聊天(Chat)
Deepseek reasoning 對話格式(Reasoning Content)
📝 簡介
Deepseek-reasoner 是 DeepSeek 推出的推理模型。在輸出最終回答之前,模型會先輸出一段思維鏈內容,以提升最終答案的準確性。API 向使用者開放 deepseek-reasoner 思維鏈的內容,以供使用者檢視、展示、蒸餾使用。
💡 請求示例
基礎文字對話 ✅
curl https://api.deepseek.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $API_KEY" \
-d '{
"model": "deepseek-reasoner",
"messages": [
{
"role": "user",
"content": "9.11 and 9.8, which is greater?"
}
],
"max_tokens": 4096
}'響應示例:
{
"id": "chatcmpl-123",
"object": "chat.completion",
"created": 1677652288,
"model": "deepseek-reasoner",
"choices": [
{
"index": 0,
"message": {
"role": "assistant",
"reasoning_content": "讓我一步步思考:\n1. 我們需要比較9.11和9.8的大小\n2. 兩個數都是小數,我們可以直接比較\n3. 9.8 = 9.80\n4. 9.11 `< 9.80\n5. 所以9.8更大",
"content": "9.8 is greater than 9.11."
},
"finish_reason": "stop"
}
],
"usage": {
"prompt_tokens": 10,
"completion_tokens": 15,
"total_tokens": 25
}
}流式響應 ✅
curl https://api.deepseek.com/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer $API_KEY" \
-d '{
"model": "deepseek-reasoner",
"messages": [
{
"role": "user",
"content": "9.11 and 9.8, which is greater?"
}
],
"stream": true
}'流式響應示例:
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"deepseek-reasoner","choices":[{"index":0,"delta":{"role":"assistant","reasoning_content":"讓我"},"finish_reason":null}]}
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"deepseek-reasoner","choices":[{"index":0,"delta":{"reasoning_content":"一步步"},"finish_reason":null}]}
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"deepseek-reasoner","choices":[{"index":0,"delta":{"reasoning_content":"思考:"},"finish_reason":null}]}
// ... 更多思維鏈內容 ...
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"deepseek-reasoner","choices":[{"index":0,"delta":{"content":"9.8"},"finish_reason":null}]}
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"deepseek-reasoner","choices":[{"index":0,"delta":{"content":" is greater"},"finish_reason":null}]}
// ... 更多最終答案內容 ...
{"id":"chatcmpl-123","object":"chat.completion.chunk","created":1694268190,"model":"deepseek-reasoner","choices":[{"index":0,"delta":{},"finish_reason":"stop"}]}📮 請求
端點
POST /v1/chat/completions鑑權方法
在請求頭中包含以下內容進行 API 金鑰認證:
Authorization: Bearer $API_KEY其中 $DEEPSEEK_API_KEY 是您的 API 金鑰。
請求體引數
messages
- 型別:陣列
- 必需:是
到目前為止包含對話的訊息列表。請注意,如果您在輸入的 messages 序列中傳入了 reasoning_content,API 會返回 400 錯誤。
model
- 型別:字串
- 必需:是
- 值:deepseek-reasoner
要使用的模型 ID。目前僅支援 deepseek-reasoner。
max_tokens
- 型別:整數
- 必需:否
- 預設值:4096
- 最大值:8192
最終回答的最大長度(不含思維鏈輸出)。請注意,思維鏈的輸出最多可以達到 32K tokens。
stream
- 型別:布林值
- 必需:否
- 預設值:false
是否使用流式響應。
不支援的引數
以下引數當前不支援:
- temperature
- top_p
- presence_penalty
- frequency_penalty
- logprobs
- top_logprobs
注意:為了相容已有軟體,設定 temperature、top_p、presence_penalty、frequency_penalty 引數不會報錯,但也不會生效。設定 logprobs、top_logprobs 會報錯。
支援的功能
- 對話補全
- 對話字首續寫 (Beta)
不支援的功能
- Function Call
- Json Output
- FIM 補全 (Beta)
📥 響應
成功響應
返回一個聊天補全物件,如果請求被流式傳輸,則返回聊天補全塊物件的流式序列。
id
- 型別:字串
- 說明:響應的唯一識別符號
object
- 型別:字串
- 說明:物件型別,值為 "chat.completion"
created
- 型別:整數
- 說明:響應建立時間戳
model
- 型別:字串
- 說明:使用的模型名稱,值為 "deepseek-reasoner"
choices
- 型別:陣列
- 說明:包含生成的回覆選項
- 屬性:
index: 選項索引message: 包含角色、思維鏈內容和最終回答的訊息物件role: 角色,值為 "assistant"reasoning_content: 思維鏈內容content: 最終回答內容
finish_reason: 完成原因
usage
- 型別:物件
- 說明:token 使用統計
- 屬性:
prompt_tokens: 提示使用的 token 數completion_tokens: 補全使用的 token 數total_tokens: 總 token 數
📝 上下文拼接說明
在每一輪對話過程中,模型會輸出思維鏈內容(reasoning_content)和最終回答(content)。在下一輪對話中,之前輪輸出的思維鏈內容不會被拼接到上下文中,如下圖所示:

注意
如果您在輸入的 messages 序列中,傳入了reasoning_content,API 會返回 400 錯誤。因此,請刪除 API 響應中的 reasoning_content 欄位,再發起 API 請求,方法如下方使用示例所示。
使用示例:
from openai import OpenAI
client = OpenAI(api_key="<DeepSeek API Key>`", base_url="https://api.deepseek.com")
# 第一輪對話
messages = [{"role": "user", "content": "9.11 and 9.8, which is greater?"}]
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages
)
reasoning_content = response.choices[0].message.reasoning_content
content = response.choices[0].message.content
# 第二輪對話 - 只拼接最終回答content
messages.append({'role': 'assistant', 'content': content})
messages.append({'role': 'user', 'content': "How many Rs are there in the word 'strawberry'?"})
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages
)流式響應示例:
# 第一輪對話
messages = [{"role": "user", "content": "9.11 and 9.8, which is greater?"}]
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages,
stream=True
)
reasoning_content = ""
content = ""
for chunk in response:
if chunk.choices[0].delta.reasoning_content:
reasoning_content += chunk.choices[0].delta.reasoning_content
else:
content += chunk.choices[0].delta.content
# 第二輪對話 - 只拼接最終回答content
messages.append({"role": "assistant", "content": content})
messages.append({'role': 'user', 'content': "How many Rs are there in the word 'strawberry'?"})
response = client.chat.completions.create(
model="deepseek-reasoner",
messages=messages,
stream=True
)