Adding sliders for temp, top_p and top_k

app.py

@@ -26,13 +26,12 @@ model.to(device)
 # Set up conversational memory using LangChain's ConversationBufferMemory
 memory = ConversationBufferMemory()
 
-# Define the chatbot function with memory
-def chat_with_distilgpt2(input_text):
+# Define the chatbot function with memory and additional parameters
+def chat_with_distilgpt2(input_text, temperature, top_p, top_k):
     # Retrieve conversation history
     conversation_history = memory.load_memory_variables({})['history']
     
     # Combine the (possibly summarized) history with the current user input
-    #full_input = f"{conversation_history}\nUser: {input_text}\nAssistant:"
     no_memory_input = f"Question: {input_text}\nAnswer:"
     
     # Tokenize the input and convert to tensor
@@ -48,7 +47,10 @@ def chat_with_distilgpt2(input_text):
         repetition_penalty=1.2,
         early_stopping=True,
         pad_token_id=tokenizer.eos_token_id,
-        eos_token_id=tokenizer.eos_token_id
+        eos_token_id=tokenizer.eos_token_id,
+        temperature=temperature,  # Add temperature from slider
+        top_p=top_p,              # Add top_p from slider
+        top_k=top_k               # Add top_k from slider
     )
     
     # Decode the model output
@@ -59,20 +61,20 @@ def chat_with_distilgpt2(input_text):
     
     return response
 
-# Set up the Gradio interface
+# Set up the Gradio interface with additional sliders
 interface = gr.Interface(
     fn=chat_with_distilgpt2,
-    inputs=gr.Textbox(label="Chat with DistilGPT-2"),
-    outputs=gr.Textbox(label="DistilGPT-2's Response"),
-    title="DistilGPT-2 Chatbot with Memory",
-    description="This is a simple chatbot powered by the DistilGPT-2 model with conversational memory, using LangChain.",
+    inputs=[
+        gr.Textbox(label="Chat with DistilGPT-2"),  # User input text
+        gr.Slider(0.1, 1.0, step=0.1, value=1.0, label="Temperature"),  # Slider for temperature
+        gr.Slider(0.0, 1.0, step=0.1, value=1.0, label="Top-p"),       # Slider for top-p
+        gr.Slider(1, 100, step=1, value=50, label="Top-k")             # Slider for top-k
+    ],
+    outputs=gr.Textbox(label="DistilGPT-2's Response"),  # Model response
+    title="DistilGPT-2 Chatbot with Memory and Adjustable Parameters",
+    description="This is a simple chatbot powered by the DistilGPT-2 model with conversational memory, using LangChain. You can adjust temperature, top-p, and top-k using the sliders.",
 )
 
 # Launch the Gradio app
 interface.launch()
 
-
-
-
-
-