Update pages/Omnilog.py

pages/Omnilog.py

@@ -1,26 +1,58 @@
 import streamlit as st
 import re, hashlib
+from utils.file_utils import normalize_log_line, keyword_search
+from utils.summarizer import summarize_text
 
 st.title("📜 Omnilog")
-st.write("Log analyzer module")
+st.write("Log analyzer with normalization, search, and AI summaries")
+
+# Init counters
+if "uploaded_files" not in st.session_state:
+    st.session_state.uploaded_files = []
+if "errors" not in st.session_state:
+    st.session_state.errors = []
 
 uploaded = st.file_uploader("Upload a log file", type=["log", "txt"])
 if uploaded:
-    content = uploaded.read().decode("utf-8", errors="ignore")
+    try:
+        content = uploaded.read().decode("utf-8", errors="ignore")
+
+        # Track uploaded file
+        st.session_state.uploaded_files.append(uploaded.name)
+
+        # Normalize
+        normalized = [normalize_log_line(line) for line in content.splitlines()]
+
+        # Display normalized preview
+        st.subheader("🧹 Normalized Logs")
+        st.code("\n".join(normalized[:50]))
+
+        # Stats
+        st.subheader("📊 Stats")
+        st.metric("Total Lines", len(normalized))
+        st.metric("Unique Entries", len(set(normalized)))
+        st.write("SHA1 Digest:", hashlib.sha1(content.encode()).hexdigest())
 
-    noise = re.compile(r"^\w{3}\s+\d+\s+\d{2}:\d{2}:\d{2}\s+[\w\-\.\:]+\s+")
-    normalized = [noise.sub("", line) for line in content.splitlines()]
+        # Keyword search
+        query = st.text_input("🔍 Search logs")
+        matches = []
+        if query:
+            matches = keyword_search("\n".join(normalized), query)
+            st.success(f"Found {len(matches)} matches")
+            st.code("\n".join(matches[:50]))
 
-    st.subheader("🧹 Normalized Logs")
-    st.code("\n".join(normalized[:50]))
+        # AI summarization
+        st.subheader("🧠 AI Summary")
+        summary = summarize_text("\n".join(normalized))
+        st.write(summary)
 
-    st.subheader("📊 Stats")
-    st.metric("Total Lines", len(normalized))
-    st.metric("Unique Entries", len(set(normalized)))
-    st.write("SHA1 Digest:", hashlib.sha1(content.encode()).hexdigest())
+        # Save results for Chatbot context
+        st.session_state.omnilog_output = {
+            "normalized_preview": "\n".join(normalized[:50]),
+            "matches": matches[:50],
+            "summary": summary,
+        }
 
-    query = st.text_input("🔍 Search logs")
-    if query:
-        matches = [line for line in normalized if query.lower() in line.lower()]
-        st.success(f"Found {len(matches)} matches")
-        st.code("\n".join(matches[:50]))
+    except Exception as e:
+        st.error(f"⚠️ Error processing log: {e}")
+        st.session_state.errors.append(str(e))