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POST
https://api.apimart.ai
/
v1
/
chat
/
completions
curl --request POST \
  --url https://api.apimart.ai/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-4o", # Can be replaced with any supported model ID
    "messages": [
      {
        "role": "system",
        "content": "You are a professional AI assistant."
      },
      {
        "role": "user",
        "content": "Tell me about the history of artificial intelligence."
      }
    ]
  }'

{
  "code": 200,
  "data": {
    "id": "chatcmpl-9876543210",
    "object": "chat.completion",
    "created": 1677652288,
    "model": "gpt-4o",
    "choices": [
      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "The history of artificial intelligence (AI) dates back to the 1950s...\n\n1. **Early Period (1950s-1960s)**: The proposal of the Turing Test marked the beginning of AI research...\n\n2. **Expert Systems Era (1970s-1980s)**: Rule-based systems began to be applied in medical diagnosis, financial analysis, and other fields...\n\n3. **Rise of Machine Learning (1990s-2000s)**: Statistical learning methods gradually became mainstream...\n\n4. **Deep Learning Revolution (2010s-Present)**: Breakthroughs in neural network technology brought explosive growth to AI..."
        },
        "finish_reason": "stop"
      }
    ],
    "usage": {
      "prompt_tokens": 28,
      "completion_tokens": 320,
      "total_tokens": 348
    }
  }
}

curl --request POST \
  --url https://api.apimart.ai/v1/chat/completions \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '{
    "model": "gpt-4o", # Can be replaced with any supported model ID
    "messages": [
      {
        "role": "system",
        "content": "You are a professional AI assistant."
      },
      {
        "role": "user",
        "content": "Tell me about the history of artificial intelligence."
      }
    ]
  }'

{
  "code": 200,
  "data": {
    "id": "chatcmpl-9876543210",
    "object": "chat.completion",
    "created": 1677652288,
    "model": "gpt-4o",
    "choices": [
      {
        "index": 0,
        "message": {
          "role": "assistant",
          "content": "The history of artificial intelligence (AI) dates back to the 1950s...\n\n1. **Early Period (1950s-1960s)**: The proposal of the Turing Test marked the beginning of AI research...\n\n2. **Expert Systems Era (1970s-1980s)**: Rule-based systems began to be applied in medical diagnosis, financial analysis, and other fields...\n\n3. **Rise of Machine Learning (1990s-2000s)**: Statistical learning methods gradually became mainstream...\n\n4. **Deep Learning Revolution (2010s-Present)**: Breakthroughs in neural network technology brought explosive growth to AI..."
        },
        "finish_reason": "stop"
      }
    ],
    "usage": {
      "prompt_tokens": 28,
      "completion_tokens": 320,
      "total_tokens": 348
    }
  }
}

​
Authorizations

​
Authorization
string
required
All API endpoints require Bearer Token authenticationGet your API Key:Visit the API Key Management Page to get your API KeyAdd it to the request header:
Authorization: Bearer YOUR_API_KEY

​
Body

​
model
string
required
Model nameSupported models include:
  • OpenAI: gpt-5, gpt-5-chat-latest, gpt-5-mini, gpt-5-nano, gpt-5-pro
  • Anthropic: claude-sonnet-4-5-20250929, claude-opus-4-1-20250805, claude-haiku-4-5-20251001, claude-opus-4-1-20250805-thinking, claude-sonnet-4-5-20250929-thinking
  • Google: gemini-2.5-pro, gemini-2.5-flash, gemini-2.5-pro-thinking, gemini-2.5-flash-lite
  • DeepSeek: deepseek-v3.1-250821, deepseek-v3.1-think-250821, deepseek-v3-0324
  • Doubao: doubao-seed-1-6-251015, doubao-seed-1-6-flash-250828, doubao-seed-1-6-thinking-250715
  • More models being added continuously…
​
messages
array
required
List of conversation messagesExample:
[{"role": "user", "content": "Hello, please introduce yourself"}]
Advanced usage:Add system prompt (to define AI behavior):
[
  {"role": "system", "content": "You are a professional Python tutor"},
  {"role": "user", "content": "How do I learn programming?"}
]
Multi-turn conversation (with context):
[
  {"role": "user", "content": "Hello"},
  {"role": "assistant", "content": "Hi! How can I help you?"},
  {"role": "user", "content": "Tell me about AI"}
]
Role descriptions:
  • user: User message (use this most of the time)
  • system: System prompt to set AI behavior and role
  • assistant: AI’s previous responses, used for conversation context
​
temperature
number
Controls output randomness, range 0-2
  • Lower values (e.g., 0.2) make output more deterministic
  • Higher values (e.g., 1.8) make output more random
Default: 1.0
​
max_tokens
integer
Maximum number of tokens to generateDifferent models have different maximum limits, please refer to specific model documentation
​
stream
boolean
Whether to use streaming output
  • true: Streaming response (SSE format)
  • false: Complete response at once
Default: false
​
top_p
number
Nucleus sampling parameter, range 0-1Controls diversity of generated text, recommend using either this or temperatureDefault: 1.0
​
frequency_penalty
number
Frequency penalty, range -2.0 to 2.0Positive values reduce the likelihood of repeating the same wordsDefault: 0
​
presence_penalty
number
Presence penalty, range -2.0 to 2.0Positive values increase the likelihood of talking about new topicsDefault: 0
​
stop
string or array
Stop sequencesUp to 4 sequences where generation will stop when encountered
​
n
integer
Number of completions to generateDefault: 1⚠️ Note: Must enter a plain number (e.g., 1), do not use quotes or it will cause an error

​
Response

​
id
string
Unique identifier for the response
​
object
string
Object type, fixed as chat.completion
​
created
integer
Creation timestamp
​
model
string
The actual model name used
​
choices
array
List of generated responses
​
usage
object
Token usage statistics

​
Supported Models

​
OpenAI Series

  • gpt-5 - GPT-5 base model
  • gpt-5-chat-latest - GPT-5 latest chat version
  • gpt-5-mini - GPT-5 lightweight version, cost-effective
  • gpt-5-nano - GPT-5 ultra-lightweight version
  • gpt-5-pro - GPT-5 professional enhanced version

​
Anthropic Series

  • claude-haiku-4-5-20251001 - Claude 4.5 fast response version
  • claude-sonnet-4-5-20250929 - Claude 4.5 balanced version
  • claude-opus-4-1-20250805 - Most powerful Claude 4.1 flagship model
  • claude-opus-4-1-20250805-thinking - Claude 4.1 Opus deep thinking version
  • claude-sonnet-4-5-20250929-thinking - Claude 4.5 Sonnet deep thinking version

​
Google Series

  • gemini-2.5-flash - Gemini 2.5 fast version
  • gemini-2.5-pro - Gemini 2.5 professional version
  • gemini-2.5-flash-lite - Gemini 2.5 ultra-lightweight version
  • gemini-2.5-pro-thinking - Gemini 2.5 Pro deep thinking version

​
DeepSeek Series

  • deepseek-v3.1-250821 - DeepSeek V3.1 base version
  • deepseek-v3.1-think-250821 - DeepSeek V3.1 thinking version
  • deepseek-v3-0324 - DeepSeek V3 standard version

​
Doubao Series

  • doubao-seed-1-6-flash-250828 - Doubao Seed 1.6 fast version
  • doubao-seed-1-6-thinking-250715 - Doubao Seed 1.6 thinking version
  • doubao-seed-1-6-251015 - Doubao Seed 1.6 standard version

​
Usage Examples

​
Basic Conversation

{
  "model": "gpt-4o",
  "messages": [
    {"role": "user", "content": "Hello"}
  ]
}

​
System Prompt

{
  "model": "claude-3-5-sonnet",
  "messages": [
    {"role": "system", "content": "You are a professional Python programming tutor"},
    {"role": "user", "content": "How to use list comprehensions?"}
  ]
}

​
Multi-turn Conversation

{
  "model": "gemini-2.0-flash",
  "messages": [
    {"role": "user", "content": "What is machine learning?"},
    {"role": "assistant", "content": "Machine learning is a branch of artificial intelligence..."},
    {"role": "user", "content": "Can you give me an example?"}
  ]
}

​
Streaming Output

{
  "model": "gpt-4o",
  "messages": [
    {"role": "user", "content": "Write a poem about spring"}
  ],
  "stream": true
}