Integrate Langtrace with DeepSeek

Introduction

We are excited to announce that Langtrace now supports DeepSeek's family of models natively. This means Langtrace will automatically capture traces and metrics including token usage, cost, latency and model hyper parameters automatically if you are using DeepSeek's family of models.

Setup

1. Sign up to Langtrace, create a project and get a Langtrace API key

2. Install Langtrace SDK

pip install -U langtrace-python-sdk

3. Setup the .env var

export LANGTRACE_API_KEY=YOUR_LANGTRACE_API_KEY

4. Initialize Langtrace in your code

import os
from langtrace_python_sdk import langtrace # Must precede any llm module imports
from openai import OpenAI

langtrace.init(api_key = os.environ['LANGTRACE_API_KEY'])


client = OpenAI(api_key="<DeepSeek API Key>", base_url="https://api.deepseek.com")

response = client.chat.completions.create(
    model="deepseek-chat",
    messages=[
        {"role": "system", "content": "You are a helpful assistant"},
        {"role": "user", "content": "Hello"},
    ],
    stream=False
)

print(chat_completion.choices[0].message.content)

5. See the traces in Langtrace

For more information check out our docs - https://docs.langtrace.ai/supported-integrations/llm-tools/deepseek#deepseek

Useful Resources

• Getting started with Langtrace https://docs.langtrace.ai/introduction

• Langtrace Website https://langtrace.ai/

• Langtrace Discord https://discord.langtrace.ai/

• Langtrace Github https://github.com/Scale3-Labs/langtrace

• Langtrace Twitter(X) https://x.com/langtrace_ai

• Langtrace Linkedin https://www.linkedin.com/company/langtrace/about/