Chat Completion

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:

1. 1

   Your app

   Send with +

2. 2

   CallMissed gateway

   Authenticate the key, check credits, route by model id

3. 3

   Provider

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

4. 4

   CallMissed gateway

   Stream tokens back and deduct credits when the response completes

5. 5

   Your app

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

Tip: The model id decides routing automatically — you never pick a backend. 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-105b",
    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

OpenAI Python SDK note — The OpenAI client validates kwargs against its known parameters, so a CallMissed-specific field such as reasoning_effort raises TypeError: Completions.create() got an unexpected keyword argument. Pass it via extra_body instead:

client.chat.completions.create(
    model="kimi-k2.6",
    messages=[...],
    extra_body={"reasoning_effort": "none"},
)

Raw HTTP / curl users can keep it at the top level — only the OpenAI SDK gates kwargs.

Model Substitution

CallMissed never substitutes your model. Send a model and you get that model, or a clean error (429/503 with Retry-After). You are never billed for a model you did not name.

Need a model that is not in the catalog? See Models on demand.

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="gpt-5.6-sol",   # 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"}},
        ],
    }],
)

Vision-capable models: gpt-5.6-sol, gpt-5.6-terra, gpt-5.6-luna, gpt-5.5, gpt-4o, gpt-4.1, gpt-5-mini, grok-4.3, kimi-k2.5, kimi-k2.5-fast, kimi-k2.6, kimi-k2.7-code, gemma-4-26b-a4b-it, mistral-small-3.1.

GET /v1/models is authoritative. Read supports_vision there rather than hard-coding this list.

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"))

Snapshot — GET /v1/models is authoritative:

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"
  }
}