Create BulkDigest.py

pages/BulkDigest.py

@@ -0,0 +1,75 @@
+import streamlit as st
+import os, hashlib, re
+from utils.file_utils import normalize_log_line
+from utils.summarizer import summarize_text
+from utils.docgen import generate_doc
+
+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 = []
+
+uploads = st.file_uploader(
+    "Upload files (scripts, logs, text, PDFs)", 
+    type=["py", "sh", "txt", "log", "pdf"], 
+    accept_multiple_files=True
+)
+
+if uploads:
+    digests = []
+    for f in uploads:
+        try:
+            content = f.read().decode("utf-8", errors="ignore")
+            sha1 = hashlib.sha1(content.encode()).hexdigest()
+
+            # Detect type
+            is_log = f.name.endswith(".log")
+            is_script = f.name.endswith(".py") or f.name.endswith(".sh")
+
+            # Normalize logs
+            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
+            summary = summarize_text(content)
+
+            # Script docs if applicable
+            doc = generate_doc(f.name, "uploaded", content) if is_script else None
+
+            result = {
+                "name": f.name,
+                "sha1": sha1,
+                "preview": preview,
+                "summary": summary,
+                "doc": doc,
+            }
+            digests.append(result)
+
+            # Track upload
+            st.session_state.uploaded_files.append(f.name)
+
+            # Display in UI
+            st.subheader(f"📄 {f.name}")
+            st.code(preview)
+            st.markdown(f"**SHA1:** `{sha1}`")
+            st.write("🧠 **Summary:**", summary)
+            if doc:
+                st.write("📘 **Generated Documentation:**")
+                st.markdown(doc)
+
+        except Exception as e:
+            st.error(f"⚠️ Error processing {f.name}: {e}")
+            st.session_state.errors.append(str(e))
+
+    # Save to session state for Chatbot
+    st.session_state.bulk_digests = digests
+    st.success(f"✅ Bulk digestion complete for {len(digests)} files.")