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use serde_json::{json, Value};
/// 包装请求体为 v1internal 格式
pub fn wrap_request(
body: &Value,
project_id: &str,
mapped_model: &str,
account_id: Option<&str>,
session_id: Option<&str>,
token: Option<&crate::proxy::token_manager::ProxyToken>, // [NEW] 动态规格注入
) -> Value {
// 优先使用传入的 mapped_model,其次尝试从 body 获取
let original_model = body
.get("model")
.and_then(|v| v.as_str())
.unwrap_or(mapped_model);
// 如果 mapped_model 是空的,则使用 original_model
let final_model_name = if !mapped_model.is_empty() {
mapped_model
} else {
original_model
};
// [ADDED v4.1.24] 计算 message_count 供 requestId 使用
let message_count = body.get("contents")
.and_then(|c| c.as_array())
.map(|a| a.len())
.unwrap_or(1);
// 复制 body 以便修改
let mut inner_request = body.clone();
// 深度清理 [undefined] 字符串 (Cherry Studio 等客户端常见注入)
crate::proxy::mappers::common_utils::deep_clean_undefined(&mut inner_request, 0);
// [FIX #1522] Inject dummy IDs for Claude models in Gemini protocol
// Google v1internal requires 'id' for tool calls when the model is Claude,
// even though the standard Gemini protocol doesn't have it.
let is_target_claude = final_model_name.to_lowercase().contains("claude");
if let Some(contents) = inner_request
.get_mut("contents")
.and_then(|c| c.as_array_mut())
{
for content in contents {
// 每条消息维护独立的计数器,确保 Call 和对应的 Response 生成相同的 ID (兜底规则)
let mut name_counters: std::collections::HashMap<String, usize> =
std::collections::HashMap::new();
if let Some(parts) = content.get_mut("parts").and_then(|p| p.as_array_mut()) {
for part in parts {
if let Some(obj) = part.as_object_mut() {
// 1. 处理 functionCall (Assistant 请求调用工具)
if let Some(fc) = obj.get_mut("functionCall") {
if fc.get("id").is_none() && is_target_claude {
let name =
fc.get("name").and_then(|n| n.as_str()).unwrap_or("unknown");
let count = name_counters.entry(name.to_string()).or_insert(0);
let call_id = format!("call_{}_{}", name, count);
*count += 1;
fc.as_object_mut()
.unwrap()
.insert("id".to_string(), json!(call_id));
tracing::debug!("[Gemini-Wrap] Request stage: Injected missing call_id '{}' for Claude model", call_id);
}
}
// 2. 处理 functionResponse (User 回复工具结果)
if let Some(fr) = obj.get_mut("functionResponse") {
if fr.get("id").is_none() && is_target_claude {
// 启发:如果客户端(如 OpenCode)在响应时没带 ID,说明它收到响应时就没 ID。
// 我们在这里生成的 ID 必须与我们在 inject_ids_to_response 中注入响应的 ID 一致。
let name =
fr.get("name").and_then(|n| n.as_str()).unwrap_or("unknown");
let count = name_counters.entry(name.to_string()).or_insert(0);
let call_id = format!("call_{}_{}", name, count);
*count += 1;
fr.as_object_mut()
.unwrap()
.insert("id".to_string(), json!(call_id));
tracing::debug!("[Gemini-Wrap] Request stage: Injected synced response_id '{}' for Claude model", call_id);
}
}
// 3. 处理 thoughtSignature
if obj.contains_key("functionCall") && obj.get("thoughtSignature").is_none()
{
if let Some(s_id) = session_id {
if let Some(sig) = crate::proxy::SignatureCache::global()
.get_session_signature(s_id)
{
obj.insert("thoughtSignature".to_string(), json!(sig));
tracing::debug!("[Gemini-Wrap] Injected signature (len: {}) for session: {}", sig.len(), s_id);
} else {
// [FIX #2167] Session 缓存为空时对 flash 模型注入哨兵值
// Flash 模型如果不提供任何签名,Gemini API 会拒绝 functionCall
let is_flash = final_model_name.to_lowercase().contains("gemini-3-flash")
|| final_model_name.to_lowercase().contains("gemini-3.1-flash");
if is_flash {
obj.insert("thoughtSignature".to_string(), json!("skip_thought_signature_validator"));
tracing::debug!("[Gemini-Wrap] [FIX #2167] Injected sentinel signature for flash model (no session cache)");
}
}
}
}
}
}
}
}
}
// [FIX Issue #1355] Gemini Flash thinking budget capping
// [CONFIGURABLE] 现在改为遵循全局 Thinking Budget 配置
// [FIX #1557] Also apply to Pro/Thinking models to ensure budget processing
// [FIX #1557] Auto-inject thinkingConfig if missing for these models
let lower_model = final_model_name.to_lowercase();
if lower_model.contains("flash")
|| lower_model.contains("pro")
|| lower_model.contains("thinking")
{
// [NEW] Extract OpenAI-style max_tokens before mutably borrowing gen_config
let req_max_tokens = inner_request.get("max_tokens").and_then(|v| v.as_u64());
// Determine model family and capability beforehand to avoid borrow checker conflicts
let is_claude = lower_model.contains("claude");
let is_preview = lower_model.contains("preview");
let should_inject = lower_model.contains("thinking")
|| (lower_model.contains("gemini-2.0-pro") && !is_preview)
|| (lower_model.contains("gemini-3-pro") && !is_preview)
|| (lower_model.contains("gemini-3.1-pro") && !is_preview);
if should_inject {
// Scope for borrowing inner_request/gen_config
let mut has_thinking = false;
if is_claude {
has_thinking = inner_request.get("thinking").is_some();
} else {
if let Some(gc) = inner_request.get("generationConfig").and_then(|v| v.as_object()) {
has_thinking = gc.get("thinkingConfig").is_some();
}
}
if !has_thinking {
tracing::debug!(
"[Gemini-Wrap] Auto-injecting default thinking for {}",
final_model_name
);
// [FIX] 统一注入到 generationConfig.thinkingConfig
// 使用动态规格提供的默认预算
let default_budget = crate::proxy::model_specs::get_thinking_budget(final_model_name, token);
let gen_config = inner_request
.as_object_mut()
.unwrap()
.entry("generationConfig")
.or_insert(json!({}))
.as_object_mut()
.unwrap();
gen_config.insert(
"thinkingConfig".to_string(),
json!({
"includeThoughts": true,
"thinkingBudget": default_budget
}),
);
}
}
// Re-acquire gen_config to satisfy borrow checker and scope requirements for later logic
let gen_config = inner_request
.as_object_mut()
.unwrap()
.entry("generationConfig")
.or_insert(json!({}))
.as_object_mut()
.unwrap();
// [ADDED v4.1.24] Inject topK=40 and topP=1.0 if not present to match official client
if !gen_config.contains_key("topK") {
gen_config.insert("topK".to_string(), json!(40));
}
if !gen_config.contains_key("topP") {
gen_config.insert("topP".to_string(), json!(1.0));
}
// [FIX] Convert v1beta thinkingLevel (string) to v1internal thinkingBudget (number).
// Clients (e.g. OpenClaw, Cline) may send thinkingLevel which v1internal does not accept,
// causing 400 INVALID_ARGUMENT. Convert before any budget processing below.
if let Some(thinking_config) = gen_config.get_mut("thinkingConfig") {
if let Some(level) = thinking_config.get("thinkingLevel").and_then(|v| v.as_str()).map(|s| s.to_uppercase()) {
let thinking_budget_cap = crate::proxy::model_specs::get_thinking_budget(final_model_name, token);
let budget: i64 = match level.as_str() {
"NONE" => 0,
"LOW" => (thinking_budget_cap / 4).max(4096) as i64,
"MEDIUM" => (thinking_budget_cap / 2).max(8192) as i64,
"HIGH" => thinking_budget_cap as i64,
_ => (thinking_budget_cap / 2).max(8192) as i64, // safe default
};
tracing::info!(
"[Gemini-Wrap] Converting thinkingLevel '{}' to thinkingBudget {}",
level, budget
);
if let Some(tc) = thinking_config.as_object_mut() {
tc.remove("thinkingLevel");
tc.insert("thinkingBudget".to_string(), json!(budget));
}
}
}
if let Some(thinking_config) = gen_config.get_mut("thinkingConfig") {
if let Some(budget_val) = thinking_config.get("thinkingBudget") {
if let Some(budget_i64) = budget_val.as_i64() {
// [NEW] -1 indicates native dynamic mode, skip capping
if budget_i64 != -1 {
let budget = budget_i64 as u64;
let thinking_budget_cap = crate::proxy::model_specs::get_thinking_budget(final_model_name, token);
let tb_config = crate::proxy::config::get_thinking_budget_config();
let final_budget = match tb_config.mode {
crate::proxy::config::ThinkingBudgetMode::Passthrough => budget,
crate::proxy::config::ThinkingBudgetMode::Custom => {
let val = tb_config.custom_value as u64;
let is_limited = (final_model_name.contains("gemini")
|| final_model_name.contains("thinking"))
&& !final_model_name.contains("-image");
if is_limited && val > thinking_budget_cap {
thinking_budget_cap
} else {
val
}
}
crate::proxy::config::ThinkingBudgetMode::Auto => {
let is_limited = (final_model_name.contains("gemini")
|| final_model_name.contains("thinking"))
&& !final_model_name.contains("-image");
if is_limited && budget > thinking_budget_cap {
thinking_budget_cap
} else {
budget
}
}
crate::proxy::config::ThinkingBudgetMode::Adaptive => budget,
};
if final_budget != budget {
thinking_config["thinkingBudget"] = json!(final_budget);
}
}
}
}
}
// [FIX #1747] Ensure max_tokens (maxOutputTokens) is greater than thinking_budget
// Google v1internal requires maxOutputTokens > thinkingBudget.
// [FIX #1825] Handle adaptive fallback (incl. -1 and thinkingLevel)
let thinking_config_opt = gen_config.get("thinkingConfig");
let is_adaptive = thinking_config_opt.map_or(false, |t| {
t.get("thinkingLevel").is_some() || t.get("thinkingBudget").and_then(|v| v.as_i64()) == Some(-1)
}) || (thinking_config_opt.and_then(|t| t.get("thinkingBudget").and_then(|v| v.as_u64())) == Some(32768) && is_claude);
if let Some(thinking_config) = gen_config.get("thinkingConfig") {
let budget_opt = thinking_config.get("thinkingBudget").and_then(|v| v.as_i64());
// For adaptive or dynamic mode, we only need to ensure max tokens is large.
// For fixed budget, we must satisfy maxOutputTokens > thinkingBudget.
let current_max = gen_config
.get("maxOutputTokens")
.and_then(|v| v.as_u64())
.or(req_max_tokens);
if is_adaptive {
if current_max.map_or(true, |m| m < 131072) {
gen_config.insert("maxOutputTokens".to_string(), json!(131072));
}
} else if let Some(budget_i64) = budget_opt {
if budget_i64 > 0 {
let budget = budget_i64 as u64;
let min_required_max = budget + 8192;
if current_max.map_or(true, |m| m <= budget) {
tracing::info!(
"[Gemini-Wrap] Bumping maxOutputTokens from {:?} to {} to satisfy thinkingBudget ({})",
current_max, min_required_max, budget
);
gen_config.insert("maxOutputTokens".to_string(), json!(min_required_max));
}
}
}
}
}
// [NEW] 按模型对 maxOutputTokens 进行三层限额 (Dynamic > Static Default > 65535)
// 修复: gemini-cli 等客户端发送的 131072 超过部分模型支持的上限,导致 v1internal 返回 400 INVALID_ARGUMENT
{
let final_cap = crate::proxy::model_specs::get_max_output_tokens(final_model_name, token);
let gen_config = inner_request
.as_object_mut()
.unwrap()
.entry("generationConfig")
.or_insert(serde_json::json!({}))
.as_object_mut()
.unwrap();
if let Some(current) = gen_config.get("maxOutputTokens").and_then(|v| v.as_u64()) {
if current > final_cap {
tracing::debug!(
"[Gemini-Wrap] Capped maxOutputTokens from {} to {} for model {}",
current, final_cap, final_model_name
);
gen_config.insert("maxOutputTokens".to_string(), serde_json::json!(final_cap));
}
}
}
// This caused upstream to return empty/invalid responses, leading to 'NoneType' object has no attribute 'strip' in Python clients.
// relying on upstream defaults or user provided values is safer.
// 提取 tools 列表以进行联网探测 (Gemini 风格可能是嵌套的)
let tools_val: Option<Vec<Value>> = inner_request
.get("tools")
.and_then(|t| t.as_array())
.map(|arr| arr.clone());
// [FIX] Extract OpenAI-compatible image parameters from root (for gemini-3-pro-image)
let size = body.get("size").and_then(|v| v.as_str());
let quality = body.get("quality").and_then(|v| v.as_str());
let image_size = body.get("imageSize").and_then(|v| v.as_str()); // [NEW] Direct imageSize support
// Use shared grounding/config logic
let config = crate::proxy::mappers::common_utils::resolve_request_config(
original_model,
final_model_name,
&tools_val,
size, // [FIX] Pass size parameter
quality, // [FIX] Pass quality parameter
image_size, // [NEW] Pass direct imageSize parameter
Some(body), // [NEW] Pass request body for imageConfig parsing
);
// Clean tool declarations (remove forbidden Schema fields like multipleOf, and remove redundant search decls)
if let Some(tools) = inner_request.get_mut("tools") {
if let Some(tools_arr) = tools.as_array_mut() {
for tool in tools_arr {
if let Some(decls) = tool.get_mut("functionDeclarations") {
if let Some(decls_arr) = decls.as_array_mut() {
// 1. 过滤掉联网关键字函数
decls_arr.retain(|decl| {
if let Some(name) = decl.get("name").and_then(|v| v.as_str()) {
if name == "web_search" || name == "google_search" {
return false;
}
}
true
});
// 2. 清洗剩余 Schema
// [FIX] Gemini CLI 使用 parametersJsonSchema,而标准 Gemini API 使用 parameters
// 需要将 parametersJsonSchema 重命名为 parameters
for decl in decls_arr {
// 检测并转换字段名
if let Some(decl_obj) = decl.as_object_mut() {
// 如果存在 parametersJsonSchema,将其重命名为 parameters
if let Some(params_json_schema) =
decl_obj.remove("parametersJsonSchema")
{
let mut params = params_json_schema;
crate::proxy::common::json_schema::clean_json_schema(
&mut params,
);
decl_obj.insert("parameters".to_string(), params);
} else if let Some(params) = decl_obj.get_mut("parameters") {
// 标准 parameters 字段
crate::proxy::common::json_schema::clean_json_schema(params);
}
}
}
}
}
}
}
}
tracing::debug!(
"[Debug] Gemini Wrap: original='{}', mapped='{}', final='{}', type='{}'",
original_model,
final_model_name,
config.final_model,
config.request_type
);
// Inject googleSearch tool if needed
if config.inject_google_search {
// [NEW] 阶段 7.3: 如果是 WebSearch 类型,注入官方特定属性 (maxResultCount: 5)
if config.request_type == "web_search" {
if let Some(obj) = inner_request.as_object_mut() {
let tools_entry = obj.entry("tools").or_insert_with(|| json!([]));
if let Some(tools_arr) = tools_entry.as_array_mut() {
tools_arr.push(json!({
"googleSearch": {
"enhancedContent": {
"imageSearch": {
"maxResultCount": 5
}
}
}
}));
}
}
} else {
crate::proxy::mappers::common_utils::inject_google_search_tool(&mut inner_request, Some(&config.final_model));
}
}
// Inject imageConfig if present (for image generation models)
if let Some(image_config) = config.image_config {
if let Some(obj) = inner_request.as_object_mut() {
// 1. Filter tools: remove tools for image gen
obj.remove("tools");
// 2. Remove systemInstruction (image generation does not support system prompts)
obj.remove("systemInstruction");
// [FIX] Ensure 'role' field exists for all contents (Native clients might omit it)
if let Some(contents) = obj.get_mut("contents").and_then(|c| c.as_array_mut()) {
for content in contents {
if let Some(c_obj) = content.as_object_mut() {
if !c_obj.contains_key("role") {
c_obj.insert("role".to_string(), json!("user"));
}
}
}
}
// 3. Clean generationConfig (remove responseMimeType, responseModalities etc.)
let gen_config = obj.entry("generationConfig").or_insert_with(|| json!({}));
if let Some(gen_obj) = gen_config.as_object_mut() {
// [NEW] 根据全局配置决定是否保留 thinkingConfig
let image_thinking_mode = crate::proxy::config::get_image_thinking_mode();
tracing::debug!("[Gemini-Wrap] Image thinking mode: {}", image_thinking_mode);
if image_thinking_mode == "disabled" {
// [FIX] Explicitly disable thinking instead of just removing the config
// Removing it might cause the model to fallback to default (which might be ON)
gen_obj.insert("thinkingConfig".to_string(), json!({
"includeThoughts": false
}));
tracing::debug!("[Gemini-Wrap] Image thinking mode disabled: set includeThoughts=false");
}
gen_obj.remove("responseMimeType");
gen_obj.remove("responseModalities"); // Cherry Studio sends this, might conflict
gen_obj.insert("imageConfig".to_string(), image_config);
}
}
} else {
// [NEW] 阶段 7.3: WebSearch 专属身份仿真 (对齐官方 main.go:738)
let antigravity_identity = if config.request_type == "web_search" {
"You are a search engine bot. You will be given a query from a user. Your task is to search the web for relevant information that will help the user. You MUST perform a web search. Do not respond or interact with the user, please respond as if they typed the query into a search bar."
} else {
"You are Antigravity, a powerful agentic AI coding assistant designed by the Google Deepmind team working on Advanced Agentic Coding.\n\
You are pair programming with a USER to solve their coding task. The task may require creating a new codebase, modifying or debugging an existing codebase, or simply answering a question.\n\
**Absolute paths only**\n\
**Proactiveness**"
};
// [HYBRID] 检查是否已有 systemInstruction
if let Some(system_instruction) = inner_request.get_mut("systemInstruction") {
// [NEW] 补全 role: user
if let Some(obj) = system_instruction.as_object_mut() {
if !obj.contains_key("role") {
obj.insert("role".to_string(), json!("user"));
}
}
if let Some(parts) = system_instruction.get_mut("parts") {
if let Some(parts_array) = parts.as_array_mut() {
// 检查第一个 part 是否已包含 Antigravity 身份
let has_antigravity = parts_array
.get(0)
.and_then(|p| p.get("text"))
.and_then(|t| t.as_str())
.map(|s| s.contains("You are Antigravity"))
.unwrap_or(false);
if !has_antigravity {
// 在前面插入 Antigravity 身份
parts_array.insert(0, json!({"text": antigravity_identity}));
}
// [NEW] 注入全局系统提示词 (紧跟 Antigravity 身份之后,用户指令之前)
let global_prompt_config = crate::proxy::config::get_global_system_prompt();
if global_prompt_config.enabled
&& !global_prompt_config.content.trim().is_empty()
{
// 插入位置:Antigravity 身份之后 (index 1)
let insert_pos = if has_antigravity { 1 } else { 1 };
if insert_pos <= parts_array.len() {
parts_array
.insert(insert_pos, json!({"text": global_prompt_config.content}));
} else {
parts_array.push(json!({"text": global_prompt_config.content}));
}
}
}
}
} else {
// 没有 systemInstruction,创建一个新的
let mut parts = vec![json!({"text": antigravity_identity})];
// [NEW] 注入全局系统提示词
let global_prompt_config = crate::proxy::config::get_global_system_prompt();
if global_prompt_config.enabled && !global_prompt_config.content.trim().is_empty() {
parts.push(json!({"text": global_prompt_config.content}));
}
inner_request["systemInstruction"] = json!({
"role": "user",
"parts": parts
});
}
}
// [ADDED v4.1.24] 扩展 toolConfig 到 VALIDATED 模式
if inner_request.get("tools").is_some() && !inner_request.get("toolConfig").is_some() {
inner_request["toolConfig"] = json!({
"functionCallingConfig": { "mode": "VALIDATED" }
});
}
// [ADDED v4.1.24] 注入基于账号的稳定 sessionId
if let Some(account_id_str) = account_id {
inner_request["sessionId"] = json!(crate::proxy::common::session::derive_session_id(account_id_str));
}
let sid = session_id.unwrap_or("default");
// [NEW] 1. 深度对齐 requestId 格式 (官方格式: agent/{timestamp_ms}/{random_hex_8bytes})
// 每次请求生成完全唯一的 ID,避免重试时的幂等性冲突导致 Google 返回旧缓存
let timestamp_ms = chrono::Utc::now().timestamp_millis();
let random_hex = &uuid::Uuid::new_v4().simple().to_string()[..8]; // 移除对外部 hex crate 的依赖
let official_request_id = format!("agent/{}/{}", timestamp_ms, random_hex);
// [NEW] 2. 动态 userAgent 仿真 (支持 jetski)
// 根据账号属性或域名判断。Go Worker 中企业/GCP 账号通常使用 jetski 指纹。
let is_enterprise = if let Some(t) = token {
!t.email.ends_with("@gmail.com") && !t.email.ends_with("@googlemail.com")
} else {
false
};
// [NEW] 阶段 7.2: 动态 IDEType 指纹对齐
let official_ide_type = if is_enterprise { "JETSKI" } else { "ANTIGRAVITY" };
let official_user_agent = if is_enterprise { "jetski" } else { "antigravity" };
// [NEW] 如果是 loadCodeAssist 请求,注入 metadata 字段对齐官方
if final_model_name == "loadCodeAssist" || inner_request.get("metadata").is_some() {
let metadata = inner_request.as_object_mut().unwrap().entry("metadata").or_insert(json!({}));
if let Some(m_obj) = metadata.as_object_mut() {
if m_obj.get("ideType").is_none() {
m_obj.insert("ideType".to_string(), json!(official_ide_type));
}
}
}
// [NEW] 3. 条件注入 enabledCreditTypes
// 这是官方 Worker 极高权重的一个指纹字段。
// 只有在非图像生成请求(即 agent 类型请求)时注入,避免图像生成场景出现 Credit 判定异常。
// 特别注意:这是 Google 识别“官方客户端”的重要凭证之一。
let is_agent_request = config.request_type != "image_gen";
let mut final_request_obj = json!({
"project": project_id,
"requestId": official_request_id,
"request": inner_request,
"model": config.final_model,
"userAgent": official_user_agent,
"requestType": if is_agent_request { "agent" } else { "image_gen" }
});
if is_agent_request {
if let Some(obj) = final_request_obj.as_object_mut() {
// 强制注入 Google One AI 信用额度支持标号
obj.insert("enabledCreditTypes".to_string(), json!(["GOOGLE_ONE_AI"]));
}
}
final_request_obj
}
#[cfg(test)]
mod test_fixes {
use super::*;
use serde_json::json;
#[test]
fn test_wrap_request_with_signature() {
let session_id = "test-session-sig";
let signature = "test-signature-must-be-longer-than-fifty-characters-to-be-cached-by-signature-cache-12345"; // > 50 chars
crate::proxy::SignatureCache::global().cache_session_signature(
session_id,
signature.to_string(),
1,
);
let body = json!({
"model": "gemini-pro",
"contents": [{
"role": "user",
"parts": [{
"functionCall": {
"name": "get_weather",
"args": {"location": "London"}
}
}]
}]
});
let result = wrap_request(&body, "proj", "gemini-pro", None, Some(session_id), None);
let injected_sig = result["request"]["contents"][0]["parts"][0]["thoughtSignature"]
.as_str()
.unwrap();
assert_eq!(injected_sig, signature);
}
}
/// 解包响应(提取 response 字段)
pub fn unwrap_response(response: &Value) -> Value {
response.get("response").unwrap_or(response).clone()
}
/// [NEW v3.3.18] 为 Claude 模型的 Gemini 响应自动注入 Tool ID
///
/// 目点是为了让客户端(如 OpenCode/Vercel AI SDK)能感知到 ID,
/// 并在下一轮对话中原样带回,从而满足 Google v1internal 对 Claude 模型的校验。
pub fn inject_ids_to_response(response: &mut Value, model_name: &str) {
if !model_name.to_lowercase().contains("claude") {
return;
}
if let Some(candidates) = response
.get_mut("candidates")
.and_then(|c| c.as_array_mut())
{
for candidate in candidates {
if let Some(parts) = candidate
.get_mut("content")
.and_then(|c| c.get_mut("parts"))
.and_then(|p| p.as_array_mut())
{
let mut name_counters: std::collections::HashMap<String, usize> =
std::collections::HashMap::new();
for part in parts {
if let Some(fc) = part.get_mut("functionCall").and_then(|f| f.as_object_mut()) {
if fc.get("id").is_none() {
let name = fc.get("name").and_then(|n| n.as_str()).unwrap_or("unknown");
let count = name_counters.entry(name.to_string()).or_insert(0);
let call_id = format!("call_{}_{}", name, count);
*count += 1;
fc.insert("id".to_string(), json!(call_id));
tracing::debug!("[Gemini-Wrap] Response stage: Injected synthetic call_id '{}' for client", call_id);
}
}
}
}
}
}
}
#[cfg(test)]
mod tests {
use super::*;
use serde_json::json;
#[test]
fn test_wrap_request() {
let body = json!({
"model": "gemini-2.5-flash",
"contents": [{"role": "user", "parts": [{"text": "Hi"}]}]
});
let result = wrap_request(&body, "test-project", "gemini-2.5-flash", None, None, None);
assert_eq!(result["project"], "test-project");
assert_eq!(result["model"], "gemini-2.5-flash");
assert!(result["requestId"].as_str().unwrap().starts_with("agent/"));
}
#[test]
fn test_unwrap_response() {
let wrapped = json!({
"response": {
"candidates": [{"content": {"parts": [{"text": "Hello"}]}}]
}
});
let result = unwrap_response(&wrapped);
assert!(result.get("candidates").is_some());
assert!(result.get("response").is_none());
}
#[test]
fn test_antigravity_identity_injection_with_role() {
let body = json!({
"model": "gemini-pro",
"messages": []
});
let result = wrap_request(&body, "test-proj", "gemini-pro", None, None, None);
// 验证 systemInstruction
let sys = result
.get("request")
.unwrap()
.get("systemInstruction")
.unwrap();
}
#[test]
fn test_gemini_flash_thinking_budget_capping() {
// Ensure default config (Auto mode)
crate::proxy::config::update_thinking_budget_config(crate::proxy::config::ThinkingBudgetConfig::default());
let body = json!({
"model": "gemini-2.0-flash-thinking-exp",
"generationConfig": {
"thinkingConfig": {
"includeThoughts": true,
"thinkingBudget": 32000
}
}
});
// Test with Flash model
let result = wrap_request(&body, "test-proj", "gemini-2.0-flash-thinking-exp", None, None, None);
let req = result.get("request").unwrap();
let gen_config = req.get("generationConfig").unwrap();
let budget = gen_config["thinkingConfig"]["thinkingBudget"]
.as_u64()
.unwrap();
// Should be capped at 24576
assert_eq!(budget, 24576);
// Test with Pro model (should NOT cap)
let body_pro = json!({
"model": "gemini-2.0-pro-exp",
"generationConfig": {
"thinkingConfig": {
"includeThoughts": true,
"thinkingBudget": 32000
}
}
});
let result_pro = wrap_request(&body_pro, "test-proj", "gemini-2.0-pro-exp", None, None, None);
let budget_pro = result_pro["request"]["generationConfig"]["thinkingConfig"]
["thinkingBudget"]
.as_u64()
.unwrap();
// [FIX #1592] Pro models now also capped to 24576 in wrap_request logic
assert_eq!(budget_pro, 24576);
}
#[test]
fn test_image_thinking_mode_disabled() {
// 1. Set global mode to disabled
crate::proxy::config::update_image_thinking_mode(Some("disabled".to_string()));
// 2. Create a request for an image model (which triggers the image logic)
// Note: resolve_request_config needs to return image_config for the logic to trigger
// So we use a model name that resolves to image_gen
let body = json!({
"model": "gemini-3-pro-image-2k",
"contents": [{"role": "user", "parts": [{"text": "Draw a cat"}]}]
});
let result = wrap_request(&body, "test-proj", "gemini-3-pro-image-2k", None, None, None);
let req = result.get("request").unwrap();
let gen_config = req.get("generationConfig").unwrap();
// 3. Verify thinkingConfig has includeThoughts: false
let thinking_config = gen_config.get("thinkingConfig").unwrap();
assert_eq!(thinking_config["includeThoughts"], false);
// 4. Reset global mode
crate::proxy::config::update_image_thinking_mode(Some("enabled".to_string()));
}
#[test]
fn test_user_instruction_preservation() {
let body = json!({
"model": "gemini-pro",
"systemInstruction": {
"role": "user",
"parts": [{"text": "User custom prompt"}]
}
});
let result = wrap_request(&body, "test-proj", "gemini-pro", None, None, None);
let sys = result
.get("request")
.unwrap()
.get("systemInstruction")
.unwrap();
let parts = sys.get("parts").unwrap().as_array().unwrap();
// Should have 2 parts: Antigravity + User
assert_eq!(parts.len(), 2);
assert!(parts[0]
.get("text")
.unwrap()
.as_str()
.unwrap()
.contains("You are Antigravity"));
assert_eq!(
parts[1].get("text").unwrap().as_str().unwrap(),
"User custom prompt"
);
}
#[test]
fn test_duplicate_prevention() {
let body = json!({
"model": "gemini-pro",
"systemInstruction": {
"parts": [{"text": "You are Antigravity..."}]
}
});
let result = wrap_request(&body, "test-proj", "gemini-pro", None, None, None);
let sys = result
.get("request")
.unwrap()
.get("systemInstruction")
.unwrap();
let parts = sys.get("parts").unwrap().as_array().unwrap();
// Should NOT inject duplicate, so only 1 part remains
assert_eq!(parts.len(), 1);
}
#[test]
fn test_image_generation_with_reference_images() {
// Create 14 reference images + 1 text prompt
let mut parts = Vec::new();
parts.push(json!({"text": "Generate a variation"}));
for _ in 0..14 {
parts.push(json!({
"inlineData": {
"mimeType": "image/jpeg",
"data": "base64data..."
}
}));
}
let body = json!({
"model": "gemini-3-pro-image",
"contents": [{"parts": parts}]
});
let result = wrap_request(&body, "test-proj", "gemini-3-pro-image", None, None, None);
let request = result.get("request").unwrap();
let contents = request.get("contents").unwrap().as_array().unwrap();
let result_parts = contents[0].get("parts").unwrap().as_array().unwrap();
// Verify all 15 parts (1 text + 14 images) are preserved
assert_eq!(result_parts.len(), 15);
}
#[test]
fn test_gemini_pro_thinking_budget_processing() {
// Update global config to Custom mode to verify logic execution
use crate::proxy::config::{
update_thinking_budget_config, ThinkingBudgetConfig, ThinkingBudgetMode,
};
// Save old config (optional, but good practice if tests ran in parallel, but here it's fine)
update_thinking_budget_config(ThinkingBudgetConfig {
mode: ThinkingBudgetMode::Custom,
custom_value: 1024, // Distinct value
effort: None,
});
let body = json!({
"model": "gemini-3-pro-preview",
"generationConfig": {
"thinkingConfig": {
"includeThoughts": true,
"thinkingBudget": 32000
}
}
});
// Test with Pro model
let result = wrap_request(&body, "test-proj", "gemini-3-pro-preview", None, None, None);
let req = result.get("request").unwrap();
let gen_config = req.get("generationConfig").unwrap();
let budget = gen_config["thinkingConfig"]["thinkingBudget"]
.as_u64()
.unwrap();
// If logic executes, it sees Custom mode and sets 1024
// If logic skipped, it keeps 32000
assert_eq!(
budget, 1024,
"Budget should be overridden to 1024 by custom config, proving logic execution"
);
// Restore default (Auto 24576)
update_thinking_budget_config(ThinkingBudgetConfig::default());
}
#[cfg(test)]
mod test_v4_fixes {
use super::*;
use serde_json::json;
#[test]
fn test_claude_no_root_thinking_injection() {
// 验证 Claude 模型不会在根目录注入 thinking,而是注入到 generationConfig.thinkingConfig
// 并且 budget 默认为 16000
// 使用 Auto 模式避免干扰
crate::proxy::config::update_thinking_budget_config(
crate::proxy::config::ThinkingBudgetConfig {
mode: crate::proxy::config::ThinkingBudgetMode::Auto,
custom_value: 0,
effort: None,
},
);
let body = json!({
"model": "claude-3-7-sonnet-thinking",
"messages": [{"role": "user", "content": "hi"}]
});
let result = wrap_request(&body, "proj", "claude-3-7-sonnet-thinking", None, None, None);
let req = result.get("request").unwrap();
// 1. 确保根目录没有 thinking
assert!(req.get("thinking").is_none(), "Root level 'thinking' should NOT be present");
// 2. 确保 generationConfig.thinkingConfig 存在
let gen_config = req.get("generationConfig").expect("generationConfig should be present");
let thinking_config = gen_config.get("thinkingConfig").expect("thinkingConfig should be injected");
// 3. 验证 Claude 默认预算为 16000
let budget = thinking_config["thinkingBudget"].as_u64().expect("thinkingBudget should be a number");
assert_eq!(budget, 16000, "Claude default thinking budget should be 16000");
}
#[test]
fn test_gemini_thinking_injection_default() {
// 验证 Gemini 模型注入默认预算 24576
let body = json!({
"model": "gemini-2.0-flash-thinking-exp",
"contents": [{"role": "user", "parts": [{"text": "hi"}]}]
});
let result = wrap_request(&body, "proj", "gemini-2.0-flash-thinking-exp", None, None, None);
let req = result.get("request").unwrap();
let gen_config = req.get("generationConfig").unwrap();
let thinking_config = gen_config.get("thinkingConfig").unwrap();
let budget = thinking_config["thinkingBudget"].as_u64().unwrap();
assert_eq!(budget, 24576, "Gemini default thinking budget should be 24576");
}
}
#[test]
fn test_gemini_pro_auto_inject_thinking() {
// Reset thinking budget to auto mode at the start to avoid interference from parallel tests
crate::proxy::config::update_thinking_budget_config(
crate::proxy::config::ThinkingBudgetConfig {
mode: crate::proxy::config::ThinkingBudgetMode::Auto,
custom_value: 24576,
effort: None,
},
);
// Request WITHOUT thinkingConfig
let body = json!({
"model": "gemini-3-pro-preview",
// No generationConfig or empty one
"generationConfig": {}
});
// Test with Pro-preview model (should NOT auto-inject to avoid 400)
let result = wrap_request(&body, "test-proj", "gemini-3-pro-preview", None, None, None);
let req = result.get("request").unwrap();
let gen_config = req.get("generationConfig").unwrap();
// Should NOT have auto-injected thinkingConfig
assert!(
gen_config.get("thinkingConfig").is_none(),
"Should NOT auto-inject thinkingConfig for gemini-3-pro-preview to avoid 400 error"
);
// Test with standard gemini-3-pro (non-preview)
let body_std = json!({
"model": "gemini-3-pro",
"generationConfig": {}
});
let result_std = wrap_request(&body_std, "test-proj", "gemini-3-pro", None, None, None);
let gen_config_std = result_std.get("request").unwrap().get("generationConfig").unwrap();
assert!(
gen_config_std.get("thinkingConfig").is_some(),
"Should still auto-inject thinkingConfig for standard gemini-3-pro"
);
}
#[test]
fn test_openai_image_params_support() {
// Test Case 1: Standard Size + Quality (HD/4K)
let body_1 = json!({
"model": "gemini-3-pro-image",
"size": "1920x1080",
"quality": "hd",
"prompt": "Test"
});
let result_1 = wrap_request(&body_1, "test-proj", "gemini-3-pro-image", None, None, None);
let req_1 = result_1.get("request").unwrap();
let gen_config_1 = req_1.get("generationConfig").unwrap();
let image_config_1 = gen_config_1.get("imageConfig").unwrap();
assert_eq!(image_config_1["aspectRatio"], "16:9");
assert_eq!(image_config_1["imageSize"], "4K");
// Test Case 2: Aspect Ratio String + Standard Quality
let body_2 = json!({
"model": "gemini-3-pro-image",
"size": "1:1",
"quality": "standard",
"prompt": "Test"
});
let result_2 = wrap_request(&body_2, "test-proj", "gemini-3-pro-image", None, None, None);
let req_2 = result_2.get("request").unwrap();
let image_config_2 = req_2["generationConfig"]["imageConfig"]
.as_object()
.unwrap();
assert_eq!(image_config_2["aspectRatio"], "1:1");
assert_eq!(image_config_2["imageSize"], "1K");
}
#[test]
fn test_mixed_tools_injection_gemini_native() {
// 验证 Gemini Native 协议在 Gemini 2.0+ 下支持混合工具
let body = json!({
"contents": [{"parts": [{"text": "Hello"}]}],
"tools": [{"functionDeclarations": [{"name": "get_weather", "parameters": {"type": "OBJECT", "properties": {"location": {"type": "STRING"}}}}]}],
"generationConfig": {}
});
// 模拟 -online 触发的 RequestConfig
use crate::proxy::mappers::common_utils::resolve_request_config;
let _config = resolve_request_config("-online", "gemini-2.0-flash", &None, None, None, None, None);
// 实际上 wrap_request 内部会根据 config.inject_google_search 调用 inject_google_search_tool
// 但 wrap_request 的签名不直接接受 RequestConfig,它内部逻辑如下:
// if config.inject_google_search { ... }
// 我们改为直接测试涉及的 wrap_request 逻辑片段。
// 由于测试 wrap_request 比较复杂(涉及外部 config),
// 我们可以直接验证 inject_google_search_tool 在 native 格式下的表现。
let mut inner_request = body.clone();
crate::proxy::mappers::common_utils::inject_google_search_tool(&mut inner_request, Some("gemini-2.0-flash"));
let tools = inner_request["tools"].as_array().expect("Should have tools");
let has_functions = tools.iter().any(|t| t.get("functionDeclarations").is_some());
let has_google_search = tools.iter().any(|t| t.get("googleSearch").is_some());
assert!(has_functions, "Should contain functionDeclarations");
assert!(has_google_search, "Should contain googleSearch (Gemini 2.0+ supports mixed tools)");
}
}
|