p2d-deepseek 0.1.5

Unofficial Python client for DeepSeek — supports default & expert models, thinking, and web search.

p2d-deepseek

Unofficial Python client for DeepSeek. Supports default and expert models with thinking and web search — no special API needed, just your DeepSeek auth token.

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Installation

Using pip (recommended):

pip install p2d-deepseek

Upgrade to latest version:

pip install p2d-deepseek --upgrade

Install specific version:

pip install p2d-deepseek==0.1.3

Note: The PyPI package is named p2d-deepseek but the Python import name is deepseek. Install with pip install p2d-deepseek, then use from deepseek import DeepSeekClient in your code.

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Getting Your Auth Token

To use this package, you need your DeepSeek auth token. Choose whichever method suits you best.

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Method 1 — LocalStorage (Fastest, Desktop)

This is the quickest way if you are on a desktop browser.

1. Go to chat.deepseek.com and log in
2. Open DevTools — press F12 or right-click anywhere → Inspect
3. Go to the Application tab (if hidden, click » to find it)
4. In the left sidebar, expand Local Storage → click https://chat.deepseek.com
5. Find the key called userToken
6. Copy the value field — that is your token

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Method 2 — Network Tab (Desktop)

Use this if the LocalStorage method does not work for you.

1. Go to chat.deepseek.com and log in
2. Open DevTools → Network tab
3. Send any message in the chat
4. Click on any request going to chat.deepseek.com
5. Open the Headers section
6. Find the authorization header and copy its value (without the Bearer prefix)

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Method 3 — Kiwi Browser (Android / Mobile)

Mobile users can extract the token using Kiwi Browser, which supports DevTools.

1. Install Kiwi Browser from the Play Store
2. Open chat.deepseek.com and log in
3. Tap the menu (⋮) → Developer Tools
4. Go to the Application tab → Local Storage → https://chat.deepseek.com
5. Find the key called userToken and copy the value field

Note: Kiwi Browser is only available on Android. iPhone users can use a laptop or PC with any of the desktop methods above.

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Cloudflare Issues

If you see a "Just a moment..." page or requests are being blocked, DeepSeek has triggered a Cloudflare challenge. In this case:

• Try logging out and back in on chat.deepseek.com
• Wait a few minutes, then grab a fresh token
• If the problem keeps happening, switch to a different network (e.g. mobile data vs Wi-Fi)
• Avoid making too many requests in a short time — space them out to stay under the radar

Your token is tied to your session. If DeepSeek logs you out or your session expires, just repeat any of the steps above to get a fresh one.

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Quick Start

from deepseek import DeepSeekClient

client = DeepSeekClient(api_key="YOUR_TOKEN_HERE")

response = client.chat("What is the capital of France?")
print(response.response)

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Models

Model	Description
default	Standard DeepSeek model — fast, general purpose
expert	Expert model — deeper reasoning, more detailed answers

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Feature Flags

Flag	Type	Default	Description
model	str	"default"	Model to use: "default" or "expert"
thinking	bool	False	Enable chain-of-thought reasoning
search	bool	False	Enable live web search
session_id	str	None	Reuse an existing chat session

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Usage Examples

Basic — default model

from deepseek import DeepSeekClient

client = DeepSeekClient(api_key="YOUR_TOKEN_HERE")

response = client.chat("Explain quantum computing")
print(response.response)

Expert model

response = client.chat(
    "Solve this integral: ∫x²dx",
    model="expert"
)
print(response.response)

Thinking enabled

response = client.chat(
    "What is 17 * 23?",
    thinking=True
)
print(response.response)

if response.thinking_content:
    print("\n--- Thinking ---")
    print(response.thinking_content)

Web search enabled

response = client.chat(
    "What happened in the news today?",
    search=True
)
print(response.response)

Expert + thinking

response = client.chat(
    "Prove that sqrt(2) is irrational",
    model="expert",
    thinking=True
)
print(response.response)

Expert + web search

response = client.chat(
    "Latest AI research papers in 2025",
    model="expert",
    search=True
)
print(response.response)

Default + thinking + web search

response = client.chat(
    "What is today's weather in Mumbai?",
    thinking=True,
    search=True
)
print(response.response)

Expert + thinking + web search (all enabled)

response = client.chat(
    "Analyze the current state of AI regulation globally",
    model="expert",
    thinking=True,
    search=True
)
print(response.response)

if response.thinking_content:
    print("\n--- Thinking Process ---")
    print(response.thinking_content)

Continue a conversation (reuse session)

response1 = client.chat("My name is Alex")
session_id = response1.session_id

response2 = client.chat("What is my name?", session_id=session_id)
print(response2.response)

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Response Object

Every client.chat() call returns a ChatResponse:

Field	Type	Description
response	str	The model's reply (clean plain text)
thinking_content	str | None	Chain-of-thought (only when thinking=True)
session_id	str	Session ID — use to continue conversations
message_id	int	Message ID in the session
model_type	str	Model used (default or expert)
thinking_enabled	bool	Whether thinking was enabled
search_enabled	bool	Whether web search was enabled
status	str	Response status from DeepSeek

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Notes

• Tokens expire when your DeepSeek session ends — refresh using any method above
• Web search slightly increases response time but adds real-time data
• Thinking mode exposes the model's internal reasoning before the final answer
• All responses are automatically stripped of HTML tags and citation markers

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License

MIT — made by addy