Update app.py

app.py

@@ -8,16 +8,6 @@ from huggingface_hub import login
 # Space configuration
 SPACE_DIR = os.environ.get("HF_HOME", os.getcwd())
 
-# Load and preprocess the PDF content
-try:
-    pdf_path = os.path.join(SPACE_DIR, "LTDOCS.pdf")
-    with open(pdf_path, 'rb') as file:
-        pdf_reader = PyPDF2.PdfReader(file)
-        pdf_content = ' '.join([page.extract_text() for page in pdf_reader.pages])
-        pdf_content = pdf_content.lower().strip()
-except Exception as e:
-    pdf_content = ""
-    print(f"Error loading PDF: {e}")
 
 def init_huggingface_auth():
     """Space-friendly authentication"""
@@ -38,91 +28,120 @@ def init_huggingface_auth():
 if not init_huggingface_auth():
     print("Warning: Authentication failed")
 
-# Initialize the pipeline with CPU optimization
-try:
-    pipe = pipeline(
-        "text-generation",
-        model="google/gemma-2-2b-jpn-it",
-        device_map="auto",
-        model_kwargs={
-            "torch_dtype": torch.float16,
-            "low_cpu_mem_usage": True
-        }
-    )
-except Exception as e:
-    print(f"Model loading error: {e}")
-    raise
-
-SYSTEM_PROMPT = f"""You are Foton, Swahili AI assistant. Tasks:
-1. Swahili translations
-2. Teach Swahili vocabulary/grammar
-3. Explain cultural context
-4. Help practice conversations
-5. Programming assistance using: {pdf_content}
-
-Maintain friendly, patient demeanor with cultural context.
+
+# Load and preprocess the PDF content
+pdf_path = os.path.join(SPACE_DIR, "LTDOCS.pdf")
+with open(pdf_path, 'rb') as file:
+      pdf_reader = PyPDF2.PdfReader(file)
+      pdf_content = ' '.join([page.extract_text() for page in pdf_reader.pages])
+      pdf_content = pdf_content.lower().strip()
+
+
+
+# Initialize the pipeline
+pipe = pipeline(
+    "text-generation",
+    model="google/gemma-2-2b-jpn-it",
+    model_kwargs={"torch_dtype": torch.bfloat16},
+    device="cpu",  # replace with "mps" to run on a Mac device
+)
+
+# System prompt and welcome message (using your existing definitions)
+SYSTEM_PROMPT = f"""You Foton the chat bot assistant of the Company Lugha taussi, an AI language assistant specialized in African languages, with a focus on Swahili. Your primary tasks are:
+1. Providing accurate translations between Swahili and other languages
+2. Teaching Swahili vocabulary and grammar
+3. Explaining cultural context behind Swahili expressions
+4. Helping users practice Swahili conversation
+5. Based on the programing doc  for lughah Tausi Programing which is in swahili , the following information is relevant: {pdf_content} .assist users in programing and installing lugha tausi programing language"
+
+Always maintain a friendly and patient demeanor, and provide cultural context when relevant speak mostly swahili and change when asked.
 """
 
-def format_messages(history):
-    """Format chat history with system prompt"""
-    messages = [{"role": "system", "content": SYSTEM_PROMPT}]
-    for msg in history:
-        if isinstance(msg, dict) and "role" in msg and "content" in msg:
-            messages.append(msg)
-    return messages
+WELCOME_MESSAGE = "**Karibu Lugha Tausi!** Mimi ni Foton, msaidizi wako wa kibinafsi wa Kiswahili. Niko hapa kukusaidia kujifunza, kuelewa, na kuzungumza Kiswahili. **Ninaweza kukusaidiaje leo?** Hebu tuanze! 😊"
 
-def generate_response(history):
-    """Generate AI response"""
-    try:
-        messages = format_messages(history)
-        
-        prompt = "\n".join([f"{m['role']}: {m['content']}" for m in messages])
-        
-        output = pipe(
-            prompt,
-            max_new_tokens=256,
-            temperature=0.1,
-            top_p=0.9,
-            do_sample=True,
-            return_full_text=False
-        )
-        return output[0]["generated_text"].strip()
-    except Exception as e:
-        print(f"Generation error: {e}")
-        return "Samahani, nimekutana na tatizo. Tafadhali jaribu tena baadaye."
+def format_chat_message(messages, system_prompt=SYSTEM_PROMPT):
+    """Format the chat messages with system prompt"""
+    formatted_prompt = f"{system_prompt}\n\n"
+
+    for message in messages:
+        if isinstance(message, tuple):
+            role, content = message
+            if role == "user":
+                formatted_prompt += f"User: {content}\nLugha Tausi: "
+            elif role == "assistant":
+                formatted_prompt += f"{content}\n"
+
+    return formatted_prompt
 
-# Create Gradio interface with Space optimizations
+def chat_response(message, history):
+    """Generate response for Gradio chat interface"""
+    # Convert history to the format expected by the model
+    messages = []
+    for user_msg, bot_msg in history:
+        messages.append(("user", user_msg))
+        messages.append(("assistant", bot_msg))
+    messages.append(("user", message))
+
+    formatted_input = format_chat_message(messages)
+    outputs = pipe(
+        formatted_input,
+        return_full_text=False,
+        max_new_tokens=256,
+        temperature=0.1,
+        top_p=0.9,
+        do_sample=True
+    )
+    return outputs[0]["generated_text"].strip()
+
+# Create Gradio interface
 with gr.Blocks(theme=gr.themes.Soft()) as demo:
-    gr.Markdown("# Lugha Tausi - Swahili Assistant")
-    
     chatbot = gr.Chatbot(
-        value=[{"role": "assistant", "content": "**Karibu Lugha Tausi!** Mimi ni Foton, msaidizi wako wa Kiswahili. Niko hapa kukusaidia kujifunza na kuzungumza Kiswahili. **Ninaweza kukusaidiaje leo?** 😊"}],
+        value=[(None, WELCOME_MESSAGE)],
         height=600,
-        show_label=False,
-        avatar_images=(None, "user.png"),
-        bubble_full_width=False,
-        show_share_button=False,
-        type="messages"
+        show_label=False
     )
-    
-    msg = gr.Textbox(placeholder="Andika ujumbe wako hapa...", show_label=False)
-    clear = gr.Button("Futa Mazungumzo")
+    msg = gr.Textbox(
+        placeholder="Type your message here...",
+        show_label=False
+    )
+    clear = gr.Button("Clear Chat")
 
-    def respond(message, history):
-        history.append({"role": "user", "content": message})
-        bot_response = generate_response(history)
-        history.append({"role": "assistant", "content": bot_response})
-        return "", history
+    def user_input(message, history):
+        return "", history + [(message, None)]
 
-    msg.submit(respond, [msg, chatbot], [msg, chatbot])
-    clear.click(lambda: [None, []], None, [msg, chatbot], queue=False)
+    def bot_response(history):
+        if len(history) == 0:
+            history.append((None, WELCOME_MESSAGE))
+            return history
+
+        user_message = history[-1][0]
+        bot_message = chat_response(user_message, history[:-1])
+        history[-1] = (user_message, bot_message)
+        return history
+
+    def clear_chat():
+        return [], [(None, WELCOME_MESSAGE)]
+
+    # Set up the message flow
+    msg.submit(
+        user_input,
+        [msg, chatbot],
+        [msg, chatbot],
+        queue=False
+    ).then(
+        bot_response,
+        chatbot,
+        chatbot
+    )
+
+    clear.click(
+        clear_chat,
+        None,
+        [chatbot],
+        queue=False
+    )
 
+# Launch the interface
 if __name__ == "__main__":
-    demo.launch(
-        server_name="0.0.0.0",
-        server_port=7860,
-        auth=os.getenv("SPACE_AUTH"),
-        show_error=True,
-        share=True,  # Explicitly disable sharing
-        ssr_mode=False
-    )
+    demo.launch(share=True,ssr_mode=False )
+