Could not parse LLM output.
I am doing Q-A for CSV data using langchain CSV agent.
Here is my code:
import os
import pandas as pd
from langchain_experimental.agents.agent_toolkits import create_csv_agent
from langchain.llms import OpenAI
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
from transformers import pipeline
from langchain.llms import HuggingFacePipeline
from langchain.prompts import ChatPromptTemplate
os.environ["OPENAI_API_KEY"] = "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"
df = pd.read_csv("dataset.csv")
tokenizer = AutoTokenizer.from_pretrained("google/flan-t5-xl")
model = AutoModelForSeq2SeqLM.from_pretrained(
"google/flan-t5-xl",
max_length=512
)
pipe = pipeline(
"text2text-generation",
model=model,
tokenizer=tokenizer,
max_length=512,
repetition_penalty=1.15,
)
local_llm = HuggingFacePipeline(pipeline=pipe)
agent = create_csv_agent(
llm=local_llm, path="dataset.csv", verbose=True, handle_parsing_errors=True
)
try:
result = agent.run("How many people have same height?, return answer in text format.")
print("Result->", result)
prnt("Ket", result.keys())
except Exception as e:
print("e===", e)
In here I am getting error as : Could not parse LLM output.
So how to solve this issue?
If anyone have any idea then please help me to solve it out.