Method create_completion

finagent/provider/provider.py:256–350

Create a chat completion using the OpenAI API Supports both GPT-4 and GPT-4V). Example Usage: image_path = "path_to_your_image.jpg" base64_image = encode_image(image_path) response, info = self.create_completion( model="gpt-4-vision-preview",

(
        self,
        messages: List[Dict[str, str]],
        model: str | None = None,
        temperature: float = 1.0,
        seed: int | None = 42,
        max_tokens: int = 4096,
    )

    def create_completion(
        self,
        messages: List[Dict[str, str]],
        model: str | None = None,
        temperature: float = 1.0,
        seed: int | None = 42,
        max_tokens: int = 4096,
    ) -> Tuple[str, Dict[str, int]]:
        """Create a chat completion using the OpenAI API

        Supports both GPT-4 and GPT-4V).

        Example Usage:
        image_path = "path_to_your_image.jpg"
        base64_image = encode_image(image_path)
        response, info = self.create_completion(
            model="gpt-4-vision-preview",
            messages=[
              {
                "role": "user",
                "content": [
                  {
                    "type": "text",
                    "text": "What’s in this image?"
                  },
                  {
                    "type": "image_url",
                    "image_url": {
                      "url": f"data:image/jpeg;base64,{base64_image}"
                    }
                  }
                ]
              }
            ],
        )
        """

        if model is None:
            model = self.llm_model

        # print(f"Creating chat completion with model {model}, temperature {temperature}, max_tokens {max_tokens}")

        @backoff.on_exception(
            backoff.constant,
            (
                APIError, 
                RateLimitError, 
                APITimeoutError),
            max_tries=self.retries,
            interval=10,
        )
        def _generate_response_with_retry(
            messages: List[Dict[str, str]],
            model: str,
            temperature: float,
            seed: int | None,
            max_tokens: int = 512,
        ) -> Tuple[str, Dict[str, int]]: