"OutputParserException: Could not parse LLM output" in create_pandas_dataframe_agent

[ArchieLuxton]

I get the "OutputParserException" error almost every time I run the agent, particularly when using the GPT-4 model. For example:

Requst: Calculate the average occupancy for each day of the week. It's absolutely crucial that you just return the dataframe.

Using a simple dataframe with few columns, I get the error: OutputParserException: Could not parse LLM output: Thought: To calculate the average occupancy for each day of the week, I need to group the dataframe by the 'Day_of_week' column and then calculate the mean of the 'Average_Occupancy' column for each group. I will use the pandas groupby() and mean() functions to achieve this.``

This happens almost every time when using gpt-4, and when using gpt-3.5-turbo, it doesn't listen to the second half of the instruction and returns a Pandas formula that returns the dataframe instead of the acutal data. Using gpt-3.5-turbo does seem to make it run more reliably (despite the incorrect result).

[shtratos]

Can you post the full prompt that goes into the model?

You can use tracing dashboard to capture that. https://python.langchain.com/en/latest/tracing.html

[tevslin]

I am getting the parser message (sometimes) when asking questions which do not require using Python tool or the panda to answer. The problem is often that the raw answer is returned without either an indication that the chain is finished or the expected "Action:...Action Input:.." sequence which regex is testing for

[Walker555]

I have similar issue: OutputParserException: Could not parse LLM output: 'Thought: I need to filter the dataframe to find rows where ...etc.

The MRKLOutputParser couldn't find the expected "Action:...Action Input:.." sequence which regex is testing for. Is it possible to specify another output_parser in method create_pandas_dataframe_agent ?

[Walker555]

It looks like the suggestion https://python.langchain.com/en/latest/modules/agents/agent_executors/examples/handle_parsing_errors.html works: agent = create_pandas_dataframe_agent(model, df, verbose=True, handle_parsing_errors="Check your output and make sure it conforms!")

[limgw1]

I have faced a similar issue while using the create_pandas_dataframe_agent as a modification to the CAMEL code. There is a part of the prompts specified by the CAMEL documentation code that has this snippet.

1. Instruct with a necessary input:
Instruction: <YOUR_INSTRUCTION>
Input: <YOUR_INPUT>

2. Instruct without any input:
Instruction: <YOUR_INSTRUCTION>
Input: None

I removed both the Input: parts and now the code works as intended. When I saw that the regex for the MRKL output parser was looking for the word Input I assumed that the output was read incorrectly because of my prompt.

[limgw1]

An addendum to my previous comment. After a few different tries it seems that the error is still occurring. It just happens that the current set of questions worked fine. Another solution that I tried and seemed to fix several problems down the line is by running this code. Note the extra IMPORTANT: line I added to the built in prompt template.

agent_name.agent.llm_chain.prompt.template = """
You are working with a pandas dataframe in Python. The name of the dataframe is `df`.
You should use the tools below to answer the question posed of you:

python_repl_ast: A Python shell. Use this to execute python commands. Input should be a valid python command. When using this tool, sometimes output is abbreviated - make sure it does not look abbreviated before using it in your answer.

Use the following format:

Question: the input question you must answer
Thought: you should always think about what to do
Action: the action to take, should be `python_repl_ast`
Action Input: the input to the action
Observation: the result of the action
...the Thought/Action/Action Input/Observation can repeat N times
Thought: I now know the answer to the question
Final Answer: the final answer to the original input question

This is the result of `print(df.head())`:
{df_head}

IMPORTANT: Every <Thought:> must either come with an <Action: and Action Input:> or <Final Answer:>

Begin!
Question: {input}
{agent_scratchpad}
"""

[dosubot[bot]]

Hi, @ArchieLuxton! 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.

From what I understand, you reported an issue regarding an "OutputParserException" error that occurs when running the agent with the GPT-4 model. This error prevents the parsing of the LLM output, leading to incorrect results or failure to listen to instructions. There have been some suggestions from other users, such as switching to the GPT-3.5-turbo model or modifying the code and prompt template to handle the parsing errors.

Before we proceed, we would like to confirm if this issue is still relevant to the latest version of the LangChain repository. If it is, please let us know by commenting on this issue. Otherwise, feel free to close the issue yourself. If we don't receive any response within 7 days, the issue will be automatically closed.

Thank you for your understanding, and we appreciate your contribution to the LangChain project. If you have any further questions or concerns, please don't hesitate to reach out.

[Realvincentyuan]

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

This does not work, I am using Llama 2 'llama-2-7b-chat.Q5_0.gguf', though I did find that larger Llama 2 model works better, without any code changes