Create app.py

app.py

@@ -0,0 +1,63 @@
+from transformers import pipeline
+import gradio as gr
+import json
+
+# Initialize the pipeline with the new model
+pipe = pipeline("text-generation", model="Blexus/Quble_test_model_v1_INSTRUCT_v1")
+
+DATABASE_PATH = "database.json"
+
+def load_database():
+    try:
+        with open(DATABASE_PATH, "r") as file:
+            return json.load(file)
+    except FileNotFoundError:
+        return {}
+
+def save_database(database):
+    with open(DATABASE_PATH, "w") as file:
+        json.dump(database, file)
+
+def format_prompt(message, history):
+    # Format prompt according to the new template
+    prompt = "SYSTEM: You are a helpful assistant, with no access to external functions.\n<|endofsystem|>\n"
+    for user_prompt, bot_response in history:
+        prompt += f"USER: {user_prompt}\n\n\nASSISTANT: {bot_response}<|endoftext|>\n"
+    prompt += f"USER: {message}\n\n\nASSISTANT:"
+    return prompt
+
+def generate(
+    prompt, history, temperature=0.9, max_new_tokens=4096, top_p=0.9, repetition_penalty=1.2,
+):
+    database = load_database()  # Load the database
+    temperature = float(temperature)
+    if temperature < 1e-2:
+        temperature = 1e-2
+    top_p = float(top_p)
+
+    formatted_prompt = format_prompt(prompt, history)
+    if formatted_prompt in database:
+        response = database[formatted_prompt]
+    else:
+        # Use the pipeline to generate the response
+        response = pipe(formatted_prompt, max_new_tokens=max_new_tokens, temperature=temperature, top_p=top_p, repetition_penalty=repetition_penalty)[0]["generated_text"]
+        response_text = response.split("ASSISTANT:")[1].strip()  # Extract the assistant's response
+        database[formatted_prompt] = response_text
+        save_database(database)  # Save the updated database
+
+    yield response_text
+
+css = """
+  #mkd {
+    height: 500px; 
+    overflow: auto; 
+    border: 1px solid #ccc; 
+  }
+"""
+
+with gr.Blocks(css=css) as demo:
+    gr.ChatInterface(
+        generate,
+    )
+
+demo.launch(debug=True)