mirror of
https://github.com/crewAIInc/crewAI.git
synced 2026-05-01 23:32:39 +00:00
Crewating a tool output parser
This commit is contained in:
João Moura
@@ -1,12 +1,15 @@
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from typing import Any, List
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from typing import Any, List, Union
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from langchain.output_parsers import PydanticOutputParser
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import instructor
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from langchain.prompts import PromptTemplate
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from langchain_core.tools import BaseTool
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from langchain_openai import ChatOpenAI
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from openai import OpenAI
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from crewai.agents.tools_handler import ToolsHandler
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from crewai.telemtry import Telemetry
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from crewai.tools.tool_calling import ToolCalling
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from crewai.tools.tool_calling import InstructorToolCalling, ToolCalling
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from crewai.tools.tool_output_parser import ToolOutputParser
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from crewai.utilities import I18N, Printer
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@@ -44,7 +47,7 @@ class ToolUsage:
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self._printer: Printer = Printer()
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self._telemetry: Telemetry = Telemetry()
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self._run_attempts: int = 1
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self._max_parsing_attempts: int = 3
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self._max_parsing_attempts: int = 2
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self._remeber_format_after_usages: int = 3
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self.tools_description = tools_description
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self.tools_names = tools_names
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@@ -62,38 +65,54 @@ class ToolUsage:
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tool = self._select_tool(calling.function_name)
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return self._use(tool_string=tool_string, tool=tool, calling=calling)
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def _use(self, tool_string: str, tool: BaseTool, calling: ToolCalling) -> None:
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try:
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if self._check_tool_repeated_usage(calling=calling):
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def _use(
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self,
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tool_string: str,
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tool: BaseTool,
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calling: Union[ToolCalling, InstructorToolCalling],
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) -> None:
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if self._check_tool_repeated_usage(calling=calling):
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try:
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result = self._i18n.errors("task_repeated_usage").format(
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tool=calling.function_name, tool_input=calling.arguments
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tool=calling.function_name,
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tool_input=", ".join(calling.arguments.values()),
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)
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else:
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self.tools_handler.on_tool_start(calling=calling)
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result = self.tools_handler.cache.read(
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tool=calling.function_name, input=calling.arguments
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self._printer.print(content=f"\n\n{result}\n", color="yellow")
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self._telemetry.tool_repeated_usage(
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llm=self.llm, tool_name=tool.name, attempts=self._run_attempts
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)
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result = self._format_result(result=result)
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return result
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except Exception:
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pass
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if not result:
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result = tool._run(**calling.arguments)
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self.tools_handler.on_tool_end(calling=calling, output=result)
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self.tools_handler.on_tool_start(calling=calling)
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self._printer.print(content=f"\n\n{result}\n", color="yellow")
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self._telemetry.tool_usage(
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llm=self.llm, tool_name=tool.name, attempts=self._run_attempts
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)
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result = self.tools_handler.cache.read(
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tool=calling.function_name, input=calling.arguments
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)
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result = self._format_result(result=result)
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return result
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except Exception:
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self._run_attempts += 1
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if self._run_attempts > self._max_parsing_attempts:
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self._telemetry.tool_usage_error(llm=self.llm)
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return ToolUsageErrorException(
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self._i18n.errors("tool_usage_error")
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).message
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return self.use(tool_string=tool_string)
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if not result:
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try:
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result = tool._run(**calling.arguments)
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except Exception as e:
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self._run_attempts += 1
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if self._run_attempts > self._max_parsing_attempts:
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self._telemetry.tool_usage_error(llm=self.llm)
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return ToolUsageErrorException(
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self._i18n.errors("tool_usage_exception").format(error=e)
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).message
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return self.use(tool_string=tool_string)
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self.tools_handler.on_tool_end(calling=calling, output=result)
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self._printer.print(content=f"\n\n{result}\n", color="yellow")
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self._telemetry.tool_usage(
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llm=self.llm, tool_name=tool.name, attempts=self._run_attempts
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)
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result = self._format_result(result=result)
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return result
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def _format_result(self, result: Any) -> None:
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self.task.used_tools += 1
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@@ -111,13 +130,15 @@ class ToolUsage:
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)
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return result
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def _check_tool_repeated_usage(self, calling: ToolCalling) -> None:
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def _check_tool_repeated_usage(
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self, calling: Union[ToolCalling, InstructorToolCalling]
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) -> None:
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if last_tool_usage := self.tools_handler.last_used_tool:
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return calling == last_tool_usage
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def _select_tool(self, tool_name: str) -> BaseTool:
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for tool in self.tools:
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if tool.name == tool_name:
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if tool.name.lower() == tool_name.lower():
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return tool
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raise Exception(f"Tool '{tool_name}' not found.")
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@@ -132,27 +153,63 @@ class ToolUsage:
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descriptions.append(
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"\n".join(
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[
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f"Funtion Name: {tool.name}",
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f"Funtion attributes: {args}",
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f"Tool Name: {tool.name.lower()}",
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f"Description: {tool.description}",
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f"Tool Arguments: {args}",
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]
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)
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)
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return "\n--\n".join(descriptions)
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def _tool_calling(self, tool_string: str) -> ToolCalling:
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def _tool_calling(
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self, tool_string: str
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) -> Union[ToolCalling, InstructorToolCalling]:
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try:
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parser = PydanticOutputParser(pydantic_object=ToolCalling)
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prompt = PromptTemplate(
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template="Return a valid schema for the one tool you must use with its arguments and values.\n\nTools available:\n\n{available_tools}\n\nUse this text to inform a valid ouput schema:\n{tool_string}\n\n{format_instructions}\n```",
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input_variables=["tool_string"],
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partial_variables={
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"available_tools": self._render(),
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"format_instructions": parser.get_format_instructions(),
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},
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tool_string = tool_string.replace(
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"Thought: Do I need to use a tool? Yes", ""
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)
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chain = prompt | self.llm | parser
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calling = chain.invoke({"tool_string": tool_string})
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tool_string = tool_string.replace("Action:", "Tool Name:")
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tool_string = tool_string.replace("Action Input:", "Tool Arguments:")
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if (isinstance(self.llm, ChatOpenAI)) and (
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self.llm.openai_api_base == None
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):
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client = instructor.patch(
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OpenAI(
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base_url=self.llm.openai_api_base,
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api_key=self.llm.openai_api_key,
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),
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mode=instructor.Mode.JSON,
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)
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calling = client.chat.completions.create(
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model=self.llm.model_name,
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messages=[
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{
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"role": "user",
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"content": f"Tools available:\n\n{self._render()}\n\nReturn a valid schema for the tool, use this text to inform a valid ouput schema:\n{tool_string}```",
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}
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],
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response_model=InstructorToolCalling,
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)
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else:
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parser = ToolOutputParser(pydantic_object=ToolCalling)
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prompt = PromptTemplate(
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template="Tools available:\n\n{available_tools}\n\nReturn a valid schema for the tool, use this text to inform a valid ouput schema:\n{tool_string}\n\n{format_instructions}\n```",
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input_variables=["tool_string"],
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partial_variables={
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"available_tools": self._render(),
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"format_instructions": """
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The schema should have the following structure, only two key:
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- function_name: str
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- arguments: dict (with all arguments being passed)
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Example:
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{"function_name": "function_name", "arguments": {"arg_name1": "value", "arg_name2": 2}}
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""",
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},
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)
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chain = prompt | self.llm | parser
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calling = chain.invoke({"tool_string": tool_string})
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except Exception:
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self._run_attempts += 1
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