```pythonfrom langchain.chat_models import ChatOpenAIfr...

Plain Text

from langchain.chat_models import ChatOpenAI
from langchain.agents import initialize_agent
from langchain.chains.conversation.memory import ConversationBufferMemory
from llama_hub.file.unstructured.base import UnstructuredReader
from llama_index.tools import QueryEngineTool
from llama_index.agent import OpenAIAgent
...
agent_executor = initialize_agent(
    [query_engine_tool.to_langchain_tool], llm, agent="conversational-react-description", memory=memory
)

Traceback (most recent call last):
  File "D:\Documendz\code-python\LLM chat app\speechtt.py", line 74, in <module>
    agent_executor = initialize_agent(
  File "D:\Documendz\code-python\LLM chat app\aienv\lib\site-packages\langchain\agents\initialize.py", line 58, in initialize_agent
    agent_obj = agent_cls.from_llm_and_tools(
  File "D:\Documendz\code-python\LLM chat app\aienv\lib\site-packages\langchain\agents\conversational\base.py", line 107, in from_llm_and_tools
    cls._validate_tools(tools)
  File "D:\Documendz\code-python\LLM chat app\aienv\lib\site-packages\langchain\agents\conversational\base.py", line 89, in _validate_tools
    validate_tools_single_input(cls.__name__, tools)
  File "D:\Documendz\code-python\LLM chat app\aienv\lib\site-packages\langchain\agents\utils.py", line 9, in validate_tools_single_input
    if not tool.is_single_input:
AttributeError: 'function' object has no attribute 'is_single_input'

why am i getting this error

11 comments

kkapa.ai

Please stand by @betermagne as I search the knowledge base. I normally take about 20 seconds or so. :wave:

kkapa.ai

----------------------
The error message you're seeing is AttributeError: 'function' object has no attribute 'is_single_input'. This error is raised because the tool object you're trying to access the is_single_input attribute from is a function, not an object of a class that has the is_single_input attribute.

In the code snippet you provided, you're trying to convert a QueryEngineTool to a langchain tool using the to_langchain_tool method. However, based on the information provided in the extracts, it's not clear if the QueryEngineTool class or its instances have a to_langchain_tool method.

The extracts do show that QueryEngineTool instances can be used to initialize an OpenAIAgent from the llama_index.agent module, but there's no mention of a to_langchain_tool method or compatibility with langchain agents.

Here's an example of how a QueryEngineTool is used to initialize an OpenAIAgent:

Plain Text

from llama_index.agent import OpenAIAgent

agent = OpenAIAgent.from_tools(tools, verbose=True)

In this example, tools is a list of QueryEngineTool instances.

To resolve the error, you might need to check the documentation or source code of the QueryEngineTool and langchain classes to see if there's a way to convert a QueryEngineTool to a langchain tool. If there isn't, you might need to use a different approach to initialize your langchain agent.

Please note that this advice is based on the information provided in the extracts and might not fully resolve your issue. If you're still having trouble, I recommend checking the documentation of the libraries you're using or reaching out to their respective communities for support.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
----------------------

bbetermagne

@kapa.ai are you kidding me? are you even upto date with the docs? there is indeed a to_langchain_tool method for every BaseTool instance

kkapa.ai

Let me check the knowledge base for you. One moment! :books:

kkapa.ai

----------------------
I apologize for the confusion. Based on the information provided in the extracts, it's indeed possible to convert a tool to a LangChain tool using the to_langchain_structured_tool method. Here's an example of how it's done:

Plain Text

lc_tool = tool.to_langchain_structured_tool(verbose=True)

In this example, tool is an instance of a class that inherits from BaseTool.

However, in the code snippet you provided, you're trying to use the to_langchain_tool method, not to_langchain_structured_tool. If to_langchain_tool is indeed a method of QueryEngineTool or BaseTool, you might be able to resolve the error by replacing to_langchain_tool with to_langchain_structured_tool.

Here's how you might modify your code:

Plain Text

from langchain.chat_models import ChatOpenAI
from langchain.agents import initialize_agent
from langchain.chains.conversation.memory import ConversationBufferMemory
from llama_hub.file.unstructured.base import UnstructuredReader
from llama_index.tools import QueryEngineTool
from llama_index.agent import OpenAIAgent

# ... other code ...

query_engine_tool = QueryEngineTool(...)  # Initialize your QueryEngineTool

agent_executor = initialize_agent(
    [query_engine_tool.to_langchain_structured_tool()],  # Use to_langchain_structured_tool instead of to_langchain_tool
    llm,
    agent="conversational-react-description",
    memory=memory
)

Please note that this advice is based on the information provided in the extracts and might not fully resolve your issue. If you're still having trouble, I recommend checking the documentation of the libraries you're using or reaching out to their respective communities for support.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
----------------------

bbetermagne

@kapa.ai are you actually joking with me right now? what even is the difference between to structured tool and to tool, cause the last time i checked , both of them exist

kkapa.ai

Let me check the knowledge base for you. One moment! :books:

kkapa.ai

----------------------
I apologize for any confusion. Based on the information provided in the extracts, it's clear that there are methods to convert a tool to a LangChain tool. However, the specific methods mentioned are to_langchain_structured_tool and to_langchain_tool.

The to_langchain_structured_tool method is used to convert a tool to a structured LangChain tool. Here's an example of how it's used:

Plain Text

lc_tool = tool.to_langchain_structured_tool(verbose=True)

In this example, tool is an instance of a class that inherits from BaseTool.

The to_langchain_tool method is not explicitly mentioned in the provided extracts. However, based on your question, it seems that this method also exists and is used to convert a tool to a LangChain tool.

Without more information, it's hard to say what the exact differences between these two methods are. They might create different types of LangChain tools, or they might configure the tools in different ways.

To understand the differences between these methods, I recommend checking the documentation or source code of the classes that define these methods. This should provide you with a detailed explanation of what each method does and how they differ.

Please note that this advice is based on the information provided in the extracts and might not fully answer your question. If you're still having trouble, I recommend checking the documentation of the libraries you're using or reaching out to their respective communities for support.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
----------------------

bbetermagne

@kapa.ai wdym you have no information? you are literally the bot with access to docs

kkapa.ai

Let me check the knowledge base for you. One moment! :books:

kkapa.ai

----------------------
I apologize for any confusion. As an AI, I can only provide information based on the extracts provided to me. In this case, the extracts do not contain specific information about the to_langchain_tool and to_langchain_structured_tool methods.

While I can infer that these methods are used to convert a tool to a LangChain tool, I don't have enough information to explain the exact differences between these methods or why you're seeing the AttributeError: 'function' object has no attribute 'is_single_input' error.

To resolve this issue, I recommend checking the documentation or source code of the classes that define these methods. This should provide you with a detailed explanation of what each method does, how they differ, and why you might be seeing this error.

If you're still having trouble, consider reaching out to the communities or support channels associated with the libraries you're using. They might be able to provide more specific and detailed help.
----------------------
Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
----------------------

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```pythonfrom langchain.chat_models import ChatOpenAIfrom langchain.agents import initia