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feat: 跨格式 thinking/reasoning 透传与 Antigravity 适配器增强
- 内部表示层新增 ThinkingBlock，统一 Claude thinking / Gemini thought / OpenAI reasoning_content - Claude/Gemini/OpenAI/OpenAI CLI normalizer 全面支持 thinking 内容的解析、流式处理和跨格式转换 - schema_utils 重写为完整的 JSON Schema 清洗逻辑（$ref 展开、allOf 合并、anyOf 折叠、白名单过滤） - Antigravity envelope 新增模型别名映射、Google Search 注入、thoughtSignature 注入、图像生成配置解析 Close #161
This commit is contained in:
fawney19
@@ -73,10 +73,86 @@ MIN_SIGNATURE_LENGTH = 50 # 与 Antigravity-Manager 对齐
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# ============== Thinking Budget ==============
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THINKING_BUDGET_AUTO_CAP = 24576
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THINKING_BUDGET_DEFAULT_INJECT = 16000
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THINKING_BUDGET_DEFAULT_INJECT = 24576 # 对齐 AM wrapper.rs (was 16000)
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# 包含这些关键字的模型会自动注入 thinkingConfig（如果缺失）
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THINKING_MODELS_AUTO_INJECT_KEYWORDS = ("thinking", "gemini-2.0-pro", "gemini-3-pro")
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# ============== Model Alias Mapping ==============
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# 对齐 AM common_utils.rs: 将预览/别名映射回上游物理模型名
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MODEL_ALIAS_MAP: dict[str, str] = {
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"gemini-3-pro-preview": "gemini-3-pro-high",
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"gemini-3-pro-image-preview": "gemini-3-pro-image",
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"gemini-3-flash-preview": "gemini-3-flash",
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}
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# ============== Google Search (Grounding) ==============
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# 对齐 AM common_utils.rs: 仅 gemini-2.5-flash 支持 googleSearch tool
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WEB_SEARCH_MODEL = "gemini-2.5-flash"
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# 联网工具检测关键字（对齐 AM detects_networking_tool）
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NETWORKING_TOOL_KEYWORDS = frozenset(
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{
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"web_search",
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"google_search",
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"web_search_20250305",
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"google_search_retrieval",
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}
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)
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# ============== Image Generation ==============
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# 上游图像生成模型的固定名称
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IMAGE_GEN_UPSTREAM_MODEL = "gemini-3-pro-image"
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# 模型后缀 → 宽高比映射
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IMAGE_ASPECT_RATIO_SUFFIXES: dict[str, str] = {
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"-21x9": "21:9",
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"-21-9": "21:9",
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"-16x9": "16:9",
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"-16-9": "16:9",
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"-9x16": "9:16",
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"-9-16": "9:16",
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"-4x3": "4:3",
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"-4-3": "4:3",
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"-3x4": "3:4",
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"-3-4": "3:4",
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"-3x2": "3:2",
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"-3-2": "3:2",
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"-2x3": "2:3",
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"-2-3": "2:3",
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"-5x4": "5:4",
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"-5-4": "5:4",
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"-4x5": "4:5",
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"-4-5": "4:5",
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"-1x1": "1:1",
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"-1-1": "1:1",
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}
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# 标准宽高比字符串（用于直接匹配 size 参数）
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STANDARD_ASPECT_RATIOS = frozenset(
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{
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"21:9",
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"16:9",
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"9:16",
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"4:3",
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"3:4",
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"3:2",
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"2:3",
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"5:4",
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"4:5",
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"1:1",
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}
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)
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# 宽高比容差匹配表：(ratio, label)
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ASPECT_RATIO_TABLE: tuple[tuple[float, str], ...] = (
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(21.0 / 9.0, "21:9"),
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(16.0 / 9.0, "16:9"),
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(4.0 / 3.0, "4:3"),
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(3.0 / 4.0, "3:4"),
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(9.0 / 16.0, "9:16"),
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(3.0 / 2.0, "3:2"),
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(2.0 / 3.0, "2:3"),
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(5.0 / 4.0, "5:4"),
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(4.0 / 5.0, "4:5"),
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(1.0, "1:1"),
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)
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# ============== Retry ==============
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RETRY_429_BASE_SECONDS = 5.0
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RETRY_503_BASE_SECONDS = 10.0
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@@ -107,10 +183,15 @@ ANTIGRAVITY_SYSTEM_INSTRUCTION = (
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__all__ = [
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"ANTIGRAVITY_SYSTEM_INSTRUCTION",
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"ASPECT_RATIO_TABLE",
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"DAILY_BASE_URL",
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"DUMMY_THOUGHT_SIGNATURE",
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"HTTP_USER_AGENT",
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"IMAGE_ASPECT_RATIO_SUFFIXES",
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"IMAGE_GEN_UPSTREAM_MODEL",
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"MIN_SIGNATURE_LENGTH",
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"MODEL_ALIAS_MAP",
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"NETWORKING_TOOL_KEYWORDS",
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"PROD_BASE_URL",
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"REQUEST_USER_AGENT",
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"RETRY_429_BASE_SECONDS",
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@@ -119,12 +200,14 @@ __all__ = [
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"RETRY_503_MAX_SECONDS",
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"SANDBOX_BASE_URL",
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"SIGNATURE_ERROR_KEYWORDS",
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"STANDARD_ASPECT_RATIOS",
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"THINKING_BUDGET_AUTO_CAP",
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"THINKING_BUDGET_DEFAULT_INJECT",
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"THINKING_MODELS_AUTO_INJECT_KEYWORDS",
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"URL_UNAVAILABLE_TTL_SECONDS",
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"V1INTERNAL_PATH_TEMPLATE",
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"VERSION_FETCH_URL",
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"WEB_SEARCH_MODEL",
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"get_http_user_agent",
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"parse_version_string",
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"update_user_agent_version",
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@@ -13,6 +13,10 @@ wire format:
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- JSON Schema 禁止字段清洗
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- Antigravity System Instruction 注入
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- Signature 错误检测
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- Model alias mapping（preview → physical）
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- Google Search (grounding) 注入
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- thoughtSignature 注入到 functionCall parts
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- Image generation config 注入（aspectRatio / imageSize）
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"""
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from __future__ import annotations
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@@ -22,20 +26,85 @@ from typing import Any
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from src.services.provider.adapters.antigravity.constants import (
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ANTIGRAVITY_SYSTEM_INSTRUCTION,
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ASPECT_RATIO_TABLE,
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IMAGE_ASPECT_RATIO_SUFFIXES,
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IMAGE_GEN_UPSTREAM_MODEL,
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MODEL_ALIAS_MAP,
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NETWORKING_TOOL_KEYWORDS,
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)
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from src.services.provider.adapters.antigravity.constants import (
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REQUEST_USER_AGENT as ANTIGRAVITY_REQUEST_USER_AGENT,
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)
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from src.services.provider.adapters.antigravity.constants import (
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SIGNATURE_ERROR_KEYWORDS,
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STANDARD_ASPECT_RATIOS,
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THINKING_BUDGET_AUTO_CAP,
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THINKING_BUDGET_DEFAULT_INJECT,
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THINKING_MODELS_AUTO_INJECT_KEYWORDS,
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WEB_SEARCH_MODEL,
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get_http_user_agent,
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)
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from src.services.provider.adapters.antigravity.url_availability import url_availability
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from src.services.provider.request_context import get_selected_base_url
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# ---------------------------------------------------------------------------
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# Key normalization: snake_case → camelCase
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# ---------------------------------------------------------------------------
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# The Gemini normalizer (gemini.py) outputs snake_case keys that mirror protobuf
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# field names (e.g. "generation_config", "function_declarations"). However, the
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# Antigravity v1internal JSON protocol (like the REST Gemini API) uses camelCase
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# for all field names. A mismatch causes downstream processing functions in this
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# module to silently skip keys or create duplicate entries.
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#
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# We normalise once at the entry point of wrap_v1internal_request so that every
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# subsequent helper can safely assume camelCase.
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_TOP_LEVEL_KEY_RENAMES: dict[str, str] = {
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"system_instruction": "systemInstruction",
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"generation_config": "generationConfig",
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"tool_config": "toolConfig",
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# safety_settings 在 wrap_v1internal_request 入口处已 pop，无需映射
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}
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_GENERATION_CONFIG_KEY_RENAMES: dict[str, str] = {
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"max_output_tokens": "maxOutputTokens",
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"stop_sequences": "stopSequences",
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"top_p": "topP",
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"top_k": "topK",
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"thinking_config": "thinkingConfig",
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"response_modalities": "responseModalities",
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"response_mime_type": "responseMimeType",
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}
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def _normalize_to_camel_case(body: dict[str, Any]) -> None:
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"""In-place normalise known Gemini snake_case keys to their camelCase form.
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This must be called **before** any other processing so that all helpers
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in this module can consistently use camelCase lookups.
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"""
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# 1. Top-level keys
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for snake, camel in _TOP_LEVEL_KEY_RENAMES.items():
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if snake in body and camel not in body:
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body[camel] = body.pop(snake)
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# 2. Inside tools: function_declarations → functionDeclarations
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tools = body.get("tools")
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if isinstance(tools, list):
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for tool in tools:
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if isinstance(tool, dict):
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if "function_declarations" in tool and "functionDeclarations" not in tool:
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tool["functionDeclarations"] = tool.pop("function_declarations")
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# 3. Inside generationConfig: normalise sub-keys
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gc = body.get("generationConfig")
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if isinstance(gc, dict):
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for snake, camel in _GENERATION_CONFIG_KEY_RENAMES.items():
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if snake in gc and camel not in gc:
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gc[camel] = gc.pop(snake)
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# ---------------------------------------------------------------------------
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# Request body 预处理工具函数（对齐 AM wrapper.rs / common_utils.rs）
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# ---------------------------------------------------------------------------
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@@ -164,18 +233,26 @@ def _clean_tool_declarations(inner_request: dict[str, Any]) -> None:
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for tool in tools:
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if not isinstance(tool, dict):
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continue
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decls = tool.get("functionDeclarations")
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# 支持 camelCase + snake_case
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decls_key = (
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"functionDeclarations"
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if "functionDeclarations" in tool
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else "function_declarations" if "function_declarations" in tool else None
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)
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if decls_key is None:
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continue
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decls = tool.get(decls_key)
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if not isinstance(decls, list):
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continue
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# 1. 过滤搜索关键字函数
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# 1. 过滤搜索关键字函数（对齐 NETWORKING_TOOL_KEYWORDS）
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decls[:] = [
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d
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for d in decls
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if not (
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isinstance(d, dict)
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and isinstance(d.get("name"), str)
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and d["name"] in ("web_search", "google_search")
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and d["name"] in NETWORKING_TOOL_KEYWORDS
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)
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]
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@@ -203,6 +280,296 @@ def _clean_json_schema(schema: dict[str, Any]) -> None:
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clean_gemini_schema(schema)
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# ---------------------------------------------------------------------------
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# Model alias mapping（对齐 AM common_utils.rs）
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# ---------------------------------------------------------------------------
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def _resolve_model_alias(model: str) -> str:
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"""将预览/别名模型名映射回上游物理模型名。
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对齐 AM common_utils.rs resolve_request_config：
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- gemini-3-pro-preview → gemini-3-pro-high
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- gemini-3-pro-image-preview → gemini-3-pro-image
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- gemini-3-flash-preview → gemini-3-flash
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- 同时剥离 -online 后缀
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"""
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resolved = model.rstrip()
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# 剥离 -online 后缀（联网意图由 tools 检测，不依赖后缀传递到上游）
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resolved = resolved.removesuffix("-online")
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return MODEL_ALIAS_MAP.get(resolved, resolved)
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# ---------------------------------------------------------------------------
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# Google Search (Grounding) 检测与注入（对齐 AM common_utils.rs）
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# ---------------------------------------------------------------------------
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def _detect_networking_tools(inner_request: dict[str, Any]) -> bool:
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"""检测请求中是否包含联网/搜索工具声明。
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对齐 AM common_utils.rs detects_networking_tool，支持多种声明风格：
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1. Claude/Anthropic 直发风格: {"name": "web_search"} / {"type": "web_search_20250305"}
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2. OpenAI 嵌套风格: {"type": "function", "function": {"name": "web_search"}}
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3. Gemini 原生风格: {"functionDeclarations": [{"name": "web_search"}]}
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4. Gemini googleSearch 声明: {"googleSearch": {}}
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"""
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tools = inner_request.get("tools")
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if not isinstance(tools, list):
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return False
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for tool in tools:
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if not isinstance(tool, dict):
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continue
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# 1. 直发风格: name / type 字段
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name = tool.get("name")
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if isinstance(name, str) and name in NETWORKING_TOOL_KEYWORDS:
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return True
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type_ = tool.get("type")
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if isinstance(type_, str) and type_ in NETWORKING_TOOL_KEYWORDS:
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return True
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# 2. OpenAI 嵌套风格
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func = tool.get("function")
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if isinstance(func, dict):
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fn_name = func.get("name")
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if isinstance(fn_name, str) and fn_name in NETWORKING_TOOL_KEYWORDS:
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return True
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# 3. Gemini functionDeclarations 风格（支持 camelCase + snake_case）
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decls = tool.get("functionDeclarations")
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if decls is None:
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decls = tool.get("function_declarations")
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if isinstance(decls, list):
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for decl in decls:
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if isinstance(decl, dict):
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decl_name = decl.get("name")
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if isinstance(decl_name, str) and decl_name in NETWORKING_TOOL_KEYWORDS:
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return True
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# 4. Gemini googleSearch / googleSearchRetrieval 声明
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if tool.get("googleSearch") is not None or tool.get("googleSearchRetrieval") is not None:
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return True
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return False
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def _detect_online_suffix(model: str) -> bool:
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"""检测模型名是否含 -online 后缀（联网意图）。"""
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return model.rstrip().endswith("-online")
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def _inject_google_search_tool(inner_request: dict[str, Any]) -> None:
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"""注入 googleSearch tool 到请求中。
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对齐 AM common_utils.rs inject_google_search_tool：
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- 如果已有 functionDeclarations，跳过（v1internal 不支持混用）
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- 先清理已有的 googleSearch / googleSearchRetrieval
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- 注入 {"googleSearch": {}}
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"""
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tools = inner_request.setdefault("tools", [])
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if not isinstance(tools, list):
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inner_request["tools"] = [{"googleSearch": {}}]
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return
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# 如果已有 functionDeclarations，不注入（v1internal 不支持混用 search 和 functions）
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has_functions = any(
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isinstance(t, dict) and ("functionDeclarations" in t or "function_declarations" in t)
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for t in tools
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)
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if has_functions:
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return
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# 清理已存在的 googleSearch / googleSearchRetrieval（避免重复）
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tools[:] = [
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t
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for t in tools
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if not (isinstance(t, dict) and ("googleSearch" in t or "googleSearchRetrieval" in t))
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]
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# 注入
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tools.append({"googleSearch": {}})
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# ---------------------------------------------------------------------------
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# thoughtSignature 注入到 functionCall parts（对齐 AM wrapper.rs）
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# ---------------------------------------------------------------------------
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def _inject_thought_signatures(inner_request: dict[str, Any], session_id: str | None) -> None:
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"""为 functionCall parts 注入 thoughtSignature（从 session signature cache）。
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对齐 AM wrapper.rs：当 functionCall part 缺少 thoughtSignature 时，
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从 session cache 中恢复签名，确保 thinking 模型的多轮 tool call 连续性。
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"""
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if not session_id:
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return
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try:
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from src.services.provider.adapters.antigravity.signature_cache import signature_cache
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except Exception:
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return
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cached_sig = signature_cache.get_session_signature(session_id)
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if not cached_sig:
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return
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contents = inner_request.get("contents")
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if not isinstance(contents, list):
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return
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for content in contents:
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if not isinstance(content, dict):
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continue
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parts = content.get("parts")
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if not isinstance(parts, list):
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continue
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for part in parts:
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if not isinstance(part, dict):
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continue
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# 只处理有 functionCall 且缺少 thoughtSignature 的 part
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if "functionCall" in part and part.get("thoughtSignature") is None:
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part["thoughtSignature"] = cached_sig
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# ---------------------------------------------------------------------------
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# Image Generation Config（对齐 AM common_utils.rs parse_image_config_with_params）
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# ---------------------------------------------------------------------------
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|
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||||
def _calculate_aspect_ratio(size: str) -> str:
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"""从 "WIDTHxHEIGHT" 或 "W:H" 字符串计算宽高比。
|
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|
||||
对齐 AM common_utils.rs calculate_aspect_ratio_from_size：
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1. 先检查是否已是标准比例字符串 (如 "16:9")
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2. 解析 WIDTHxHEIGHT 并容差匹配
|
||||
3. 默认返回 "1:1"
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||||
"""
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if size in STANDARD_ASPECT_RATIOS:
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||||
return size
|
||||
|
||||
if "x" in size:
|
||||
try:
|
||||
w_str, h_str = size.split("x", 1)
|
||||
width, height = float(w_str), float(h_str)
|
||||
if width > 0 and height > 0:
|
||||
ratio = width / height
|
||||
for target_ratio, label in ASPECT_RATIO_TABLE:
|
||||
if abs(ratio - target_ratio) < 0.05:
|
||||
return label
|
||||
except (ValueError, ZeroDivisionError):
|
||||
pass
|
||||
|
||||
return "1:1"
|
||||
|
||||
|
||||
def _parse_image_config(
|
||||
model: str,
|
||||
inner_request: dict[str, Any],
|
||||
) -> tuple[dict[str, Any], str]:
|
||||
"""解析图像生成配置，返回 (imageConfig, clean_model_name)。
|
||||
|
||||
对齐 AM common_utils.rs parse_image_config_with_params + resolve_request_config：
|
||||
1. 从请求体中提取 OpenAI 风格 size / quality 参数（优先）
|
||||
2. 回退到模型后缀解析 (如 -16x9, -4k)
|
||||
3. 合并请求体中的 generationConfig.imageConfig（如果存在）
|
||||
4. 上游模型固定为 "gemini-3-pro-image"
|
||||
"""
|
||||
# 提取 OpenAI 风格参数（可能由跨格式转换层注入到请求根部）
|
||||
size = inner_request.pop("size", None)
|
||||
quality = inner_request.pop("quality", None)
|
||||
if not isinstance(size, str):
|
||||
size = None
|
||||
if not isinstance(quality, str):
|
||||
quality = None
|
||||
|
||||
# --- 解析 aspectRatio ---
|
||||
aspect_ratio = "1:1"
|
||||
if size:
|
||||
aspect_ratio = _calculate_aspect_ratio(size)
|
||||
else:
|
||||
lower_model = model.lower()
|
||||
for suffix, ratio in IMAGE_ASPECT_RATIO_SUFFIXES.items():
|
||||
if suffix in lower_model:
|
||||
aspect_ratio = ratio
|
||||
break
|
||||
|
||||
config: dict[str, Any] = {"aspectRatio": aspect_ratio}
|
||||
|
||||
# --- 解析 imageSize ---
|
||||
if quality:
|
||||
q_lower = quality.lower()
|
||||
if q_lower in ("hd", "4k"):
|
||||
config["imageSize"] = "4K"
|
||||
elif q_lower in ("medium", "2k"):
|
||||
config["imageSize"] = "2K"
|
||||
elif q_lower in ("standard", "1k"):
|
||||
config["imageSize"] = "1K"
|
||||
else:
|
||||
lower_model = model.lower()
|
||||
if "-4k" in lower_model or "-hd" in lower_model:
|
||||
config["imageSize"] = "4K"
|
||||
elif "-2k" in lower_model:
|
||||
config["imageSize"] = "2K"
|
||||
|
||||
# --- 合并请求体中已有的 imageConfig（body 可以覆盖除 imageSize 降级外的字段） ---
|
||||
gen_config = inner_request.get("generationConfig")
|
||||
if isinstance(gen_config, dict):
|
||||
body_image_config = gen_config.get("imageConfig")
|
||||
if isinstance(body_image_config, dict):
|
||||
for key, value in body_image_config.items():
|
||||
# 防止 body 降级 inferred imageSize（对齐 AM 的 shield 逻辑）
|
||||
if (
|
||||
key == "imageSize"
|
||||
and (value == "1K" or value is None)
|
||||
and "imageSize" in config
|
||||
):
|
||||
continue
|
||||
config[key] = value
|
||||
|
||||
return config, IMAGE_GEN_UPSTREAM_MODEL
|
||||
|
||||
|
||||
def _apply_image_gen_config(inner_request: dict[str, Any], image_config: dict[str, Any]) -> None:
|
||||
"""将 imageConfig 应用到请求的 generationConfig 中。
|
||||
|
||||
对齐 AM wrapper.rs 的图像生成处理：
|
||||
- 移除 tools / systemInstruction
|
||||
- 确保 contents 中每个 content 有 role 字段
|
||||
- 清理 generationConfig 中与图像生成冲突的字段
|
||||
- 注入 imageConfig
|
||||
- 处理图像思维模式（默认 disabled）
|
||||
"""
|
||||
# 移除不兼容字段（_normalize_to_camel_case 已统一 key，仅需 camelCase）
|
||||
for key in ("tools", "toolConfig", "systemInstruction"):
|
||||
inner_request.pop(key, None)
|
||||
|
||||
# 确保 contents 中每个 content 有 role 字段
|
||||
contents = inner_request.get("contents")
|
||||
if isinstance(contents, list):
|
||||
for content in contents:
|
||||
if isinstance(content, dict) and "role" not in content:
|
||||
content["role"] = "user"
|
||||
|
||||
# 清理 generationConfig
|
||||
gen_config = inner_request.setdefault("generationConfig", {})
|
||||
if not isinstance(gen_config, dict):
|
||||
gen_config = {}
|
||||
inner_request["generationConfig"] = gen_config
|
||||
|
||||
# 移除与图像生成冲突的字段（_normalize_to_camel_case 已统一 key）
|
||||
for key in ("responseMimeType", "responseModalities"):
|
||||
gen_config.pop(key, None)
|
||||
|
||||
# 注入 imageConfig
|
||||
gen_config["imageConfig"] = image_config
|
||||
|
||||
# 图像思维模式：默认 disabled（对齐 AM wrapper.rs image_thinking_mode）
|
||||
gen_config["thinkingConfig"] = {"includeThoughts": False}
|
||||
|
||||
|
||||
def _compact_contents(inner_request: dict[str, Any]) -> None:
|
||||
"""Strip invalid parts, drop empty contents, merge consecutive same-role.
|
||||
|
||||
@@ -345,57 +712,89 @@ def wrap_v1internal_request(
|
||||
) -> dict[str, Any]:
|
||||
"""Wrap a GeminiRequest into Antigravity V1InternalRequest.
|
||||
|
||||
处理流程（对齐 AM wrapper.rs）：
|
||||
1. 移除 model（移到顶层）
|
||||
2. 移除 safetySettings（v1internal 不支持）
|
||||
3. 深度清理 [undefined] 字符串
|
||||
4. Claude model tool ID 注入（图像生成模型跳过）
|
||||
5. Thinking budget 处理
|
||||
6. 工具声明清洗（图像生成模型跳过）
|
||||
7. System Instruction 注入（图像生成模型跳过）
|
||||
8. 清理空 parts 的 contents 并合并连续同角色条目
|
||||
9. 注入 sessionId（对齐 CLIProxyAPI）
|
||||
10. 构建 v1internal 信封
|
||||
处理流程（对齐 AM wrapper.rs + common_utils.rs）：
|
||||
1. 移除 model / safetySettings
|
||||
2. 深度清理 [undefined] 字符串
|
||||
3. 模型别名映射（preview → physical）
|
||||
4. 联网检测 + -online 后缀检测
|
||||
5. 图像生成检测 + imageConfig 解析
|
||||
6. Claude model tool ID 注入
|
||||
7. thoughtSignature 注入到 functionCall parts
|
||||
8. Thinking budget 处理
|
||||
9. 工具声明清洗
|
||||
10. Google Search 注入（联网请求）
|
||||
11. System Instruction 注入
|
||||
12. 清理空 parts 的 contents 并合并连续同角色条目
|
||||
13. 注入 sessionId
|
||||
14. 构建 v1internal 信封
|
||||
"""
|
||||
from src.api.handlers.gemini.image_gen import is_image_gen_model
|
||||
|
||||
inner_request = dict(gemini_request)
|
||||
inner_request.pop("model", None)
|
||||
inner_request.pop("safetySettings", None)
|
||||
inner_request.pop("safety_settings", None)
|
||||
|
||||
is_image_gen = is_image_gen_model(model)
|
||||
# 0. 统一 snake_case → camelCase（Gemini normalizer 输出 snake_case，但
|
||||
# v1internal 以及本模块所有 helper 均使用 camelCase）
|
||||
_normalize_to_camel_case(inner_request)
|
||||
|
||||
# 1. 深度清理 [undefined]
|
||||
_deep_clean_undefined(inner_request)
|
||||
|
||||
if not is_image_gen:
|
||||
# 2. Claude tool ID 注入
|
||||
_inject_claude_tool_ids_request(inner_request, model)
|
||||
# 2. 模型别名映射（对齐 AM common_utils.rs）
|
||||
has_online_suffix = _detect_online_suffix(model)
|
||||
final_model = _resolve_model_alias(model)
|
||||
|
||||
# 3. Thinking budget 处理
|
||||
_process_thinking_budget(inner_request, model)
|
||||
# 3. 联网检测（对齐 AM：-online 后缀或客户端声明了联网工具）
|
||||
has_networking = has_online_suffix or _detect_networking_tools(inner_request)
|
||||
|
||||
# 4. 图像生成检测 + imageConfig 解析
|
||||
is_image_gen = is_image_gen_model(final_model)
|
||||
|
||||
if is_image_gen:
|
||||
# 解析 imageConfig 并确定上游模型名
|
||||
image_config, final_model = _parse_image_config(final_model, inner_request)
|
||||
_apply_image_gen_config(inner_request, image_config)
|
||||
request_type = "image_gen"
|
||||
# 图像生成不需要联网
|
||||
has_networking = False
|
||||
else:
|
||||
# 5. Claude tool ID 注入
|
||||
_inject_claude_tool_ids_request(inner_request, final_model)
|
||||
|
||||
# 6. thoughtSignature 注入到 functionCall parts（对齐 AM wrapper.rs）
|
||||
session_id = inner_request.get("sessionId")
|
||||
if not isinstance(session_id, str):
|
||||
# 提前生成 sessionId 用于 signature 查找
|
||||
session_id = _generate_stable_session_id(inner_request)
|
||||
inner_request["sessionId"] = session_id
|
||||
_inject_thought_signatures(inner_request, session_id)
|
||||
|
||||
# 7. Thinking budget 处理（图像生成和普通请求都需要）
|
||||
_process_thinking_budget(inner_request, final_model)
|
||||
|
||||
if not is_image_gen:
|
||||
# 4. 工具声明清洗
|
||||
# 8. 工具声明清洗
|
||||
_clean_tool_declarations(inner_request)
|
||||
|
||||
# 5. System Instruction 注入
|
||||
_inject_system_instruction(inner_request)
|
||||
else:
|
||||
# 图像生成模型：对齐 AM wrapper.rs，移除不兼容字段
|
||||
inner_request.pop("tools", None)
|
||||
inner_request.pop("toolConfig", None)
|
||||
inner_request.pop("tool_config", None)
|
||||
inner_request.pop("systemInstruction", None)
|
||||
inner_request.pop("system_instruction", None)
|
||||
request_type = "image_gen"
|
||||
# 9. Google Search 注入（对齐 AM common_utils.rs）
|
||||
if has_networking:
|
||||
# 仅 gemini-2.5-flash 支持 googleSearch（对齐 AM：其他模型降级到 2.5-flash）
|
||||
if final_model != WEB_SEARCH_MODEL:
|
||||
final_model = WEB_SEARCH_MODEL
|
||||
_inject_google_search_tool(inner_request)
|
||||
request_type = "web_search"
|
||||
|
||||
# 6. 清理空 parts 的 contents 并合并连续同角色条目
|
||||
# 跨格式转换（如 Responses API reasoning 块）可能产生空 parts 的 content，
|
||||
# Gemini API 要求每个 content 至少有一个有效 part，并且严格交替 user/model 角色。
|
||||
# 10. System Instruction 注入
|
||||
_inject_system_instruction(inner_request)
|
||||
|
||||
# 11. 清理空 parts 的 contents 并合并连续同角色条目
|
||||
# 跨格式转换（如 Responses API reasoning 块）可能产生空 parts 的 content，
|
||||
# Gemini API 要求每个 content 至少有一个有效 part，并且严格交替 user/model 角色。
|
||||
_compact_contents(inner_request)
|
||||
|
||||
# 7. 注入 sessionId（对齐 CLIProxyAPI/sub2api）
|
||||
# 12. 注入 sessionId（如果还没有的话）
|
||||
if "sessionId" not in inner_request:
|
||||
inner_request["sessionId"] = _generate_stable_session_id(inner_request)
|
||||
|
||||
@@ -403,7 +802,7 @@ def wrap_v1internal_request(
|
||||
"project": project_id,
|
||||
"requestId": f"agent-{uuid.uuid4()}",
|
||||
"request": inner_request,
|
||||
"model": model,
|
||||
"model": final_model,
|
||||
"userAgent": ANTIGRAVITY_REQUEST_USER_AGENT,
|
||||
"requestType": request_type,
|
||||
}
|
||||
|
||||
Reference in New Issue
Block a user