Update app.py

app.py

@@ -3,40 +3,27 @@ import gradio as gr
 
 client = InferenceClient("mistralai/Mixtral-8x7B-Instruct-v0.1")
 
-def format_prompt(message, history):
-    prompt = "<s>"
-    for user_prompt, bot_response in history:
-        prompt += f"[INST] {user_prompt} [/INST]"
-        prompt += f" {bot_response}</s> "
-    prompt += f"[INST] {message} [/INST]"
-    return prompt
-
-def generate(
-    prompt, history, temperature=0.2, max_new_tokens=30000, top_p=0.9, repetition_penalty=1.0,
-):
+def generate(prompt, temperature=0.2, max_new_tokens=30000, top_p=0.9, repetition_penalty=1.0):
     temperature = max(float(temperature), 0.01)
     top_p = max(min(float(top_p), 1.0), 0.0)
     repetition_penalty = max(float(repetition_penalty), 0.01)
 
-    generate_kwargs = dict(
-        temperature=temperature,
-        max_new_tokens=max_new_tokens,
-        top_p=top_p,
-        repetition_penalty=repetition_penalty,
-        do_sample=True,
-        seed=42,
-    )
-
-    formatted_prompt = format_prompt(prompt, history)
+    generate_kwargs = {
+        "temperature": temperature,
+        "max_new_tokens": max_new_tokens,
+        "top_p": top_p,
+        "repetition_penalty": repetition_penalty,
+        "do_sample": True,
+        "seed": 42,
+    }
 
-    # Generate text
-    response = client.text_generation(formatted_prompt, **generate_kwargs)
+    response = client.text_generation(prompt, **generate_kwargs)
     generated_text = response["generated_text"]
     return generated_text
 
 iface = gr.Interface(
     fn=generate,
-    inputs=["text", "text", gr.inputs.Slider(0.1, 2.0), gr.inputs.Slider(100, 50000), gr.inputs.Slider(0.1, 1.0)],
+    inputs=["text", gr.inputs.Slider(0.1, 2.0), gr.inputs.Slider(100, 50000), gr.inputs.Slider(0.1, 1.0)],
     outputs="text",
     title="Text Generation"
 )