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import gradio as gr
from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
# Load pre-trained Hugging Face model for recommendation tasks
model_name = "TinyLlama/TinyLlama-1.1B-Chat-v1.0" # Specialized model for general tasks
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForCausalLM.from_pretrained(model_name)
# Increase the tokenizer's max length to handle larger inputs
tokenizer.model_max_length = 2048 # Increase this to a higher number if needed
text_generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
def laptop_recommendation(user_input, task):
"""
Handles laptop recommendation tasks based on user preferences.
Parameters:
- user_input: str, the input text from the user with laptop preferences.
- task: str, the type of task (e.g., "Recommendation", "Compare", "Budget Recommendation").
Returns:
- str: The generated response.
"""
if task == "Recommendation":
prompt = f"Recommend a laptop based on the following preferences:\n{user_input}\nRecommended Laptop:"
elif task == "Compare":
prompt = f"Compare two laptops based on the following specifications:\n{user_input}\nComparison:"
elif task == "Budget Recommendation":
prompt = f"Recommend the best laptop for the following budget:\n{user_input}\nRecommended Laptop for Budget:"
else:
return "Invalid task selected."
response = text_generator(
prompt,
max_length=97,
num_return_sequences=1,
pad_token_id=tokenizer.eos_token_id,
temperature=0.7,
top_p=0.9
)[0]["generated_text"]
return response[len(prompt):].strip()
def gradio_interface(user_input, task):
if not user_input.strip():
return "Please enter some input."
return laptop_recommendation(user_input, task)
with gr.Blocks(theme=gr.themes.Default(primary_hue="blue", secondary_hue="green", neutral_hue="slate")) as laptop_recommendation_ui:
gr.Markdown(
"""
<h1 style="text-align:center; color: #3b82f6;">💻 Laptop Recommendation Chatbot</h1>
<p style="text-align:center; color: #10b981; font-size: 18px;">
Get personalized laptop recommendations, detailed comparisons, and budget-friendly options.
</p>
""",
elem_id="header"
)
with gr.Row():
with gr.Column(scale=1):
user_input = gr.Textbox(
lines=5,
placeholder="Enter your laptop preferences here...",
label="Your Input",
elem_id="user-input",
)
task = gr.Radio(
["Recommendation", "Compare", "Budget Recommendation"],
label="Select Task",
elem_id="task-selector"
)
with gr.Column(scale=1):
output = gr.Textbox(
lines=10,
label="Chatbot Response",
elem_id="response",
)
with gr.Row():
submit_button = gr.Button("Submit", elem_id="submit-btn")
clear_button = gr.Button("Clear", elem_id="clear-btn")
submit_button.click(gradio_interface, inputs=[user_input, task], outputs=output)
clear_button.click(lambda: ("", ""), None, [user_input, output])
gr.Markdown(
"""
<style>
#header h1 {
font-family: 'Arial', sans-serif;
font-weight: bold;
}
#user-input, #response {
font-family: 'Courier New', monospace;
border: 2px solid #3b82f6;
border-radius: 10px;
}
#task-selector label {
font-family: 'Verdana', sans-serif;
color: #3b82f6;
}
#submit-btn {
background-color: #3b82f6;
color: white;
border-radius: 10px;
}
#clear-btn {
background-color: #10b981;
color: white;
border-radius: 10px;
}
</style>
"""
)
laptop_recommendation_ui.launch()
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