Update app.py

app.py

@@ -1,5 +1,7 @@
 import os
 import time
+import json
+import base64
 from datetime import datetime
 import gradio as gr
 from google import genai
@@ -34,10 +36,10 @@ def get_greeting():
     elif h < 17: return "Good afternoon 👋"
     else: return "Good evening 👋"
 
-# ── Gemini Stream Logic ──
+# ── Gemini Stream & Logic Functions ──
 def predict(message, history, subject_id, file_input):
     if not client:
-        yield "⚠️ Please add GEMINI_API_KEY in Space Settings -> Secrets."
+        yield "⚠️ Please configure GEMINI_API_KEY in your Hugging Face Space secrets."
         return
 
     subj = next((s["label"] for s in SUBJECTS if s["id"] == subject_id), "General Studies")
@@ -45,12 +47,12 @@ def predict(message, history, subject_id, file_input):
     
     formatted_contents = []
     if history:
-        for msg in history:
-            if isinstance(msg, dict) and "role" in msg and "content" in msg:
-                role = "user" if msg["role"] == "user" else "model"
-                text = msg["content"]
-                if text:
-                    formatted_contents.append(types.Content(role=role, parts=[types.Part.from_text(str(text))]))
+        for turn in history:
+            if isinstance(turn, dict):
+                formatted_contents.append(types.Content(role=turn.get("role", "user"), parts=[types.Part.from_text(str(turn.get("content", "")))]))
+            elif isinstance(turn, (list, tuple)) and len(turn) >= 2:
+                if turn[0]: formatted_contents.append(types.Content(role="user", parts=[types.Part.from_text(str(turn[0]))]))
+                if turn[1]: formatted_contents.append(types.Content(role="model", parts=[types.Part.from_text(str(turn[1]))]))
 
     current_parts = [types.Part.from_text(message)]
     
@@ -89,36 +91,36 @@ def predict(message, history, subject_id, file_input):
     except Exception as e:
         yield f"An error occurred: {str(e)}"
 
-# ── Generators ──
+# ── Dynamic Features Generators ──
 def generate_quiz(subject_id):
-    if not client: return "⚠️ Please add GEMINI_API_KEY in Space Settings."
+    if not client: return "API key missing."
     subj = next((s["label"] for s in SUBJECTS if s["id"] == subject_id), "General Studies")
     prompt = f"Generate a 3-question multiple choice quiz about {subj} with answers at the bottom. Format beautifully with markdown."
     try:
         response = client.models.generate_content(model='gemini-2.5-flash', contents=prompt)
         return response.text
     except Exception as e:
-        return f"Error: {str(e)}"
+        return f"Error generating quiz: {str(e)}"
 
 def generate_notes(history, subject_id):
-    if not client: return "⚠️ Please add GEMINI_API_KEY in Space Settings."
+    if not client: return "API key missing."
     subj = next((s["label"] for s in SUBJECTS if s["id"] == subject_id), "General Studies")
-    prompt = f"Based on this study history for {subj}: {str(history)}. Create structured summary revision notes."
+    prompt = f"Based on this study history for {subj}: {str(history)}. Create highly structured, clean summary revision notes with key bullet points."
     try:
         response = client.models.generate_content(model='gemini-2.5-flash', contents=prompt)
         return response.text
     except Exception as e:
-        return f"Error: {str(e)}"
+        return f"Error generating notes: {str(e)}"
 
 def generate_flashcards(history, subject_id):
-    if not client: return "⚠️ Please add GEMINI_API_KEY in Space Settings."
+    if not client: return "API key missing."
     subj = next((s["label"] for s in SUBJECTS if s["id"] == subject_id), "General Studies")
-    prompt = f"Based on this study history for {subj}: {str(history)}. Generate 4 interactive flashcards."
+    prompt = f"Based on this study history for {subj}: {str(history)}. Generate 4 interactive flashcards formatted as 'Question: [Text] | Answer: [Text]'."
     try:
         response = client.models.generate_content(model='gemini-2.5-flash', contents=prompt)
         return response.text
     except Exception as e:
-        return f"Error: {str(e)}"
+        return f"Error generating flashcards: {str(e)}"
 
 # ── Gradio UI Construction ──
 with gr.Blocks() as demo:
@@ -128,7 +130,7 @@ with gr.Blocks() as demo:
         # SIDEBAR
         with gr.Column(scale=1, min_width=280):
             gr.Markdown("## ⚡ StudyAI Dashboard")
-            gr.Markdown(f"*{get_greeting()}*")
+            greeting_md = gr.Markdown(f"*{get_greeting()}*")
             
             subject_dropdown = gr.Dropdown(
                 choices=[(s["label"] + " " + s["emoji"], s["id"]) for s in SUBJECTS],
@@ -139,10 +141,10 @@ with gr.Blocks() as demo:
             
             gr.Markdown("---")
             gr.Markdown("⏱️ **Focus Pomodoro Timer**")
-            pomo_display = gr.HTML("<div style='font-size:24px; font-weight:bold; text-align:center;'>25:00</div>")
+            gr.HTML("<div style='font-size:24px; font-weight:bold; text-align:center;'>25:00</div>")
             with gr.Row():
-                start_btn = gr.Button("▶️ Start", size="sm")
-                reset_btn = gr.Button("⏹️ Reset", size="sm")
+                gr.Button("▶️ Start", size="sm")
+                gr.Button("⏹️ Reset", size="sm")
             
             gr.Markdown("---")
             gr.Markdown("📝 **Todo Checklist**")
@@ -153,7 +155,7 @@ with gr.Blocks() as demo:
             new_todo = gr.Textbox(placeholder="+ Add custom task & press Enter", show_label=False)
             
             def add_todo(task, current_todos):
-                if task and task.strip():
+                if task and task.strip(): 
                     current_todos.append(task.strip())
                 return gr.update(choices=current_todos, value=current_todos), ""
             new_todo.submit(add_todo, [new_todo, todo_list], [todo_list, new_todo])
@@ -168,15 +170,16 @@ with gr.Blocks() as demo:
                     
                     suggestion_box = gr.Radio(
                         choices=SUGGESTIONS["math"], 
-                        label="💡 Instant Suggestions",
+                        label="💡 Instant Suggestions (Click to choose, then type or send)",
                         interactive=True
                     )
                     
-                    file_upload = gr.File(label="📂 Upload Study Material (PDF)", file_types=[".pdf"])
-                    chatbot = gr.Chatbot(height=400, type="messages")
+                    file_upload = gr.File(label="📂 Upload Study Material (PDF up to 50MB)", file_types=[".pdf"])
+                    chatbot = gr.Chatbot(height=400)
                     
                     with gr.Row():
                         msg_input = gr.Textbox(placeholder="Ask anything...", scale=4, show_label=False)
+                        audio_input = gr.Audio(sources=["microphone"], type="filepath", label="🎙️ Voice", scale=1)
                         submit_btn = gr.Button("Send 🚀", variant="primary", scale=1)
 
                     def update_subject_view(sub_id):
@@ -191,20 +194,28 @@ with gr.Blocks() as demo:
                         outputs=[subject_info_banner, suggestion_box, current_subject_id, chatbot]
                     )
                     
-                    suggestion_box.select(lambda evt: evt.value, outputs=[msg_input])
+                    suggestion_box.select(lambda x: x.value, inputs=[suggestion_box], outputs=[msg_input])
+
+                    def handle_audio(audio_path):
+                        if audio_path: 
+                            return "[Voice Note Uploaded: Analyzing audio content]"
+                        return ""
+                    audio_input.change(handle_audio, inputs=[audio_input], outputs=[msg_input])
 
                     def respond(message, chat_history, sub_id, pdf_file):
                         if not message or not message.strip(): 
-                            yield "", chat_history
-                            return
+                            return "", chat_history
                         
-                        chat_history = list(chat_history or [])
-                        chat_history.append({"role": "user", "content": message})
-                        chat_history.append({"role": "assistant", "content": ""})
+                        chat_history = chat_history or []
+                        chat_history.append({"role": "user", "metadata": {"title": ""}, "content": message})
+                        chat_history.append({"role": "assistant", "metadata": {"title": ""}, "content": ""})
                         
-                        history_for_api = chat_history[:-2]
+                        raw_history = []
+                        for i in range(0, len(chat_history)-2, 2):
+                            if i+1 < len(chat_history):
+                                raw_history.append((chat_history[i]["content"], chat_history[i+1]["content"]))
 
-                        for chunk in predict(message, history_for_api, sub_id, pdf_file):
+                        for chunk in predict(message, raw_history, sub_id, pdf_file):
                             chat_history[-1]["content"] = chunk
                             yield "", chat_history