Delete swarms/utils/function_caller_model.py

swarms/utils/function_caller_model.py

@@ -1,123 +0,0 @@
-import os
-from concurrent.futures import ThreadPoolExecutor
-from typing import List
-
-from pydantic import BaseModel
-
-
-from openai import OpenAI
-
-SUPPORTED_MODELS = [
-    "o3-mini-2025-1-31",
-    "o1-2024-12-17",
-    "gpt-4o-mini-2024-07-18",
-    "gpt-4o-2024-08-06",
-]
-
-
-def check_api_key():
-    api_key = os.getenv("OPENAI_API_KEY")
-    if api_key is None:
-        raise ValueError(
-            "API key is not set. Please set the API key using the api_key parameter."
-        )
-    return api_key
-
-
-class OpenAIFunctionCaller:
-    """
-    A class to interact with the OpenAI API for generating text based on a system prompt and a task.
-
-    Attributes:
-    - system_prompt (str): The system prompt to guide the AI's response.
-    - api_key (str): The API key for the OpenAI service.
-    - temperature (float): The temperature parameter for the AI model, controlling randomness.
-    - base_model (BaseModel): The Pydantic model to parse the response into.
-    - max_tokens (int): The maximum number of tokens in the response.
-    - client (OpenAI): The OpenAI client instance.
-    """
-
-    def __init__(
-        self,
-        system_prompt: str,
-        base_model: BaseModel,
-        api_key: str = os.getenv("OPENAI_API_KEY"),
-        temperature: float = 0.1,
-        max_tokens: int = 5000,
-        model_name: str = "gpt-4o-2024-08-06",
-    ):
-        self.system_prompt = system_prompt
-        self.api_key = api_key
-        self.temperature = temperature
-        self.base_model = base_model
-        self.max_tokens = max_tokens
-        self.model_name = model_name
-
-        self.client = OpenAI(api_key=self.api_key)
-
-    def run(self, task: str):
-        """
-        Run the OpenAI model with the system prompt and task to generate a response.
-
-        Args:
-        - task (str): The task to be completed.
-        - *args: Additional positional arguments for the OpenAI API.
-        - **kwargs: Additional keyword arguments for the OpenAI API.
-
-        Returns:
-        - BaseModel: The parsed response based on the base_model.
-        """
-        try:
-            completion = self.client.beta.chat.completions.parse(
-                model=self.model_name,
-                messages=[
-                    {"role": "system", "content": self.system_prompt},
-                    {"role": "user", "content": task},
-                ],
-                response_format=self.base_model,
-                max_tokens=self.max_tokens,
-                temperature=self.temperature,
-            )
-
-            return completion.choices[0].message.parsed
-
-        except Exception as e:
-            print(f"There was an error: {e}")
-
-    def check_model_support(self):
-        # need to print the supported models
-        for model in SUPPORTED_MODELS:
-            print(model)
-
-        return SUPPORTED_MODELS
-
-    def batch_run(self, tasks: List[str]) -> List[BaseModel]:
-        """
-        Batch run the OpenAI model with the system prompt and task to generate a response.
-        """
-        return [self.run(task) for task in tasks]
-
-    def concurrent_run(self, tasks: List[str]) -> List[BaseModel]:
-        """
-        Concurrent run the OpenAI model with the system prompt and task to generate a response.
-        """
-        with ThreadPoolExecutor(max_workers=len(tasks)) as executor:
-            return list(executor.map(self.run, tasks))
-
-
-# class TestModel(BaseModel):
-#     name: str
-#     age: int
-
-# # Example usage
-# model = OpenAIFunctionCaller(
-#     system_prompt="You are a helpful assistant that returns structured data about people.",
-#     base_model=TestModel,
-#     api_key=os.getenv("OPENAI_API_KEY"),
-#     temperature=0.7,
-#     max_tokens=1000
-# )
-
-# # Test with a more appropriate prompt for the TestModel schema
-# response = model.run("Tell me about a person named John who is 25 years old")
-# print(response)