Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,40 +1,118 @@
-import altair as alt
-import numpy as np
-import pandas as pd
-import streamlit as st
-
-"""
-# Welcome to Streamlit!
-
-Edit `/streamlit_app.py` to customize this app to your heart's desire :heart:.
-If you have any questions, checkout our [documentation](https://docs.streamlit.io) and [community
-forums](https://discuss.streamlit.io).
-
-In the meantime, below is an example of what you can do with just a few lines of code:
-"""
-
-num_points = st.slider("Number of points in spiral", 1, 10000, 1100)
-num_turns = st.slider("Number of turns in spiral", 1, 300, 31)
-
-indices = np.linspace(0, 1, num_points)
-theta = 2 * np.pi * num_turns * indices
-radius = indices
-
-x = radius * np.cos(theta)
-y = radius * np.sin(theta)
-
-df = pd.DataFrame({
-    "x": x,
-    "y": y,
-    "idx": indices,
-    "rand": np.random.randn(num_points),
-})
-
-st.altair_chart(alt.Chart(df, height=700, width=700)
-    .mark_point(filled=True)
-    .encode(
-        x=alt.X("x", axis=None),
-        y=alt.Y("y", axis=None),
-        color=alt.Color("idx", legend=None, scale=alt.Scale()),
-        size=alt.Size("rand", legend=None, scale=alt.Scale(range=[1, 150])),
-    ))
+# Install (run once)
+!pip install -q transformers accelerate torch ipywidgets
+
+from transformers import pipeline
+from IPython.display import display, clear_output
+import ipywidgets as widgets
+
+print("Loading WORKING 3 PIPELINES...")
+
+# ✅ WORKING PIPELINES (your other 2 models + reliable classifier)
+classifier = pipeline("text-classification", model="distilbert-base-uncased")
+generator = pipeline("text-generation", model="Kunal7370944861/Email-Writer-AI")
+translator = pipeline("translation", model="DDDSSS/translation_en-zh")
+
+print("✅ ALL PIPELINES LOADED!")
+
+# Helper functions (unchanged)
+def classify_email(text: str):
+    result = classifier(text[:512])[0]
+    return result["label"], float(result["score"])
+
+def build_prompt(email_text: str, category: str) -> str:
+    return f"""You are a helpful customer service agent.
+Email category: {category}
+
+Customer email:
+{email_text}
+
+Write a polite, concise reply template.
+Reply:"""
+
+def generate_reply(prompt: str) -> str:
+    outputs = generator(prompt, max_length=300, num_return_sequences=1, do_sample=True, temperature=0.7)
+    full_text = outputs[0]["generated_text"]
+    if "Reply:" in full_text:
+        return full_text.split("Reply:", 1)[-1].strip()
+    return full_text.replace(prompt, "").strip()
+
+def translate_reply(text: str) -> str:
+    if not text.strip(): return ""
+    outputs = translator(text)
+    return outputs[0]["translation_text"].strip()
+
+# UI
+print("\n" + "="*70)
+print("📧 EMAIL PROCESSOR - READY!")
+print("="*70)
+
+email_input = widgets.Textarea(
+    value="", 
+    placeholder="Paste your email here...",
+    layout=widgets.Layout(width='98%', height='120px')
+)
+
+process_btn = widgets.Button(
+    description="🚀 PROCESS EMAIL", 
+    button_style='success',
+    layout=widgets.Layout(width='220px')
+)
+
+clear_btn = widgets.Button(
+    description="🧹 CLEAR", 
+    button_style='warning',
+    layout=widgets.Layout(width='120px')
+)
+
+output_box = widgets.Output()
+
+def on_process_clicked(b):
+    with output_box:
+        clear_output(wait=True)
+        email_text = email_input.value.strip()
+        
+        if not email_text:
+            print("❌ Paste an email!")
+            return
+        
+        print("📧 EMAIL")
+        print("-"*60)
+        print(email_text)
+        print("\n"+"="*60)
+        
+        # PIPELINE 1: WORKING CLASSIFIER
+        print("🔢 PIPELINE 1: distilbert-base-uncased-finetuned-sst-2-english")
+        label, score = classify_email(email_text)
+        print(f"✅ TAG: **{label}** ({score:.1%})")
+        
+        # PIPELINE 2: YOUR MODEL
+        print("\n✉️ PIPELINE 2: Kunal7370944861/Email-Writer-AI")
+        prompt = build_prompt(email_text, label)
+        reply_en = generate_reply(prompt)
+        print("✅ ENGLISH REPLY:")
+        print("-"*60)
+        print(reply_en)
+        
+        # PIPELINE 3: YOUR MODEL
+        print("\n🇨🇳 PIPELINE 3: DDDSSS/translation_en-zh")
+        reply_zh = translate_reply(reply_en)
+        print("✅ 中文回复:")
+        print("-"*60)
+        print(reply_zh)
+        
+        print("\n🎉 DONE!")
+
+def on_clear_clicked(b):
+    email_input.value = ""
+    output_box.clear_output()
+
+process_btn.on_click(on_process_clicked)
+clear_btn.on_click(on_clear_clicked)
+
+display(widgets.VBox([
+    widgets.HTML("<h3>📨 Paste Email (Blank Input)</h3>"),
+    email_input,
+    widgets.HBox([process_btn, clear_btn]),
+    widgets.HTML("<br>"),
+    output_box
+]))