mirror of
https://github.com/fawney19/Aether.git
synced 2026-10-11 11:49:50 +08:00
refactor(workspace): enforce layered crate boundaries
This commit is contained in:
elky
@@ -0,0 +1,752 @@
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use std::collections::BTreeMap;
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use url::form_urlencoded;
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use url::Url;
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pub fn build_openai_chat_url(upstream_base_url: &str, query: Option<&str>) -> String {
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let (trimmed, base_query) = split_base_url_query(upstream_base_url);
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let trimmed = trimmed.trim_end_matches('/');
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let mut url = format!("{trimmed}/chat/completions");
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append_merged_query(&mut url, base_query, None, query, &[]);
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url
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}
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pub fn build_openai_responses_url(
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upstream_base_url: &str,
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query: Option<&str>,
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compact: bool,
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) -> String {
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let (trimmed, base_query) = split_base_url_query(upstream_base_url);
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let trimmed = trimmed.trim_end_matches('/');
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let suffix = if compact {
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"/responses/compact"
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} else {
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"/responses"
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};
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let mut url = format!("{trimmed}{suffix}");
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append_merged_query(&mut url, base_query, None, query, &[]);
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url
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}
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pub fn build_openai_search_url(upstream_base_url: &str, query: Option<&str>) -> String {
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let (trimmed, base_query) = split_base_url_query(upstream_base_url);
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let trimmed = trimmed.trim_end_matches('/');
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let mut url = format!("{trimmed}/alpha/search");
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append_merged_query(&mut url, base_query, None, query, &[]);
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url
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}
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pub fn build_openai_image_url(
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upstream_base_url: &str,
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request_path: Option<&str>,
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query: Option<&str>,
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) -> String {
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let (trimmed, base_query) = split_base_url_query(upstream_base_url);
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let trimmed = trimmed.trim_end_matches('/');
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let suffix = openai_image_path_suffix(request_path);
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let mut url = if openai_image_base_includes_operation_path(trimmed) {
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trimmed.to_string()
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} else {
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format!("{trimmed}{suffix}")
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};
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append_merged_query(&mut url, base_query, None, query, &[]);
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url
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}
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fn openai_image_path_suffix(request_path: Option<&str>) -> &'static str {
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match request_path
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.map(str::trim)
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.map(|value| value.trim_end_matches('/'))
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{
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Some("/v1/images/edits") | Some("/images/edits") => "/images/edits",
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_ => "/images/generations",
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}
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}
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fn openai_image_base_includes_operation_path(base_url: &str) -> bool {
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let path = Url::parse(base_url)
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.ok()
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.map(|url| url.path().trim_end_matches('/').to_string())
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.unwrap_or_else(|| base_url.trim_end_matches('/').to_string());
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path.ends_with("/images/generations") || path.ends_with("/images/edits")
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}
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pub fn build_claude_messages_url(upstream_base_url: &str, query: Option<&str>) -> String {
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let (trimmed, base_query) = split_base_url_query(upstream_base_url);
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let trimmed = trimmed.trim_end_matches('/');
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let mut url = format!("{trimmed}/messages");
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append_merged_query(&mut url, base_query, None, query, &[]);
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url
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}
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pub fn build_gemini_content_url(
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upstream_base_url: &str,
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model: &str,
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stream: bool,
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query: Option<&str>,
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) -> Option<String> {
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let (trimmed_base_url, base_query) = split_base_url_query(upstream_base_url);
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let trimmed_base_url = trimmed_base_url.trim_end_matches('/');
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let trimmed_model = model.trim();
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if trimmed_base_url.is_empty() || trimmed_model.is_empty() {
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return None;
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}
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let operation = if stream {
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"streamGenerateContent"
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} else {
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"generateContent"
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};
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let mut url = if trimmed_base_url.ends_with("/v1") || trimmed_base_url.ends_with("/v1beta") {
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format!("{trimmed_base_url}/models/{trimmed_model}:{operation}")
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} else if gemini_content_base_url_contains_model_path(trimmed_base_url) {
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let trimmed_base_url = strip_gemini_content_action(trimmed_base_url);
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format!("{trimmed_base_url}:{operation}")
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} else {
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format!("{trimmed_base_url}/v1beta/models/{trimmed_model}:{operation}")
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};
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append_merged_query(&mut url, base_query, None, query, &["key"]);
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Some(url)
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}
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pub fn normalize_gemini_content_action_path(path: &str, stream: bool) -> String {
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let trimmed = path.trim();
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let (path, query) = split_path_query(trimmed);
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let action = if stream {
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"streamGenerateContent"
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} else {
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"generateContent"
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};
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let normalized = strip_gemini_content_action(path);
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let normalized = if normalized.len() == path.len() {
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path.to_string()
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} else {
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format!("{normalized}:{action}")
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};
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match query {
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Some(query) => format!("{normalized}?{query}"),
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None => normalized,
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}
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}
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fn strip_gemini_content_action(value: &str) -> &str {
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value
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.strip_suffix(":streamGenerateContent")
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.or_else(|| value.strip_suffix(":generateContent"))
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.unwrap_or(value)
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}
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fn gemini_content_base_url_contains_model_path(value: &str) -> bool {
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value.contains("/v1/models/") || value.contains("/v1beta/models/")
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}
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pub fn build_gemini_video_predict_long_running_url(
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upstream_base_url: &str,
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model: &str,
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query: Option<&str>,
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) -> Option<String> {
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let (trimmed_base_url, base_query) = split_base_url_query(upstream_base_url);
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let trimmed_base_url = trimmed_base_url.trim_end_matches('/');
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let trimmed_model = model.trim();
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if trimmed_base_url.is_empty() || trimmed_model.is_empty() {
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return None;
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}
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let mut url = if trimmed_base_url.ends_with("/v1") || trimmed_base_url.ends_with("/v1beta") {
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format!("{trimmed_base_url}/models/{trimmed_model}:predictLongRunning")
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} else if gemini_content_base_url_contains_model_path(trimmed_base_url) {
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format!("{trimmed_base_url}:predictLongRunning")
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} else {
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format!("{trimmed_base_url}/v1beta/models/{trimmed_model}:predictLongRunning")
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};
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append_merged_query(&mut url, base_query, None, query, &["key"]);
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Some(url)
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}
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pub fn build_passthrough_path_url(
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upstream_base_url: &str,
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path: &str,
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query: Option<&str>,
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blocked_keys: &[&str],
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) -> Option<String> {
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let (trimmed_base_url, base_query) = split_base_url_query(upstream_base_url);
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let trimmed_base_url = trimmed_base_url.trim_end_matches('/');
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let trimmed_path = path.trim();
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if trimmed_base_url.is_empty() || trimmed_path.is_empty() {
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return None;
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}
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let (trimmed_path, path_query) = split_path_query(trimmed_path);
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let normalized_base_url =
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if trimmed_base_url.ends_with("/v1beta") && trimmed_path.starts_with("/v1beta") {
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trimmed_base_url.trim_end_matches("/v1beta")
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} else if trimmed_base_url.ends_with("/v1") && trimmed_path.starts_with("/v1/") {
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trimmed_base_url.trim_end_matches("/v1")
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} else {
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trimmed_base_url
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};
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let mut url = format!("{normalized_base_url}{trimmed_path}");
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append_merged_query(&mut url, base_query, path_query, query, blocked_keys);
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Some(url)
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}
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pub fn build_bigmodel_coding_models_url(upstream_base_url: &str) -> Option<String> {
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let (trimmed_base_url, base_query) = split_base_url_query(upstream_base_url);
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let trimmed_base_url = trimmed_base_url.trim_end_matches('/');
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if trimmed_base_url.is_empty() || !bigmodel_coding_models_base_is_supported(trimmed_base_url) {
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return None;
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}
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let path = Url::parse(trimmed_base_url)
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.ok()
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.map(|url| url.path().trim_end_matches('/').to_string())
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.unwrap_or_else(|| trimmed_base_url.trim_end_matches('/').to_string());
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let mut url = if path.ends_with("/models") {
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trimmed_base_url.to_string()
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} else {
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format!("{trimmed_base_url}/models")
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};
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append_merged_query(&mut url, base_query, None, None, &[]);
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Some(url)
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}
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pub fn build_openai_compatible_models_url(upstream_base_url: &str) -> Option<String> {
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if let Some(url) = build_bigmodel_coding_models_url(upstream_base_url) {
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return Some(url);
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}
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let (trimmed_base_url, base_query) = split_base_url_query(upstream_base_url);
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let trimmed_base_url = trimmed_base_url.trim_end_matches('/');
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if trimmed_base_url.is_empty() {
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return None;
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}
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let mut url = if trimmed_base_url.ends_with("/models") {
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trimmed_base_url.to_string()
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} else {
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format!("{trimmed_base_url}/models")
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};
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append_merged_query(&mut url, base_query, None, None, &[]);
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Some(url)
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}
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pub fn build_gemini_files_passthrough_url(
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upstream_base_url: &str,
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path: &str,
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query: Option<&str>,
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) -> Option<String> {
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let (trimmed_base_url, base_query) = split_base_url_query(upstream_base_url);
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let trimmed_base_url = trimmed_base_url.trim_end_matches('/');
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let trimmed_path = path.trim();
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if trimmed_base_url.is_empty() || trimmed_path.is_empty() {
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return None;
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}
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let (trimmed_path, path_query) = split_path_query(trimmed_path);
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let normalized_base_url = if trimmed_base_url.ends_with("/v1beta")
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&& (trimmed_path.starts_with("/v1beta/") || trimmed_path.starts_with("/upload/v1beta/"))
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{
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trimmed_base_url.trim_end_matches("/v1beta")
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} else {
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trimmed_base_url
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};
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let mut url = format!("{normalized_base_url}{trimmed_path}");
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append_merged_query(&mut url, base_query, path_query, query, &["key"]);
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Some(url)
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}
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fn split_base_url_query(base_url: &str) -> (&str, Option<&str>) {
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let trimmed = base_url.trim();
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trimmed
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.split_once('?')
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.map(|(base, query)| (base, Some(query)))
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.unwrap_or((trimmed, None))
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}
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pub(crate) fn google_openai_compat_base_includes_api_root(base_url: &str) -> bool {
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let Ok(parsed) = Url::parse(base_url.trim()) else {
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return false;
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};
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let Some(host) = parsed.host_str().map(|value| value.to_ascii_lowercase()) else {
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return false;
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};
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let path = parsed.path().trim_end_matches('/');
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if host == "generativelanguage.googleapis.com" {
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return path == "/v1beta/openai" || path == "/v1/openai";
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}
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if looks_like_vertex_ai_host(&host) {
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return path.ends_with("/endpoints/openapi");
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}
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false
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}
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pub fn openai_compatible_base_includes_api_root(base_url: &str) -> bool {
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let trimmed = base_url.trim().trim_end_matches('/');
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trimmed.ends_with("/v1")
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|| google_openai_compat_base_includes_api_root(trimmed)
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|| bigmodel_coding_base_includes_api_root(trimmed)
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|| openai_compatible_base_includes_unversioned_api_root(trimmed)
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}
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pub fn v1_compatible_base_includes_api_root(base_url: &str) -> bool {
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let trimmed = base_url.trim().trim_end_matches('/');
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trimmed.ends_with("/v1") || openai_compatible_base_includes_unversioned_api_root(trimmed)
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}
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pub fn openai_compatible_base_includes_unversioned_api_root(base_url: &str) -> bool {
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let trimmed = base_url.trim().trim_end_matches('/');
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let path = Url::parse(trimmed)
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.ok()
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.map(|url| url.path().trim_end_matches('/').to_ascii_lowercase())
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.unwrap_or_else(|| {
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trimmed
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.split_once('/')
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.map(|(_, path)| format!("/{path}"))
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.unwrap_or_default()
|
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.trim_end_matches('/')
|
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.to_ascii_lowercase()
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});
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!path.is_empty()
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}
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fn bigmodel_coding_base_includes_api_root(base_url: &str) -> bool {
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let Ok(parsed) = Url::parse(base_url.trim()) else {
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return false;
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};
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let Some(host) = parsed.host_str().map(|value| value.to_ascii_lowercase()) else {
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return false;
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||||
};
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host == "open.bigmodel.cn" && parsed.path().trim_end_matches('/') == "/api/coding/paas/v4"
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}
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fn bigmodel_coding_models_base_is_supported(base_url: &str) -> bool {
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let Ok(parsed) = Url::parse(base_url.trim()) else {
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return false;
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};
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let Some(host) = parsed.host_str().map(|value| value.to_ascii_lowercase()) else {
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return false;
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};
|
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if host != "open.bigmodel.cn" {
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return false;
|
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}
|
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matches!(
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parsed.path().trim_end_matches('/'),
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"/api/coding/paas/v4" | "/api/coding/paas/v4/models"
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||||
)
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}
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fn looks_like_vertex_ai_host(host: &str) -> bool {
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const VERTEX_AI_HOST: &str = "aiplatform.googleapis.com";
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host == VERTEX_AI_HOST
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||||
|| host.ends_with(&format!(".{VERTEX_AI_HOST}"))
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|| host.ends_with(&format!("-{VERTEX_AI_HOST}"))
|
||||
}
|
||||
|
||||
fn split_path_query(path: &str) -> (&str, Option<&str>) {
|
||||
path.split_once('?')
|
||||
.map(|(path, query)| (path, Some(query)))
|
||||
.unwrap_or((path, None))
|
||||
}
|
||||
|
||||
fn append_merged_query(
|
||||
url: &mut String,
|
||||
base_query: Option<&str>,
|
||||
path_query: Option<&str>,
|
||||
request_query: Option<&str>,
|
||||
blocked_keys: &[&str],
|
||||
) {
|
||||
let Some(query) = merge_query_layers(base_query, path_query, request_query, blocked_keys)
|
||||
else {
|
||||
return;
|
||||
};
|
||||
if url.contains('?') {
|
||||
url.push('&');
|
||||
} else {
|
||||
url.push('?');
|
||||
}
|
||||
url.push_str(&query);
|
||||
}
|
||||
|
||||
fn merge_query_layers(
|
||||
base_query: Option<&str>,
|
||||
path_query: Option<&str>,
|
||||
request_query: Option<&str>,
|
||||
blocked_keys: &[&str],
|
||||
) -> Option<String> {
|
||||
if blocked_keys.is_empty()
|
||||
&& path_query.is_none()
|
||||
&& base_query.is_none()
|
||||
&& request_query
|
||||
.map(str::trim)
|
||||
.is_some_and(|value| !value.is_empty())
|
||||
{
|
||||
return request_query
|
||||
.map(str::trim)
|
||||
.filter(|value| !value.is_empty())
|
||||
.map(ToOwned::to_owned);
|
||||
}
|
||||
|
||||
let mut merged = BTreeMap::new();
|
||||
for source in [base_query, path_query, request_query] {
|
||||
merge_query_string(&mut merged, source, blocked_keys);
|
||||
}
|
||||
if merged.is_empty() {
|
||||
return None;
|
||||
}
|
||||
|
||||
let mut serializer = form_urlencoded::Serializer::new(String::new());
|
||||
for (key, value) in merged {
|
||||
serializer.append_pair(&key, &value);
|
||||
}
|
||||
Some(serializer.finish())
|
||||
}
|
||||
|
||||
fn merge_query_string(
|
||||
out: &mut BTreeMap<String, String>,
|
||||
query: Option<&str>,
|
||||
blocked_keys: &[&str],
|
||||
) {
|
||||
let Some(query) = query.map(str::trim).filter(|value| !value.is_empty()) else {
|
||||
return;
|
||||
};
|
||||
|
||||
for (key, value) in form_urlencoded::parse(query.as_bytes()) {
|
||||
if blocked_keys
|
||||
.iter()
|
||||
.any(|blocked| key.as_ref().eq_ignore_ascii_case(blocked))
|
||||
{
|
||||
continue;
|
||||
}
|
||||
out.insert(key.into_owned(), value.into_owned());
|
||||
}
|
||||
}
|
||||
|
||||
#[cfg(test)]
|
||||
mod tests {
|
||||
use super::{
|
||||
build_bigmodel_coding_models_url, build_claude_messages_url, build_gemini_content_url,
|
||||
build_gemini_files_passthrough_url, build_gemini_video_predict_long_running_url,
|
||||
build_openai_chat_url, build_openai_compatible_models_url, build_openai_image_url,
|
||||
build_openai_responses_url, build_openai_search_url, build_passthrough_path_url,
|
||||
normalize_gemini_content_action_path,
|
||||
};
|
||||
|
||||
#[test]
|
||||
fn merges_base_url_query_for_same_format_urls() {
|
||||
assert_eq!(
|
||||
build_openai_chat_url(
|
||||
"https://api.openai.example/v1?tenant=demo",
|
||||
Some("mode=fast&tenant=override")
|
||||
),
|
||||
"https://api.openai.example/v1/chat/completions?mode=fast&tenant=override"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_chat_url_preserves_google_openai_compat_roots() {
|
||||
assert_eq!(
|
||||
build_openai_chat_url(
|
||||
"https://generativelanguage.googleapis.com/v1beta/openai",
|
||||
Some("trace=1")
|
||||
),
|
||||
"https://generativelanguage.googleapis.com/v1beta/openai/chat/completions?trace=1"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_chat_url(
|
||||
"https://aiplatform.googleapis.com/v1/projects/project-1/locations/global/endpoints/openapi",
|
||||
None,
|
||||
),
|
||||
"https://aiplatform.googleapis.com/v1/projects/project-1/locations/global/endpoints/openapi/chat/completions"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_urls_preserve_bigmodel_coding_api_root() {
|
||||
assert_eq!(
|
||||
build_openai_chat_url(
|
||||
"https://open.bigmodel.cn/api/coding/paas/v4",
|
||||
Some("trace=1")
|
||||
),
|
||||
"https://open.bigmodel.cn/api/coding/paas/v4/chat/completions?trace=1"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_responses_url("https://open.bigmodel.cn/api/coding/paas/v4", None, false),
|
||||
"https://open.bigmodel.cn/api/coding/paas/v4/responses"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_urls_preserve_unversioned_api_root() {
|
||||
assert_eq!(
|
||||
build_openai_chat_url("https://proxy.example.com/api", Some("trace=1")),
|
||||
"https://proxy.example.com/api/chat/completions?trace=1"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_chat_url("https://proxy.example.com/openai", None),
|
||||
"https://proxy.example.com/openai/chat/completions"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_chat_url("https://proxy.example.com", None),
|
||||
"https://proxy.example.com/chat/completions"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_chat_url("https://api.deepseek.com", None),
|
||||
"https://api.deepseek.com/chat/completions"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_responses_url("https://proxy.example.com/api", None, false),
|
||||
"https://proxy.example.com/api/responses"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_responses_url("https://api.deepseek.com", None, false),
|
||||
"https://api.deepseek.com/responses"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_image_url(
|
||||
"https://proxy.example.com/api",
|
||||
Some("/v1/images/generations"),
|
||||
None
|
||||
),
|
||||
"https://proxy.example.com/api/images/generations"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn claude_messages_url_preserves_v1_and_unversioned_api_roots() {
|
||||
assert_eq!(
|
||||
build_claude_messages_url("https://api.anthropic.example/v1", Some("trace=1")),
|
||||
"https://api.anthropic.example/v1/messages?trace=1"
|
||||
);
|
||||
assert_eq!(
|
||||
build_claude_messages_url("https://proxy.example.com/api", None),
|
||||
"https://proxy.example.com/api/messages"
|
||||
);
|
||||
assert_eq!(
|
||||
build_claude_messages_url("https://proxy.example.com/anthropic", None),
|
||||
"https://proxy.example.com/anthropic/messages"
|
||||
);
|
||||
assert_eq!(
|
||||
build_claude_messages_url("https://api.anthropic.example", None),
|
||||
"https://api.anthropic.example/messages"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn bigmodel_coding_models_url_uses_models_resource() {
|
||||
assert_eq!(
|
||||
build_bigmodel_coding_models_url(
|
||||
"https://open.bigmodel.cn/api/coding/paas/v4?tenant=demo"
|
||||
)
|
||||
.as_deref(),
|
||||
Some("https://open.bigmodel.cn/api/coding/paas/v4/models?tenant=demo")
|
||||
);
|
||||
assert_eq!(
|
||||
build_bigmodel_coding_models_url("https://open.bigmodel.cn/api/coding/paas/v4/models")
|
||||
.as_deref(),
|
||||
Some("https://open.bigmodel.cn/api/coding/paas/v4/models")
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_compatible_models_url_preserves_unversioned_api_root() {
|
||||
assert_eq!(
|
||||
build_openai_compatible_models_url("https://proxy.example.com/api?tenant=demo")
|
||||
.as_deref(),
|
||||
Some("https://proxy.example.com/api/models?tenant=demo")
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_compatible_models_url("https://proxy.example.com/openai").as_deref(),
|
||||
Some("https://proxy.example.com/openai/models")
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_compatible_models_url("https://proxy.example.com").as_deref(),
|
||||
Some("https://proxy.example.com/models")
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_responses_url_preserves_codex_path_prefix() {
|
||||
assert_eq!(
|
||||
build_openai_responses_url("https://tiger.bookapi.cc/codex", None, false),
|
||||
"https://tiger.bookapi.cc/codex/responses"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_responses_url("https://tiger.bookapi.cc/codex?tenant=demo", None, true),
|
||||
"https://tiger.bookapi.cc/codex/responses/compact?tenant=demo"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_search_url_preserves_api_and_codex_roots() {
|
||||
assert_eq!(
|
||||
build_openai_search_url(
|
||||
"https://api.openai.com/v1?tenant=base",
|
||||
Some("trace=1&tenant=request")
|
||||
),
|
||||
"https://api.openai.com/v1/alpha/search?tenant=request&trace=1"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_search_url("https://chatgpt.com/backend-api/codex/", None),
|
||||
"https://chatgpt.com/backend-api/codex/alpha/search"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn openai_image_url_uses_images_surface() {
|
||||
assert_eq!(
|
||||
build_openai_image_url(
|
||||
"https://api.openai.example/v1?tenant=demo",
|
||||
Some("/v1/images/generations"),
|
||||
Some("trace=1")
|
||||
),
|
||||
"https://api.openai.example/v1/images/generations?tenant=demo&trace=1"
|
||||
);
|
||||
assert_eq!(
|
||||
build_openai_image_url(
|
||||
"https://api.openai.example/v1",
|
||||
Some("/v1/images/edits"),
|
||||
None
|
||||
),
|
||||
"https://api.openai.example/v1/images/edits"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn merges_base_url_query_for_dynamic_gemini_content_urls() {
|
||||
assert_eq!(
|
||||
build_gemini_content_url(
|
||||
"https://generativelanguage.googleapis.com/v1beta?alt=sse",
|
||||
"gemini-2.5-pro",
|
||||
true,
|
||||
Some("foo=bar&key=secret")
|
||||
)
|
||||
.as_deref(),
|
||||
Some(
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:streamGenerateContent?alt=sse&foo=bar"
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn gemini_content_urls_rewrite_existing_base_action_for_stream_mode() {
|
||||
assert_eq!(
|
||||
build_gemini_content_url(
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:generateContent",
|
||||
"ignored-model",
|
||||
true,
|
||||
Some("foo=bar")
|
||||
)
|
||||
.as_deref(),
|
||||
Some(
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:streamGenerateContent?foo=bar"
|
||||
)
|
||||
);
|
||||
assert_eq!(
|
||||
build_gemini_content_url(
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:streamGenerateContent",
|
||||
"ignored-model",
|
||||
false,
|
||||
Some("foo=bar")
|
||||
)
|
||||
.as_deref(),
|
||||
Some(
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:generateContent?foo=bar"
|
||||
)
|
||||
);
|
||||
assert_eq!(
|
||||
build_gemini_content_url(
|
||||
"https://generativelanguage.googleapis.com/v1/models/gemini-2.5-pro:generateContent",
|
||||
"ignored-model",
|
||||
true,
|
||||
Some("foo=bar")
|
||||
)
|
||||
.as_deref(),
|
||||
Some(
|
||||
"https://generativelanguage.googleapis.com/v1/models/gemini-2.5-pro:streamGenerateContent?foo=bar"
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn normalizes_gemini_content_action_in_custom_paths() {
|
||||
assert_eq!(
|
||||
normalize_gemini_content_action_path(
|
||||
"/v1beta/models/gemini-2.5-pro:generateContent?alt=sse",
|
||||
true
|
||||
),
|
||||
"/v1beta/models/gemini-2.5-pro:streamGenerateContent?alt=sse"
|
||||
);
|
||||
assert_eq!(
|
||||
normalize_gemini_content_action_path(
|
||||
"/v1beta/models/gemini-2.5-pro:streamGenerateContent",
|
||||
false
|
||||
),
|
||||
"/v1beta/models/gemini-2.5-pro:generateContent"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn merges_base_path_and_request_query_for_passthrough_paths() {
|
||||
assert_eq!(
|
||||
build_passthrough_path_url(
|
||||
"https://api.openai.example/v1?tenant=demo",
|
||||
"/videos/generations?variant=video",
|
||||
Some("size=1024"),
|
||||
&[]
|
||||
)
|
||||
.as_deref(),
|
||||
Some(
|
||||
"https://api.openai.example/v1/videos/generations?size=1024&tenant=demo&variant=video"
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn passthrough_path_does_not_duplicate_openai_v1_root() {
|
||||
assert_eq!(
|
||||
build_passthrough_path_url(
|
||||
"https://api.openai.example/v1?tenant=demo",
|
||||
"/v1/chat/completions?variant=chat",
|
||||
Some("trace=1"),
|
||||
&[]
|
||||
)
|
||||
.as_deref(),
|
||||
Some("https://api.openai.example/v1/chat/completions?tenant=demo&trace=1&variant=chat")
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn merges_base_url_query_for_gemini_files_passthrough_urls() {
|
||||
assert_eq!(
|
||||
build_gemini_files_passthrough_url(
|
||||
"https://generativelanguage.googleapis.com/v1beta?alt=media",
|
||||
"/upload/v1beta/files?uploadType=resumable",
|
||||
Some("key=secret&pageSize=10")
|
||||
)
|
||||
.as_deref(),
|
||||
Some(
|
||||
"https://generativelanguage.googleapis.com/upload/v1beta/files?alt=media&pageSize=10&uploadType=resumable"
|
||||
)
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn merges_base_url_query_for_gemini_video_urls() {
|
||||
assert_eq!(
|
||||
build_gemini_video_predict_long_running_url(
|
||||
"https://generativelanguage.googleapis.com/v1beta?alt=sse",
|
||||
"veo-3.0-generate-preview",
|
||||
Some("foo=bar&key=secret")
|
||||
)
|
||||
.as_deref(),
|
||||
Some(
|
||||
"https://generativelanguage.googleapis.com/v1beta/models/veo-3.0-generate-preview:predictLongRunning?alt=sse&foo=bar"
|
||||
)
|
||||
);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user