Update app.py

app.py

@@ -1,26 +1,28 @@
+from huggingface_hub import InferenceClient
 import gradio as gr
-from transformers import AutoTokenizer, AutoModelForCausalLM
 
-# Load the model and tokenizer
-tokenizer = AutoTokenizer.from_pretrained("meta-llama/Meta-Llama-3.1-8B")
-model = AutoModelForCausalLM.from_pretrained("meta-llama/Meta-Llama-3.1-8B")
+# Set up the client for Mistral model inference
+client = InferenceClient("mistralai/Mistral-7B-Instruct-v0.3")
 
-def generate_text(prompt, max_length=150):
-    inputs = tokenizer(prompt, return_tensors="pt")
-    outputs = model.generate(**inputs, max_length=max_length, num_return_sequences=1, do_sample=True)
-    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+def generate_text(prompt):
+    response = client.text_generation(prompt, max_new_tokens=200, temperature=0.7)
+    return response
 
 def generate_argument(topic, stance):
-    prompt = f"Generate a compelling argument for the following debate topic.\nTopic: {topic}\nStance: {stance}\nArgument:"
-    response = generate_text(prompt, max_length=200)
-    argument = response.split("Argument:")[1].strip()
-    return argument
+    prompt = f"""Generate a compelling argument for the following debate topic.
+Topic: {topic}
+Stance: {stance}
+Argument:"""
+    response = generate_text(prompt)
+    return response.split("Argument:")[1].strip()
 
 def generate_counterargument(topic, original_argument):
-    prompt = f"Generate a strong counterargument for the following debate topic and argument.\nTopic: {topic}\nOriginal Argument: {original_argument}\nCounterargument:"
-    response = generate_text(prompt, max_length=200)
-    counterargument = response.split("Counterargument:")[1].strip()
-    return counterargument
+    prompt = f"""Generate a strong counterargument for the following debate topic and argument.
+Topic: {topic}
+Original Argument: {original_argument}
+Counterargument:"""
+    response = generate_text(prompt)
+    return response.split("Counterargument:")[1].strip()
 
 def debate_assistant(topic, stance):
     argument = generate_argument(topic, stance)
@@ -35,8 +37,8 @@ iface = gr.Interface(
         gr.Radio(["For", "Against"], label="Stance")
     ],
     outputs=gr.Textbox(label="Generated Debate Arguments"),
-    title="AI-powered Debate Assistant (Meta-Llama 3.1)",
-    description="Enter a debate topic and choose a stance to generate arguments and counterarguments using Meta-Llama 3.1."
+    title="AI-powered Debate Assistant (Mistral-7B-Instruct-v0.3)",
+    description="Enter a debate topic and choose a stance to generate arguments and counterarguments using Mistral-7B-Instruct-v0.3."
 )
 
 # Launch the interface