Update app.py

app.py

@@ -1,35 +1,28 @@
-# -*- coding: utf-8 -*-
-"""llama_cpp_quiz_generator.ipynb
-
-Automatically generated by Colab.
-
-Original file is located at
-    https://colab.research.google.com/drive/1V287A0U9MlfTEEPjBPDsREKdNMbxwg9V
-"""
-
-!pip install langchain
-!pip install llama-cpp-python
-!pip install langchain_community
-
-# Mount the Google Drive folder to Colab
-from google.colab import drive
-drive.mount('/content/drive')
-
 from langchain.prompts import ChatPromptTemplate
 from langchain.chains import LLMChain
 from langchain_community.llms import LlamaCpp
+from huggingface_hub import hf_hub_download
+
+hf_hub_download(
+    repo_id="bartowski/Meta-Llama-3.1-8B-Instruct-GGUF",
+    filename="Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf",
+    local_dir = "./models"
+)
 
 llm = LlamaCpp(
-    model_path="/content/drive/My Drive/LLM/models/Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf",
+    model_path="models/Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf",
     )
 
-prompt = ChatPromptTemplate.from_template(
-    "Generate 2 questions and their correct answers based on the following text:\n\n{text}\n\n"
-)
-
-chain = LLMChain(llm=llm, prompt=prompt)
+# Generator function
+def gen_quiz(input, num):
+    prompt = ChatPromptTemplate.from_template(
+    "Generate {num} questions and their correct answers based on the following text:\n\n{text}\n\n")
+    chain = LLMChain(llm=llm, prompt=prompt)    
+    quiz = chain.invoke(input)
+    return quiz['text']
 
-text = "In general, IFC, or “Industry Foundation Classes”, \
+# Example
+text_example = "In general, IFC, or “Industry Foundation Classes”, \
 is a standardized, digital description of the built environment, \
 including buildings and civil infrastructure. \
 It is an open, international standard (ISO 16739-1:2018), \
@@ -37,5 +30,17 @@ meant to be vendor-neutral, or agnostic, and usable across a wide range of hardw
 software platforms, and interfaces for many different use cases. \
 The IFC schema specification is the primary technical deliverable of buildingSMART International to fulfill its goal to promote openBIM."
 
-quiz = chain.invoke(text)
-print(quiz['text'])
+
+import gradio as gr
+
+# Gradio Interface
+gr.close_all()
+demo = gr.Interface(fn=gen_quiz, 
+                    inputs=[gr.Textbox(label="Text to generate quiz from", lines=6),
+                            gr.Slider(minimum=1, maximum=10, value=2048, step=1, label="Number of Quiz")],
+                    outputs=[gr.Textbox(label="Result", lines=10)],
+                    examples=[[text_example, 3]],
+                    title="Quiz Generator with LlamaCpp",
+                    description="Generating quiz based on given texts using Meta-Llama-3.1-8B-Instruct-Q5_K_M.gguf!"
+                   )
+demo.launch()