Update app.py

app.py

@@ -7,38 +7,16 @@ from huggingface_hub import hf_hub_download #load from huggingfaces
 
 
 llm = Llama(model_path= hf_hub_download(repo_id="TheBloke/Vigogne-2-7B-Instruct-GGML", filename="vigogne-2-7b-instruct.ggmlv3.q4_1.bin"), n_ctx=2048) #download model from hf/ n_ctx=2048 for high ccontext length
-chat_history = []
 
-def generate_text(message,history):
+description = " Bro i dont want learn! i just want results "
+def generate_text(input_text):
+    output = llm(f"Q: {input_text} \n A:", max_tokens=521, stop=["Q:", "\n"], echo=True,)
+    return output['choices'][0]['text']
 
-if len(history) > 0:
-        user_input, bot_response = history[-1]  # Get the latest pair from history
-        chat_history.append([user_input, message])
-    else:
-        chat_history.append([message, ""])  # If history is empty, just add the user input
-   
-input_text = message
-    output = llm(f"Q: {input_text} \n A:", max_tokens=521, stop=["Q:", "\n"], echo=True)
-    response = output['choices'][0]['text']
-
-    # Append the bot response to the chat history
-    chat_history[-1][1] = response
-
-    return response
-     
 
 input_text = gr.inputs.Textbox(lines= 10, label="Enter your input text")
 output_text = gr.outputs.Textbox(label="Output text")
 
-description = " currently running ggml models with llama.cpp implementation in python [https://github.com/abetlen/llama-cpp-python]"
-
-examples = [
-    ["What is the capital of France? ", "The capital of France is Paris."],
-    ["Who wrote the novel 'Pride and Prejudice'?", "The novel 'Pride and Prejudice' was written by Jane Austen."],
-    ["What is the square root of 64?", "The square root of 64 is 8."]
-]
-
-demo = gr.ChatInterface(random_response).launch()
+demo = gr.Interface(fn=generate_text, inputs=input_text, outputs=output_text, title="Running Llama on CPU is Hard", description=description, examples=examples)
 demo.queue()
 demo.launch()
-