Update pages/BulkDigest.py

pages/BulkDigest.py

@@ -1,54 +1,60 @@
 import streamlit as st
 import os, hashlib, re, sys
 
-# ─── Ensure utils/ is importable ──────────────────────────────
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
+# ─── Ensure omniscientframework package is importable ────────────────
+ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
+PACKAGE_PATH = os.path.abspath(os.path.join(ROOT_PATH, ".."))
+if PACKAGE_PATH not in sys.path:
+    sys.path.insert(0, PACKAGE_PATH)
 
+# ─── Import project utilities ────────────────────────────────────────
 from omniscientframework.utils.file_utils import normalize_log_line
 from omniscientframework.utils.summarizer import summarize_text
 from omniscientframework.utils.docgen import generate_doc
 
+# ─── Page Setup ─────────────────────────────────────────────────────
 st.title("📂 AI Bulk Digest")
 st.write("Upload multiple files for batch digestion, summarization, and documentation.")
 
-# 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 = []
-if "bulk_digests" not in st.session_state:
-    st.session_state.bulk_digests = []
+# ─── Initialize Session State ───────────────────────────────────────
+for key in ("uploaded_files", "errors", "bulk_digests"):
+    if key not in st.session_state:
+        st.session_state[key] = []
 
+# ─── File Upload ────────────────────────────────────────────────────
 uploads = st.file_uploader(
-    "Upload files (scripts, logs, text, PDFs)", 
-    type=["py", "sh", "txt", "log", "pdf"], 
+    "Upload files (scripts, logs, text, PDFs)",
+    type=["py", "sh", "txt", "log", "pdf"],
     accept_multiple_files=True
 )
 
+# ─── Bulk Processing Logic ─────────────────────────────────────────
 if uploads:
     digests = []
     for f in uploads:
         try:
+            # Read content
             content = f.read().decode("utf-8", errors="ignore")
             sha1 = hashlib.sha1(content.encode()).hexdigest()
 
-            # Detect type
+            # File type detection
             is_log = f.name.endswith(".log")
-            is_script = f.name.endswith(".py") or f.name.endswith(".sh")
+            is_script = f.name.endswith((".py", ".sh"))
 
-            # Normalize logs
+            # Normalize log lines
             if is_log:
                 normalized = [normalize_log_line(line) for line in content.splitlines()]
                 preview = "\n".join(normalized[:30])
             else:
                 preview = "\n".join(content.splitlines()[:30])
 
-            # AI summary
+            # Generate AI summary
             summary = summarize_text(content)
 
-            # Script docs if applicable
+            # Auto-generate documentation for scripts
             doc = generate_doc(f.name, "uploaded", content) if is_script else None
 
+            # Build result object
             result = {
                 "name": f.name,
                 "sha1": sha1,
@@ -58,10 +64,10 @@ if uploads:
             }
             digests.append(result)
 
-            # Track upload
+            # Track file name
             st.session_state.uploaded_files.append(f.name)
 
-            # Display in UI
+            # ─── Display Results ───────────────────────────────
             st.subheader(f"📄 {f.name}")
             st.code(preview)
             st.markdown(f"**SHA1:** `{sha1}`")
@@ -74,6 +80,6 @@ if uploads:
             st.error(f"⚠️ Error processing {f.name}: {e}")
             st.session_state.errors.append(str(e))
 
-    # Save to session state for Chatbot
+    # Save to session state
     st.session_state.bulk_digests = digests
     st.success(f"✅ Bulk digestion complete for {len(digests)} files.")