Implement Anthropic-Compatible Features - Developer Guide

The Infercom API supports Anthropic’s Messages API format (/v1/messages), enabling you to use the Anthropic Python SDK and compatible tooling with Infercom’s models. This is useful for applications and frameworks built around the Anthropic API, such as Claude Code, LangChain’s Anthropic provider, or custom agentic workflows.

Note

The Anthropic SDK was designed for Claude models. When using it with Infercom, you’re accessing open-source models (like gpt-oss, Gemma, DeepSeek) through an Anthropic-compatible interface - not Claude itself.

Install the Anthropic SDK

pip install anthropic

Configure the client

Set the base_url to Infercom’s API and provide your Infercom API key.

Note

Don’t have an Infercom API key? Get yours from the API keys and URLs page.

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.infercom.ai",
    api_key="your-infercom-api-key"
)

Basic usage

Non-streaming example

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.infercom.ai",
    api_key="your-infercom-api-key"
)

message = client.messages.create(
    model="gpt-oss-120b",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "What is the capital of Germany?"}
    ]
)

print(message.content[0].text)

Streaming example

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.infercom.ai",
    api_key="your-infercom-api-key"
)

with client.messages.stream(
    model="gpt-oss-120b",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "Write a haiku about AI."}
    ]
) as stream:
    for text in stream.text_stream:
        print(text, end="", flush=True)

System prompts

Use the system parameter to provide instructions to the model.

message = client.messages.create(
    model="gpt-oss-120b",
    max_tokens=1024,
    system="You are a helpful assistant that speaks like a pirate.",
    messages=[
        {"role": "user", "content": "Hello!"}
    ]
)

Multi-turn conversations

message = client.messages.create(
    model="gpt-oss-120b",
    max_tokens=1024,
    messages=[
        {"role": "user", "content": "My name is Thomas."},
        {"role": "assistant", "content": "Nice to meet you, Thomas!"},
        {"role": "user", "content": "What is my name?"}
    ]
)

Tool use (function calling)

The Anthropic Messages API supports tool use for models that have function calling capabilities.

Note

Tool use works with gpt-oss-120b. Other models may not reliably call tools. See Function calling for model-specific guidance.

Defining tools

import anthropic

client = anthropic.Anthropic(
    base_url="https://api.infercom.ai",
    api_key="your-infercom-api-key"
)

message = client.messages.create(
    model="gpt-oss-120b",
    max_tokens=200,
    tools=[
        {
            "name": "get_weather",
            "description": "Get the current weather in a given location",
            "input_schema": {
                "type": "object",
                "properties": {
                    "location": {
                        "type": "string",
                        "description": "The city and country, e.g. Munich, Germany"
                    }
                },
                "required": ["location"]
            }
        }
    ],
    messages=[
        {"role": "user", "content": "What's the weather in Munich?"}
    ]
)

print(message.content)

If the model decides to use the tool, the response will include a tool_use content block:

[
  {
    "type": "tool_use",
    "id": "call_abc123",
    "name": "get_weather",
    "input": {"location": "Munich, Germany"}
  }
]

Providing tool results

After executing the tool, send the result back to continue the conversation:

message = client.messages.create(
    model="gpt-oss-120b",
    max_tokens=200,
    tools=[
        {
            "name": "get_weather",
            "description": "Get the current weather in a given location",
            "input_schema": {
                "type": "object",
                "properties": {
                    "location": {"type": "string"}
                },
                "required": ["location"]
            }
        }
    ],
    messages=[
        {"role": "user", "content": "What's the weather in Munich?"},
        {
            "role": "assistant",
            "content": [
                {
                    "type": "tool_use",
                    "id": "call_abc123",
                    "name": "get_weather",
                    "input": {"location": "Munich, Germany"}
                }
            ]
        },
        {
            "role": "user",
            "content": [
                {
                    "type": "tool_result",
                    "tool_use_id": "call_abc123",
                    "content": "Sunny, 22°C"
                }
            ]
        }
    ]
)

print(message.content[0].text)

Async usage

import anthropic
import asyncio

async def main():
    client = anthropic.AsyncAnthropic(
        base_url="https://api.infercom.ai",
        api_key="your-infercom-api-key"
    )

    message = await client.messages.create(
        model="gpt-oss-120b",
        max_tokens=1024,
        messages=[
            {"role": "user", "content": "Hello!"}
        ]
    )
    print(message.content[0].text)

asyncio.run(main())

Using curl

You can also call the Messages API directly with curl:

curl https://api.infercom.ai/v1/messages \
  -H "Content-Type: application/json" \
  -H "x-api-key: your-infercom-api-key" \
  -H "anthropic-version: 2023-06-01" \
  -d '{
    "model": "gpt-oss-120b",
    "max_tokens": 1024,
    "messages": [
      {"role": "user", "content": "Hello!"}
    ]
  }'

Supported parameters

Parameter	Type	Description
model	string	Required. The model to use (e.g., gpt-oss-120b)
messages	array	Required. Array of message objects with role and content
max_tokens	integer	Required. Maximum tokens to generate
system	string	System prompt for the model
temperature	number	Sampling temperature (0.0-2.0). No default, unlike the Anthropic API, which defaults to 1.0.
top_p	number	Nucleus sampling parameter
top_k	integer	Top-k sampling parameter
stop_sequences	array	Custom stop sequences
stream	boolean	Enable streaming responses
tools	array	Tool definitions for function calling
tool_choice	object	Control tool usage (auto, any, or specific tool)

Unsupported features

The following Anthropic-specific features are not supported:

• Extended thinking (thinking parameter)
• Prompt caching (cache_control)
• Vision/image inputs
• PDF file inputs
• Citations
• Server-side tools (web search, code execution)
• Batch API
• repetition_penalty (accepted and ignored on this endpoint, and an upcoming platform release will reject it; use /v1/chat/completions)

Differences from Anthropic’s API

Aspect	Anthropic	Infercom
Models	Claude (Opus, Sonnet, Haiku)	Open-source models (gpt-oss, Gemma, DeepSeek, Llama)
Base URL	https://api.anthropic.com	https://api.infercom.ai
API key header	x-api-key	x-api-key (same)
Version header	Required: anthropic-version	Supported but optional
Error shape	Anthropic error format	Anthropic error format (see below)

Error responses

/v1/messages returns errors in the Anthropic shape, not the OpenAI envelope used by Infercom’s other endpoints. The body carries a top-level "type": "error", and the error object holds message and type only:

{
  "type": "error",
  "error": {
    "type": "not_found_error",
    "message": "The model `nonexistent-model` does not exist or you do not have access to it."
  },
  "request_id": "req_6313f64378ad4a89b6005ab233a3f2a9"
}

Field	Notes
type (top level)	Always error
error.type	authentication_error, invalid_request_error or not_found_error
error.message	Human-readable explanation
error.param / error.code	Not returned. The OpenAI-compatible endpoints provide these; /v1/messages does not
request_id	Present on every status. Most carry a req_ prefix; the 401 does not

This shape is returned for every error status, including 400, 401, 404, 410 and 422. See API error codes for the shapes the other endpoints use.

When to use Anthropic vs OpenAI compatibility

Use case	Recommended API
Existing Anthropic SDK code	Anthropic Messages API (/v1/messages)
Claude Code, LangChain Anthropic	Anthropic Messages API (/v1/messages)
OpenAI SDK code	OpenAI Chat Completions API (/v1/chat/completions)
Agentic workflows, coding tools	Responses API (/v1/responses)
New projects	Any - all three APIs work with the same models

Related documentation

• OpenAI compatibility - Using the OpenAI SDK
• Function calling - Detailed guide on tool use
• Responses API - Agentic workflows with structured outputs
• Supported models - Available models and capabilities