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"
Domain
Subdomains
Classes
Dependencies
- langchain_classic.agents.agent
- langchain_classic.agents.conversational.prompt
- langchain_core.agents
- langchain_core.exceptions
- re
Source
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).
Analyze Your Own Codebase
Get architecture documentation, dependency graphs, and domain analysis for your codebase in minutes.
Try Supermodel Free