mirror of
https://github.com/langchain-ai/streamlit-agent.git
synced 2026-07-01 09:25:05 -04:00
Joshua Carroll
90 lines
2.7 KiB
Python
90 lines
2.7 KiB
Python
from langchain.agents import AgentType
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from langchain_experimental.agents import create_pandas_dataframe_agent
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from langchain.callbacks import StreamlitCallbackHandler
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from langchain.chat_models import ChatOpenAI
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import streamlit as st
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import pandas as pd
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import os
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file_formats = {
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"csv": pd.read_csv,
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"xls": pd.read_excel,
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"xlsx": pd.read_excel,
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"xlsm": pd.read_excel,
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"xlsb": pd.read_excel,
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}
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def clear_submit():
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"""
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Clear the Submit Button State
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Returns:
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"""
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st.session_state["submit"] = False
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@st.cache_data(ttl="2h")
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def load_data(uploaded_file):
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try:
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ext = os.path.splitext(uploaded_file.name)[1][1:].lower()
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except:
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ext = uploaded_file.split(".")[-1]
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if ext in file_formats:
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return file_formats[ext](uploaded_file)
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else:
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st.error(f"Unsupported file format: {ext}")
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return None
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st.set_page_config(page_title="LangChain: Chat with pandas DataFrame", page_icon="🦜")
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st.title("🦜 LangChain: Chat with pandas DataFrame")
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uploaded_file = st.file_uploader(
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"Upload a Data file",
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type=list(file_formats.keys()),
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help="Various File formats are Support",
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on_change=clear_submit,
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)
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if not uploaded_file:
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st.warning(
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"This app uses LangChain's `PythonAstREPLTool` which is vulnerable to arbitrary code execution. Please use caution in deploying and sharing this app."
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)
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if uploaded_file:
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df = load_data(uploaded_file)
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openai_api_key = st.sidebar.text_input("OpenAI API Key", type="password")
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if "messages" not in st.session_state or st.sidebar.button("Clear conversation history"):
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st.session_state["messages"] = [{"role": "assistant", "content": "How can I help you?"}]
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for msg in st.session_state.messages:
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st.chat_message(msg["role"]).write(msg["content"])
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if prompt := st.chat_input(placeholder="What is this data about?"):
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st.session_state.messages.append({"role": "user", "content": prompt})
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st.chat_message("user").write(prompt)
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if not openai_api_key:
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st.info("Please add your OpenAI API key to continue.")
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st.stop()
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llm = ChatOpenAI(
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temperature=0, model="gpt-3.5-turbo-0613", openai_api_key=openai_api_key, streaming=True
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)
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pandas_df_agent = create_pandas_dataframe_agent(
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llm,
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df,
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verbose=True,
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agent_type=AgentType.OPENAI_FUNCTIONS,
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handle_parsing_errors=True,
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)
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with st.chat_message("assistant"):
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st_cb = StreamlitCallbackHandler(st.container(), expand_new_thoughts=False)
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response = pandas_df_agent.run(st.session_state.messages, callbacks=[st_cb])
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st.session_state.messages.append({"role": "assistant", "content": response})
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st.write(response)
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