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Multi-round Conversation

This guide will introduce how to use the DeepSeek /chat/completions API for multi-turn conversations.

The DeepSeek /chat/completions API is a "stateless" API, meaning the server does not record the context of the user's requests. Therefore, the user must concatenate all previous conversation history and pass it to the chat API with each request.

The following code in Python demonstrates how to concatenate context to achieve multi-turn conversations.

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

# Round 1
messages = [{"role": "user", "content": "What's the highest mountain in the world?"}]
response = client.chat.completions.create(
    model="deepseek-chat",
    messages=messages
)

messages.append(response.choices[0].message)
print(f"Messages Round 1: {messages}")

# Round 2
messages.append({"role": "user", "content": "What is the second?"})
response = client.chat.completions.create(
    model="deepseek-chat",
    messages=messages
)

messages.append(response.choices[0].message)
print(f"Messages Round 2: {messages}")

In the first round of the request, the messages passed to the API are:

[
    {"role": "user", "content": "What's the highest mountain in the world?"}
]

In the second round of the request:

  1. Add the model's output from the first round to the end of the messages.
  2. Add the new question to the end of the messages.

The messages ultimately passed to the API are:

[
    {"role": "user", "content": "What's the highest mountain in the world?"},
    {"role": "assistant", "content": "The highest mountain in the world is Mount Everest."},
    {"role": "user", "content": "What is the second?"}
]