Update src/streamlit_app.py

src/streamlit_app.py

@@ -1,6 +1,7 @@
-import os
+# import os
 import json
 from typing import Dict, Any, List
+import uuid
 
 import streamlit as st
 from transformers import (
@@ -96,24 +97,41 @@ def get_pipeline(task: str, model_id: str):
 def section_header(title, emoji="✨"):
     st.markdown(f"## {emoji} {title}")
 
-def model_picker(task_filter: str) -> Dict[str, Any]:
-    """Model selection widget"""
+def model_picker(task_filter: str, context: str = "") -> Dict[str, Any]:
+    """Model selection widget with unique keys"""
     subset = {k: v for k, v in MODEL_REGISTRY.items() if v["task"] == task_filter}
     names = list(subset.keys())
     
+    # Create unique key suffix
+    unique_suffix = f"{context}_{task_filter}_{uuid.uuid4().hex[:8]}"
+    
     if not names:
         st.warning(f"No models registered for task: {task_filter}")
         st.info("You can add a custom model repo ID below.")
-        repo = st.text_input("Model repo on Hugging Face", placeholder="org/model-id")
-        return {"name": "Custom", "task": task_filter, "repo": repo, "paper": "N/A", "notes": "Custom model"}
+        repo = st.text_input(
+            "Model repo on Hugging Face", 
+            placeholder="org/model-id",
+            key=f"repo_custom_{unique_suffix}"
+        )
+        return {
+            "name": "Custom", 
+            "task": task_filter, 
+            "repo": repo, 
+            "paper": "N/A", 
+            "notes": "Custom model"
+        }
     
-    choice = st.selectbox("Pick a model", names, key=f"picker_{task_filter}_{len(names)}")
+    choice = st.selectbox(
+        "Pick a model", 
+        names, 
+        key=f"picker_{unique_suffix}"
+    )
     cfg = subset[choice]
     repo = st.text_input(
         "Model repo on Hugging Face", 
         value=cfg["repo"], 
         placeholder="org/model-id",
-        key=f"repo_{choice}"
+        key=f"repo_{unique_suffix}"
     )
     st.caption(f"**Paper**: {cfg['paper']}  \n**Notes**: {cfg['notes']}")
     return {
@@ -152,7 +170,7 @@ tabs = st.tabs([
 # -----------------------------
 with tabs[0]:
     section_header("Meter classification (text)", "📏")
-    cfg = model_picker("text-classification")
+    cfg = model_picker("text-classification", context="meter")
     verse = st.text_area(
         "Paste a single bayt (verse) or hemistich", 
         height=120, 
@@ -202,10 +220,10 @@ with tabs[1]:
     col1, col2 = st.columns(2)
     with col1:
         st.markdown("**Era**")
-        cfg_era = model_picker("text-classification")
+        cfg_era = model_picker("text-classification", context="era")
     with col2:
         st.markdown("**Theme**")
-        cfg_theme = model_picker("text-classification")
+        cfg_theme = model_picker("text-classification", context="theme")
 
     text = st.text_area(
         "Paste verse(s) for classification", 
@@ -278,7 +296,7 @@ with tabs[1]:
 # -----------------------------
 with tabs[2]:
     section_header("Diacritization (seq2seq)", "🕊️")
-    cfg_diac = model_picker("text2text-generation")
+    cfg_diac = model_picker("text2text-generation", context="diac")
     src = st.text_area(
         "Undiacritized verse(s)", 
         height=150, 
@@ -316,7 +334,7 @@ with tabs[2]:
 # -----------------------------
 with tabs[3]:
     section_header("Poetry generation", "📝")
-    cfg_gen = model_picker("text-generation")
+    cfg_gen = model_picker("text-generation", context="gen")
     prompt = st.text_area(
         "Prompt (include hints: meter / qafiyah / theme)",
         height=150,