Upload 3 files

app.py

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+import os
+import pickle
+from pathlib import Path
+import streamlit as st
+import streamlit_authenticator as stauth
+import traceback
+from dataset_loader import load_dataset
+from dotenv import load_dotenv
+
+load_dotenv()
+
+if not os.path.isdir("spsetia_chatbot_data"):
+    load_dataset()
+
+from spsetia_chatbot_data.utils import (
+    run_conversation,
+    record_db,
+    hashed_passwords,
+)
+
+
+st.set_page_config(page_title="S P Setia Chatbot", page_icon=":robot:", layout="wide")
+
+
+# --- USER AUTHENTICATION ---
+names = ["S P Setia Admin"]
+usernames = ["spsetia_admin"]
+
+authenticator = stauth.Authenticate(
+    names,
+    usernames,
+    hashed_passwords,
+    "spsetia_chatbot",
+    "eqiddnksadjw",
+    cookie_expiry_days=30,
+)
+
+name, authentication_status, username = authenticator.login("Login", "main")
+
+if authentication_status == False:
+    st.error("Username/password is incorrect")
+
+if authentication_status == None:
+    st.warning("Please enter your username and password")
+
+if authentication_status:
+    st.sidebar.title(f"S P Setia Chatbot")
+    st.sidebar.header(f"Welcome {name}")
+    authenticator.logout("Logout", "sidebar")
+    if st.sidebar.button("Refresh Chat"):
+        st.session_state.messages = [
+            {"role": "assistant", "content": "How may I help you?"}
+        ]
+    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..."):
+                    response = run_conversation(
+                        st.session_state.messages, prompt, username
+                    )
+                    qa_id = response[4]
+                    prompt_tokens = response[5]
+                    completion_tokens = response[6]
+                    if response[3]:
+                        if isinstance(response[0], list):
+                            answer = ""
+                            for item in response[0]:
+                                answer += f"""{item[0]}\n"""
+                                st.text(item[0])
+                                for image in item[1]:
+                                    if image:
+                                        st.image(image)
+                            reference = f"""  \n\nReference  \nfolder: {response[2]["folder"]}  \nfile: {response[2]["file"]}"""
+                            st.text(reference)
+                            answer += reference
+                            record_db(
+                                content=answer,
+                                qa_id=qa_id,
+                                msg_mode=1,
+                                recipient_id=username,
+                                prompt_tokens=prompt_tokens,
+                                completion_tokens=completion_tokens,
+                            )
+                        else:
+                            answer = response[0]
+                            reference = f"""  \n\nReference  \nfolder: {response[2]["folder"]}  \nfile: {response[2]["file"]}"""
+                            answer += reference
+                            st.text(answer)
+                            record_db(
+                                content=answer,
+                                qa_id=qa_id,
+                                msg_mode=1,
+                                recipient_id=username,
+                                prompt_tokens=prompt_tokens,
+                                completion_tokens=completion_tokens,
+                            )
+                    else:
+                        answer = response[0]
+                        st.text(answer)
+                        if images := response[1]:
+                            if isinstance(images, list):
+                                for image in images:
+                                    st.image(image)
+                        record_db(
+                            content=answer,
+                            qa_id=qa_id,
+                            msg_mode=1,
+                            recipient_id=username,
+                            prompt_tokens=prompt_tokens,
+                            completion_tokens=completion_tokens,
+                        )
+
+            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="spsetia_chatbot_data",
+        repo_type="dataset",
+        clone_from="cjzhi98/spsetia-chatbot",
+        token=True,
+    )
+    repo.git_pull()

requirements.txt

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+openai
+pandas
+fuzzywuzzy
+python-dotenv
+numpy
+python-Levenshtein
+streamlit
+streamlit-authenticator==0.1.5
+prettyprint
+boto3
+huggingface_hub