p2d-deepseek 0.1.8

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==0.1.8

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)

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)

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)

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:

• 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

Your token is tied to your session. If DeepSeek logs you out or your session expires, 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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Response Fields

Every client.chat() call returns a ChatResponse object with these fields:

Field	Type	Description
response	str	Clean final answer from the model
thinking_content	str | None	Raw thinking process (only when thinking=True, else None)
full_response	str	Thinking first + answer below — use this in bots when thinking is enabled
answer	str	Same as response — clean final answer only
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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Thinking Mode — Important

When thinking=True, the model shows its internal reasoning before giving the final answer.

Which field to use?

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

response.response          # "391"  ← just the clean answer
response.thinking_content  # "We need to compute 17 * 23..."  ← just the thinking
response.full_response     # thinking first + answer below (combined in one string)

In a bot — always use full_response

response = client.chat(user_message, thinking=True)

# WRONG — sends two separate messages, thinking appears twice
await message.reply(response.response)
await message.reply(response.thinking_content)

# CORRECT — one message, thinking first, answer below
await message.reply(response.full_response)

Without thinking — use response

response = client.chat(user_message)  # thinking=False by default

await message.reply(response.response)  # just the clean answer, nothing else

full_response when thinking is disabled

If thinking=False, full_response returns the same thing as response — no thinking content, just the clean answer. So you can safely always use full_response and it will work correctly in both cases.

# Works correctly whether thinking=True or thinking=False
await message.reply(response.full_response)

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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.full_response)
# Output:
# We need to compute 17 * 23. 17*20=340, 17*3=51, total is 391.
#
# 17 multiplied by 23 equals 391.

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.full_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.full_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.full_response)

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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Error Handling

from deepseek import DeepSeekClient, DeepSeekConnectionError, DeepSeekAPIError

client = DeepSeekClient(api_key="YOUR_TOKEN_HERE")

try:
    response = client.chat("Hello!")
    print(response.response)
except DeepSeekConnectionError as e:
    print(f"Connection failed: {e}")
except DeepSeekAPIError as e:
    print(f"API error: {e}")

Exception	When it happens
DeepSeekConnectionError	Cannot connect to DeepSeek (network issue)
DeepSeekAPIError	Token expired/invalid, or DeepSeek returned an error

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Demo Script

Save this as demo.py and run it with your token:

from deepseek import DeepSeekClient, DeepSeekConnectionError, DeepSeekAPIError

TOKEN = "YOUR_TOKEN_HERE"

client = DeepSeekClient(api_key=TOKEN)

print("=" * 50)
print("Test 1: Basic chat")
print("=" * 50)
r = client.chat("Say hello in 5 different languages")
print(r.response)
print()

print("=" * 50)
print("Test 2: Thinking mode")
print("=" * 50)
r = client.chat("What is 17 * 23?", thinking=True)
print("-- Thinking --")
print(r.thinking_content)
print()
print("-- Answer --")
print(r.response)
print()
print("-- full_response (use this in bots) --")
print(r.full_response)
print()

print("=" * 50)
print("Test 3: Web search")
print("=" * 50)
r = client.chat("What is today's date?", search=True)
print(r.response)
print()

print("=" * 50)
print("Test 4: Expert model")
print("=" * 50)
r = client.chat("What is the square root of 144?", model="expert")
print(r.response)
print()

print("=" * 50)
print("Test 5: Session continuity")
print("=" * 50)
r1 = client.chat("My name is Alex")
r2 = client.chat("What is my name?", session_id=r1.session_id)
print(r2.response)
print()

print("=" * 50)
print("Test 6: Error handling")
print("=" * 50)
bad_client = DeepSeekClient(api_key="invalid_token")
try:
    bad_client.chat("Hello")
except DeepSeekAPIError as e:
    print(f"Caught error correctly: {e}")

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Telegram Bot Example

import asyncio
from telegram import Update
from telegram.ext import ApplicationBuilder, MessageHandler, filters, ContextTypes
from deepseek import DeepSeekClient, DeepSeekConnectionError, DeepSeekAPIError

TOKEN = "YOUR_DEEPSEEK_TOKEN"
BOT_TOKEN = "YOUR_TELEGRAM_BOT_TOKEN"

client = DeepSeekClient(api_key=TOKEN)


async def handle_message(update: Update, context: ContextTypes.DEFAULT_TYPE):
    user_message = update.message.text

    def run():
        return client.chat(user_message, thinking=True)

    try:
        response = await asyncio.to_thread(run)
        await update.message.reply_text(response.full_response)
    except DeepSeekConnectionError:
        await update.message.reply_text("Connection error, please try again.")
    except DeepSeekAPIError as e:
        await update.message.reply_text(f"Error: {e}")


app = ApplicationBuilder().token(BOT_TOKEN).build()
app.add_handler(MessageHandler(filters.TEXT & ~filters.COMMAND, handle_message))
app.run_polling()

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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
• Always use response.full_response in bots when thinking is enabled to avoid duplicate messages

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License

MIT — made by addy