KiranRand commited on
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0c546ad
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1 Parent(s): d0a3d53

Update app.py

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  1. app.py +34 -23
app.py CHANGED
@@ -1,28 +1,39 @@
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  import gradio as gr
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- from transformers import pipeline
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- # Load the pre-trained model
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- itinerary_generator = pipeline("text-generation", model="rahmanazhar/Travereel-Model-V1")
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- def generate_kerala_itinerary(duration, interests, budget, specific_places="Kerala"):
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- """Generates a Kerala trip itinerary based on user inputs."""
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- prompt = f"Generate a {duration}-day trip plan for {specific_places}, Kerala, focusing on {interests} with a {budget} budget."
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- generated_text = itinerary_generator(prompt, max_length=500, num_return_sequences=1, do_sample=True, top_k=50, top_p=0.95)[0]['generated_text']
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- return generated_text.strip()
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- # Define the input and output interfaces for Gradio
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- iface = gr.Interface(
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- fn=generate_kerala_itinerary,
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- inputs=[
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- gr.Slider(minimum=1, maximum=10, step=1, label="Duration (Days)"),
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- gr.Textbox(label="Your Interests (e.g., beaches, mountains, backwaters, culture)"),
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- gr.Radio(choices=["low", "medium", "high"], label="Budget"),
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- gr.Textbox(label="Specific Places in Kerala (Optional, leave blank for general Kerala trip)")
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- ],
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- outputs=gr.Textbox(label="Generated Kerala Trip Plan"),
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- title="Kerala Trip Planner AI",
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- description="Enter your desired trip duration, interests, and budget to get a personalized Kerala itinerary powered by the Travereel model."
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- )
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- # Launch the Gradio interface
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- iface.launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  import gradio as gr
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+ from transformers import AutoModelForSeq2SeqLM, AutoTokenizer, pipeline
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+ model_name = "rahmanazhar/Travereel-Model-V1"
 
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+ try:
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+ tokenizer = AutoTokenizer.from_pretrained(model_name)
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+ model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
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+ itinerary_generator = pipeline("text2text-generation", model=model, tokenizer=tokenizer)
 
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+ def generate_kerala_itinerary(duration, interests, budget, specific_places="Kerala"):
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+ """Generates a Kerala trip itinerary based on user inputs."""
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+ prompt = f"Generate a {duration}-day trip plan for {specific_places}, Kerala, focusing on {interests} with a {budget} budget."
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+ generated_text = itinerary_generator(prompt, max_length=500, num_return_sequences=1, do_sample=True, top_k=50, top_p=0.95)[0]['generated_text']
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+ return generated_text.strip()
 
 
 
 
 
 
 
 
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+ # Define the input and output interfaces for Gradio
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+ iface = gr.Interface(
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+ fn=generate_kerala_itinerary,
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+ inputs=[
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+ gr.Slider(minimum=1, maximum=10, step=1, label="Duration (Days)"),
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+ gr.Textbox(label="Your Interests (e.g., beaches, mountains, backwaters, culture)"),
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+ gr.Radio(choices=["low", "medium", "high"], label="Budget"),
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+ gr.Textbox(label="Specific Places in Kerala (Optional, leave blank for general Kerala trip)")
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+ ],
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+ outputs=gr.Textbox(label="Generated Kerala Trip Plan"),
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+ title="Kerala Trip Planner AI",
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+ description="Enter your desired trip duration, interests, and budget to get a personalized Kerala itinerary powered by the Travereel model."
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+ )
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+
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+ # Launch the Gradio interface
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+ iface.launch()
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+
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+ except Exception as e:
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+ print(f"Error loading model: {e}")
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+ def error_message():
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+ return f"Error loading the model: {e}. Please check the logs."
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+ iface = gr.Interface(fn=error_message, inputs=[], outputs=gr.Textbox(), title="Kerala Trip Planner AI (Error)")
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+ iface.launch()