app.py

from ctransformers import AutoModelForCausalLM
import gradio as gr


llms = {
"tinnyllama":{"name": "TheBloke/TinyLlama-1.1B-1T-OpenOrca-GGUF", "file":"tinyllama-1.1b-1t-openorca.Q4_K_M.gguf", "suffix":"<|im_end|><|im_start|>assistant", "prefix":"<|im_start|>system You are a helpful assistant  <|im_end|><|im_start|>user"},
"orca2":{"name": "TheBloke/Orca-2-7B-GGUF", "file":"orca-2-7b.Q4_K_M.gguf", "suffix":"<|im_end|><|im_start|>assistant", "prefix":"<|im_start|>system You are a helpful assistant<|im_end|><|im_start|>user "},
"zephyr":{"name": "TheBloke/zephyr-7B-beta-GGUF", "file":"zephyr-7b-beta.Q4_K_M.gguf", "suffix":"</s><|assistant|>", "prefix":"<|system|>You are a helpful assistant</s><|user|> "},
"mixtral":{"name": "TheBloke/Mistral-7B-Instruct-v0.1-GGUF", "file":"mistral-7b-instruct-v0.1.Q4_K_M.gguf", "suffix":"[/INST]", "prefix":"<s>[INST] "},
"llama2":{"name": "TheBloke/Llama-2-7B-Chat-GGUF", "file":"llama-2-7b-chat.Q4_K_M.gguf", "suffix":"[/INST]", "prefix":"[INST] <<SYS>> You are a helpful assistant <</SYS>>"},
"llama2":{"name": "TheBloke/SOLAR-10.7B-Instruct-v1.0-GGUF", "file":"solar-10.7b-instruct-v1.0.Q4_K_M.gguf", "suffix":"\n### Assistant:\n", "prefix":"### User:\n"}
}

for k in llms.keys():
    AutoModelForCausalLM.from_pretrained(llms[k]['name'], model_file=llms[k]['file'])

def stream(prompt, llm_name, UL):
    
    prefix=llms[llm_name]['prefix']
    suffix=llms[llm_name]['suffix']
    user="""
    {prompt}"""
    
    llm = AutoModelForCausalLM.from_pretrained(llms[llm_name]['name'], model_file=llms[llm_name]['file'])

    prompt = f"{prefix}{user.replace('{prompt}', item.prompt)}{suffix}"
    return llm(prompt)

css = """
  h1 {
  text-align: center;
}
#duplicate-button {
  margin: auto;
  color: white;
  background: #1565c0;
  border-radius: 100vh;
}
.contain {
  max-width: 900px;
  margin: auto;
  padding-top: 1.5rem;
}
"""

select_llm = gradio.Dropdown(choices=llms.keys(), value=llms.keys()[0], max_choices=1)

chat_interface = gr.ChatInterface(
    fn=stream,
    additional_inputs=[select_llm],
    stop_btn=None,
    examples=[
        ["explain Large language model"],
        ["what is quantum computing"]
    ],
)

with gr.Blocks(css=css) as demo:
    gr.HTML("<h1><center>Gathnex Free LLM Deployment Space<h1><center>")
    gr.HTML("<h3><center><a href='https://medium.com/@gathnex'>Gathnex AI</a>💬<h3><center>")
    gr.DuplicateButton(value="Duplicate Space for private use", elem_id="duplicate-button")
    chat_interface.render()
    gr.Markdown(greety)
    
if __name__ == "__main__":
    demo.queue(max_size=10).launch()