typos

README.md

@@ -126,13 +126,14 @@ In this updated schema, we use the `Field` class from `pydantic` to add descript
 ```python hl_lines="2 3"
 class UserDetails(OpenAISchema):
  "Correctly extracted user information"
+
  name: str = Field(..., description="User's full name")
  age: int
 
 UserDetails.openai_schema
 ```
 
-```json hl_lines="3 8"
+```json
 {
 "name": "UserDetails",
 "description": "Correctly extracted user information",
@@ -204,7 +205,7 @@ Including **autocompletion**:
 ![autocomplete](docs/img/ide_support.png)
 
 And even **inline errors**
-d
+
 ![errors](docs/img/error2.png)
 
 ## OpenAI Schema and Pydantic

docs/index.md

@@ -146,60 +146,57 @@ Note that if the `Field` contains a description for a parameter as well as the d
 !!! 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.
 
- ```python hl_lines="3 5 7"
- class UserDetails(OpenAISchema):
-  """
-  Correctly extracted user information
-  :param name: the user's full name
-  :param age: age of the user
-  """
-  name: str = Field(..., description="User's full name")
-  age: int
-
- UserDetails.openai_schema
- ```
+```python
+class UserDetails(OpenAISchema):
+ """
+ Correctly extracted user information
 
- ```json hl_lines="3 9 13"
- {
- "name": "UserDetails",
- "description": "Correctly extracted user information",
- "parameters": {
-  "type": "object",
-  "properties": {
-  "name": {
-  "type": "string",
-  "description": "User's full name"
-  },
-  "age": {
-  "type": "integer"
-  "description": "age of the user"
-  }
-  },
-  "required": [
-  "age",
-  "name"
-  ]
- }
+ :param name: the user's full name
+ :param age: age of the user
+ """
+ name: str = Field(..., description="User's full name")
+ age: int
+
+UserDetails.openai_schema
+```
+
+```json hl_lines="3 9 13"
+{
+"name": "UserDetails",
+"description": "Correctly extracted user information",
+"parameters": {
+ "type": "object",
+ "properties": {
+ "name": {
+ "type": "string",
+ "description": "User's full name"
+ },
+ "age": {
+ "type": "integer"
+ "description": "age of the user"
  }
- ```
+ },
+ "required": [
+ "age",
+ "name"
+ ]
+}
+}
+```
 
 ### Section 3: Calling the ChatCompletion
 
 With the schema defined, let's proceed with calling the `ChatCompletion` API using the defined schema and messages.
 
-```python hl_lines="11 12 15"
+```python hl_lines="11 12"
 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
- """
  name: str = Field(..., description="User's full name")
  age: int
 
+
 completion = openai.ChatCompletion.create(
  model="gpt-3.5-turbo-0613",
  functions=[UserDetails.openai_schema],
@@ -219,8 +216,9 @@ Note that we have omitted the additional parameters that can be included in the
 
 To deserialize the response from the `ChatCompletion` API back into an instance of the `UserDetails` class, we can use the `from_response` method.
 
-```python hl_lines="1"
+```python
 user = UserDetails.from_response(completion)
+
 print(user.name) # Output: John Doe
 print(user.age) # Output: 30
 ```