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import gradio as gr | |
from langchain import PromptTemplate, LLMChain | |
from langchain.llms import HuggingFaceHub | |
template_by_step = """Question: {question} | |
Answer: Let's think step by step.""" | |
models = ["MBZUAI/LaMini-Flan-T5-248M", "MBZUAI/LaMini-Flan-T5-783M"] | |
def run( | |
question: gr.Textbox = None, | |
repo_id: gr.Dropdown = models[0], | |
temperature: gr.Slider = 0.5, | |
max_length: gr.Slider = 512, | |
by_steq: gr.Checkbox = False, | |
): | |
template = template_by_step if by_steq else "{question}" | |
prompt = PromptTemplate(template=template, input_variables=["question"]) | |
llm = HuggingFaceHub( | |
repo_id=repo_id, | |
model_kwargs={"temperature": temperature, "max_length": max_length} | |
) | |
llm_chain = LLMChain(prompt=prompt, llm=llm) | |
result = llm_chain.run(question) | |
print(result) | |
return result | |
inputs = [ | |
gr.Textbox(label="Question", lines=3), | |
gr.Dropdown(choices=models, | |
value=models[0], label="Model", allow_custom_value=True), | |
gr.Slider(0.0, 1.0, value=0.5, step=0.05, label="Temperature"), | |
gr.Slider(64, 1024, value=512, label="Max Length"), | |
gr.Checkbox(label="Think step by step", value=False), | |
] | |
examples = [ | |
["What is the capital of France?"], | |
["What's the Earth total population?"], | |
["Who won the FIFA World Cup in the year 1994?"], | |
["What NFL team won the Super Bowl in the year Justin Bieber was born?"], | |
["Translate the following to French: There are so many plans"], | |
["Write an article to introduce machine learning"], | |
["Please let me know if you think the given place deserves to be visited and why: \"Beijing, China\""], | |
] | |
title = "Langchain w/ HF Models" | |
gr.Interface( | |
fn=run, | |
inputs=inputs, | |
outputs='label', | |
title=title, | |
examples=examples, | |
).launch() | |