fix: normalizer preserves compaction summaries, dedupes goal_context, no auto-reset on compacted input

src/translate-proxy.py

@@ -4310,13 +4310,19 @@ def _antigravity_normalize_context(input_data):
     if os.environ.get("ANTIGRAVITY_AUTO_RESET_POLLUTED_CONTEXT", "1") != "1":
         auto_reset = False
 
-    if is_simple and (auto_reset or n_tool_outputs == 0):
+    has_compaction_summary = any(
+        isinstance(it, dict) and it.get("type") == "message" and it.get("role") == "user"
+        and ("Auto-compacted" in str(it.get("content", "")) or "auto-compacted" in str(it.get("content", "")).lower())
+        for it in input_data
+    )
+
+    if is_simple and auto_reset and not has_compaction_summary:
         system_items = [it for it in input_data if isinstance(it, dict) and it.get("type") == "message" and it.get("role") in ("developer", "system")]
         user_item = input_data[latest_user_idx]
         result = system_items + [user_item] if system_items else [user_item]
         print(f"[antigravity-context] raw_items={n_raw} compacted_items={n_raw} final_items={len(result)}", file=sys.stderr)
         print(f"[antigravity-context] raw_tool_outputs={n_tool_outputs} kept_tool_outputs=0", file=sys.stderr)
-        print(f"[antigravity-context] simple_latest_user=true auto_reset={auto_reset}", file=sys.stderr)
+        print(f"[antigravity-context] simple_latest_user=true auto_reset={auto_reset} has_compaction={has_compaction_summary}", file=sys.stderr)
         return result
 
     dev_messages = []
@@ -4357,6 +4363,22 @@ def _antigravity_normalize_context(input_data):
     tail_start = max(0, len(recent_items) - 6)
     recent_tail = recent_items[tail_start:]
 
+    deduped_tail = []
+    seen_goal_context = False
+    for idx, msg_item in recent_tail:
+        content_str = ""
+        c = msg_item.get("content", "")
+        if isinstance(c, str):
+            content_str = c
+        elif isinstance(c, list):
+            content_str = " ".join(p.get("text", p.get("input_text", "")) for p in c if isinstance(p, dict))
+        if "<goal_context>" in content_str:
+            if seen_goal_context:
+                continue
+            seen_goal_context = True
+        deduped_tail.append((idx, msg_item))
+    recent_tail = deduped_tail if deduped_tail else recent_tail
+
     tool_call_ids = set()
     for _, t_item in kept_tools:
         cid = t_item.get("call_id", t_item.get("id", ""))
@@ -4371,6 +4393,15 @@ def _antigravity_normalize_context(input_data):
 
     result = list(dev_messages)
 
+    compaction_summaries = []
+    for idx, msg_item in recent_items:
+        if msg_item is input_data[latest_user_idx]:
+            continue
+        c = msg_item.get("content", "")
+        content_str = c if isinstance(c, str) else " ".join(p.get("text", p.get("input_text", "")) for p in c if isinstance(p, dict)) if isinstance(c, list) else ""
+        if "Auto-compacted" in content_str or "auto-compacted" in content_str.lower():
+            compaction_summaries.append(msg_item)
+
     if n_summarized > 0:
         summary_text = f"[Tool history summary: {n_summarized} older tool outputs omitted. {n_tool_calls} prior function calls were made for file inspection/editing.]"
         result.append({"type": "message", "role": "user", "content": [{"type": "input_text", "text": summary_text}]})
@@ -4381,6 +4412,9 @@ def _antigravity_normalize_context(input_data):
     for _, tool_item in kept_tools:
         result.append(tool_item)
 
+    for cs_item in compaction_summaries:
+        result.append(cs_item)
+
     for _, msg_item in recent_tail:
         if msg_item is not input_data[latest_user_idx]:
             result.append(msg_item)
@@ -4408,7 +4442,10 @@ def _antigravity_normalize_context(input_data):
 
     if total_chars > _ANTIGRAVITY_EMERGENCY_CHARS:
         print(f"[antigravity-context] EMERGENCY: {total_chars} chars exceeds limit, resetting to minimal", file=sys.stderr)
-        result = list(dev_messages) + [input_data[latest_user_idx]]
+        result = list(dev_messages)
+        if compaction_summaries:
+            result.extend(compaction_summaries)
+        result.append(input_data[latest_user_idx])
         total_chars = sum(len(json.dumps(it, ensure_ascii=False)) for it in result)
 
     while len(result) > _ANTIGRAVITY_MAX_CONTENTS and total_chars > _ANTIGRAVITY_SOFT_CHARS: