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output_parser.py — langchain Source File

Architecture documentation for output_parser.py, a python file in the langchain codebase. 5 imports, 0 dependents.

Entity Profile

Dependency Diagram

graph LR
  c987d773_4ee0_05e6_37b6_25d9936daac6["output_parser.py"]
  67ec3255_645e_8b6e_1eff_1eb3c648ed95["re"]
  c987d773_4ee0_05e6_37b6_25d9936daac6 --> 67ec3255_645e_8b6e_1eff_1eb3c648ed95
  80d582c5_7cc3_ac96_2742_3dbe1cbd4e2b["langchain_core.agents"]
  c987d773_4ee0_05e6_37b6_25d9936daac6 --> 80d582c5_7cc3_ac96_2742_3dbe1cbd4e2b
  75137834_4ba7_dc43_7ec5_182c05eceedf["langchain_core.exceptions"]
  c987d773_4ee0_05e6_37b6_25d9936daac6 --> 75137834_4ba7_dc43_7ec5_182c05eceedf
  e160f068_75de_4342_6673_9969b919de85["langchain_classic.agents.agent"]
  c987d773_4ee0_05e6_37b6_25d9936daac6 --> e160f068_75de_4342_6673_9969b919de85
  08b9d246_36f3_9e50_1e87_83eccdb017c3["langchain_classic.agents.conversational.prompt"]
  c987d773_4ee0_05e6_37b6_25d9936daac6 --> 08b9d246_36f3_9e50_1e87_83eccdb017c3
  style c987d773_4ee0_05e6_37b6_25d9936daac6 fill:#6366f1,stroke:#818cf8,color:#fff

Relationship Graph

Source Code

import re

from langchain_core.agents import AgentAction, AgentFinish
from langchain_core.exceptions import OutputParserException

from langchain_classic.agents.agent import AgentOutputParser
from langchain_classic.agents.conversational.prompt import FORMAT_INSTRUCTIONS


class ConvoOutputParser(AgentOutputParser):
    """Output parser for the conversational agent."""

    ai_prefix: str = "AI"
    """Prefix to use before AI output."""

    format_instructions: str = FORMAT_INSTRUCTIONS
    """Default formatting instructions"""

    def get_format_instructions(self) -> str:
        """Returns formatting instructions for the given output parser."""
        return self.format_instructions

    def parse(self, text: str) -> AgentAction | AgentFinish:
        """Parse the output from the agent into an AgentAction or AgentFinish object.

        Args:
            text: The text to parse.

        Returns:
            An AgentAction or AgentFinish object.
        """
        if f"{self.ai_prefix}:" in text:
            return AgentFinish(
                {"output": text.rsplit(f"{self.ai_prefix}:", maxsplit=1)[-1].strip()},
                text,
            )
        regex = r"Action: (.*?)[\n]*Action Input: ([\s\S]*)"
        match = re.search(regex, text, re.DOTALL)
        if not match:
            msg = f"Could not parse LLM output: `{text}`"
            raise OutputParserException(msg)
        action = match.group(1)
        action_input = match.group(2)
        return AgentAction(action.strip(), action_input.strip(" ").strip('"'), text)

    @property
    def _type(self) -> str:
        return "conversational"

Subdomains

Dependencies

  • langchain_classic.agents.agent
  • langchain_classic.agents.conversational.prompt
  • langchain_core.agents
  • langchain_core.exceptions
  • re

Frequently Asked Questions

What does output_parser.py do?
output_parser.py is a source file in the langchain codebase, written in python. It belongs to the AgentOrchestration domain, ToolInterface subdomain.
What does output_parser.py depend on?
output_parser.py imports 5 module(s): langchain_classic.agents.agent, langchain_classic.agents.conversational.prompt, langchain_core.agents, langchain_core.exceptions, re.
Where is output_parser.py in the architecture?
output_parser.py is located at libs/langchain/langchain_classic/agents/conversational/output_parser.py (domain: AgentOrchestration, subdomain: ToolInterface, directory: libs/langchain/langchain_classic/agents/conversational).

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