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https://github.com/crewAIInc/crewAI.git
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Feature/use converter instead of manually trimming (#894)
* Exploring output being passed to tool selector to see if we can better format data * WIP. Adding JSON repair functionality * Almost done implementing JSON repair. Testing fixes vs current base case. * More action cleanup with additional tests * WIP. Trying to figure out what is going on with tool descriptions * Update tool description generation * WIP. Trying to find out what is causing the tools to duplicate * Replacing tools properly instead of duplicating them accidentally * Fixing issues for MR * Update dependencies for JSON_REPAIR * More cleaning up pull request * preppering for call * Fix type-checking issues --------- Co-authored-by: João Moura <joaomdmoura@gmail.com>
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@@ -1,9 +1,10 @@
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import os
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from inspect import signature
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from typing import Any, List, Optional, Tuple
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from langchain.agents.agent import RunnableAgent
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from langchain.agents.tools import BaseTool
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from langchain.agents.tools import tool as LangChainTool
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from langchain.tools.render import render_text_description
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from langchain_core.agents import AgentAction
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from langchain_core.callbacks import BaseCallbackHandler
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from langchain_openai import ChatOpenAI
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@@ -167,14 +168,16 @@ class Agent(BaseAgent):
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if memory.strip() != "":
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task_prompt += self.i18n.slice("memory").format(memory=memory)
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tools = tools or self.tools
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parsed_tools = self._parse_tools(tools or []) # type: ignore # Argument 1 to "_parse_tools" of "Agent" has incompatible type "list[Any] | None"; expected "list[Any]"
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tools = tools or self.tools or []
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parsed_tools = self._parse_tools(tools)
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self.create_agent_executor(tools=tools)
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self.agent_executor.tools = parsed_tools
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self.agent_executor.task = task
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self.agent_executor.tools_description = render_text_description(parsed_tools)
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# TODO: COMPARE WITH ARGS AND WITHOUT ARGS
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self.agent_executor.tools_description = self._render_text_description_and_args(
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parsed_tools
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)
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self.agent_executor.tools_names = self.__tools_names(parsed_tools)
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if self.crew and self.crew._train:
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@@ -189,6 +192,7 @@ class Agent(BaseAgent):
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"tools": self.agent_executor.tools_description,
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}
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)["output"]
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if self.max_rpm:
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self._rpm_controller.stop_rpm_counter()
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@@ -220,7 +224,7 @@ class Agent(BaseAgent):
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Returns:
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An instance of the CrewAgentExecutor class.
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"""
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tools = tools or self.tools
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tools = tools or self.tools or []
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agent_args = {
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"input": lambda x: x["input"],
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@@ -315,6 +319,7 @@ class Agent(BaseAgent):
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tools_list = []
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for tool in tools:
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tools_list.append(tool)
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return tools_list
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def _training_handler(self, task_prompt: str) -> str:
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@@ -341,6 +346,52 @@ class Agent(BaseAgent):
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)
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return task_prompt
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def _render_text_description(self, tools: List[BaseTool]) -> str:
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"""Render the tool name and description in plain text.
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Output will be in the format of:
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.. code-block:: markdown
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search: This tool is used for search
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calculator: This tool is used for math
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"""
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description = "\n".join(
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[
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f"Tool name: {tool.name}\nTool description:\n{tool.description}"
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for tool in tools
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]
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)
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return description
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def _render_text_description_and_args(self, tools: List[BaseTool]) -> str:
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"""Render the tool name, description, and args in plain text.
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Output will be in the format of:
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.. code-block:: markdown
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search: This tool is used for search, args: {"query": {"type": "string"}}
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calculator: This tool is used for math, \
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args: {"expression": {"type": "string"}}
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"""
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tool_strings = []
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for tool in tools:
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args_schema = str(tool.args)
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if hasattr(tool, "func") and tool.func:
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sig = signature(tool.func)
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description = (
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f"Tool Name: {tool.name}{sig}\nTool Description: {tool.description}"
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)
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else:
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description = (
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f"Tool Name: {tool.name}\nTool Description: {tool.description}"
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)
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tool_strings.append(f"{description}\nTool Arguments: {args_schema}")
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return "\n".join(tool_strings)
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@staticmethod
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def __tools_names(tools) -> str:
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return ", ".join([t.name for t in tools])
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