app.py

import gradio as gr
import time
import ctypes #to run on C api directly 
import llama_cpp
from llama_cpp import Llama
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


def generate_text(input_text):
    output = llm(f"Q: {input_text}  A:", max_tokens=521, stop=["Q:", "\n"], echo=True)
    return output['choices'][0]['text']

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.Interface(fn=generate_text, inputs=input_text, outputs=output_text, title="Llama Language Model", description=description, examples=examples)
demo.queue()
demo.launch()