Revert "Docstring parsing using docstring-parser"

docs/index.md

@@ -130,29 +130,20 @@ from instructor import OpenAISchema
 from pydantic import Field
 
 class UserDetails(OpenAISchema):
-    """"
-    Correctly extracted user information
-    :param age: age of the user
-    """
+    "Correctly extracted user information"
     name: str = Field(..., description="User's full name")
     age: int
 ```
 
-In this updated schema, we use the `Field` class from `pydantic` to add descriptions to the `name` field. Moreover, we use the docstring to add information for the parameter `age`. 
-In both cases, the description provides information about the fields, giving even more context to the language model.
-Information from the docstring is extracted using [docstring-parser](https://github.com/rr-/docstring_parser) which supports different docstring styles.
-Note that if the `Field` contains a description for a parameter as well as the docstring, the `Field`'s description is used. 
+In this updated schema, we use the `Field` class from `pydantic` to add descriptions to the `name` field. The description provides information about the field, giving even more context to the language model.
+
 
 !!! note "Code, schema, and prompt"
-We can run `openai_schema` to see exactly what the API will see, notice how the docstrings, attributes, types, and parameter descriptions are now part of the schema. This describes on this library's core philosophies.
+     We can run `openai_schema` to see exactly what the API will see, notice how the docstrings, attributes, types, and field descriptions are now part of the schema. This describes on this library's core philosophies.
 
     ```python hl_lines="2 3"
     class UserDetails(OpenAISchema):
-        """
-        Correctly extracted user information
-        :param name: the user's full name
-        :param age: age of the user
-        """
+        "Correctly extracted user information"
         name: str = Field(..., description="User's full name")
         age: int
 
@@ -167,12 +158,11 @@ We can run `openai_schema` to see exactly what the API will see, notice how the
         "type": "object",
         "properties": {
         "name": {
-            "type": "string",
-            "description": "User's full name"
+            "description": "User's full name",
+            "type": "string"
         },
         "age": {
             "type": "integer"
-            "description": "age of the user"
         }
         },
         "required": [
@@ -192,11 +182,7 @@ from instructor import OpenAISchema
 from pydantic import Field
 
 class UserDetails(OpenAISchema):
-    """
-    Correctly extracted user information
-    :param name: the user's full name
-    :param age: age of the user
-    """
+    "Correctly extracted user information"
     name: str = Field(..., description="User's full name")
     age: int
 

instructor/function_calls.py

@@ -21,7 +21,6 @@
 # SOFTWARE.
 
 import json
-from docstring_parser import parse
 from functools import wraps
 from typing import Any, Callable
 from pydantic import BaseModel, validate_arguments
@@ -66,25 +65,20 @@ def sum(a: int, b: int) -> int:
     def __init__(self, func: Callable) -> None:
         self.func = func
         self.validate_func = validate_arguments(func)
-        self.docstring = parse(self.func.__doc__)
-
         parameters = self.validate_func.model.model_json_schema()
         parameters["properties"] = {
             k: v
             for k, v in parameters["properties"].items()
             if k not in ("v__duplicate_kwargs", "args", "kwargs")
         }
-        for param in self.docstring.params:
-            if (name := param.arg_name) in parameters["properties"] and (description := param.description):
-                parameters["properties"][name]["description"] = description
         parameters["required"] = sorted(
             k for k, v in parameters["properties"].items() if not "default" in v
         )
         _remove_a_key(parameters, "additionalProperties")
         _remove_a_key(parameters, "title")
         self.openai_schema = {
             "name": self.func.__name__,
-            "description": self.docstring.short_description,
+            "description": self.func.__doc__,
             "parameters": parameters,
         }
         self.model = self.validate_func.model
@@ -134,20 +128,17 @@ def openai_schema(cls):
             model_json_schema (dict): A dictionary in the format of OpenAI's schema as jsonschema
         """
         schema = cls.model_json_schema()
-        docstring = parse(cls.__doc__)
         parameters = {
             k: v for k, v in schema.items() if k not in ("title", "description")
         }
-        for param in docstring.params:
-            if (name := param.arg_name) in parameters["properties"] and (description := param.description):
-                if "description" not in parameters["properties"][name]:
-                    parameters["properties"][name]["description"] = description
-
         parameters["required"] = sorted(
             k for k, v in parameters["properties"].items() if not "default" in v
         )
 
-        schema["description"] = docstring.short_description
+        if "description" not in schema:
+            schema[
+                "description"
+            ] = f"Correctly extracted `{cls.__name__}` with all the required parameters with correct types"
 
         _remove_a_key(parameters, "additionalProperties")
         _remove_a_key(parameters, "title")