Update streamlit_app.py

streamlit_app.py

@@ -1,5 +1,6 @@
 import streamlit as st
 import os
+import hashlib
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
 import torch
 from upload_to_s3 import upload_file_to_s3
@@ -66,8 +67,9 @@ Only output valid markdown text.
         outputs = model.generate(**inputs, max_new_tokens=300)
     runbook_text = tokenizer.decode(outputs[0], skip_special_tokens=True).strip()
 
-    safe_filename = log_text.lower().replace(" ", "_").replace(":", "").replace('"', '').replace(".", "")
-    runbook_path = f"runbooks/runbook_{safe_filename}.md"
+    hash_id = hashlib.md5(log_text.encode()).hexdigest()[:8]
+    runbook_path = f"runbooks/runbook_{hash_id}.md"
+
     os.makedirs("runbooks", exist_ok=True)
     with open(runbook_path, "w", encoding="utf-8") as f:
         f.write(runbook_text)
@@ -106,7 +108,7 @@ if st.button(" Classify + Generate Runbook"):
 
                     if success:
                         s3_url = f"https://{bucket_name}.s3.{aws_region}.amazonaws.com/{s3_path}"
-                        send_slack_alert(log, s3_url, slack_url)
+                        send_slack_alert(log, s3_url)
                         st.success(" Slack alert sent.")
                         st.markdown(f"[ View Runbook on S3]({s3_url})")
                         st.download_button(" Download Runbook", runbook_md, file_name=os.path.basename(runbook_path))