Upload 3 files

app.py

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+import json
+import gradio as gr
+import os
+from dataset_loader import load_dataset
+
+if not os.path.isdir("jlc_chatbot_data"):
+    load_dataset()
+
+from jlc_chatbot_data.utils import run_conversation
+
+
+import streamlit as st
+import traceback
+
+st.set_page_config(page_title="Facility Management Chatbot", page_icon=":robot:")
+
+
+if "messages" not in st.session_state:
+    st.session_state.messages = [
+        {"role": "assistant", "content": "How may I help you?"}
+    ]
+
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.write(message["content"])
+
+if prompt := st.chat_input():
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.write(prompt)
+
+if st.session_state.messages[-1]["role"] != "assistant":
+    try:
+        with st.chat_message("assistant"):
+            with st.spinner("Thinking..."):
+                answer = run_conversation(st.session_state.messages, prompt)
+            st.write(answer.replace("\n", "  \n"))
+
+        message = {"role": "assistant", "content": answer}
+        st.session_state.messages.append(message)
+    except:
+        st.error("An error occurred. Please try again.")
+        traceback.print_exc()

dataset_loader.py

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+from huggingface_hub import Repository
+from huggingface_hub import login
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+
+def load_dataset():
+    login(token=os.getenv("HUB_TOKEN"))
+
+    repo = Repository(
+        local_dir="jlc_chatbot_data",
+        repo_type="dataset",
+        clone_from="cjzhi98/facility-management-chatbot",
+        token=True,
+    )
+    repo.git_pull()

requirements.txt

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+requests
+python-dotenv
+huggingface_hub
+streamlit
+openai