Skip to main content

​
Request Body

​
model
string
required
ID of the model to use. See Models for available options.
​
messages
array
required
A list of messages comprising the conversation.Each message object contains:
  • role (string): system, user, or assistant
  • content (string | array): The message content
​
temperature
number
default:"1"
Sampling temperature between 0 and 2. Higher values make output more random.
​
max_tokens
integer
Maximum number of tokens to generate.
​
stream
boolean
default:"false"
If true, partial message deltas will be sent as SSE events.
​
stream_options
object
Options for streaming. Set include_usage: true to receive token usage in stream chunks.
​
top_p
number
default:"1"
Nucleus sampling parameter. We recommend altering this or temperature, not both.
​
frequency_penalty
number
default:"0"
Number between -2.0 and 2.0. Positive values penalize repeated tokens.
​
presence_penalty
number
default:"0"
Number between -2.0 and 2.0. Positive values penalize tokens already in the text.
​
stop
string | array
Up to 4 sequences where the API will stop generating tokens.
​
tools
array
A list of tools the model may call (function calling).
​
tool_choice
string | object
Controls how the model uses tools. Options: auto, none, required, or a specific tool object.
​
parallel_tool_calls
boolean
default:"true"
Whether to enable parallel function calling. Set to false to call functions sequentially.
​
max_completion_tokens
integer
Maximum tokens for the completion. Alternative to max_tokens, useful for newer reasoning-enabled model families.
​
reasoning_effort
string
Reasoning effort for reasoning-enabled models. Options: low, medium, high.
​
seed
integer
Random seed for deterministic sampling.
​
n
integer
default:"1"
Number of completions to generate (1-128).
​
logprobs
boolean
Whether to return log probabilities.
​
top_logprobs
integer
Number of top log probabilities to return (0-20). Requires logprobs: true.
​
top_k
integer
Top-K sampling parameter (for Anthropic/Gemini models).
​
response_format
object
Response format specification. Use {"type": "json_object"} for JSON mode, or {"type": "json_schema", "json_schema": {...}} for structured outputs.
​
logit_bias
object
Modify the likelihood of specified tokens appearing. Map token IDs (as strings) to bias values from -100 to 100.
​
user
string
A unique identifier representing your end-user for abuse monitoring.
​
cache_control
object
LemonData cache control options.
  • type (string): Cache strategy - default, no_cache, no_store, response_only, semantic_only
  • max_age (integer): Cache TTL in seconds (max 86400)

​
Response

​
id
string
Unique identifier for the completion.
​
object
string
Always chat.completion.
​
created
integer
Unix timestamp of when the completion was created.
​
model
string
The model used for completion.
​
choices
array
List of completion choices.Each choice contains:
  • index (integer): Index of the choice
  • message (object): The generated message
  • finish_reason (string): Why the model stopped (stop, length, tool_calls)
​
usage
object
Token usage statistics.
  • prompt_tokens (integer): Tokens in the prompt
  • completion_tokens (integer): Tokens in the completion
  • total_tokens (integer): Total tokens used
curl -X POST "https://api.lemondata.cc/v1/chat/completions" \
  -H "Authorization: Bearer sk-your-api-key" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gpt-4o",
    "messages": [
      {"role": "system", "content": "You are a helpful assistant."},
      {"role": "user", "content": "Hello!"}
    ],
    "temperature": 0.7,
    "max_tokens": 1000
  }'

{
  "id": "chatcmpl-abc123",
  "object": "chat.completion",
  "created": 1706000000,
  "model": "gpt-4o",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hello! How can I help you today?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 20,
    "completion_tokens": 9,
    "total_tokens": 29
  }
}