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POST
/
v1
/
inference
Execute Raw Inference
curl --request POST \
  --url https://api.mixpeek.com/v1/inference \
  --header 'Content-Type: application/json' \
  --data '
{
  "provider": "<string>",
  "model": "<string>",
  "inputs": {},
  "parameters": {
    "max_tokens": 500,
    "temperature": 0.7
  }
}
'
{
  "data": "<unknown>",
  "provider": "<string>",
  "model": "<string>",
  "latency_ms": 123,
  "tokens_used": {
    "completion": 120,
    "prompt": 15,
    "total": 135
  }
}

Headers

​
Authorization
string

REQUIRED: Bearer token authentication using your API key. Format: 'Bearer sk_xxxxxxxxxxxxx'. You can create API keys in the Mixpeek dashboard under Organization Settings.

​
X-Namespace
string

REQUIRED: Namespace identifier for scoping this request. All resources (collections, buckets, taxonomies, etc.) are scoped to a namespace. You can provide either the namespace name or namespace ID. Format: ns_xxxxxxxxxxxxx (ID) or a custom name like 'my-namespace'

Body

application/json

Request for raw inference without retriever framework.

This endpoint provides direct access to inference services with minimal configuration. Ideal for simple LLM calls, embeddings, transcription, or vision tasks without requiring collection setup or retriever configuration.

Examples: # Chat completion { "provider": "openai", "model": "gpt-4o-mini", "inputs": {"prompts": ["What is AI?"]}, "parameters": {"temperature": 0.7, "max_tokens": 500} }

# Text embedding
{
    "provider": "openai",
    "model": "text-embedding-3-large",
    "inputs": {"text": "machine learning"},
    "parameters": {}
}

# Audio transcription
{
    "provider": "openai",
    "model": "whisper-1",
    "inputs": {"audio_url": "https://example.com/audio.mp3"},
    "parameters": {}
}

# Vision (multimodal)
{
    "provider": "openai",
    "model": "gpt-4o",
    "inputs": {
        "prompts": ["Describe this image"],
        "image_url": "https://example.com/image.jpg"
    },
    "parameters": {"temperature": 0.5}
}
​
provider
string
required

Provider name: openai, google, anthropic

​
model
string
required

Model identifier specific to the provider

​
inputs
Inputs · object
required

Model-specific inputs. Chat: {prompts: [str]}, Embeddings: {text: str} or {texts: [str]}, Transcription: {audio_url: str}, Vision: {prompts: [str], image_url: str}

​
parameters
Parameters · object

Optional parameters for inference. Common: temperature (float), max_tokens (int), schema (dict for structured output)

Example:
{ "max_tokens": 500, "temperature": 0.7 }

Response

Successful Response

Response from raw inference.

Returns the inference results along with metadata about the request.

​
data
any
required

Inference results (structure varies by modality)

​
provider
string
required

Provider that was used

​
model
string
required

Model that was used

​
latency_ms
number
required

Total inference latency in milliseconds

​
tokens_used
Tokens Used · object

Token usage statistics (if available)

Example:
{
  "completion": 120,
  "prompt": 15,
  "total": 135
}