mirror of
https://github.com/fawney19/Aether.git
synced 2026-10-10 11:19:50 +08:00
refactor(workspace): enforce layered crate boundaries
This commit is contained in:
elky
@@ -0,0 +1,985 @@
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use serde_json::Value;
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use aether_ai_formats::api::{
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is_claude_messages_shaped_body_on_openai_chat_endpoint, is_openai_responses_family_format,
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normalize_api_format_alias,
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};
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use aether_ai_formats::{convert_request_pure_with_context, FormatContext, FormatError};
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use crate::{CandidateFailureDiagnostic, CandidateFailureDiagnosticKind};
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pub fn request_body_build_failure_extra_data(
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body_json: &Value,
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client_api_format: &str,
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provider_api_format: &str,
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) -> Option<Value> {
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let diagnostic =
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diagnose_request_body_build_failure(body_json, client_api_format, provider_api_format)?;
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Some(
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diagnostic
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.formats(client_api_format, provider_api_format)
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.source(request_body_build_source(
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client_api_format,
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provider_api_format,
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))
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.to_extra_data(),
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)
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}
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pub fn request_conversion_failure_extra_data(
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body_json: &Value,
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client_api_format: &str,
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provider_api_format: &str,
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mapped_model: Option<&str>,
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request_path: Option<&str>,
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upstream_is_stream: bool,
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source: impl Into<String>,
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) -> Option<Value> {
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let diagnostic = diagnose_request_conversion_failure(
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body_json,
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client_api_format,
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provider_api_format,
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mapped_model,
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request_path,
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upstream_is_stream,
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)?;
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Some(
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diagnostic
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.formats(client_api_format, provider_api_format)
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.source(source)
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.to_extra_data(),
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)
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}
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pub fn same_format_provider_request_body_failure_extra_data(
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body_json: &Value,
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provider_api_format: &str,
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body_rules: Option<&Value>,
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context: &str,
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) -> Option<Value> {
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let diagnostic =
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diagnose_same_format_provider_request_body_failure(body_json, body_rules, context)?;
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Some(
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diagnostic
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.formats(provider_api_format, provider_api_format)
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.source(context)
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.to_extra_data(),
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)
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}
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type RequestBodyBuildDiagnostic = CandidateFailureDiagnostic;
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type RequestConversionDiagnostic = CandidateFailureDiagnostic;
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fn diagnose_request_conversion_failure(
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body_json: &Value,
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client_api_format: &str,
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provider_api_format: &str,
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mapped_model: Option<&str>,
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request_path: Option<&str>,
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upstream_is_stream: bool,
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) -> Option<RequestConversionDiagnostic> {
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let mut context = FormatContext::default().with_upstream_stream(upstream_is_stream);
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if let Some(mapped_model) = mapped_model
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.map(str::trim)
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.filter(|value| !value.is_empty())
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{
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context = context.with_mapped_model(mapped_model);
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}
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if let Some(request_path) = request_path
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.map(str::trim)
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.filter(|value| !value.is_empty())
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{
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context = context.with_request_path(request_path);
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}
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let source_format =
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compatible_source_format_for_diagnostic(body_json, client_api_format, provider_api_format);
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match convert_request_pure_with_context(
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source_format.as_str(),
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provider_api_format,
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body_json,
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&context,
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) {
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Ok(_) => {
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diagnose_request_body_build_failure(body_json, client_api_format, provider_api_format)
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.filter(CandidateFailureDiagnostic::has_specific_path)
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.or_else(|| Some(fallback_request_conversion_diagnostic()))
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}
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Err(error) => {
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let format_diagnostic =
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diagnostic_from_format_error(&error, client_api_format, provider_api_format);
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if format_diagnostic.has_specific_path() {
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Some(format_diagnostic)
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} else {
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diagnose_request_body_build_failure(
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body_json,
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client_api_format,
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provider_api_format,
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)
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.filter(CandidateFailureDiagnostic::has_specific_path)
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.or(Some(format_diagnostic))
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}
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}
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}
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}
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fn fallback_request_conversion_diagnostic() -> RequestConversionDiagnostic {
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diagnostic(
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"$",
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"请求体转换本身已通过；失败可能发生在 Body 规则应用或后续上游请求体语义校验",
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)
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}
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fn diagnose_request_body_build_failure(
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body_json: &Value,
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client_api_format: &str,
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provider_api_format: &str,
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) -> Option<RequestBodyBuildDiagnostic> {
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if !body_json.is_object() {
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return Some(diagnostic("$", "请求体必须是 JSON object"));
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}
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if is_openai_responses_client_format(client_api_format) {
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if let Some(diagnostic) = diagnose_openai_responses_request(body_json) {
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return Some(diagnostic);
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}
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return Some(diagnostic(
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"$",
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"OpenAI Responses 请求体初步结构检查通过；失败可能发生在后续跨格式转换或 Body 规则应用",
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));
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}
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if client_api_format == "openai:chat"
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&& (provider_api_format.starts_with("claude:")
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|| provider_api_format.starts_with("gemini:"))
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{
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return diagnose_openai_chat_cross_format_request(body_json, provider_api_format);
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}
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Some(diagnostic(
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"$",
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"请求体转换失败；当前转换器未返回更细的字段路径",
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))
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}
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fn compatible_source_format_for_diagnostic(
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body_json: &Value,
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client_api_format: &str,
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provider_api_format: &str,
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) -> String {
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let client_api_format = normalize_api_format_alias(client_api_format);
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let provider_api_format = normalize_api_format_alias(provider_api_format);
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if client_api_format == "openai:chat"
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&& provider_api_format == "claude:messages"
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&& is_claude_messages_shaped_body_on_openai_chat_endpoint(body_json)
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{
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return "claude:messages".to_string();
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}
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client_api_format
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}
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fn diagnostic_from_format_error(
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error: &FormatError,
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client_api_format: &str,
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provider_api_format: &str,
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) -> RequestConversionDiagnostic {
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CandidateFailureDiagnostic::new(
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CandidateFailureDiagnosticKind::RequestConversion,
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format_error_path(error),
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format_error_message(error, client_api_format, provider_api_format),
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)
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}
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fn format_error_path(error: &FormatError) -> String {
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match error {
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FormatError::UnsupportedField { field, .. }
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| FormatError::UnauditedField { field, .. }
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| FormatError::InvalidEnumValue { field, .. }
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| FormatError::LossyConversionBlocked { field, .. }
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| FormatError::InvalidTargetField { field, .. } => field_to_json_path(field),
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FormatError::UnsupportedFormat(_)
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| FormatError::RequestParseFailed { .. }
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| FormatError::RequestEmitFailed { .. }
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| FormatError::ResponseParseFailed { .. }
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| FormatError::ResponseEmitFailed { .. } => "$".to_string(),
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}
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}
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fn field_to_json_path(field: &str) -> String {
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let field = field.trim();
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if field.is_empty() || field == "$" {
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return "$".to_string();
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}
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if field.starts_with('$') {
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return field.to_string();
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}
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format!("$.{}", field)
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.replace("[].", "[*].")
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.replace("[]", "[*]")
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}
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fn format_error_message(
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error: &FormatError,
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client_api_format: &str,
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provider_api_format: &str,
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) -> String {
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match error {
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FormatError::UnsupportedFormat(format) => {
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format!("不支持的 API 格式 {format}，无法执行 {client_api_format} → {provider_api_format} 转换")
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}
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FormatError::RequestParseFailed { format } => {
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format!("无法按 {format} 解析请求体；请检查请求体结构和字段类型是否符合该格式")
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}
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FormatError::RequestEmitFailed { format } => {
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format!("无法生成 {format} 上游请求体；请检查源请求是否缺少目标格式必需字段或包含不可映射结构")
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}
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FormatError::ResponseParseFailed { format } => {
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format!("无法按 {format} 解析响应体")
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}
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FormatError::ResponseEmitFailed { format } => {
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format!("无法生成 {format} 响应体")
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}
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FormatError::UnsupportedField {
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format,
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field,
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reason,
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} => {
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format!("{format} 字段 {field} 不支持跨格式转换：{reason}")
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}
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FormatError::UnauditedField {
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source_format,
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target_format,
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field,
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reason,
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} => {
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format!("{source_format} 字段 {field} 尚未审计，不能转换到 {target_format}：{reason}")
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}
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FormatError::InvalidEnumValue {
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format,
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field,
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value,
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} => {
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format!("{format} 字段 {field} 的枚举值 {value:?} 无效，无法转换")
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}
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FormatError::LossyConversionBlocked {
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source_format,
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target_format,
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field,
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reason,
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} => {
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format!("{source_format} 字段 {field} 不能无损转换到 {target_format}：{reason}")
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}
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FormatError::InvalidTargetField {
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format,
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field,
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reason,
|
||||
} => {
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format!("目标格式 {format} 字段 {field} 无效：{reason}")
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}
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}
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}
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fn is_openai_responses_client_format(client_api_format: &str) -> bool {
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is_openai_responses_family_format(client_api_format)
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}
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|
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fn diagnose_same_format_provider_request_body_failure(
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body_json: &Value,
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body_rules: Option<&Value>,
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context: &str,
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) -> Option<RequestBodyBuildDiagnostic> {
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||||
if !body_json.is_object() {
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return Some(diagnostic("$", "反代请求体必须是 JSON object"));
|
||||
}
|
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if body_rules.is_some_and(|rules| !rules.is_array()) {
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return Some(diagnostic(
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"$.endpoint.body_rules",
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"Endpoint Body 规则必须是数组，本地反代无法应用该配置",
|
||||
));
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}
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match context {
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"kiro_envelope" => Some(diagnostic(
|
||||
"$",
|
||||
"Kiro 反代请求体包装失败；请检查 Kiro auth_config 与 Endpoint Body 规则",
|
||||
)),
|
||||
"antigravity_envelope" => Some(diagnostic(
|
||||
"$",
|
||||
"Antigravity 反代请求体包装失败；请检查请求体是否满足该传输封装要求",
|
||||
)),
|
||||
_ => Some(diagnostic(
|
||||
"$",
|
||||
"反代请求体构建失败；当前路径未返回更细的字段信息",
|
||||
)),
|
||||
}
|
||||
}
|
||||
|
||||
fn diagnose_openai_chat_cross_format_request(
|
||||
body_json: &Value,
|
||||
provider_api_format: &str,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
if provider_api_format.starts_with("claude:")
|
||||
&& is_claude_messages_shaped_body_on_openai_chat_endpoint(body_json)
|
||||
{
|
||||
return Some(diagnostic(
|
||||
"$",
|
||||
"请求体看起来是 Claude Messages 原生格式；Aether 会按 Claude Messages 兼容路径处理，若仍失败请检查 Claude messages/tools/tool_choice 结构或 Body 规则",
|
||||
));
|
||||
}
|
||||
|
||||
let request = body_json.as_object()?;
|
||||
|
||||
if let Some(messages) = request.get("messages") {
|
||||
let Some(messages) = messages.as_array() else {
|
||||
return Some(diagnostic(
|
||||
"$.messages",
|
||||
"OpenAI Chat 的 messages 必须是数组",
|
||||
));
|
||||
};
|
||||
for (message_index, message) in messages.iter().enumerate() {
|
||||
let Some(message_object) = message.as_object() else {
|
||||
return Some(diagnostic(
|
||||
format!("$.messages[{message_index}]"),
|
||||
"message 必须是 object",
|
||||
));
|
||||
};
|
||||
let role = message_object
|
||||
.get("role")
|
||||
.and_then(Value::as_str)
|
||||
.unwrap_or_default()
|
||||
.trim()
|
||||
.to_ascii_lowercase();
|
||||
match role.as_str() {
|
||||
"system" | "developer" => {
|
||||
if let Some(diagnostic) = diagnose_openai_text_content(
|
||||
message_object.get("content"),
|
||||
format!("$.messages[{message_index}].content"),
|
||||
) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
}
|
||||
"user" | "assistant" => {
|
||||
if let Some(diagnostic) = diagnose_openai_content_blocks(
|
||||
message_object.get("content"),
|
||||
format!("$.messages[{message_index}].content"),
|
||||
role.as_str(),
|
||||
) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
if role == "assistant" {
|
||||
if let Some(diagnostic) = diagnose_openai_assistant_tool_calls(
|
||||
message_object.get("tool_calls"),
|
||||
format!("$.messages[{message_index}].tool_calls"),
|
||||
) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
}
|
||||
}
|
||||
"tool" => {
|
||||
let valid_tool_call_id = message_object
|
||||
.get("tool_call_id")
|
||||
.and_then(Value::as_str)
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty());
|
||||
if !valid_tool_call_id {
|
||||
return Some(diagnostic(
|
||||
format!("$.messages[{message_index}].tool_call_id"),
|
||||
"tool 消息必须包含非空 tool_call_id",
|
||||
));
|
||||
}
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if let Some(diagnostic) = diagnose_openai_tools(request.get("tools"), provider_api_format) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
diagnose_openai_tool_choice(request.get("tool_choice"))
|
||||
}
|
||||
|
||||
fn diagnose_openai_responses_request(body_json: &Value) -> Option<RequestBodyBuildDiagnostic> {
|
||||
let request = body_json.as_object()?;
|
||||
|
||||
if let Some(diagnostic) = diagnose_openai_responses_text_content(
|
||||
request.get("instructions"),
|
||||
"$.instructions".to_string(),
|
||||
) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
|
||||
if let Some(diagnostic) = diagnose_openai_responses_input(request.get("input")) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
if let Some(diagnostic) = diagnose_openai_responses_tools(request.get("tools")) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
diagnose_openai_responses_tool_choice(request.get("tool_choice"))
|
||||
}
|
||||
|
||||
fn diagnose_openai_responses_input(input: Option<&Value>) -> Option<RequestBodyBuildDiagnostic> {
|
||||
let input = input?;
|
||||
match input {
|
||||
Value::Null | Value::String(_) => None,
|
||||
Value::Array(items) => {
|
||||
for (item_index, item) in items.iter().enumerate() {
|
||||
if item.is_string() {
|
||||
continue;
|
||||
}
|
||||
let item_path = format!("$.input[{item_index}]");
|
||||
let Some(item_object) = item.as_object() else {
|
||||
return Some(diagnostic(
|
||||
item_path,
|
||||
"OpenAI Responses input 数组项必须是 string 或 object",
|
||||
));
|
||||
};
|
||||
let item_type = item_object
|
||||
.get("type")
|
||||
.and_then(Value::as_str)
|
||||
.unwrap_or("message")
|
||||
.trim()
|
||||
.to_ascii_lowercase();
|
||||
match item_type.as_str() {
|
||||
"message" => {
|
||||
let role = item_object
|
||||
.get("role")
|
||||
.and_then(Value::as_str)
|
||||
.unwrap_or("user")
|
||||
.trim()
|
||||
.to_ascii_lowercase();
|
||||
if role == "system" || role == "developer" {
|
||||
if let Some(diagnostic) = diagnose_openai_responses_text_content(
|
||||
item_object.get("content"),
|
||||
format!("{item_path}.content"),
|
||||
) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
} else if let Some(diagnostic) = diagnose_openai_responses_message_content(
|
||||
item_object.get("content"),
|
||||
format!("{item_path}.content"),
|
||||
) {
|
||||
return Some(diagnostic);
|
||||
}
|
||||
}
|
||||
"function_call" => {
|
||||
let valid_name = item_object
|
||||
.get("name")
|
||||
.and_then(Value::as_str)
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty());
|
||||
if !valid_name {
|
||||
return Some(diagnostic(
|
||||
format!("{item_path}.name"),
|
||||
"function_call 必须包含非空 name",
|
||||
));
|
||||
}
|
||||
}
|
||||
_ => {}
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
_ => Some(diagnostic(
|
||||
"$.input",
|
||||
"OpenAI Responses input 必须是 string、array 或 null",
|
||||
)),
|
||||
}
|
||||
}
|
||||
|
||||
fn diagnose_openai_responses_text_content(
|
||||
content: Option<&Value>,
|
||||
path: String,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
match content {
|
||||
None | Some(Value::Null) | Some(Value::String(_)) => None,
|
||||
Some(Value::Array(parts)) => {
|
||||
for (part_index, part) in parts.iter().enumerate() {
|
||||
if !part.is_object() {
|
||||
return Some(diagnostic(
|
||||
format!("{path}[{part_index}]"),
|
||||
"文本 content 数组项必须是 object",
|
||||
));
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
Some(_) => Some(diagnostic(
|
||||
path,
|
||||
"文本 content 必须是 string、array 或 null",
|
||||
)),
|
||||
}
|
||||
}
|
||||
|
||||
fn diagnose_openai_responses_message_content(
|
||||
content: Option<&Value>,
|
||||
path: String,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
match content {
|
||||
None | Some(Value::Null) | Some(Value::String(_)) => None,
|
||||
Some(Value::Array(parts)) => {
|
||||
for (part_index, part) in parts.iter().enumerate() {
|
||||
let part_path = format!("{path}[{part_index}]");
|
||||
let Some(part_object) = part.as_object() else {
|
||||
return Some(diagnostic(part_path, "message content 数组项必须是 object"));
|
||||
};
|
||||
let part_type = part_object
|
||||
.get("type")
|
||||
.and_then(Value::as_str)
|
||||
.unwrap_or_default()
|
||||
.trim()
|
||||
.to_ascii_lowercase();
|
||||
if matches!(
|
||||
part_type.as_str(),
|
||||
"input_image" | "output_image" | "image_url"
|
||||
) && image_part_url(part_object).is_none()
|
||||
{
|
||||
return Some(diagnostic(
|
||||
part_path,
|
||||
"图片 content 缺少 image_url/url，无法规范化为 OpenAI Chat 图片内容",
|
||||
));
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
Some(_) => None,
|
||||
}
|
||||
}
|
||||
|
||||
fn diagnose_openai_text_content(
|
||||
content: Option<&Value>,
|
||||
path: String,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
match content {
|
||||
None | Some(Value::Null) | Some(Value::String(_)) => None,
|
||||
Some(Value::Array(parts)) => {
|
||||
for (part_index, part) in parts.iter().enumerate() {
|
||||
if !part.is_object() {
|
||||
return Some(diagnostic(
|
||||
format!("{path}[{part_index}]"),
|
||||
"content 数组项必须是 object",
|
||||
));
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
Some(_) => Some(diagnostic(path, "content 必须是 string、array 或 null")),
|
||||
}
|
||||
}
|
||||
|
||||
fn diagnose_openai_content_blocks(
|
||||
content: Option<&Value>,
|
||||
path: String,
|
||||
role: &str,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
match content {
|
||||
None | Some(Value::Null) | Some(Value::String(_)) => None,
|
||||
Some(Value::Array(parts)) => {
|
||||
for (part_index, part) in parts.iter().enumerate() {
|
||||
let part_path = format!("{path}[{part_index}]");
|
||||
let Some(part_object) = part.as_object() else {
|
||||
return Some(diagnostic(part_path, "content 数组项必须是 object"));
|
||||
};
|
||||
let part_type = part_object
|
||||
.get("type")
|
||||
.and_then(Value::as_str)
|
||||
.unwrap_or_default();
|
||||
if matches!(part_type, "image_url" | "input_image" | "output_image")
|
||||
&& role == "user"
|
||||
&& image_part_url(part_object).is_none()
|
||||
{
|
||||
return Some(diagnostic(
|
||||
part_path,
|
||||
"图片 content 缺少 image_url/url，无法转换为 Claude image block",
|
||||
));
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
Some(_) => Some(diagnostic(path, "content 必须是 string、array 或 null")),
|
||||
}
|
||||
}
|
||||
|
||||
fn diagnose_openai_assistant_tool_calls(
|
||||
tool_calls: Option<&Value>,
|
||||
path: String,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
let tool_calls = tool_calls?;
|
||||
let Some(tool_calls) = tool_calls.as_array() else {
|
||||
return Some(diagnostic(path, "assistant.tool_calls 必须是数组"));
|
||||
};
|
||||
for (tool_call_index, tool_call) in tool_calls.iter().enumerate() {
|
||||
let tool_call_path = format!("{path}[{tool_call_index}]");
|
||||
let Some(tool_call_object) = tool_call.as_object() else {
|
||||
return Some(diagnostic(tool_call_path, "tool_call 必须是 object"));
|
||||
};
|
||||
let Some(function) = tool_call_object.get("function").and_then(Value::as_object) else {
|
||||
return Some(diagnostic(
|
||||
format!("{tool_call_path}.function"),
|
||||
"tool_call 必须包含 function object",
|
||||
));
|
||||
};
|
||||
let valid_name = function
|
||||
.get("name")
|
||||
.and_then(Value::as_str)
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty());
|
||||
if !valid_name {
|
||||
return Some(diagnostic(
|
||||
format!("{tool_call_path}.function.name"),
|
||||
"tool_call.function.name 必须是非空字符串",
|
||||
));
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
|
||||
fn diagnose_openai_tools(
|
||||
tools: Option<&Value>,
|
||||
provider_api_format: &str,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
let tools = tools?;
|
||||
let Some(tools) = tools.as_array() else {
|
||||
return Some(diagnostic("$.tools", "OpenAI Chat 的 tools 必须是数组"));
|
||||
};
|
||||
for (tool_index, tool) in tools.iter().enumerate() {
|
||||
let tool_path = format!("$.tools[{tool_index}]");
|
||||
let Some(tool_object) = tool.as_object() else {
|
||||
return Some(diagnostic(tool_path, "tool 必须是 object"));
|
||||
};
|
||||
if tool_object
|
||||
.get("type")
|
||||
.and_then(Value::as_str)
|
||||
.is_some_and(|value| value != "function")
|
||||
{
|
||||
continue;
|
||||
}
|
||||
let Some(function) = tool_object.get("function").and_then(Value::as_object) else {
|
||||
let native_tool_hint = if provider_api_format.starts_with("claude:") {
|
||||
"；如果这是 Claude 原生 tool，请改为 OpenAI function tool 格式"
|
||||
} else if provider_api_format.starts_with("gemini:") {
|
||||
"；如果这是 Gemini 原生 tool，请改为 OpenAI function tool 格式"
|
||||
} else {
|
||||
""
|
||||
};
|
||||
return Some(diagnostic(
|
||||
format!("{tool_path}.function"),
|
||||
format!("OpenAI tool 必须包含 function object{native_tool_hint}"),
|
||||
));
|
||||
};
|
||||
let valid_name = function
|
||||
.get("name")
|
||||
.and_then(Value::as_str)
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty());
|
||||
if !valid_name {
|
||||
return Some(diagnostic(
|
||||
format!("{tool_path}.function.name"),
|
||||
"OpenAI tool 的 function.name 必须是非空字符串",
|
||||
));
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
|
||||
fn diagnose_openai_responses_tools(tools: Option<&Value>) -> Option<RequestBodyBuildDiagnostic> {
|
||||
let tools = tools?;
|
||||
let tool_values = tools.as_array()?;
|
||||
for (tool_index, tool) in tool_values.iter().enumerate() {
|
||||
let tool_path = format!("$.tools[{tool_index}]");
|
||||
let Some(tool_object) = tool.as_object() else {
|
||||
return Some(diagnostic(tool_path, "OpenAI Responses tool 必须是 object"));
|
||||
};
|
||||
let tool_type = tool_object
|
||||
.get("type")
|
||||
.and_then(Value::as_str)
|
||||
.unwrap_or("function")
|
||||
.trim()
|
||||
.to_ascii_lowercase();
|
||||
if tool_type.starts_with("web_search")
|
||||
|| tool_object.get("function").is_some()
|
||||
|| tool_type != "function"
|
||||
{
|
||||
continue;
|
||||
}
|
||||
let valid_name = tool_object
|
||||
.get("name")
|
||||
.and_then(Value::as_str)
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty());
|
||||
if !valid_name {
|
||||
return Some(diagnostic(
|
||||
format!("{tool_path}.name"),
|
||||
"OpenAI Responses function tool 必须包含非空 name",
|
||||
));
|
||||
}
|
||||
}
|
||||
None
|
||||
}
|
||||
|
||||
fn diagnose_openai_responses_tool_choice(
|
||||
tool_choice: Option<&Value>,
|
||||
) -> Option<RequestBodyBuildDiagnostic> {
|
||||
let Some(Value::Object(object)) = tool_choice else {
|
||||
return None;
|
||||
};
|
||||
let is_cli_function_choice = object.get("function").is_none()
|
||||
&& object
|
||||
.get("type")
|
||||
.and_then(Value::as_str)
|
||||
.is_some_and(|value| value.eq_ignore_ascii_case("function"));
|
||||
if !is_cli_function_choice {
|
||||
return None;
|
||||
}
|
||||
let valid_name = object
|
||||
.get("name")
|
||||
.and_then(Value::as_str)
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty());
|
||||
if valid_name {
|
||||
None
|
||||
} else {
|
||||
Some(diagnostic(
|
||||
"$.tool_choice.name",
|
||||
"OpenAI Responses tool_choice 指定 function 时必须包含非空 name",
|
||||
))
|
||||
}
|
||||
}
|
||||
|
||||
fn diagnose_openai_tool_choice(tool_choice: Option<&Value>) -> Option<RequestBodyBuildDiagnostic> {
|
||||
let Some(Value::Object(object)) = tool_choice else {
|
||||
return None;
|
||||
};
|
||||
let valid_name = object
|
||||
.get("function")
|
||||
.and_then(Value::as_object)
|
||||
.and_then(|function| function.get("name"))
|
||||
.and_then(Value::as_str)
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty());
|
||||
if valid_name {
|
||||
None
|
||||
} else {
|
||||
Some(diagnostic(
|
||||
"$.tool_choice.function.name",
|
||||
"tool_choice 指定具体工具时必须包含非空 function.name",
|
||||
))
|
||||
}
|
||||
}
|
||||
|
||||
fn image_part_url(part_object: &serde_json::Map<String, Value>) -> Option<&str> {
|
||||
part_object
|
||||
.get("image_url")
|
||||
.and_then(|value| {
|
||||
value.as_str().or_else(|| {
|
||||
value
|
||||
.as_object()
|
||||
.and_then(|object| object.get("url"))
|
||||
.and_then(Value::as_str)
|
||||
})
|
||||
})
|
||||
.or_else(|| part_object.get("url").and_then(Value::as_str))
|
||||
.map(str::trim)
|
||||
.filter(|value| !value.is_empty())
|
||||
}
|
||||
|
||||
fn diagnostic(path: impl Into<String>, message: impl Into<String>) -> RequestBodyBuildDiagnostic {
|
||||
CandidateFailureDiagnostic::new(
|
||||
CandidateFailureDiagnosticKind::RequestBodyBuild,
|
||||
path,
|
||||
message,
|
||||
)
|
||||
}
|
||||
|
||||
fn request_body_build_source(client_api_format: &str, provider_api_format: &str) -> String {
|
||||
format!("{client_api_format}_to_{provider_api_format}")
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use serde_json::json;
|
||||
|
||||
use super::{request_body_build_failure_extra_data, request_conversion_failure_extra_data};
|
||||
|
||||
#[test]
|
||||
fn openai_chat_to_claude_recognizes_compatible_claude_native_tool_shape() {
|
||||
let body = json!({
|
||||
"model": "gpt-5.4",
|
||||
"messages": [{ "role": "user", "content": "hello" }],
|
||||
"tools": [{
|
||||
"name": "read_file",
|
||||
"description": "Read a file",
|
||||
"input_schema": { "type": "object" }
|
||||
}]
|
||||
});
|
||||
|
||||
let diagnostic =
|
||||
request_body_build_failure_extra_data(&body, "openai:chat", "claude:messages")
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(diagnostic["request_body_build_error"]["path"], "$");
|
||||
assert_eq!(
|
||||
diagnostic["failure_diagnostic"]["kind"],
|
||||
"request_body_build"
|
||||
);
|
||||
assert_eq!(
|
||||
diagnostic["failure_diagnostic"]["source"],
|
||||
"openai:chat_to_claude:messages"
|
||||
);
|
||||
assert!(diagnostic["request_body_build_error"]["message"]
|
||||
.as_str()
|
||||
.expect("message")
|
||||
.contains("Claude Messages 原生格式"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_chat_to_claude_reports_invalid_message_content_part() {
|
||||
let body = json!({
|
||||
"model": "gpt-5.4",
|
||||
"messages": [{
|
||||
"role": "user",
|
||||
"content": ["not-an-object"]
|
||||
}]
|
||||
});
|
||||
|
||||
let diagnostic =
|
||||
request_body_build_failure_extra_data(&body, "openai:chat", "claude:messages")
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(
|
||||
diagnostic["request_body_build_error"]["path"],
|
||||
"$.messages[0].content[0]"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_chat_to_gemini_reports_gemini_native_tool_shape() {
|
||||
let body = json!({
|
||||
"model": "gpt-5.4",
|
||||
"messages": [{ "role": "user", "content": "hello" }],
|
||||
"tools": [{
|
||||
"functionDeclarations": [{
|
||||
"name": "search",
|
||||
"parameters": { "type": "object" }
|
||||
}]
|
||||
}]
|
||||
});
|
||||
|
||||
let diagnostic =
|
||||
request_body_build_failure_extra_data(&body, "openai:chat", "gemini:generate_content")
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(
|
||||
diagnostic["request_body_build_error"]["path"],
|
||||
"$.tools[0].function"
|
||||
);
|
||||
assert!(diagnostic["request_body_build_error"]["message"]
|
||||
.as_str()
|
||||
.expect("message")
|
||||
.contains("Gemini 原生 tool"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_responses_reports_invalid_function_call_name() {
|
||||
let body = json!({
|
||||
"model": "gpt-5.4",
|
||||
"input": [{
|
||||
"type": "function_call",
|
||||
"arguments": "{}"
|
||||
}]
|
||||
});
|
||||
|
||||
let diagnostic =
|
||||
request_body_build_failure_extra_data(&body, "openai:responses", "claude:messages")
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(
|
||||
diagnostic["request_body_build_error"]["path"],
|
||||
"$.input[0].name"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_responses_reports_invalid_tool_choice_name() {
|
||||
let body = json!({
|
||||
"model": "gpt-5.4",
|
||||
"input": "hello",
|
||||
"tool_choice": { "type": "function" }
|
||||
});
|
||||
|
||||
let diagnostic = request_body_build_failure_extra_data(
|
||||
&body,
|
||||
"openai:responses",
|
||||
"gemini:generate_content",
|
||||
)
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(
|
||||
diagnostic["request_body_build_error"]["path"],
|
||||
"$.tool_choice.name"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn request_conversion_reports_lossy_incompatible_field_path() {
|
||||
let body = json!({
|
||||
"model": "gpt-5.4",
|
||||
"messages": [{ "role": "user", "content": "hello" }],
|
||||
"n": 2
|
||||
});
|
||||
|
||||
let diagnostic = request_conversion_failure_extra_data(
|
||||
&body,
|
||||
"openai:chat",
|
||||
"openai:responses",
|
||||
Some("gpt-5.4"),
|
||||
Some("/v1/chat/completions"),
|
||||
false,
|
||||
"test_conversion",
|
||||
)
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(
|
||||
diagnostic["failure_diagnostic"]["kind"],
|
||||
"request_conversion"
|
||||
);
|
||||
assert_eq!(diagnostic["failure_diagnostic"]["path"], "$.n");
|
||||
assert_eq!(diagnostic["request_conversion_error"]["path"], "$.n");
|
||||
assert!(diagnostic["failure_diagnostic"]["message"]
|
||||
.as_str()
|
||||
.expect("message")
|
||||
.contains("字段 n"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn same_format_provider_reports_non_object_body() {
|
||||
let diagnostic = super::same_format_provider_request_body_failure_extra_data(
|
||||
&json!("raw"),
|
||||
"openai:chat",
|
||||
None,
|
||||
"same_format",
|
||||
)
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(diagnostic["request_body_build_error"]["path"], "$");
|
||||
assert!(diagnostic["request_body_build_error"]["message"]
|
||||
.as_str()
|
||||
.expect("message")
|
||||
.contains("反代请求体必须是 JSON object"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn same_format_provider_reports_invalid_body_rules_shape() {
|
||||
let diagnostic = super::same_format_provider_request_body_failure_extra_data(
|
||||
&json!({ "model": "gpt-5.4" }),
|
||||
"openai:chat",
|
||||
Some(&json!({ "action": "set" })),
|
||||
"same_format",
|
||||
)
|
||||
.expect("diagnostic");
|
||||
|
||||
assert_eq!(
|
||||
diagnostic["request_body_build_error"]["path"],
|
||||
"$.endpoint.body_rules"
|
||||
);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user