Using the API

TheAgentic API is compatible with the OpenAI SDK. You can use your existing OpenAI SDK to call TheAgentic's LLMs, just by swapping the base_url and the api_key.

from openai import OpenAI

client = OpenAI(
    base_url="https://api.theagentic.ai/v1",
    api_key="YOUR_API_KEY",
)

answer = client.chat.completions.create(
    model="agentic-turbo",
    messages=[
        {"role": "system", "content": "Your system prompt"},
        {
            "role": "user",
            "content": "Tell me a joke",
        },
    ],
)
print(answer)

Supported Models

TheAgentic-Turbo: Low-latency, production optimized LLM
Slug for OpenAI SDK: agentic-turbo
TheAgentic-Thinker: Reasoning LLM fit for agentic tasks
Slug for OpenAI SDK: agentic-thinker or agentic-large

Tool Calling

TheAgentic's LLM API supports OpenAI-like tool-calling.
Here's an example that makes a request to TheAgentic API a tool using the OpenAI SDK:

from openai import OpenAI

client = OpenAI(
    base_url="https://api.theagentic.ai/v1",
    api_key="YOUR_API_KEY",
)

answer = client.chat.completions.create(
    model="agentic-turbo",
    messages=[
        {
            "role":"system",
            "content":"Your system prompt"
        },
        {
            "role":"user",
            "content":"What is the weather like in San Francisco?"
        }
    ],
    tools=[
        {
            "type":"function",
            "function":{
                "name":"get_weather",
                "description":"Get weather information for a specific location.",
                "parameters":{
                    "type":"object",
                    "properties":{
                        "location":{
                            "type":"string",
                            "description":"Name of the location"
                        }
                    },
                    "required":[
                        "location"
                    ]
                }
            }
        }
    ]
)

print(answer)

Reasoning Tokens

To see the reasoning tokens in each response, you can pass in return_reasoning=True in the extra_body parameter of the chat completion request.

response = client.chat.completions.create(
    model="agentic-large",
    messages=[...],
    extra_body={"return_reasoning": True},
)

The response will include the reasoning tokens in the reasoning_content of the ChatCompletionMessage object.

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

When streaming the response, the reasoning tokens will be streamed in the reasoning_content field.

for chunk in response:
    print(chunk.choices[0].message.reasoning_content)