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Nathan Brooks
Nathan Brooks

Posted on Originally published at cometapi.com

Grok 4.7 from Python: OpenAI SDK, Two Endpoint Shapes, and a Model Allowlist

#ai #opensource #agents

xAI shipped Grok 4.7 in September 2026 for coding, agentic tasks, and long-form knowledge work. It carries a 500,000-token context window and speaks both the Responses API and Chat Completions.

The first request is the easy part. The maintenance cost arrives later: another credential, another SDK bootstrap, another billing relationship, another catalog of model IDs that drift between releases. I keep these models behind an OpenAI-compatible gateway (CometAPI's base URL is https://api.cometapi.com/v1), so client construction never changes and only the model string does.

Here is the path I use, from an empty venv to a request shape I am willing to put in production.

Key, shell, and isolated install

Store the credential as an environment variable. Never inline it in source, a notebook, or browser-side JavaScript.

export COMETAPI_KEY="your_cometapi_key_here"
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PowerShell:

$env:COMETAPI_KEY="your_cometapi_key_here"
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Then build a venv and pull the current SDK:

python -m venv .venv
source .venv/bin/activate
python -m pip install --upgrade openai
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On Windows, activate with .venv\Scripts\Activate.ps1. This is the same openai package and client pattern the official quickstart uses. The key, the base URL, and the model ID are the only differences.

First request against Grok 4.7 

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["COMETAPI_KEY"],
    base_url="https://api.cometapi.com/v1",
)

response = client.responses.create(
    model="grok-4.7",
    input="Explain one practical use of a unified AI API in two sentences.",
)

print(response.output_text)
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Save it as grok47_quickstart.py and run python grok47_quickstart.py. If you see text, the client is sending traffic through the gateway and resolving Grok 4.7 by ID.

What each piece is doing

  • api_key carries your gateway credential. One key covers every model enabled on that account.
  • base_url redirects the SDK away from OpenAI's default host. Keep the /v1 suffix.
  • model="grok-4.7" selects the model. Model IDs are exact and case-sensitive deployment inputs. Confirm them against the live model page before you ship.
  • client.responses.create(...) uses the Responses route, which is what the current Grok 4.7 model page documents and what xAI's own Grok 4.7 docs list as supported.

Already on Chat Completions? That works too

Yes. The September 22, 2026 changelog states that Grok 4.7 supports the Chat API format. If your codebase is built around chat.completions.create, nothing structural needs to change:

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["COMETAPI_KEY"],
    base_url="https://api.cometapi.com/v1",
)

completion = client.chat.completions.create(
    model="grok-4.7",
    messages=[
        {
            "role": "user",
            "content": "Give me a three-step API migration checklist.",
        }
    ],
)

print(completion.choices[0].message.content)
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My rule: Responses for new code, Chat Completions when you are extending an established chat integration. Do not assume native tools or model-specific parameters map one-to-one across the two formats.

One integration, several model families

A gateway earns its keep when an application needs multiple model families without a separate credential and init path per provider. The key and base URL stay fixed; the model ID is the variable.

Model IDs verified September 28, 2026. Availability, aliases, capabilities, and pricing change, so recheck before deploying.

Family Example model ID What to check before shipping
Grok grok-4.7 Coding, agentic tasks, long-form knowledge work. Verify Responses vs Chat, reasoning controls, tools, current rates.
GPT gpt-6-sol Complex coding and agentic workflows. Verify endpoint support, reasoning level, context needs, tool availability.
Claude claude-opus-5-5 High-capability reasoning and agent work. Verify Messages vs Chat format and Anthropic tool behavior.
Gemini gemini-3.8-flash Speed and multimodal workloads. Verify Gemini-native vs Chat format, media inputs, grounding options.
DeepSeek deepseek-v4-pro Advanced reasoning, coding, long-horizon agents. Verify Chat compatibility, reasoning behavior, output limits.

For a plain text flow, make the model configurable:

import os
from openai import OpenAI

client = OpenAI(
    api_key=os.environ["COMETAPI_KEY"],
    base_url="https://api.cometapi.com/v1",
)

model = os.getenv("COMETAPI_MODEL", "grok-4.7")

response = client.responses.create(
    model=model,
    input="Summarize the advantages and limits of a unified AI API.",
)

print(response.output_text)
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The reusable parts are the account, key, gateway URL, SDK construction, and your request wrapper. What still varies is the endpoint and schema a given family expects. Unification handles authentication, routing, and billing. It does not flatten upstream model behavior.

Put an allowlist in front of the model string

Never let user input reach the model argument. Keep capability metadata beside each approved ID so routing decisions stay explicit:

MODEL_CONFIG = {
    "grok": {
        "id": "grok-4.7",
        "api": "responses",
    },
    "gpt": {
        "id": "gpt-6-sol",
        "api": "responses",
    },
}

def run_text_request(client, family, prompt):
    config = MODEL_CONFIG[family]

    if config["api"] == "responses":
        result = client.responses.create(
            model=config["id"],
            input=prompt,
        )
        return result.output_text

    raise ValueError(f"Unsupported API format: {config['api']}")
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Extend the dict only after testing that model with the exact endpoint and parameters production will use. A catalog change or a typo then fails loudly instead of silently rerouting traffic.

Failure modes and their fixes

  • Auth rejected. Confirm COMETAPI_KEY exists in the same shell that launches Python, that the key is active, and that no stray quotes or whitespace came along when you copied it.
  • Model not found. Re-read the live model ID. For this walkthrough it is grok-4.7, not a display name like "Grok 4.7 API".
  • Parameter rejected. Strip provider-specific options and retry with the minimal documented body. OpenAI compatibility covers common SDK shapes, not every native knob across five vendors.
  • Rate limited or out of balance. Check quota and usage before adding retries. Blind retries multiply spend without clearing an account-level ceiling.
  • Timeouts and 5xx. Add bounded exponential backoff, an explicit request timeout, and a retry cap. Log the request ID and model; never log the key or prompt contents.

Before you point production at it

  • Keep the key in a secrets manager and rotate on exposure.
  • Pin approved model IDs in config and review the catalog on each deploy.
  • Exercise the exact streaming mode, tool calls, structured output, and multimodal inputs you intend to use.
  • Set timeouts and bounded retries. Never retry a request that was invalid to begin with.
  • Record model, latency, token usage, request ID, and cost, with secrets excluded.
  • Canary a small slice of traffic before shifting a new model or alias.

Grok 4.7 pricing snapshot

The model page lists two context tiers, in USD per 1 million tokens, verified September 28, 2026.

Tier Condition Input Cached input / cache read Output
Standard context len < 200,000 $1.60 $0.40 $4.80
Long-context tier See the current billing rule on the live model page $3.20 $0.80 $9.60

The corresponding direct xAI rates on the same page are $2.00 input, $0.50 cache read, and $6.00 output for standard context, and $4.00 / $1.00 / $12.00 for long context. That puts the displayed gateway rates 20% lower at verification time. Treat the table as a dated snapshot and pull live numbers before you model spend.

Short answers to the questions I get asked

Which model ID do I pass?

grok-4.7.

Does the OpenAI Python SDK work against it?

Yes. Construct OpenAI with your gateway key, set the base URL to https://api.cometapi.com/v1, then call a supported endpoint with model="grok-4.7".

Do I also need an xAI API key?

Not on this route. The request authenticates with the gateway key and bills through that account.

Can the same key reach GPT, Claude, Gemini, and DeepSeek?

For models enabled on your account, yes. Keep the key and base URL, swap the model ID, and use the endpoint that model documents.

Does one API mean identical parameters everywhere?

No. Access, auth, routing, and billing unify. Native tools, reasoning controls, multimodal inputs, safety settings, context limits, and endpoint support still differ per model.

Responses or Chat Completions for Grok 4.7?

Start with Responses, since the current model page ships that example. Chat Completions is documented in the changelog and is the pragmatic choice for an existing chat codebase.

What I take away

Point the OpenAI SDK at the gateway, select grok-4.7, and send the smallest request that proves the endpoint shape. Then layer on timeouts, backoff, structured logging, and a model allowlist before any real traffic hits it. One gateway keeps the plumbing stable; per-model validation is what keeps it correct.

Originally published at cometapi.com

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