Update app.py

app.py

@@ -11,40 +11,56 @@ import psutil
 from pathlib import Path
 import torch
 
-st.set_page_config(
-    page_title="LexPilot",
-    page_icon="🛩️",
-    layout="wide",
-    initial_sidebar_state="expanded"
-)
+# Page config with wide layout
+st.set_page_config(page_title="LexPilot", layout="wide")
 
-# Cache directory setup
+# Sidebar with project info
+with st.sidebar:
+    st.title("LexPilot™")
+    st.markdown(
+        """
+        LexPilot™ ingests text, PDF, and Word files to instantly analyze contracts.  
+        It delivers concise summaries and lets you ask targeted questions—  
+        giving fast, precise insights to speed up legal and procurement reviews.
+        """
+    )
+    st.markdown("---")
+    st.write("### System Status")
+    try:
+        device_status = 'GPU ✅' if torch.cuda.is_available() else 'CPU ⚠️'
+    except:
+        device_status = 'CPU (torch not configured)'
+    st.text(f"Device: {device_status}")
+    st.text(f"Memory: {psutil.virtual_memory().percent}% used")
+    st.text(f"CPU: {psutil.cpu_percent()}% used")
+
+# Setup cache directory for models
 def setup_environment():
-    cache_dir = Path("/app/models")
-    cache_dir.mkdir(exist_ok=True, parents=True)
+    cache_dir = Path(".cache/models")
+    try:
+        cache_dir.mkdir(exist_ok=True, parents=True)
+    except Exception as e:
+        st.error(f"Failed to create cache directory: {e}")
     return cache_dir
 
 cache_dir = setup_environment()
 
-# Load models with caching
 @st.cache_resource(ttl=3600)
 def load_models():
     try:
-        with st.spinner("🔄 Loading AI models (this may take 1-2 minutes)..."):
-            return {
-                'qa': pipeline(
-                    "question-answering",
-                    model="distilbert-base-cased-distilled-squad",
-                    device=-1
-                ),
-                'summarizer': pipeline(
-                    "summarization",
-                    model="sshleifer/distilbart-cnn-12-6",
-                    device=-1
-                )
-            }
+        qa_model = pipeline(
+            "question-answering",
+            model="distilbert-base-cased-distilled-squad",
+            device=-1
+        )
+        summarizer_model = pipeline(
+            "summarization",
+            model="sshleifer/distilbart-cnn-6-6",
+            device=-1
+        )
+        return {'qa': qa_model, 'summarizer': summarizer_model}
     except Exception as e:
-        st.error(f"❌ Failed to load models: {str(e)}")
+        st.error(f"Failed to load models: {e}")
         st.stop()
 
 models = load_models()
@@ -60,7 +76,7 @@ def extract_text(file):
             doc = docx.Document(file)
             return "\n".join(para.text for para in doc.paragraphs if para.text)
     except Exception as e:
-        st.error(f"⚠️ Error processing document: {str(e)}")
+        st.error(f"Error processing document: {e}")
         return ""
 
 def generate_summary(text, max_length=150):
@@ -74,7 +90,7 @@ def generate_summary(text, max_length=150):
             for chunk in chunks:
                 result = models['summarizer'](
                     chunk,
-                    max_length=max(max_length // len(chunks), 30),
+                    max_length=max(max_length//len(chunks), 30),
                     min_length=30,
                     do_sample=False
                 )
@@ -82,18 +98,13 @@ def generate_summary(text, max_length=150):
             return " ".join(summaries)
         return models['summarizer'](text, max_length=max_length)[0]['summary_text']
     except Exception as e:
-        st.error(f"❌ Summarization failed: {str(e)}")
+        st.error(f"Summarization failed: {e}")
         return ""
 
-# UI
-st.title("🛩️ LexPilot")
-st.markdown(
-    "LexPilot™ ingests text, PDF, and Word files to instantly analyze contracts. "
-    "It delivers concise summaries and lets you ask targeted questions—giving fast, precise insights to speed up legal and procurement reviews."
-)
+# Main UI title
+st.title("📄 LexPilot")
 
-with st.sidebar:
-    st.header("Upload Document")
+with st.expander("📤 Upload Document", expanded=True):
     uploaded_file = st.file_uploader("Choose PDF/DOCX", type=["pdf", "docx"])
     manual_text = st.text_area("Or paste text here:", height=150)
     context = extract_text(uploaded_file) if uploaded_file else manual_text
@@ -111,14 +122,12 @@ with tab1:
                         question=question,
                         context=context[:100000]
                     )
-                    st.success(f"Answered in {time.time() - start_time:.1f}s")
+                    st.success(f"Answered in {time.time()-start_time:.1f}s")
                     st.markdown(f"**Answer:** {result['answer']}")
                     st.progress(result['score'])
                     st.caption(f"Confidence: {result['score']:.0%}")
                 except Exception as e:
-                    st.error(f"❌ Question answering failed: {str(e)}")
-    else:
-        st.info("Upload a document or paste text to enable question answering.")
+                    st.error(f"Question answering failed: {e}")
 
 with tab2:
     if context and len(context.strip()) > 0:
@@ -129,20 +138,10 @@ with tab2:
                     start_time = time.time()
                     summary = generate_summary(context, length)
                     if summary:
-                        st.success(f"Generated in {time.time() - start_time:.1f}s")
+                        st.success(f"Generated in {time.time()-start_time:.1f}s")
                         st.markdown(f"**Summary:**\n\n{summary}")
-    else:
-        st.info("Upload a document or paste text to enable summarization.")
 
-with st.expander("⚙️ System Status"):
-    try:
-        device_status = 'GPU ✅' if torch.cuda.is_available() else 'CPU ⚠️'
-    except:
-        device_status = 'CPU (torch not configured)'
-    st.code(f"""
-Models loaded: {', '.join(models.keys())}
-Device: {device_status}
-Memory usage: {psutil.virtual_memory().percent}%
-CPU usage: {psutil.cpu_percent()}%
-Cache location: {cache_dir}
-""")
+# Show cache dir path in sidebar (optional)
+with st.sidebar:
+    st.markdown("---")
+    st.write(f"Cache directory: {cache_dir}")