Web search

python -m pip install openai

python -m pip install anthropic

curl https://api.overcontrolgroup.com/v1/chat/completions \
  -H "Authorization: Bearer $OVERCONTROL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "lume-3.5",
  "max_tokens": 512,
  "messages": [
    {
      "role": "user",
      "content": "Find the official Python tutorial and summarize what it covers, with sources."
    }
  ],
  "tools": [
    {
      "type": "web_search",
      "max_uses": 1,
      "allowed_domains": [
        "docs.python.org"
      ]
    }
  ],
  "tool_choice": {
    "type": "web_search"
  }
}'

import os
from openai import OpenAI

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

response = client.chat.completions.create(
    model="lume-3.5",
    max_tokens=512,
    messages=[
        {
            "role": "user",
            "content": "Find the official Python tutorial and summarize what it covers, with sources."
        }
    ],
    tools=[
        {
            "type": "web_search",
            "max_uses": 1,
            "allowed_domains": [
                "docs.python.org"
            ]
        }
    ],
    tool_choice={
        "type": "web_search"
    },
)

choice = response.choices[0]
if choice.finish_reason == "length":
    raise RuntimeError("The answer reached its output limit.")
answer = choice.message.model_dump(exclude_none=True)
print(answer.get("content", ""))
for annotation in answer.get("annotations", []):
    if annotation.get("type") == "url_citation":
        source = annotation["url_citation"]
        print(source["title"], source["url"])
print(response.usage.model_dump(exclude_none=True))

curl https://api.overcontrolgroup.com/v1/messages \
  -H "x-api-key: $OVERCONTROL_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
  "model": "lume-3.5",
  "max_tokens": 512,
  "messages": [
    {
      "role": "user",
      "content": "Find the official Python tutorial and summarize what it covers, with sources."
    }
  ],
  "tools": [
    {
      "type": "web_search",
      "max_uses": 1,
      "allowed_domains": [
        "docs.python.org"
      ]
    }
  ],
  "tool_choice": {
    "type": "tool",
    "name": "web_search"
  }
}'

import os
from anthropic import Anthropic

client = Anthropic(
    api_key=os.environ["OVERCONTROL_API_KEY"],
    base_url="https://api.overcontrolgroup.com",
)

message = client.messages.create(
    model="lume-3.5",
    max_tokens=512,
    messages=[
        {
            "role": "user",
            "content": "Find the official Python tutorial and summarize what it covers, with sources."
        }
    ],
    tools=[
        {
            "type": "web_search",
            "max_uses": 1,
            "allowed_domains": [
                "docs.python.org"
            ]
        }
    ],
    tool_choice={
        "type": "tool",
        "name": "web_search"
    },
)

if message.stop_reason == "max_tokens":
    raise RuntimeError("The answer reached its output limit.")
for block in message.content:
    item = block.model_dump(exclude_none=True)
    if item["type"] == "text":
        print(item["text"])
        for citation in item.get("citations", []):
            print("Citation:", citation)
    elif item["type"] == "web_search_tool_result":
        result = item["content"]
        if isinstance(result, dict) and result.get("type", "").endswith("_error"):
            print("Tool error:", result["error_code"])
        else:
            print("Tool result:", result)
print(message.usage.model_dump(exclude_none=True))