Update app.py

app.py

@@ -1,17 +1,15 @@
 import os
-import time
 import spaces
 import torch
 import gradio as gr
-from threading import Thread
 
 HF_TOKEN = os.environ.get("HF_TOKEN", None)
 
-TITLE = "<h1><center>Mistral-lab</center></h1>"
+TITLE = "<h1><center>Learning Content Generator</center></h1>"
 
 PLACEHOLDER = """
 <center>
-<p>Chat with Mistral AI LLM.</p>
+<p>Enter the topic, description, and difficulty level to generate learning content.</p>
 </center>
 """
 
@@ -37,20 +35,9 @@ model = Transformer.from_folder(mistral_models_path)
 
 
 @spaces.GPU()
-def stream_chat(
-    message: str, 
-    history: list, 
-    temperature: float = 0.3, 
-    max_new_tokens: int = 1024, 
-):
-    print(f'message: {message}')
-    print(f'history: {history}')
-
-    conversation = []
-    for prompt, answer in history:
-        conversation.append(UserMessage(content=prompt))
-        conversation.append(AssistantMessage(content=answer))
-    conversation.append(UserMessage(content=message))
+def generate_learning_content(topic: str, description: str, difficulty: str, temperature: float = 0.3, max_new_tokens: int = 1024):
+    message = f"Generate learning content on the topic '{topic}' with the description: '{description}' and difficulty level: '{difficulty}'. Provide the content in paragraph format."
+    conversation = [UserMessage(content=message)]
 
     completion_request = ChatCompletionRequest(messages=conversation)
     
@@ -61,49 +48,31 @@ def stream_chat(
         model, 
         max_tokens=max_new_tokens, 
         temperature=temperature,
-        eos_id=tokenizer.instruct_tokenizer.tokenizer.eos_id)
+        eos_id=tokenizer.instruct_tokenizer.tokenizer.eos_id
+    )
     
     result = tokenizer.instruct_tokenizer.tokenizer.decode(out_tokens[0])
     
     return result
-            
-chatbot = gr.Chatbot(height=600, placeholder=PLACEHOLDER)
 
 with gr.Blocks(theme="ocean") as demo:
     gr.HTML(TITLE)
-    gr.DuplicateButton(value="Duplicate Space for private use", elem_classes="duplicate-button")
-    gr.ChatInterface(
-        fn=stream_chat,
-        chatbot=chatbot,
-        fill_height=True,
-        additional_inputs_accordion=gr.Accordion(label="⚙️ Parameters", open=False, render=False),
-        additional_inputs=[
-            gr.Slider(
-                minimum=0,
-                maximum=1,
-                step=0.1,
-                value=0.3,
-                label="Temperature",
-                render=False,
-            ),
-            gr.Slider(
-                minimum=128,
-                maximum=8192,
-                step=1,
-                value=1024,
-                label="Max new tokens",
-                render=False,
-            ),
-        ],
-        examples=[
-            ["Help me study vocabulary: write a sentence for me to fill in the blank, and I'll try to pick the correct option."],
-            ["What are 5 creative things I could do with my kids' art? I don't want to throw them away, but it's also so much clutter."],
-            ["Tell me a random fun fact about the Roman Empire."],
-            ["Show me a code snippet of a website's sticky header in CSS and JavaScript."],
-        ],
-        cache_examples=False,
-    )
+    topic_input = gr.Textbox(label="Topic", placeholder="Enter the topic for learning content.")
+    description_input = gr.Textbox(label="Description", placeholder="Enter a brief description of the topic.")
+    difficulty_input = gr.Textbox(label="Difficulty Level", placeholder="Enter the difficulty level (easy, medium, hard).")
+    
+    temperature_slider = gr.Slider(minimum=0, maximum=1, step=0.1, value=0.3, label="Temperature")
+    tokens_slider = gr.Slider(minimum=128, maximum=8192, step=1, value=1024, label="Max New Tokens")
 
+    output = gr.Textbox(label="Generated Learning Content")
+
+    submit_button = gr.Button("Generate Content")
+
+    submit_button.click(
+        fn=generate_learning_content,
+        inputs=[topic_input, description_input, difficulty_input, temperature_slider, tokens_slider],
+        outputs=output,
+    )
 
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()