Creating a simple text agent with a function call

Get API authentication credentials as described in Authentication with the Yandex AI Studio API.

1. Create a file named index.py and add the following code to it:

   import openai
   from openai import OpenAI
   import json
   
   YANDEX_CLOUD_MODEL = "yandexgpt"
   
   client = openai.OpenAI(
       api_key=YANDEX_CLOUD_API_KEY,
       base_url="https://rest-assistant.api.cloud.yandex.net/v1",
       project=YANDEX_CLOUD_FOLDER
   )
   
   # 1. Listing the functions the model can call
   tools = [
       {
           "type": "function",
           "name": "get_weather",
           "description": "Getting current weather for the city you specify.",
           "parameters": {
               "type": "object",
               "properties": {
                   "city": {
                       "type": "string",
                       "description": "City, e.g.: Petersburg or Moscow",
                   },
               },
               "required": ["city"],
           },
       },
   ]
   
   # The simplest implementation of the function (can be replaced with a call to a real API)
   def get_weather(city):
       # Here you can implement an integration, e.g., with Yandex Weather
       return {
           "city": city,
           "temperature": "12 °C",
           "condition": "Cloudy, light breeze"
       }
   
   # Forming a list of messages to be updated
   input_list = [
       {"role": "user", "content": "What is the weather like in Krasnoyarsk?"}
   ]
   
   # 2. Requesting a model with specific features
   response = client.responses.create(
       model=f"gpt://{YANDEX_CLOUD_FOLDER}/{YANDEX_CLOUD_MODEL}",
       tools=tools,
       input=input_list,
   )
   
   # Adding the model's input to history
   input_list += response.output
   
   for item in response.output:
       if item.type == "function_call":
           if item.name == "get_weather":
               # 3. Executing the get_weather function
               weather_info = get_weather(**json.loads(item.arguments))
   
               # 4. Providing the result of the function back to the model
               input_list.append({
                   "type": "function_call_output",
                   "call_id": item.call_id,
                   "output": json.dumps(weather_info)
               })
   
   print("Final input:")
   for item in input_list:
       if isinstance(item, dict) and item.get("type") == "function_call_output":
           parsed = json.loads(item["output"])
           print("function_call_output:", parsed)
       else:
           print(item)
   
   response = client.responses.create(
       model=f"gpt://{YANDEX_CLOUD_FOLDER}/{YANDEX_CLOUD_MODEL}",
       instructions="Respond only with the weather data returned by the function.",
       tools=tools,
       input=input_list,
   )
   
   # 5. Final response
   print("Final output:")
   print(response.model_dump_json(indent=2))
   print("\n" + response.output_text)
   

2. Save authentication data into environment variables:

   export YANDEX_CLOUD_FOLDER=<folder_ID>
   export YANDEX_CLOUD_API_KEY=<API_key>
   

3. Run the file you created:

   python index.py
   

   Response example:

   Final input:
   {'role': 'user', 'content': 'What is the weather like in Krasnoyarsk?'}
   ResponseFunctionToolCall(arguments='{"city":"Krasnoyarsk"}', call_id='get_weather', name='get_weather', type='function_call', id='get_weather', status='completed', valid=True)
   function_call_output: {'city': 'Krasnoyarsk', 'temperature': '12 °C', 'condition': 'Cloudy, light breeze'}
   Final output:
   {
     "id": "70d96fac-1c4b-4f4a-9f80-56df********",
     "created_at": 1758556157206.0,
     "error": null,
     "incomplete_details": null,
     "instructions": "Respond only with the weather data returned by the function.",
     "metadata": null,
     "model": "gpt://b1gstllj8rgs********/yandexgpt",
     "object": "response",
     "output": [
       {
         "id": "f15c66e8-99a2-4647-a820-406e********",
         "content": [
           {
             "annotations": [],
             "text": "It is currently plus 12°C in Krasnoyarsk, cloudy, light breeze.",
             "type": "output_text",
             "logprobs": null,
             "valid": true
           }
         ],
         "role": "assistant",
         "status": "completed",
         "type": "message",
         "valid": true
       }
     ],
     "parallel_tool_calls": true,
     "temperature": null,
     "tool_choice": "auto",
     "tools": [
       {
         "name": "get_weather",
         "parameters": {
           "type": "object",
           "properties": {
             "city": {
               "type": "string",
               "description": "City, e.g.: Petersburg or Moscow"
             }
           },
           "required": [
             "city"
           ]
         },
         "strict": null,
         "type": "function",
         "description": "Getting current weather for the city you specify.",
         "valid": true
       }
     ],
     "top_p": null,
     "background": false,
     "conversation": null,
     "max_output_tokens": null,
     "max_tool_calls": null,
     "previous_response_id": null,
     "prompt": null,
     "prompt_cache_key": null,
     "reasoning": null,
     "safety_identifier": null,
     "service_tier": null,
     "status": "completed",
     "text": null,
     "top_logprobs": null,
     "truncation": null,
     "usage": null,
     "user": "",
     "valid": true
   }
   
   It is currently plus 12°C in Krasnoyarsk, cloudy, light breeze.