v3.11.11: stricter function_call/output pairing + Gemini sanitizer rewrite (PR #12)
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CHANGELOG.md
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CHANGELOG.md
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# Changelog
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# Changelog
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## v3.11.11 (2026-05-26)
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**Antigravity Fix: Stricter function_call/output Pairing + Gemini Sanitizer Rewrite (PR #12)**
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### Bug Fixes
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- **Stricter function_call/output pairing**: Only includes pairs where BOTH call and output exist — no orphan calls sent to Gemini
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- **Gemini sanitizer rewritten**: Tool messages (`functionCall`/`functionResponse`) are always preserved as-is, never merged or skipped
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- **Text merging more conservative**: Checks last message for tool content before merging consecutive text messages
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- **Final trimming safe**: Only removes plain `message` items, never `function_call_output` (which would break tool pairs)
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- **Merge PR #12**: Fix by qwen-chat coder
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## v3.11.10 (2026-05-26)
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## v3.11.10 (2026-05-26)
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## v3.11.10 (2026-05-26)
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**Antigravity Fix: Interleave function_call/output Pairs, Gemini Turn Trimming (PR #11)**
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**Antigravity Fix: Interleave function_call/output Pairs, Gemini Turn Trimming (PR #11)**
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codex-launcher_3.11.11_all.deb
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codex-launcher_3.11.11_all.deb
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"""
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"""
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CHANGELOG = [
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CHANGELOG = [
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("3.11.11", "2026-05-26", [
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"Fix Antigravity: stricter function_call/output pairing (PR #12)",
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"Gemini sanitizer rewritten — tool messages always preserved",
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]),
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("3.11.10", "2026-05-26", [
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("3.11.10", "2026-05-26", [
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"Fix Antigravity: interleave function_call/output pairs (PR #11)",
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"Fix Antigravity: interleave function_call/output pairs (PR #11)",
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"Gemini sanitizer: trim non-user turns for Google API compliance",
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"Gemini sanitizer: trim non-user turns for Google API compliance",
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@@ -83,6 +83,12 @@ model_catalog_json = ""
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"""
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"""
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CHANGELOG = [
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CHANGELOG = [
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("3.11.11", "2026-05-26", [
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"Fix Antigravity: stricter function_call/output pairing + Gemini sanitizer rewrite (PR #12)",
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"Only pairs where BOTH call and output exist are included — no orphan calls",
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"Gemini sanitizer: tool messages always preserved as-is, text merging more conservative",
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"Final trimming only removes plain messages, never function_call_output",
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]),
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("3.11.10", "2026-05-26", [
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("3.11.10", "2026-05-26", [
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"Fix Antigravity: interleave function_call/output pairs in correct sequence (PR #11)",
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"Fix Antigravity: interleave function_call/output pairs in correct sequence (PR #11)",
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"Fix Gemini sanitizer: trim leading/trailing non-user turns for Google API compliance",
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"Fix Gemini sanitizer: trim leading/trailing non-user turns for Google API compliance",
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@@ -4841,6 +4841,14 @@ def _antigravity_is_simple_user(text):
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return False
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return False
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def _antigravity_normalize_context(input_data, model=""):
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def _antigravity_normalize_context(input_data, model=""):
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"""
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Normalize context for Antigravity while PRESERVING function_call -> function_call_output pairs.
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Google's Gemini API requires STRICT alternation:
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- functionCall (role=model) MUST be immediately followed by functionResponse (role=user)
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This function compacts old history but NEVER breaks tool call/response pairs.
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"""
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if not isinstance(input_data, list) or len(input_data) < 2:
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if not isinstance(input_data, list) or len(input_data) < 2:
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return input_data
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return input_data
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is_claude_model = "claude" in model.lower()
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is_claude_model = "claude" in model.lower()
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@@ -4889,7 +4897,7 @@ def _antigravity_normalize_context(input_data, model=""):
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dev_messages = []
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dev_messages = []
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recent_items = []
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recent_items = []
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tool_outputs = []
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tool_outputs = []
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other_items = []
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tool_calls = []
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for i, item in enumerate(input_data):
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for i, item in enumerate(input_data):
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if not isinstance(item, dict):
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if not isinstance(item, dict):
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dev_messages.append(item)
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dev_messages.append(item)
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elif t == "function_call_output":
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elif t == "function_call_output":
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tool_outputs.append((i, item))
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tool_outputs.append((i, item))
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elif t in ("function_call",):
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elif t == "function_call":
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other_items.append((i, item))
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tool_calls.append((i, item))
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elif t == "message":
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elif t == "message":
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recent_items.append((i, item))
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recent_items.append((i, item))
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@@ -4946,19 +4954,14 @@ def _antigravity_normalize_context(input_data, model=""):
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deduped_tail.append((idx, msg_item))
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deduped_tail.append((idx, msg_item))
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recent_tail = deduped_tail if deduped_tail else recent_tail
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recent_tail = deduped_tail if deduped_tail else recent_tail
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tool_call_ids = set()
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# Build call_id -> function_call mapping
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for _, t_item in kept_tools:
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tool_call_map = {}
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cid = t_item.get("call_id", t_item.get("id", ""))
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for _, call_item in tool_calls:
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cid = call_item.get("call_id", call_item.get("id", ""))
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if cid:
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if cid:
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tool_call_ids.add(cid)
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tool_call_map[cid] = call_item
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paired_calls = []
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# Build result: maintain PAIRED sequence (function_call -> function_call_output)
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for idx, item in other_items:
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cid = item.get("call_id", item.get("id", ""))
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if cid in tool_call_ids:
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paired_calls.append((idx, item))
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# Build result maintaining proper function_call -> function_call_output pairing
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result = list(dev_messages)
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result = list(dev_messages)
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compaction_summaries = []
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compaction_summaries = []
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@@ -4974,29 +4977,21 @@ def _antigravity_normalize_context(input_data, model=""):
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summary_text = f"[Tool history summary: {n_summarized} older tool outputs omitted. {n_tool_calls} prior function calls were made for file inspection/editing.]"
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summary_text = f"[Tool history summary: {n_summarized} older tool outputs omitted. {n_tool_calls} prior function calls were made for file inspection/editing.]"
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result.append({"type": "message", "role": "user", "content": [{"type": "input_text", "text": summary_text}]})
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result.append({"type": "message", "role": "user", "content": [{"type": "input_text", "text": summary_text}]})
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# CRITICAL FIX: Interleave function_calls with their corresponding function_call_outputs
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# CRITICAL: Add tool CALLS and their corresponding OUTPUTS in PAIRED ORDER
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# to maintain the required sequence: function_call -> function_call_output -> function_call -> ...
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# Only include pairs where BOTH call and output are present
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# Build a lookup map: call_id -> function_call_output item
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added_pairs = set()
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tool_output_map = {}
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for _, tool_item in kept_tools:
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for _, tool_item in kept_tools:
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cid = tool_item.get("call_id", tool_item.get("id", ""))
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cid = tool_item.get("call_id", tool_item.get("id", ""))
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if cid:
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if cid and cid in tool_call_map and cid not in added_pairs:
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tool_output_map[cid] = tool_item
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# Add function_call FIRST, then function_call_output IMMEDIATELY
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result.append(tool_call_map[cid])
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result.append(tool_item)
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added_pairs.add(cid)
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# First, add all paired function_calls followed immediately by their responses
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# Add any orphan tool outputs (no matching call found) - these go at the end before messages
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added_call_ids = set()
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for _, call_item in paired_calls:
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cid = call_item.get("call_id", call_item.get("id", ""))
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result.append(call_item)
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added_call_ids.add(cid)
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# Immediately append the corresponding function_call_output if available
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if cid in tool_output_map:
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result.append(tool_output_map[cid])
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# Add any remaining tool outputs that weren't paired (orphans)
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for _, tool_item in kept_tools:
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for _, tool_item in kept_tools:
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cid = tool_item.get("call_id", tool_item.get("id", ""))
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cid = tool_item.get("call_id", tool_item.get("id", ""))
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if cid not in added_call_ids:
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if cid not in added_pairs:
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result.append(tool_item)
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result.append(tool_item)
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for cs_item in compaction_summaries:
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for cs_item in compaction_summaries:
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@@ -5037,7 +5032,7 @@ def _antigravity_normalize_context(input_data, model=""):
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while len(result) > _ANTIGRAVITY_MAX_CONTENTS and total_chars > _ANTIGRAVITY_SOFT_CHARS:
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while len(result) > _ANTIGRAVITY_MAX_CONTENTS and total_chars > _ANTIGRAVITY_SOFT_CHARS:
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for i in range(1, len(result) - 1):
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for i in range(1, len(result) - 1):
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if isinstance(result[i], dict) and result[i].get("type") in ("message", "function_call_output"):
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if isinstance(result[i], dict) and result[i].get("type") in ("message",):
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removed = result.pop(i)
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removed = result.pop(i)
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total_chars -= len(json.dumps(removed, ensure_ascii=False))
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total_chars -= len(json.dumps(removed, ensure_ascii=False))
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break
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break
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resp_part["functionResponse"]["id"] = call_id
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resp_part["functionResponse"]["id"] = call_id
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contents.append({"role": "user", "parts": [resp_part]})
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contents.append({"role": "user", "parts": [resp_part]})
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# CRITICAL FIX: Sanitize contents while PRESERVING functionCall -> functionResponse alternation.
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# Google's Gemini API REQUIRES: functionCall (role=model) must be immediately followed by functionResponse (role=user).
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# We NEVER merge, skip, or reorder tool-related messages.
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if OAUTH_PROVIDER.startswith("google") and "claude" not in model.lower():
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if OAUTH_PROVIDER.startswith("google") and "claude" not in model.lower():
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sanitized = []
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sanitized = []
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last_user_text = None
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last_user_text = None
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last_role = None
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for content in contents:
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for content in contents:
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role = content.get("role")
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role = content.get("role")
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parts = [p for p in content.get("parts", []) if isinstance(p, dict)]
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parts = [p for p in content.get("parts", []) if isinstance(p, dict)]
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if not parts:
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if not parts:
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continue
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continue
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# Check if this content has functionCall or functionResponse - these must be preserved
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# Check if this content has functionCall or functionResponse - these MUST be preserved as-is
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has_function_call = any("functionCall" in p for p in parts)
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has_function_call = any("functionCall" in p for p in parts)
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has_function_response = any("functionResponse" in p for p in parts)
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has_function_response = any("functionResponse" in p for p in parts)
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text_key = "\n".join([p.get("text", "") for p in parts if "text" in p]).strip()
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text_key = "\n".join([p.get("text", "") for p in parts if "text" in p]).strip()
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# Skip duplicate user text messages, but NEVER skip function responses
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if role == "user" and text_key and text_key == last_user_text and not has_function_response:
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# Tool calls/responses are NEVER merged or skipped - they must maintain strict order
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if has_function_call or has_function_response:
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sanitized.append({"role": role, "parts": parts})
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continue
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continue
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# CRITICAL FIX: Function calls (model role) and function responses (user role) MUST NOT be merged
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# Google's API requires strict alternation: functionCall (model) -> functionResponse (user)
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# For plain text messages only: skip duplicate consecutive user text
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# Never merge across role boundaries when function calls/responses are involved
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if role == "user" and text_key and text_key == last_user_text:
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if role == last_role and role in ("user", "model") and sanitized and not has_function_call and not has_function_response:
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continue
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# Only merge same-role consecutive text messages without tool content
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# Merge consecutive same-role TEXT-ONLY messages (no tool content)
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if role == last_role and role in ("user", "model") and sanitized:
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last_parts = sanitized[-1].get("parts", [])
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# Only merge if the last message is also text-only (no functionCall/functionResponse)
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last_has_tool = any("functionCall" in p or "functionResponse" in p for p in last_parts)
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if not last_has_tool:
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sanitized[-1].setdefault("parts", []).extend(parts)
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sanitized[-1].setdefault("parts", []).extend(parts)
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else:
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if role == "user" and text_key:
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last_user_text = text_key
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continue
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sanitized.append({"role": role, "parts": parts})
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sanitized.append({"role": role, "parts": parts})
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if role == "user" and text_key:
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if role == "user" and text_key:
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last_user_text = text_key
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last_user_text = text_key
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last_role = role
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last_role = role
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# Trim leading non-user messages (Google expects conversation to start with user)
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# Trim leading non-user messages (Google expects conversation to start with user)
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while sanitized and sanitized[0].get("role") != "user":
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while sanitized and sanitized[0].get("role") != "user":
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sanitized.pop(0)
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sanitized.pop(0)
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