Create app.py

app.py

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+import gradio as gr
+from transformers import AutoTokenizer, AutoModelForCausalLM
+import torch
+import firebase_admin
+from firebase_admin import credentials, db
+import os
+import json
+
+# Load Firebase credentials from firebase-key.json
+firebase_key_path = os.environ.get("FIREBASE_KEY_PATH", "firebase-key.json")
+with open(firebase_key_path, "r") as f:
+    firebase_config = json.load(f)
+
+# Initialize Firebase
+cred = credentials.Certificate(firebase_config)
+firebase_admin.initialize_app(cred, {
+    "databaseURL": "https://taskmate-d6e71-default-rtdb.firebaseio.com/"  # Confirm this URL!
+})
+ref = db.reference("tasks")
+
+# Load IBM Granite model from Hugging Face
+model_name = "ibm-granite/granite-7b-base—"  # Switch to "granite-3b" if 7b is too heavy
+tokenizer = AutoTokenizer.from_pretrained(model_name)
+model = AutoModelForCausalLM.from_pretrained(model_name)
+
+# Function to generate text with Granite
+def generate_response(prompt, max_length=100):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(**inputs, max_length=max_length, num_return_sequences=1)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
+
+# Parse user input into structured task
+def parse_task(input_text, persona="default"):
+    prompt = f"For a {persona} employee, extract task, time, priority from: '{input_text}'"
+    response = generate_response(prompt)
+    return response  # e.g., "Task: Email boss, Time: Today, Priority: High"
+
+# Generate persona-specific subtasks
+def generate_subtasks(task, persona="default"):
+    prompt = f"List 3 subtasks for '{task}' suited for a {persona} employee."
+    response = generate_response(prompt, max_length=150)
+    return response  # e.g., "1. Draft email\n2. Send it\n3. Chill"
+
+# Main chat function
+def task_mate_chat(user_input, persona, chat_history):
+    # Parse the input
+    parsed = parse_task(user_input, persona)
+    task_name = parsed.split(",")[0].replace("Task: ", "").strip()
+    
+    # Generate subtasks
+    subtasks = generate_subtasks(task_name, persona)
+    
+    # Store in Firebase
+    task_data = {
+        "input": user_input,
+        "parsed": parsed,
+        "subtasks": subtasks,
+        "persona": persona,
+        "timestamp": str(db.ServerValue.TIMESTAMP)
+    }
+    ref.push().set(task_data)
+    
+    # Format response
+    response = f"Parsed: {parsed}\nSubtasks:\n{subtasks}"
+    chat_history.append((user_input, response))
+    return "", chat_history
+
+# Gradio Interface
+with gr.Blocks(title="Task_Mate") as interface:
+    gr.Markdown("# Task_Mate: Your AI Task Buddy")
+    persona = gr.Dropdown(["lazy", "multitasker", "perfect"], label="Who are you?", value="lazy")
+    chatbot = gr.Chatbot(label="Chat with Task_Mate")
+    msg = gr.Textbox(label="Talk to me", placeholder="e.g., 'What’s today?' or 'Meeting at 2 PM'")
+    submit = gr.Button("Submit")
+    
+    # Handle chat submission
+    submit.click(
+        fn=task_mate_chat,
+        inputs=[msg, persona, chatbot],
+        outputs=[msg, chatbot]
+    )
+    
+    # Examples for each persona
+    gr.Examples(
+        examples=[
+            ["What’s today?", "lazy"],
+            ["Meeting Sarah, slides, IT call", "multitasker"],
+            ["Email boss by 3 PM", "perfect"]
+        ],
+        inputs=[msg, persona],
+        outputs=chatbot
+    )
+
+interface.launch()