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.pdf
RetryOutputParser
RetryOutputParser#
While in some cases it is possible to fix any parsing mistakes by only looking at the output, in other cases it can’t. An example of this is when the output is not just in the incorrect format, but is partially complete. Consider the below example.
from langchain.prompts import PromptTemplate, ChatPromptTemplate, HumanMessagePromptTemplate
from langchain.llms import OpenAI
from langchain.chat_models import ChatOpenAI
from langchain.output_parsers import PydanticOutputParser, OutputFixingParser, RetryOutputParser
from pydantic import BaseModel, Field, validator
from typing import List
template = """Based on the user question, provide an Action and Action Input for what step should be taken.
{format_instructions}
Question: {query}
Response:"""
class Action(BaseModel):
    action: str = Field(description="action to take")
    action_input: str = Field(description="input to the action")
        
parser = PydanticOutputParser(pydantic_object=Action)
prompt = PromptTemplate(
    template="Answer the user query.\n{format_instructions}\n{query}\n",
    input_variables=["query"],
    partial_variables={"format_instructions": parser.get_format_instructions()}
)
prompt_value = prompt.format_prompt(query="who is leo di caprios gf?")
bad_response = '{"action": "search"}'
If we try to parse this response as is, we will get an error
parser.parse(bad_response)
---------------------------------------------------------------------------
ValidationError                           Traceback (most recent call last)
File ~/workplace/langchain/langchain/output_parsers/pydantic.py:24, in PydanticOutputParser.parse(self, text)
     23     json_object = json.loads(json_str)
rtdocs_stable/api.python.langchain.com/en/stable/modules/prompts/output_parsers/examples/retry.html