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Documentation Index

Fetch the complete documentation index at: https://docs.linkup.so/llms.txt

Use this file to discover all available pages before exploring further.

Looking for OpenAI SDK?

We have a dedicated guide for using the OpenAI SDK with Linkup.
This tutorial shows you how to use OpenAI’s function calling with Linkup to build a chatbot with real-time web search capabilities.
1

Get your API Keys

Get your Linkup API key

Create a Linkup account for free to get your API key.

Get your OpenAI API key

Create an OpenAI account for free to get your API key.
2

Install and Setup

Install the required packages:
pip install linkup-sdk openai
Set up your clients:
from openai import OpenAI
from linkup import LinkupClient
import json
from datetime import datetime

openai_client = OpenAI(api_key="your_openai_api_key")
linkup_client = LinkupClient(api_key="your_linkup_api_key")
3

Define the Function Schema

Tell OpenAI about your search function using the Responses API format:
tools = [{
    "type": "function",
    "name": "search_web",
    "description": "Search the web for current information. Returns comprehensive content from relevant sources.",
    "parameters": {
        "type": "object",
        "properties": {
            "query": {
                "type": "string",
                "description": "The search query"
            }
        },
        "required": ["query"]
    }
}]
4

Build the Chatbot

Put it all together in a conversational loop using the Responses API:
system_prompt = f"You are a helpful assistant. Today is {datetime.now().strftime('%B %d, %Y')}. Use web search when you need current information."
input_list = [{"role": "system", "content": system_prompt}]

print("Chatbot ready! Type 'quit' to exit.\n")

while True:
    user_input = input("You: ").strip()
    if not user_input or user_input.lower() == "quit":
        break

    input_list.append({"role": "user", "content": user_input})

    try:
        response = openai_client.responses.create(
            model="gpt-5",
            tools=tools,
            input=input_list,
        )

        while any(item.type == "function_call" for item in response.output):
            input_list += response.output

            for item in response.output:
                if item.type == "function_call":
                    args = json.loads(item.arguments)
                    print(f"Searching with Linkup: {args['query']}...")
                    linkup_response = linkup_client.search(
                        query=args["query"],
                        depth="fast",
                        output_type="searchResults"
                    )
                    search_results_json = json.dumps(
                        linkup_response.model_dump(), indent=2
                    )
                    input_list.append({
                        "type": "function_call_output",
                        "call_id": item.call_id,
                        "output": search_results_json
                    })

            response = openai_client.responses.create(
                model="gpt-5",
                tools=tools,
                input=input_list,
            )

        input_list += response.output

        print(f"\nAssistant: {response.output_text}\n")

    except Exception as e:
        print(f"Error: {e}\n")
        input_list.pop()
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