ValueError: Could not parse LLM output

[eriktlu]

I am having trouble using langchain with llama-index (gpt-index). I don't understand what is happening on the langchain side.

When I use OpenAIChat as LLM then sometimes with some user queries I get this error:

raise ValueError(f"Could not parse LLM output: `{llm_output}`")
ValueError: Could not parse LLM output: `Thought: Do I need to use a tool? No

And to make it worse when I switch to the OpenAI LLM then the agent almost never decides to use the tool.

I am okay with either solution but I just can't seem to fix it. What is happening?

My code:

from langchain.agents import ConversationalAgent, Tool, AgentExecutor
from langchain import OpenAI, LLMChain
from langchain.llms import OpenAIChat

TOOLS = [
    Tool(
        name = "GPT Index",
        func=lambda q: str(INDEX.query(q, llm_predictor=LLM_PREDICTOR, text_qa_template=QA_PROMPT, similarity_top_k=5, response_mode="compact")),
        description="useful for when you need to answer questions about weddings or marriage.",
        return_direct=True
    ),
]

LLM=OpenAIChat(temperature=0)

prefix = """Assistant is a large language model trained by OpenAI.

Assistant is designed to support a wide range of tasks, from answering simple questions to providing detailed explanations and discussions on a wide range of topics. As a language model, Assistant can generate human-like text based on input received, and can provide natural-sounding conversation or consistent, on-topic responses.

Assistant is constantly learning and improving, and its capabilities are always evolving. It can process vast amounts of text to understand and provide accurate and helpful answers to a variety of questions. Additionally, Assistant can generate its own text based on received input, allowing it to participate in discussions on a variety of topics, or provide explanations and commentary.

Overall, Assistant is a powerful tool that can support a variety of tasks and provide valuable insights and information on a wide range of topics. Whether you need help with a specific question or want to have a conversation about a specific topic, Assistant is here to help.

TOOLS:
------
Assistant has access to the following tools."""
suffix = """Answer the questions you know to the best of your knowledge.

Begin!

User Input: {input}
{agent_scratchpad}"""

prompt = ConversationalAgent.create_prompt(
    TOOLS,
    prefix=prefix,
    suffix=suffix,
    input_variables=["input", "agent_scratchpad"]
)

llm_chain = LLMChain(llm=LLM, prompt=prompt)

agent = ConversationalAgent(llm_chain=llm_chain)
agent_executor = AgentExecutor.from_agent_and_tools(agent=agent, tools=TOOLS, verbose=True)

response = agent_executor.run(user_message)

[binbinxue]

I also have this issue, it's worse when i set higher temperature for the model (which tends to make it produce outputs with more variety). These models don't always follow the instructions and that's the issue. I think we need some try catch exception that when LLM don't follow the template then we just return its generated output.

[itjuba]

Any solution to this ??

[claust]

This issue is a duplicate of #1477.

[libratiger]

Same problem, it is ok to use the OpenAI, but not the ChatOpenAI

[eriktlu]

I'm not sure what's the difference or why but I have not had any problems when I use ChatOpenAI from langchain.chat_models instead of OpenAIChat.

[alexprice12]

Hmm, interesting. I think the model (gpt-4) is not obeying the prompt. I'm encountering this issue periodically for all parsers.

[rishibh7]

Any solution yet? ‘OpenAI’ works fine, but not ‘ChatOpenAI’

[ninehills]

I solved this question.

When you use ChatOpenAI model, Please use chat-conversational-react-description agent

https://python.langchain.com/en/latest/modules/agents/agents/examples/chat_conversation_agent.html

This agent has been optimized for parsing Chat responses .

[rishibh7]

I am using dataframe agent, how can i use 'chat-conversational-react-description' agent with it

[dosubot[bot]]

Hi, @eriktlu! I'm Dosu, and I'm here to help the LangChain team manage their backlog. I wanted to let you know that we are marking this issue as stale.

Based on my understanding, you are experiencing a ValueError when using langchain with llama-index (gpt-index), specifically when using OpenAIChat as LLM and sometimes with certain user queries. Other users have also reported similar issues and suggested using the chat-conversational-react-description agent as a potential solution. However, the issue remains unresolved.

Could you please let us know if this issue is still relevant to the latest version of the LangChain repository? If it is, please comment on this issue to let us know. Otherwise, feel free to close the issue yourself, or the issue will be automatically closed in 7 days.

Thank you for your understanding and cooperation. Let us know if you have any further questions or need any assistance.

[tiagoefreitas]

Can you explain why this is not planned as it seems to be core functionally to have a proper fix?

On Fri, 29 Sep 2023 at 17:10, dosu-beta[bot] @.***> wrote:

Closed #1657 https://github.com/langchain-ai/langchain/issues/1657 as not planned.

— Reply to this email directly, view it on GitHub https://github.com/langchain-ai/langchain/issues/1657#event-10513141099, or unsubscribe https://github.com/notifications/unsubscribe-auth/ACXJNRWTFIBYALHRPAJKDYLX43XFVANCNFSM6AAAAAAV2ESVTQ . You are receiving this because you are subscribed to this thread.Message ID: @.***>

[dosubot[bot]]

@baskaryan Could you please help @tiagoefreitas with this issue? They mentioned that the closed issue #1657 is still relevant and needs a proper fix.

[dosubot[bot]]

Hi, @eriktlu,

I'm helping the LangChain team manage their backlog and am marking this issue as stale. The issue involves encountering a ValueError when using langchain with llama-index (gpt-index) and OpenAIChat as LLM. Other users have suggested potential solutions, but the issue remains unresolved.

Could you please confirm if this issue is still relevant to the latest version of the LangChain repository? If it is, kindly let the LangChain team know by commenting on the issue. Otherwise, feel free to close the issue yourself, or it will be automatically closed in 7 days. Thank you!