Switch from Gradio to Streamlit - more stable for HF Spaces

README.md

@@ -3,9 +3,8 @@ title: Roleplay Chat Box 🎭
 emoji: 🎭
 colorFrom: purple
 colorTo: pink
-sdk: gradio
-sdk_version: 3.35.0
-app_file: app.py
+sdk: streamlit
+app_file: app_streamlit.py
 pinned: false
 license: mit
 short_description: AI roleplay chat with 3 unique characters

app_streamlit.py

@@ -0,0 +1,127 @@
+import streamlit as st
+import os
+import sys
+import asyncio
+
+# Add backend to path for imports
+backend_path = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'backend')
+sys.path.insert(0, backend_path)
+
+from backend.models.character_manager import CharacterManager
+
+# Page config
+st.set_page_config(
+    page_title="🎭 Roleplay Chat Box",
+    page_icon="🎭",
+    layout="wide"
+)
+
+# Initialize session state
+if 'character_manager' not in st.session_state:
+    st.session_state.character_manager = None
+if 'messages' not in st.session_state:
+    st.session_state.messages = []
+if 'current_character' not in st.session_state:
+    st.session_state.current_character = 'moses'
+
+def initialize_models():
+    """Initialize the character manager"""
+    if st.session_state.character_manager is None:
+        with st.spinner("🔄 Loading character models..."):
+            try:
+                st.session_state.character_manager = CharacterManager()
+                loop = asyncio.new_event_loop()
+                asyncio.set_event_loop(loop)
+                loop.run_until_complete(st.session_state.character_manager.initialize())
+                loop.close()
+                st.success("✅ Models loaded successfully!")
+                return True
+            except Exception as e:
+                st.error(f"❌ Error loading models: {str(e)}")
+                import traceback
+                st.error(traceback.format_exc())
+                return False
+    return True
+
+# Sidebar for character selection
+with st.sidebar:
+    st.title("🎭 Characters")
+    
+    character = st.radio(
+        "Choose Character",
+        options=["moses", "samsung_employee", "jinx"],
+        format_func=lambda x: {
+            "moses": "📜 Moses - Biblical Prophet",
+            "samsung_employee": "💼 Samsung Employee - Tech Expert",
+            "jinx": "💥 Jinx - Chaotic Genius"
+        }[x],
+        key="character_selector"
+    )
+    
+    # Update character if changed
+    if character != st.session_state.current_character:
+        st.session_state.current_character = character
+        st.session_state.messages = []
+    
+    st.divider()
+    
+    if st.button("🗑️ Clear Chat"):
+        st.session_state.messages = []
+        st.rerun()
+    
+    st.divider()
+    st.markdown("### About")
+    st.markdown("""
+    This app uses LoRA (Low-Rank Adaptation) to create unique character personalities.
+    
+    - **Base Model**: Qwen3-0.6B
+    - **Adapters**: Character-specific LoRA weights
+    - **Memory Efficient**: Shares one base model
+    """)
+
+# Main chat interface
+st.title("🎭 Roleplay Chat Box")
+st.markdown(f"Currently chatting with: **{st.session_state.current_character}**")
+
+# Initialize models on first run
+if not initialize_models():
+    st.stop()
+
+# Display chat messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Chat input
+if prompt := st.chat_input("Type your message here..."):
+    # Add user message to chat
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    with st.chat_message("user"):
+        st.markdown(prompt)
+    
+    # Generate response
+    with st.chat_message("assistant"):
+        with st.spinner("Thinking..."):
+            try:
+                # Convert history for context
+                conversation_history = []
+                for msg in st.session_state.messages[-6:]:  # Last 3 exchanges
+                    if msg["role"] == "user":
+                        conversation_history.append({"role": "user", "content": msg["content"]})
+                    else:
+                        conversation_history.append({"role": "assistant", "content": msg["content"]})
+                
+                # Generate response
+                response = st.session_state.character_manager.generate_response(
+                    character_id=st.session_state.current_character,
+                    user_message=prompt,
+                    conversation_history=conversation_history[:-1]  # Exclude current message
+                )
+                
+                st.markdown(response)
+                st.session_state.messages.append({"role": "assistant", "content": response})
+                
+            except Exception as e:
+                error_msg = f"❌ Error: {str(e)}"
+                st.error(error_msg)
+                st.session_state.messages.append({"role": "assistant", "content": error_msg})

requirements.txt

@@ -7,8 +7,8 @@ datasets>=2.14.0
 huggingface-hub>=0.19.0
 safetensors>=0.4.0
 
-# Gradio for Hugging Face Spaces - using known stable version
-gradio==3.35.0
+# Streamlit for Hugging Face Spaces - stable and reliable
+streamlit>=1.28.0
 
 # Backend API
 fastapi>=0.104.0