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Update app.py
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app.py
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@@ -1,8 +1,10 @@
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import streamlit as st
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# Streamlit
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st.set_page_config(page_title="Email Writer with FLAN-T5", layout="centered")
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@st.cache_resource
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def load_model():
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model_name = "google/flan-t5-large"
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@@ -12,27 +14,30 @@ def load_model():
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tokenizer, model = load_model()
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st.title("📧 AI Email Writer")
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st.write("Generate professional emails with the help of `google/flan-t5-large` model.")
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# Input
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user_instruction = st.text_area("✍️ Enter your email instruction",
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placeholder="e.g. Write a polite follow-up email to a client who hasn’t responded in a week.",
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height=150)
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temperature = st.slider("🎯 Creativity (Temperature)", 0.1, 1.0, 0.7, 0.1)
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max_tokens = st.slider("📏 Max Tokens", 50, 512, 200, 10)
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# Generate email on button click
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if st.button("Generate Email"):
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if user_instruction.strip()
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st.warning("Please enter
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else:
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with st.spinner("Generating email..."):
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st.success("Here’s your generated email:")
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st.text_area("📨 Generated Email", value=email_output, height=200)
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import streamlit as st
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# Must be the first Streamlit command
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st.set_page_config(page_title="Email Writer with FLAN-T5", layout="centered")
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from transformers import T5Tokenizer, T5ForConditionalGeneration
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@st.cache_resource
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def load_model():
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model_name = "google/flan-t5-large"
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tokenizer, model = load_model()
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# Streamlit UI
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st.title("📧 AI Email Writer")
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st.write("Generate professional emails with the help of `google/flan-t5-large` model.")
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# Input section
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user_instruction = st.text_area("✍️ Enter your email instruction",
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placeholder="e.g. Write a polite follow-up email to a client who hasn’t responded in a week.",
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height=150)
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temperature = st.slider("🎯 Creativity (Temperature)", 0.1, 1.0, 0.7, 0.1)
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max_tokens = st.slider("📏 Max Output Tokens", 50, 512, 200, 10)
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if st.button("Generate Email"):
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if not user_instruction.strip():
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st.warning("Please enter a valid instruction.")
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else:
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with st.spinner("Generating email..."):
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input_ids = tokenizer(user_instruction, return_tensors="pt").input_ids
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output_ids = model.generate(
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input_ids=input_ids,
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max_new_tokens=max_tokens,
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temperature=temperature,
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do_sample=True
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)
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email_output = tokenizer.decode(output_ids[0], skip_special_tokens=True).strip()
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st.success("Here’s your generated email:")
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st.text_area("📨 Generated Email", value=email_output, height=200)
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