Path("photo.jpg"),
        model=ModelType.VISION,
    )
    print(result.text)

Reuse an uploaded image:

img = await client.upload_image(Path("photo.jpg"))
result = await client.ask("Describe the image", image=img, model=ModelType.VISION)

Create a New Conversation

Use client.new_conversation() for a multi-turn chat. It remembers the last message_id and sends it as parent_message_id on the next turn.

chat = client.new_conversation()
await chat.ask("Remember the attached file", file=Path("notes.txt"))
reply = await chat.ask("What did the file say?")
print(reply.text)

Streaming

async for chunk in client.ask_stream("Tell me about Python"):
    print(chunk, end="", flush=True)

Streaming works with files too:

async for chunk in client.ask_stream("Summarize this file", file=Path("notes.txt")):
    print(chunk, end="", flush=True)

Result Object

result = await client.ask("Hello")
print(result.text)
print(result.session_id)
print(result.message_id)

Documentation

• DeepSeekClient methods
• Conversation
• Data types
• Exceptions
• Proof-of-Work