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# Camel.societies.workforce.structured output handler
## StructuredOutputHandler
```python theme={"system"}
class StructuredOutputHandler:
```
Handler for generating prompts and extracting structured output from
agent responses.
This handler provides functionality to:
* Generate prompts that guide agents to produce structured output
* Extract structured data from agent responses using regex patterns
* Provide fallback mechanisms when extraction fails
* Support the existing structured output schemas used in workforce.py
### generate\_structured\_prompt
```python theme={"system"}
def generate_structured_prompt(
base_prompt: str,
schema: Type[BaseModel],
examples: Optional[List[Dict[str, Any]]] = None,
additional_instructions: Optional[str] = None
):
```
Generate a prompt that guides agents to produce structured output.
**Parameters:**
* **base\_prompt** (str): The base prompt content.
* **schema** (Type\[BaseModel]): The Pydantic model schema for the expected output.
* **examples** (Optional\[List\[Dict\[str, Any]]]): Optional examples of valid output.
* **additional\_instructions** (Optional\[str]): Additional instructions for output formatting.
**Returns:**
str: The enhanced prompt with structured output instructions.
### extract\_json
```python theme={"system"}
def extract_json(text: str, schema: Optional[Type[BaseModel]] = None):
```
Extract JSON data from text using multiple patterns.
**Parameters:**
* **text** (str): The text containing JSON data.
* **schema** (Optional\[Type\[BaseModel]]): Optional schema for targeted extraction.
**Returns:**
Optional\[Dict\[str, Any]]: Extracted JSON data or None if extraction
fails.
### \_extract\_with\_schema\_patterns
```python theme={"system"}
def _extract_with_schema_patterns(text: str, schema: Type[BaseModel]):
```
Extract data using schema-specific patterns.
**Parameters:**
* **text** (str): The text to extract from.
* **schema** (Type\[BaseModel]): The schema to use for extraction.
**Returns:**
Optional\[Dict\[str, Any]]: Extracted data or None.
### parse\_structured\_response
```python theme={"system"}
def parse_structured_response(
response_text: str,
schema: Type[BaseModel],
fallback_values: Optional[Dict[str, Any]] = None
):
```
Parse agent response into structured data with fallback support.
**Parameters:**
* **response\_text** (str): The agent's response text.
* **schema** (Type\[BaseModel]): The expected schema.
* **fallback\_values** (Optional\[Dict\[str, Any]]): Fallback values to use if parsing fails.
**Returns:**
Union\[BaseModel, Dict\[str, Any]]: Parsed data as schema instance
or fallback dictionary.
### \_fix\_common\_issues
```python theme={"system"}
def _fix_common_issues(data: Dict[str, Any], schema: Type[BaseModel]):
```
Attempt to fix common validation issues in extracted data.
**Parameters:**
* **data** (Dict\[str, Any]): The extracted data.
* **schema** (Type\[BaseModel]): The target schema.
**Returns:**
Optional\[Dict\[str, Any]]: Fixed data or None if unfixable.
### \_create\_default\_instance
```python theme={"system"}
def _create_default_instance(schema: Type[BaseModel]):
```
Create a default instance of the schema with minimal required
fields.
**Parameters:**
* **schema** (Type\[BaseModel]): The schema to instantiate.
**Returns:**
BaseModel: Default instance of the schema.
### validate\_response
```python theme={"system"}
def validate_response(
response: Union[BaseModel, Dict[str, Any]],
schema: Type[BaseModel]
):
```
Validate that a response conforms to the expected schema.
**Parameters:**
* **response**: The response to validate.
* **schema** (Type\[BaseModel]): The expected schema.
**Returns:**
bool: True if valid, False otherwise.
### create\_fallback\_response
```python theme={"system"}
def create_fallback_response(
schema: Type[BaseModel],
error_message: str,
context: Optional[Dict[str, Any]] = None
):
```
Create a fallback response for a given schema with error context.
**Parameters:**
* **schema** (Type\[BaseModel]): The schema to create a response for.
* **error\_message** (str): The error message to include.
* **context** (Optional\[Dict\[str, Any]]): Additional context for the fallback.
**Returns:**
BaseModel: A valid instance of the schema with fallback values.