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import gradio as gr
from langchain import HuggingFaceHub, PromptTemplate, LLMChain
from langchain.memory import ConversationBufferMemory
repo_id = "tiiuae/falcon-7b-instruct"
template = """You are a chatbot having a conversation with a human.
{chat_history}
Human: {human_input}
Chatbot:"""
prompt = PromptTemplate(template=template, input_variables=["chat_history", "human_input"])
def generate_response(question, huggingfacehub_api_token, temperature=0.6, max_new_tokens=500):
try:
memory = ConversationBufferMemory(memory_key="chat_history")
llm = HuggingFaceHub(
huggingfacehub_api_token=huggingfacehub_api_token,
repo_id=repo_id,
model_kwargs={"temperature": temperature, "max_new_tokens": max_new_tokens},
)
llm_chain = LLMChain(prompt=prompt, llm=llm, memory=memory)
response = llm_chain.predict(chat_history="", human_input=question)
except ValueError as e:
response = "An error occurred while processing your request. Please try again later."
print(f"Error: {str(e)}")
return response
inputs = [
gr.inputs.Textbox(label="Question"),
gr.inputs.Textbox(label="HuggingFace API Token", type="password", default=None),
gr.inputs.Slider(minimum=0.1, maximum=2.0, default=0.6, label="Temperature"),
gr.inputs.Slider(minimum=100, maximum=1000, default=500, label="Max New Tokens"),
]
outputs = gr.outputs.HTML(label="Response")
title = "Chatbot Interface [BETA]"
description = "Provide a question and get helpful answers from the AI assistant. Create your huggingface account and get your API token from https://huggingface.co/settings/token."
theme=gr.themes.Base(primary_hue="blue", secondary_hue="blue")
examples = [["write a poem on Iron Man"], ["What are the benefits of using Python?"]]
iface = gr.Interface(
fn=generate_response,
inputs=inputs,
outputs=outputs,
theme=theme,
title=title,
description=description,
allow_flagging="never",
examples=examples,
)
iface.launch(debug=True, show_api=False)
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