Pipeline is stuck running in a loop with passed validator

[kirill-andr]

I keep getting an error, although I believe I implemented Haystack very close to the cookbook.

Example I used:
https://haystack.deepset.ai/tutorials/28_structured_output_with_loop

Error:

RuntimeWarning: Pipeline is stuck running in a loop. Partial outputs will be returned. Check the Pipeline graph for possible issues.
  warn(RuntimeWarning(msg))

The pipeline image:

The output validator:

import json
import pydantic
from pydantic import ValidationError
from typing import Optional, List
from colorama import Fore
from haystack import component


# Define the component input parameters
@component
class JsonGraphqlOutputValidator:
    def __init__(self, pydantic_model: pydantic.BaseModel):
        self.pydantic_model = pydantic_model
        self.iteration_counter = 0

    # Define the component output
    @component.output_types(valid_replies=List[str], invalid_replies=Optional[List[str]], error_message=Optional[str])
    def run(self, replies: List[str]):

        self.iteration_counter += 1
        ## Try to parse the LLM's reply ##
        # If the LLM's reply is a valid object, return `"valid_replies"`
        try:
            output_dict = json.loads(replies[0])
            self.pydantic_model.model_validate(output_dict)
            print(
                Fore.GREEN
                + f"OutputValidator at Iteration {self.iteration_counter}: Valid JSON from LLM - No need for looping: {replies[0]}"
            )
            return {"valid_replies": replies}

        # If the LLM's reply is corrupted or not valid, return "invalid_replies" and the "error_message" for LLM to try again
        except (ValueError, ValidationError) as e:
            print(
                Fore.RED
                + f"OutputValidator at Iteration {self.iteration_counter}: Invalid JSON from LLM - Let's try again.\n"
                  f"Output from LLM:\n {replies[0]} \n"
                  f"Error from OutputValidator: {e}"
            )
            return {"invalid_replies": replies, "error_message": str(e)}

and the code:

pipeline = Pipeline()
    pipeline.add_component(instance=PromptBuilder(template=QUERY_TEMPLATE), name="prompt_builder")
    pipeline.add_component(instance=OpenAIGenerator(api_key=Secret.from_env_var("OPENAI_API_KEY")), name="llm")
    output_validator = JsonGraphqlOutputValidator(pydantic_model=LlmResponseEndpointGraphql)
    json_schema = LlmResponseEndpointGraphql.model_json_schema()
    pipeline.add_component(instance=output_validator, name="output_validator")

    pipeline.connect("prompt_builder", "llm")
    pipeline.connect("llm", "output_validator")

    # If a component has more than one output or input, explicitly specify the connections:
    pipeline.connect("output_validator.invalid_replies", "prompt_builder.invalid_replies")
    pipeline.connect("output_validator.error_message", "prompt_builder.error_message")

    pipeline.draw("auto-correct-pipeline.png")

    result = pipeline.run({"prompt_builder": {"company": config['integration_name'], "schema": json_schema, "context": content}})
    valid_reply = result["output_validator"]["valid_replies"][0]
    valid_json = json.loads(valid_reply)
    print(valid_json)

[d-kleine]

this is a warning, not an error. also reported in issues #8641