Update app.py

app.py

@@ -122,6 +122,7 @@ def show_combined_repo_and_llm():
         df = read_csv_as_text(csv_filename)
         for col in ["strength", "weaknesses", "speciality", "relevance rating"]:
             df[col] = df[col].astype(str)
+        updated = False
         for idx, row in df.iterrows():
             if row["repo id"] == repo_id:
                 if isinstance(llm_json, dict) and "error" not in llm_json:
@@ -132,9 +133,23 @@ def show_combined_repo_and_llm():
                     df.at[idx, "weaknesses"] = weaknesses
                     df.at[idx, "speciality"] = llm_json.get("speciality", "")
                     df.at[idx, "relevance rating"] = llm_json.get("relevance rating", "")
+                    updated = True
                 else:
                     extraction_status = f"JSON extraction: FAILED\nRaw: {llm_json.get('raw', '') if isinstance(llm_json, dict) else llm_json}"
                 break
+        # If not updated (repo_id not found), append a new row
+        if not updated and isinstance(llm_json, dict) and "error" not in llm_json:
+            extraction_status = "JSON extraction: SUCCESS (new row)"
+            strengths = llm_json.get("strength", "")
+            weaknesses = llm_json.get("weaknesses", "")
+            new_row = {
+                "repo id": repo_id,
+                "strength": strengths,
+                "weaknesses": weaknesses,
+                "speciality": llm_json.get("speciality", ""),
+                "relevance rating": llm_json.get("relevance rating", "")
+            }
+            df = pd.concat([df, pd.DataFrame([new_row])], ignore_index=True)
         df.to_csv(csv_filename, index=False)
     except Exception as e:
         df = read_csv_as_text(csv_filename)