Update app.py

app.py

@@ -1,112 +1,110 @@
-import os
-import nest_asyncio
-nest_asyncio.apply()
+import os 
+import nest_asyncio 
+nest_asyncio.apply() 
+import streamlit as st 
+from transformers import pipeline 
+from huggingface_hub import login 
+from streamlit.components.v1 import html 
 
-import streamlit as st
-from transformers import pipeline
-from huggingface_hub import login
-from streamlit.components.v1 import html
+# Retrieve the token from environment variables 
+hf_token = os.environ.get("HF_TOKEN") 
+if not hf_token: 
+    st.error("Hugging Face token not found. Please set the HF_TOKEN environment variable.") 
+    st.stop() 
 
-# Retrieve the token from environment variables
-hf_token = os.environ.get("HF_TOKEN")
-if not hf_token:
-    st.error("Hugging Face token not found. Please set the HF_TOKEN environment variable.")
-    st.stop()
+# Login with the token 
+login(token=hf_token) 
 
-# Login with the token
-login(token=hf_token)
+# Initialize session state for timer and results 
+if 'result' not in st.session_state: 
+    st.session_state.result = {} 
+if 'timer_started' not in st.session_state: 
+    st.session_state.timer_started = False 
+if 'timer_frozen' not in st.session_state: 
+    st.session_state.timer_frozen = False 
 
-# Initialize session state for timer and results
-if 'result' not in st.session_state:
-    st.session_state.result = {}
-if 'timer_started' not in st.session_state:
-    st.session_state.timer_started = False
-if 'timer_frozen' not in st.session_state:
-    st.session_state.timer_frozen = False
+# Timer component using HTML and JavaScript 
+def timer(): 
+    return """ 
+    <div id="timer" style="font-size:16px;color:#666;margin-bottom:10px;">⏱️ Elapsed: 00:00</div> 
+    <script> 
+    (function() { 
+    var start = Date.now(); 
+    var timerElement = document.getElementById('timer'); 
+    localStorage.removeItem("freezeTimer"); 
+    var interval = setInterval(function() { 
+    if(localStorage.getItem("freezeTimer") === "true"){ 
+    clearInterval(interval); 
+    timerElement.style.color = '#00cc00'; 
+    return; 
+    } 
+    var elapsed = Date.now() - start; 
+    var minutes = Math.floor(elapsed / 60000); 
+    var seconds = Math.floor((elapsed % 60000) / 1000); 
+    timerElement.innerHTML = '⏱️ Elapsed: ' + 
+    (minutes < 10 ? '0' : '') + minutes + ':' + 
+    (seconds < 10 ? '0' : '') + seconds; 
+    }, 1000); 
+    })(); 
+    </script> 
+    """ 
 
-# Timer component using HTML and JavaScript
-def timer():
-    return """
-    <div id="timer" style="font-size:16px;color:#666;margin-bottom:10px;">⏱️ Elapsed: 00:00</div>
-    <script>
-    (function() {
-        var start = Date.now();
-        var timerElement = document.getElementById('timer');
-        localStorage.removeItem("freezeTimer");
-        var interval = setInterval(function() {
-            if(localStorage.getItem("freezeTimer") === "true"){
-                clearInterval(interval);
-                timerElement.style.color = '#00cc00';
-                return;
-            }
-            var elapsed = Date.now() - start;
-            var minutes = Math.floor(elapsed / 60000);
-            var seconds = Math.floor((elapsed % 60000) / 1000);
-            timerElement.innerHTML = '⏱️ Elapsed: ' + 
-                (minutes < 10 ? '0' : '') + minutes + ':' + 
-                (seconds < 10 ? '0' : '') + seconds;
-        }, 1000);
-    })();
-    </script>
-    """
+st.set_page_config(page_title="Sentiment & Report Generator", page_icon="📝") 
+st.header("Sentiment Analysis & Report Generation with Gemma") 
 
-st.set_page_config(page_title="Sentiment & Report Generator", page_icon="📝")
-st.header("Sentiment Analysis & Report Generation with Gemma")
+# Load models with caching to avoid reloading on every run 
+@st.cache_resource 
+def load_models(): 
+    sentiment_pipe = pipeline("text-classification", model="mixedbread-ai/mxbai-rerank-base-v1") 
+    gemma_pipe = pipeline("text-generation", model="google/gemma-3-1b-it", use_auth_token=hf_token) 
+    return sentiment_pipe, gemma_pipe 
 
-# Load models with caching to avoid reloading on every run
-@st.cache_resource
-def load_models():
-    sentiment_pipe = pipeline("text-classification", model="mixedbread-ai/mxbai-rerank-base-v1")
-    # Pass the token to the Gemma pipeline
-    gemma_pipe = pipeline("text-generation", model="google/gemma-3-1b-it", use_auth_token=hf_token)
-    return sentiment_pipe, gemma_pipe
+sentiment_pipe, gemma_pipe = load_models() 
 
-sentiment_pipe, gemma_pipe = load_models()
+# Provide two options for input: text area or file upload 
+uploaded_file = st.file_uploader("Upload Review File (txt format)", type=["txt"])
+user_input = st.text_area("Or, enter your text for sentiment analysis and report generation:")
 
-# User input: a text area for the text to analyze
-user_input = st.text_area("Enter your text for sentiment analysis and report generation:")
+# If a file is uploaded, override user_input with its contents
+if uploaded_file is not None:
+    try:
+        user_input = uploaded_file.read().decode("utf-8")
+    except Exception as e:
+        st.error(f"Error reading file: {e}")
 
-if st.button("Generate Report"):
-    if not user_input.strip():
+if st.button("Generate Report"): 
+    if not user_input.strip(): 
         st.error("Please enter some text!")
-    else:
-        if not st.session_state.timer_started and not st.session_state.timer_frozen:
-            st.session_state.timer_started = True
-            html(timer(), height=50)
-        
-        status_text = st.empty()
-        progress_bar = st.progress(0)
-        
-        try:
-            # Stage 1: Sentiment Analysis
-            status_text.markdown("**🔍 Running sentiment analysis...**")
-            progress_bar.progress(0)
-            sentiment_result = sentiment_pipe(user_input)
-            progress_bar.progress(50)
-            
-            # Stage 2: Generate Report using Gemma
-            status_text.markdown("**📝 Generating report with Gemma...**")
-            prompt = f"""
-Generate a detailed report based on the following analysis.
-
-Original text:
-"{user_input}"
-
-Sentiment analysis result:
-{sentiment_result}
-
-Please provide a concise summary report explaining the sentiment and key insights.
-"""
-            report = gemma_pipe(prompt, max_length=200)
-            progress_bar.progress(100)
-            status_text.success("**✅ Generation complete!**")
-            html("<script>localStorage.setItem('freezeTimer', 'true');</script>", height=0)
-            st.session_state.timer_frozen = True
-            
-            st.write("**Sentiment Analysis Result:**", sentiment_result)
-            st.write("**Generated Report:**", report[0]['generated_text'])
-            
-        except Exception as e:
-            html("<script>document.getElementById('timer').remove();</script>")
-            status_text.error(f"**❌ Error:** {str(e)}")
+    else: 
+        if not st.session_state.timer_started and not st.session_state.timer_frozen: 
+            st.session_state.timer_started = True 
+            html(timer(), height=50) 
+        status_text = st.empty() 
+        progress_bar = st.progress(0) 
+        try: 
+            # Stage 1: Sentiment Analysis 
+            status_text.markdown("**🔍 Running sentiment analysis...**") 
+            progress_bar.progress(0) 
+            sentiment_result = sentiment_pipe(user_input) 
+            progress_bar.progress(50) 
+            # Stage 2: Generate Report using Gemma 
+            status_text.markdown("**📝 Generating report with Gemma...**") 
+            prompt = f""" 
+            Generate a detailed report based on the following analysis. 
+            Original text: 
+            "{user_input}" 
+            Sentiment analysis result: 
+            {sentiment_result} 
+            Please provide a concise summary report explaining the sentiment and key insights. 
+            """ 
+            report = gemma_pipe(prompt, max_length=200) 
+            progress_bar.progress(100) 
+            status_text.success("**✅ Generation complete!**") 
+            html("<script>localStorage.setItem('freezeTimer', 'true');</script>", height=0) 
+            st.session_state.timer_frozen = True 
+            st.write("**Sentiment Analysis Result:**", sentiment_result) 
+            st.write("**Generated Report:**", report[0]['generated_text']) 
+        except Exception as e: 
+            html("<script>document.getElementById('timer').remove();</script>") 
+            status_text.error(f"**❌ Error:** {str(e)}") 
             progress_bar.empty()