Upload 3 files

app.py

@@ -1,64 +1,81 @@
-import gradio as gr
-from huggingface_hub import InferenceClient
+import streamlit as st
+from chatbot import (
+    get_googlegenai_client,
+    get_default_model,
+    load_chat_history,
+    save_chat_history
+)
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Centered Title
+st.markdown("""
+    <h1 style='text-align: center;'>Welcome, ChatGPT Clone</h1>
+""", unsafe_allow_html=True)
 
+client = get_googlegenai_client()
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+# Initialize session state
+if "googlegenai_model" not in st.session_state:
+    st.session_state["googlegenai_model"] = get_default_model()
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+if "messages" not in st.session_state:
+    st.session_state.messages = load_chat_history()
 
-    messages.append({"role": "user", "content": message})
+# Sidebar: Clear history
+with st.sidebar:
+    if st.button("Delete Chat History"):
+        st.session_state.messages = []
+        save_chat_history([])
 
-    response = ""
+# Show chat history
+for msg in st.session_state.messages:
+    role = msg["role"]
+    content = msg["content"]
 
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
+    if role == "user":
+        st.markdown(f"""
+        <div style='text-align: right; background-color: #f0f0f5; padding: 10px 15px; border-radius: 20px; margin: 10px 0; display: inline-block; max-width: 80%; float: right; clear: both;'>
+            {content}
+        </div>
+        """, unsafe_allow_html=True)
+    else:
+        st.markdown(f"""
+        <div style='text-align: left; margin: 10px 0; max-width: 80%; float: left; clear: both;'>
+            {content}
+        </div>
+        """, unsafe_allow_html=True)
+    st.markdown("<div style='clear: both'></div>", unsafe_allow_html=True)
 
-        response += token
-        yield response
+# Input field
+if prompt := st.chat_input("Ask anything"):
+    # Append user message
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    st.markdown(f"""
+    <div style='text-align: right; background-color: #f0f0f5; padding: 10px 15px; border-radius: 20px; margin: 10px 0; display: inline-block; max-width: 80%; float: right; clear: both;'>
+        {prompt}
+    </div>
+    """, unsafe_allow_html=True)
 
+    # Stream assistant response
+    full_response = ""
+    response_container = st.empty()
+    response = client.stream(st.session_state.messages)
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+    for chunk in response:
+        full_response += chunk.content or ""
+        response_container.markdown(f"""
+        <div style='text-align: left; margin: 10px 0; max-width: 80%; float: left; clear: both;'>
+            {full_response + "▌"}
+        </div>
+        """, unsafe_allow_html=True)
 
+    # Final response (cleaned up)
+    response_container.markdown(f"""
+    <div style='text-align: left; margin: 10px 0; max-width: 80%; float: left; clear: both;'>
+        {full_response}
+    </div>
+    """, unsafe_allow_html=True)
+    st.markdown("<div style='clear: both'></div>", unsafe_allow_html=True)
 
-if __name__ == "__main__":
-    demo.launch()
+    # Save assistant response
+    st.session_state.messages.append({"role": "assistant", "content": full_response})
+    save_chat_history(st.session_state.messages)

chatbot.py

@@ -0,0 +1,20 @@
+import os
+import shelve
+from langchain_google_genai import ChatGoogleGenerativeAI
+
+def get_default_model():
+    return "gemini-2.5-flash"
+
+def get_googlegenai_client():
+    return ChatGoogleGenerativeAI(model=get_default_model(), streaming=True)
+
+def get_storage_path():
+    return os.path.join("/tmp", "chat_history")
+
+def load_chat_history():
+    with shelve.open(get_storage_path()) as db:
+        return db.get("messages", [])
+
+def save_chat_history(messages):
+    with shelve.open(get_storage_path()) as db:
+        db["messages"] = messages

requirements.txt

@@ -1 +1,4 @@
-huggingface_hub==0.25.2
+streamlit>=1.32.0
+langchain>=0.1.16
+langchain-google-genai>=1.0.0
+google-generativeai>=0.5.4