Upload app.py
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app.py
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@@ -3,22 +3,29 @@ import gradio as gr
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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#
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model_id = "ibm/granite-3.3-2b-instruct"
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token = os.getenv("HF_TOKEN") #
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model
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def query_granite(prompt):
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=100)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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#
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def home():
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with gr.Blocks() as demo:
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gr.Markdown("# π₯ Welcome to HealthAI")
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gr.Markdown("Your intelligent healthcare assistant
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return demo
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def symptoms_app():
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@@ -69,10 +76,10 @@ def faqs_app():
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with gr.Blocks() as demo:
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gr.Markdown("## β FAQs")
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gr.Markdown("**Q1:** What is HealthAI?")
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gr.Markdown("**A:** It's an AI assistant to help with health-related queries using IBM Granite
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return demo
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#
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pages = [
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gr.Page(title="π Home", path="/", block=home),
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gr.Page(title="π©Ί Symptoms", path="/symptoms", block=symptoms_app),
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@@ -83,4 +90,4 @@ pages = [
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]
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app = gr.App(pages=pages)
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app.launch()
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from transformers import AutoModelForCausalLM, AutoTokenizer
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import torch
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# β
Correct IBM Granite model
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model_id = "ibm-granite/granite-3.3-2b-instruct"
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token = os.getenv("HF_TOKEN") # Load from Hugging Face Secrets
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# β
Load model and tokenizer using the updated syntax
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tokenizer = AutoTokenizer.from_pretrained(model_id, token=token)
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model = AutoModelForCausalLM.from_pretrained(
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model_id,
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token=token,
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device_map="auto",
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torch_dtype=torch.float32
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)
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def query_granite(prompt):
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inputs = tokenizer(prompt, return_tensors="pt").to(model.device)
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outputs = model.generate(**inputs, max_new_tokens=100)
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return tokenizer.decode(outputs[0], skip_special_tokens=True)
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# Pages
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def home():
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with gr.Blocks() as demo:
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gr.Markdown("# π₯ Welcome to HealthAI")
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gr.Markdown("Your intelligent healthcare assistant using IBM Granite 3.3-2B Instruct.")
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return demo
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def symptoms_app():
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with gr.Blocks() as demo:
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gr.Markdown("## β FAQs")
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gr.Markdown("**Q1:** What is HealthAI?")
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gr.Markdown("**A:** It's an AI assistant to help with health-related queries using IBM Granite 3.3-2B.")
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return demo
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# App configuration
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pages = [
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gr.Page(title="π Home", path="/", block=home),
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gr.Page(title="π©Ί Symptoms", path="/symptoms", block=symptoms_app),
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]
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app = gr.App(pages=pages)
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app.launch()
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