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Tera supports tool calling on models that advertise the tools feature in their catalog entry. The request and response shapes match the OpenAI Chat Completions API.

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Defining tools

from openai import OpenAI

client = OpenAI(base_url="https://api.tera.gw/v1", api_key="sk-tera-...")

tools = [
    {
        "type": "function",
        "function": {
            "name": "get_weather",
            "description": "Get current weather in a city",
            "parameters": {
                "type": "object",
                "properties": {
                    "city": {"type": "string", "description": "City name"},
                    "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]}
                },
                "required": ["city"]
            }
        }
    }
]

resp = client.chat.completions.create(
    model="Qwen/Qwen2.5-7B-Instruct",
    messages=[{"role": "user", "content": "What's the weather in Paris?"}],
    tools=tools,
)

print(resp.choices[0].message.tool_calls)

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Response

When the model decides to call a tool, the response carries tool_calls and finish_reason: "tool_calls": 
{
  "choices": [
    {
      "message": {
        "role": "assistant",
        "content": null,
        "tool_calls": [
          {
            "id": "call_abc123",
            "type": "function",
            "function": {
              "name": "get_weather",
              "arguments": "{\"city\":\"Paris\",\"unit\":\"celsius\"}"
            }
          }
        ]
      },
      "finish_reason": "tool_calls"
    }
  ]
}

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Returning tool results

Append the assistant’s tool call and your tool’s output to messages, then call the API again: 
messages = [
    {"role": "user", "content": "What's the weather in Paris?"},
    resp.choices[0].message,  # the assistant tool call
    {
        "role": "tool",
        "tool_call_id": "call_abc123",
        "content": "18C, partly cloudy"
    }
]

final = client.chat.completions.create(
    model="Qwen/Qwen2.5-7B-Instruct",
    messages=messages,
    tools=tools,
)
print(final.choices[0].message.content)

​
tool_choice

Default is "auto" — the model decides whether to call a tool. Other modes:
  • "none" — disable tool calling for this request
  • "required" — force a tool call
  • {"type": "function", "function": {"name": "..."}} — force a specific tool

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Streaming tool calls

With stream: true, tool call arguments arrive as deltas. Concatenate delta.tool_calls[i].function.arguments strings across chunks to reconstruct the full JSON.

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Model support

Not every model in our catalog supports tools. Check supported_features in /v1/models — only models that include "tools" will reliably call functions. See Models.