Update agent.py

agent.py

@@ -64,17 +64,23 @@ def _mistral(prompt, key):
 
 def _gemini(prompt, key):
     if not key: return {}
-    try:
-        r = requests.post(
-            f"https://generativelanguage.googleapis.com/v1beta/models/"
-            f"gemini-2.5-flash:generateContent?key={key}",
-            headers={"Content-Type":"application/json"},
-            json={"contents":[{"parts":[{"text":prompt}]}],
-                  "generationConfig":{"temperature":0.2}}, timeout=15)
-        d = r.json()
-        if "candidates" not in d: return {}
-        return _parse(d["candidates"][0]["content"]["parts"][0]["text"])
-    except Exception as e: logger.warning("Gemini: %s",e); return {}
+    for attempt in range(2):
+        try:
+            r = requests.post(
+                f"https://generativelanguage.googleapis.com/v1beta/models/"
+                f"gemini-2.5-flash:generateContent?key={key}",
+                headers={"Content-Type":"application/json"},
+                json={"contents":[{"parts":[{"text":prompt}]}],
+                      "generationConfig":{"temperature":0.2}}, timeout=30)
+            d = r.json()
+            if "candidates" not in d:
+                logger.warning("Gemini attempt %d: no candidates: %s", attempt+1, d.get("error",""))
+                time.sleep(2); continue
+            return _parse(d["candidates"][0]["content"]["parts"][0]["text"])
+        except Exception as e:
+            logger.warning("Gemini attempt %d: %s", attempt+1, e)
+            time.sleep(2)
+    return {}
 
 # ---------------------------------------------------------------------------
 # Topic labelling prompt
@@ -213,13 +219,18 @@ def llm_council(state: PipelineState) -> dict:
         "single": round((total - n_triple - n_two) / total * 100),
     }
 
-    # Save outputs
-    records = sheets[4]
-    with open("topics.json","w") as f: json.dump(records, f, indent=2)
-    pd.DataFrame(records).to_csv("topics.csv", index=False)
+    # Save outputs — 4 separate sheet files
+    sheet_paths = {}
+    names = {1:"sheet1_groq",2:"sheet2_mistral",3:"sheet3_gemini",4:"sheet4_consolidated"}
+    for sn, name in names.items():
+        path = f"{name}.csv"
+        pd.DataFrame(sheets[sn]).to_csv(path, index=False)
+        sheet_paths[sn] = path
+    with open("topics.json","w") as f: json.dump(sheets[4], f, indent=2)
 
     return {"interpretations":interps, "sheets":sheets,
-            "agreement_rates":rates, "json_path":"topics.json", "csv_path":"topics.csv"}
+            "agreement_rates":rates, "sheet_paths":sheet_paths,
+            "json_path":"topics.json"}
 
 # ---------------------------------------------------------------------------
 # LangGraph node: build mismatch table