Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,147 @@
-import altair as alt
-import numpy as np
-import pandas as pd
+import os
 import streamlit as st
+from transformers import pipeline
+import datetime
+import pyttsx3
+import tempfile
+import speech_recognition as sr
 
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+st.set_page_config(page_title="Winner Chat", layout="wide", initial_sidebar_state="expanded")
+
+# Sidebar: Model selector + Dark mode
+st.sidebar.title("⚙️ Settings")
+model_name = st.sidebar.selectbox("Choose model", ["Arni1ntares/Winner", "gpt2", "distilgpt2"])
+dark_mode = st.sidebar.toggle("🌙 Dark Mode")
+enable_tts = st.sidebar.toggle("🔊 Enable Voice Output")
+enable_mic = st.sidebar.toggle("🎙️ Enable Voice Input")
+
+# Voice recognizer
+recognizer = sr.Recognizer()
+
+@st.cache_resource(show_spinner="Loading model...")
+def load_model(model_name):
+    return pipeline("text-generation", model=model_name)
+
+pipe = load_model(model_name)
+
+# Init TTS
+tts = pyttsx3.init()
+tts.setProperty('rate', 165)
+
+# Custom CSS for message bubbles and dark mode
+def add_css():
+    css = """
+    <style>
+    .user-msg {
+        background-color: #DCF8C6;
+        padding: 0.5em 1em;
+        border-radius: 10px;
+        margin: 0.3em 0;
+    }
+    .bot-msg {
+        background-color: #F1F0F0;
+        padding: 0.5em 1em;
+        border-radius: 10px;
+        margin: 0.3em 0;
+    }
+    .avatar {
+        width: 30px; height: 30px; border-radius: 50%;
+        display: inline-block; vertical-align: middle;
+    }
+    .msg-container {
+        display: flex;
+        align-items: flex-start;
+        gap: 10px;
+    }
+    .bubble-container {
+        max-width: 80%;
+    }
+    </style>
+    """
+    if dark_mode:
+        css += """
+        <style>
+        body {
+            background-color: #0e1117;
+            color: white;
+        }
+        .bot-msg {
+            background-color: #2c2f36;
+            color: white;
+        }
+        .user-msg {
+            background-color: #005c4b;
+            color: white;
+        }
+        </style>
+        """
+    st.markdown(css, unsafe_allow_html=True)
+
+add_css()
+
+st.title("🤖 Winner Chat – Enhanced UI")
+
+# Init chat state
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat history
+for msg in st.session_state.messages:
+    avatar = "🧑" if msg["role"] == "user" else "🤖"
+    bubble_class = "user-msg" if msg["role"] == "user" else "bot-msg"
+    with st.container():
+        st.markdown(f"""
+        <div class="msg-container">
+            <div class="avatar">{avatar}</div>
+            <div class="bubble-container"><div class="{bubble_class}">{msg['content']}</div></div>
+        </div>
+        """, unsafe_allow_html=True)
+
+# Voice input
+user_input = ""
+if enable_mic:
+    st.subheader("🎙️ Voice Input")
+    mic_button = st.button("Start Listening")
+    if mic_button:
+        with sr.Microphone() as source:
+            st.info("Listening...")
+            audio = recognizer.listen(source)
+            try:
+                user_input = recognizer.recognize_google(audio)
+                st.success(f"You said: {user_input}")
+            except Exception as e:
+                st.error(f"Error: {e}")
+else:
+    user_input = st.chat_input("Type your message...")
+
+if user_input:
+    # Save user input
+    st.session_state.messages.append({"role": "user", "content": user_input})
+
+    with st.spinner("Thinking..."):
+        full_prompt = "\n".join(
+            [f"{m['role']}: {m['content']}" for m in st.session_state.messages]
+        )
+        result = pipe(full_prompt, max_new_tokens=200, temperature=0.7)[0]["generated_text"]
+        response = result.replace(full_prompt, "").strip()
+
+    st.session_state.messages.append({"role": "assistant", "content": response})
+
+    if enable_tts:
+        tts.say(response)
+        tts.runAndWait()
+
+    st.experimental_rerun()
+
+# Export conversation
+st.sidebar.markdown("---")
+if st.sidebar.button("📥 Export Chat"):
+    now = datetime.datetime.now().strftime("%Y%m%d-%H%M%S")
+    fname = f"chat_{now}.txt"
+    text = "\n".join([f"{m['role']}: {m['content']}" for m in st.session_state.messages])
+    with tempfile.NamedTemporaryFile(delete=False, mode="w", suffix=".txt") as f:
+        f.write(text)
+        st.sidebar.download_button("Download Chat", text, file_name=fname, mime="text/plain")
+
+st.markdown("---")
+st.caption("🛠 Built with Streamlit, Hugging Face, and 💛 for AI.")