delete

auto_dataframe.py

@@ -1,75 +0,0 @@
-from openai_function_call import OpenAISchema
-from pydantic import Field
-from typing import List, Any
-import openai
-
-
-class RowData(OpenAISchema):
-    row: List[Any] = Field(..., description="The values for each row")
-
-
-class Dataframe(OpenAISchema):
-    """
-    Class representing a dataframe. This class is used to convert
-    data into a frame that can be used by pandas.
-    """
-
-    data: List[RowData] = Field(
-        ...,
-        description="Correct rows of data aligned to column names, Nones are allowed",
-    )
-    columns: List[str] = Field(
-        ...,
-        description="Column names relevant from source data, should be in snake_case",
-    )
-
-    def to_pandas(self):
-        import pandas as pd
-
-        columns = self.columns
-        data = [row.row for row in self.data]
-
-        return pd.DataFrame(data=data, columns=columns)
-
-
-def dataframe(data: str) -> Dataframe:
-    completion = openai.ChatCompletion.create(
-        model="gpt-3.5-turbo-0613",
-        temperature=0.1,
-        functions=[Dataframe.openai_schema],
-        function_call={"name": Dataframe.openai_schema["name"]},
-        messages=[
-            {
-                "role": "system",
-                "content": """Map this data into a dataframe a
-                nd correctly define the correct columns and rows""",
-            },
-            {
-                "role": "user",
-                "content": f"{data}",
-            },
-        ],
-        max_tokens=1000,
-    )
-    return Dataframe.from_response(completion)
-
-
-if __name__ == "__main__":
-    df = dataframe(
-        """My name is John and I am 25 years old. I live in 
-        New York and I like to play basketball. His name is 
-        Mike and he is 30 years old. He lives in San Francisco 
-        and he likes to play baseball. Sarah is 20 years old 
-        and she lives in Los Angeles. She likes to play tennis.
-        Her name is Mary and she is 35 years old. 
-        She lives in Chicago."""
-    )
-
-    print(df.to_pandas())
-    """
-        name  age       location       hobby
-    0   John   25       New York  basketball
-    1   Mike   30  San Francisco    baseball
-    2  Sarah   20    Los Angeles      tennis
-    3   Mary   35        Chicago        None
-    """