Chat Completion

Streaming

Server-sent events for real-time responses

Function Calling

Tool use with structured outputs

Model Catalog

Pick the right model for your workload

Anthropic API

Messages API compatible endpoint

Overview

The Chat Completion API generates AI responses given a list of messages. It's fully OpenAI-compatible — use the same SDK and request format.

Endpoint: POST /v1/chat/completions

How a request flows

Every chat completion takes the same path through the platform — your app never talks to the underlying provider directly:

Your app

Send POST /v1/chat/completions with model + messages

CallMissed gateway

Authenticate the cm_ key, check credits, route by model id

Provider

Run inference on the best-fit backend — picked from the model id

CallMissed gateway

Stream tokens back and deduct credits when the response completes

Your app

Receive the completion (all at once, or token-by-token when streaming)

The model id decides routing automatically — bare ids and slash-prefixed ids are routed to the right backend for you. See How CallMissed Works.

Make your first request

Basic Usage

from openai import OpenAI

client = OpenAI(
    api_key="cm_your_key",
    base_url="https://api.callmissed.com/v1"
)

response = client.chat.completions.create(
    model="sarvam-30b",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "What is the capital of India?"}
    ]
)

print(response.choices[0].message.content)

Parameters

Frontier Parameters

When using slash-prefixed frontier models, these additional parameters are supported:

OpenAI Python SDK note — The OpenAI client validates kwargs against its known parameters and rejects provider=... (and the others above) with TypeError: Completions.create() got an unexpected keyword argument 'provider'. Pass them via extra_body instead: ``python client.chat.completions.create( model="openai/gpt-5.4", messages=[...], extra_body={ "provider": {"sort": "throughput", "order": ["openai"]}, "models": ["openai/gpt-5.4-mini"], }, ) Raw HTTP / curl users can keep provider` at the top level — only the OpenAI SDK gates kwargs.

Vision (Image Input)

Multimodal content (text + image parts) is accepted on any model whose

supports_vision flag is true in GET /v1/models. Models without vision

support reject image content with 400 unsupported_image_input before the

upstream call, so you're not charged.

from openai import OpenAI

client = OpenAI(api_key="cm_your_key", base_url="https://api.callmissed.com/v1")

resp = client.chat.completions.create(
    model="anthropic/claude-sonnet-4.6",   # supports_vision: true
    messages=[{
        "role": "user",
        "content": [
            {"type": "text", "text": "What is in this image?"},
            {"type": "image_url", "image_url": {"url": "https://example.com/cat.png"}},
        ],
    }],
)

Current vision-capable models: openai/gpt-5.4-pro, openai/gpt-5.4,

openai/gpt-5.4-mini, openai/gpt-5.4-nano, anthropic/claude-opus-4.6,

anthropic/claude-sonnet-4.6, anthropic/claude-haiku-4.5,

google/gemini-3.1-pro-preview, google/gemini-3-flash-preview, google/gemini-3.5-flash, google/gemini-3.1-flash-lite,

x-ai/grok-4.20, qwen/qwen3.5-plus, qwen/qwen3.5-flash, kimi-k2.5,

kimi-k2.6, kimi-k2.7-code, gemma-4-26b-a4b-it, mistral-small-3.1,

mistralai/mistral-small-2603, auto (free plan), openrouter/auto.

Check the live GET /v1/models response for the authoritative list — it's

computed from the same set the runtime guard uses.

Context Window

Every model in the catalog advertises a context_window (token count for the

combined prompt + completion). The GET /v1/models response exposes it under

two keys for cross-client compatibility:

• context_window (OpenAI/CallMissed canonical name)
• context_length (OpenAI SDK convention — same value)

from openai import OpenAI

client = OpenAI(api_key="cm_your_key", base_url="https://api.callmissed.com/v1")

for m in client.models.list():
    extra = m.model_extra or {}
    print(m.id, extra.get("context_window"), extra.get("supports_vision"))

Representative context windows (treat GET /v1/models as the authoritative

source — the table below is a snapshot):

Responses API

For clients built on OpenAI's newer Responses API, CallMissed exposes a compatible POST /v1/responses endpoint. It accepts a Responses-shaped body and translates to the same chat engine under the hood — so you can point an OpenAI Responses client at https://api.callmissed.com/v1 without changes.

Endpoint: POST /v1/responses

from openai import OpenAI

client = OpenAI(api_key="cm_your_key", base_url="https://api.callmissed.com/v1")

resp = client.responses.create(
    model="gpt-4.1",
    input="Write a haiku about databases.",
)
print(resp.output_text)

• input accepts a plain string or the Responses message-array form.
• Streaming is supported (stream: true) and emits Responses-style SSE events.
• The same models, pricing, vision, and tool-calling support as /v1/chat/completions apply — this is a request/response-shape adapter, not a different model set.

If you're starting fresh, /v1/chat/completions is the most widely-supported surface; use /v1/responses when porting an existing Responses-API integration.

Error Format

All errors return OpenAI-compatible format:

{
  "error": {
    "message": "Invalid API key",
    "type": "invalid_request_error",
    "code": "invalid_api_key"
  }
}