Inference API provides an OpenAI-compatible interface for chat completions, streaming chat completions, server-side web search, embeddings, and model listing. Standard OpenAI-compatible SDKs and HTTP clients can connect to the API by using Tempico endpoints and a Tempico API key.

Authentication

All API requests require an API key. Bearer authentication is the recommended method.

For compatibility, the API also supports x-api-key: <API_KEY> header.

List models

Returns available model IDs for the current account. Returned id values can be used as the model field in chat completion and embedding requests.

{
  "object": "list",
  "data": [
    {
      "id": "kimi-k2.7-code:1t",
      "object": "model",
      "created": 0,
      "owned_by": "tempicolabs",
      "context_window": 262144,
      "capabilities": [
        "chat"
      ],
      "max_output_tokens": 65536
    },
    {
      "id": "embeddinggemma:300m",
      "object": "model",
      "created": 0,
      "owned_by": "tempicolabs",
      "context_window": 2048,
      "capabilities": [
        "embeddings"
      ]
    }
  ]
}

Field	Description
id	Model ID used in API requests.
created	Model creation timestamp when available.
context_window	Maximum context length supported by the model, in tokens.
capabilities	Supported API features for the model, such as chat or embeddings.
max_output_tokens	Maximum output token limit when available.

Chat completions

Generates a model response from a conversation in OpenAI chat format. The endpoint supports standard JSON responses, streaming output, and server-side web search.

Web search

Server-side web search works as a tool available to the model during chat completion generation. For most chat models, web search is enabled by default. The model decides when search is needed and what query should be used.

Search behavior can be controlled through the prompt. System or user messages can define when search should be used, what sources to prefer, and when the model should answer without searching.

Set web_search to false to disable server-side search for a specific request.

curl https://api.tempico.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k2.7-code:1t",
    "messages": [
      {
        "role": "system",
        "content": "You are a concise technical assistant."
      },
      {
        "role": "user",
        "content": "Search the web and summarize the current Python 3.13 release status."
      }
    ],
    "max_tokens": 800,
    "temperature": 0.2,
    "web_search": true,
    "web_search_options": {
      "search_context_size": "medium",
      "user_location": {
        "type": "approximate",
        "approximate": {
          "country": "US"
        }
      },
      "safesearch": "moderate"
    }
  }'

Field	Description
model	Model that generated the response.
messages	Conversation history sent to the model in OpenAI chat format.
max_tokens	Maximum number of tokens the model can generate in the response.
web_search	Enables or disables server-side web search. Enabled by default for most models.
search_context_size	Amount of search context passed to the model. Supported values are low, medium, and high.
country	Country code used as the location hint.
safesearch	Search safety preference passed to the search backend.
accept_language	Language preference for search results.

Example Response

{
  "id": "chatcmpl-0000000000000000",
  "object": "chat.completion",
  "created": 0,
  "model": "kimi-k2.7-code:1t",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "The answer text appears here."
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 120,
    "completion_tokens": 64,
    "total_tokens": 184
  }
}

Field	Description
finish_reason	Reason generation stopped, such as reaching a stop condition or token limit.
usage	Token usage information for the request.
prompt_tokens	Number of input tokens processed by the model.
completion_tokens	Number of output tokens generated by the model.
total_tokens	Sum of input and output tokens.

Streaming chat completions

Returns a chat completion as a stream of Server-Sent Events. Each event contains a partial response chunk. The stream ends with data: [DONE].

curl https://api.tempico.com/v1/chat/completions \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "kimi-k2.7-code:1t",
    "stream": true,
    "messages": [
      {
        "role": "user",
        "content": "Write a short Python example using requests."
      }
    ]
  }'

Example Stream Response

data: {
  "id": "chatcmpl-0000000000000000",
  "object": "chat.completion.chunk",
  "created": 0,
  "model": "kimi-k2.7-code:1t",
  "choices": [
    {
      "index": 0,
      "delta": {
        "role": "assistant"
      },
      "finish_reason": null
    }
  ]
}

data: {
  "id": "chatcmpl-0000000000000000",
  "object": "chat.completion.chunk",
  "created": 0,
  "model": "kimi-k2.7-code:1t",
  "choices": [
    {
      "index": 0,
      "delta": {
        "content": "import requests\n\n"
      },
      "finish_reason": null
    }
  ]
}

data: {
  "id": "chatcmpl-0000000000000000",
  "object": "chat.completion.chunk",
  "created": 0,
  "model": "kimi-k2.7-code:1t",
  "choices": [
    {
      "index": 0,
      "delta": {},
      "finish_reason": "stop"
    }
  ]
}

data: [DONE]

Field	Description
stream	Enables streaming mode when set to true. The response is returned as Server-Sent Events instead of one JSON object.
choices	Array of streamed output choices. For normal single-response generation, this usually contains one item.
index	Position of the choice in the choices array.
delta	Incremental update for the assistant message. This object can contain role, content, or be empty in the final chunk.
finish_reason	Indicates why generation ended. The value is null while generation is still running.
data: [DONE]	Final stream marker. No more chunks are sent after this event.

Embeddings

Embeddings convert text input into vectors for semantic search, similarity matching, clustering, and ranking.

curl https://api.tempico.com/v1/embeddings \
  -H "Authorization: Bearer $API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "embeddinggemma:300m",
    "input": "Represent this text as a vector for semantic search."
  }'

Example Response

{
  "object": "list",
  "data": [
    {
      "object": "embedding",
      "index": 0,
      "embedding": [
        0.0123,
        -0.0456,
        0.0789
      ]
    }
  ],
  "model": "embeddinggemma:300m",
  "usage": {
    "prompt_tokens": 12,
    "total_tokens": 12
  }
}

Field	Description
input	Text or array of texts used to create embeddings.
embedding	Vector representation of the input text.
prompt_tokens	Number of input tokens processed by the model.
total_tokens	Total tokens counted for the request.