JsonSchemaValidator

Validates JSON content of ChatMessage against a specified JSON Schema.

Basic Information

• Type: haystack_integrations.validators.json_schema.JsonSchemaValidator

Inputs

Parameter	Type	Default	Description
messages	List[ChatMessage]		A list of ChatMessage instances to be validated. The last message in this list is the one that is validated.
json_schema	Optional[Dict[str, Any]]	None	A dictionary representing the JSON schema against which the messages' content is validated. If not provided, the schema from the component init is used.
error_template	Optional[str]	None	A custom template string for formatting the error message in case of validation. If not provided, the error_template from the component init is used.

Outputs

Parameter	Type	Default	Description
validated	List[ChatMessage]		A dictionary with the following keys: - "validated": A list of messages if the last message is valid. - "validation_error": A list of messages if the last message is invalid.
validation_error	List[ChatMessage]		A dictionary with the following keys: - "validated": A list of messages if the last message is valid. - "validation_error": A list of messages if the last message is invalid.

Overview

Work in Progress

Bear with us while we're working on adding pipeline examples and most common components connections.

Validates JSON content of ChatMessage against a specified JSON Schema.

If JSON content of a message conforms to the provided schema, the message is passed along the "validated" output. If the JSON content does not conform to the schema, the message is passed along the "validation_error" output. In the latter case, the error message is constructed using the provided error_template or a default template. These error ChatMessages can be used by LLMs in Haystack 2.x recovery loops.

Usage example:

from typing import List

from haystack import Pipeline
from haystack.components.generators.chat import OpenAIChatGenerator
from haystack.components.joiners import BranchJoiner
from haystack.components.validators import JsonSchemaValidator
from haystack import component
from haystack.dataclasses import ChatMessage

@component
class MessageProducer:

    @component.output_types(messages=List[ChatMessage])
    def run(self, messages: List[ChatMessage]) -> dict:
        return {"messages": messages}

p = Pipeline()
p.add_component("llm", OpenAIChatGenerator(model="gpt-4-1106-preview",
                                           generation_kwargs={"response_format": {"type": "json_object"}}))
p.add_component("schema_validator", JsonSchemaValidator())
p.add_component("joiner_for_llm", BranchJoiner(List[ChatMessage]))
p.add_component("message_producer", MessageProducer())

p.connect("message_producer.messages", "joiner_for_llm")
p.connect("joiner_for_llm", "llm")
p.connect("llm.replies", "schema_validator.messages")
p.connect("schema_validator.validation_error", "joiner_for_llm")

result = p.run(data={
    "message_producer": {
        "messages":[ChatMessage.from_user("Generate JSON for person with name 'John' and age 30")]},
        "schema_validator": {
            "json_schema": {
                "type": "object",
                "properties": {"name": {"type": "string"},
                "age": {"type": "integer"}
            }
        }
    }
})
print(result)
>> {'schema_validator': {'validated': [ChatMessage(_role=<ChatRole.ASSISTANT: 'assistant'>,
_content=[TextContent(text="\n{\n  "name": "John",\n  "age": 30\n}")],
_name=None, _meta={'model': 'gpt-4-1106-preview', 'index': 0,
'finish_reason': 'stop', 'usage': {'completion_tokens': 17, 'prompt_tokens': 20, 'total_tokens': 37}})]}}

Usage Example

components:
  JsonSchemaValidator:
    type: components.validators.json_schema.JsonSchemaValidator
    init_parameters:

Parameters

Init Parameters

These are the parameters you can configure in Pipeline Builder:

Parameter	Type	Default	Description
json_schema	Optional[Dict[str, Any]]	None	A dictionary representing the JSON schema against which the messages' content is validated.
error_template	Optional[str]	None	A custom template string for formatting the error message in case of validation failure.

Run Method Parameters

These are the parameters you can configure for the component's run() method. This means you can pass these parameters at query time through the API, in Playground, or when running a job. For details, see Modify Pipeline Parameters at Query Time.

Parameter	Type	Default	Description
messages	List[ChatMessage]		A list of ChatMessage instances to be validated. The last message in this list is the one that is validated.
json_schema	Optional[Dict[str, Any]]	None	A dictionary representing the JSON schema against which the messages' content is validated. If not provided, the schema from the component init is used.
error_template	Optional[str]	None	A custom template string for formatting the error message in case of validation. If not provided, the error_template from the component init is used.