fix(providers): harden tool fallback and refresh model catalogs
This commit is contained in:
Chummy
parent
43494f8331
commit
b4b379e3e7
9 changed files with 1111 additions and 367 deletions
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@ -476,6 +476,19 @@ fn canonical_provider_name(provider_name: &str) -> &str {
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}
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}
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fn allows_unauthenticated_model_fetch(provider_name: &str) -> bool {
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matches!(
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canonical_provider_name(provider_name),
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"openrouter"
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| "ollama"
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| "venice"
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| "astrai"
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| "nvidia"
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| "nvidia-nim"
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| "build.nvidia.com"
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)
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}
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/// Pick a sensible default model for the given provider.
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const MINIMAX_ONBOARD_MODELS: [(&str, &str); 5] = [
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("MiniMax-M2.5", "MiniMax M2.5 (latest, recommended)"),
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@ -488,16 +501,28 @@ const MINIMAX_ONBOARD_MODELS: [(&str, &str); 5] = [
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fn default_model_for_provider(provider: &str) -> String {
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match canonical_provider_name(provider) {
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"anthropic" => "claude-sonnet-4-5-20250929".into(),
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"openrouter" => "anthropic/claude-sonnet-4.6".into(),
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"openai" => "gpt-5.2".into(),
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"openai-codex" => "gpt-5-codex".into(),
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"venice" => "zai-org-glm-5".into(),
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"groq" => "llama-3.3-70b-versatile".into(),
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"mistral" => "mistral-large-latest".into(),
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"deepseek" => "deepseek-chat".into(),
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"xai" => "grok-4-1-fast-reasoning".into(),
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"perplexity" => "sonar-pro".into(),
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"fireworks" => "accounts/fireworks/models/llama-v3p3-70b-instruct".into(),
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"together-ai" => "meta-llama/Llama-3.3-70B-Instruct-Turbo".into(),
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"cohere" => "command-a-03-2025".into(),
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"moonshot" => "kimi-k2.5".into(),
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"glm" | "zai" => "glm-5".into(),
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"minimax" => "MiniMax-M2.5".into(),
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"qwen" => "qwen-plus".into(),
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"ollama" => "llama3.2".into(),
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"groq" => "llama-3.3-70b-versatile".into(),
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"deepseek" => "deepseek-chat".into(),
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"gemini" => "gemini-2.5-pro".into(),
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"kimi-code" => "kimi-for-coding".into(),
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_ => "anthropic/claude-sonnet-4.5".into(),
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"nvidia" | "nvidia-nim" | "build.nvidia.com" => "meta/llama-3.3-70b-instruct".into(),
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"astrai" => "anthropic/claude-sonnet-4.6".into(),
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_ => "anthropic/claude-sonnet-4.6".into(),
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}
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}
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@ -505,8 +530,8 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
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match canonical_provider_name(provider_name) {
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"openrouter" => vec![
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(
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"anthropic/claude-sonnet-4.5".to_string(),
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"Claude Sonnet 4.5 (balanced, recommended)".to_string(),
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"anthropic/claude-sonnet-4.6".to_string(),
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"Claude Sonnet 4.6 (balanced, recommended)".to_string(),
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),
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(
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"openai/gpt-5.2".to_string(),
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@ -565,18 +590,33 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
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"GPT-5.2 Codex (agentic coding)".to_string(),
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),
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],
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"openai-codex" => vec![
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(
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"gpt-5-codex".to_string(),
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"GPT-5 Codex (recommended)".to_string(),
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),
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(
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"gpt-5.2-codex".to_string(),
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"GPT-5.2 Codex (agentic coding)".to_string(),
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),
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("o4-mini".to_string(), "o4-mini (fallback)".to_string()),
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],
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"venice" => vec![
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(
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"llama-3.3-70b".to_string(),
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"Llama 3.3 70B (default, fast)".to_string(),
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"zai-org-glm-5".to_string(),
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"GLM-5 via Venice (agentic flagship)".to_string(),
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),
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(
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"claude-opus-45".to_string(),
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"Claude Opus 4.5 via Venice (strongest)".to_string(),
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"claude-sonnet-4-6".to_string(),
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"Claude Sonnet 4.6 via Venice (best quality)".to_string(),
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),
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(
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"llama-3.1-405b".to_string(),
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"Llama 3.1 405B (largest open source)".to_string(),
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"deepseek-v3.2".to_string(),
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"DeepSeek V3.2 via Venice (strong value)".to_string(),
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),
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(
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"grok-41-fast".to_string(),
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"Grok 4.1 Fast via Venice (low latency)".to_string(),
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),
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],
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"groq" => vec![
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@ -701,27 +741,27 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
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],
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"moonshot" => vec![
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(
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"kimi-latest".to_string(),
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"Kimi Latest (rolling latest assistant model)".to_string(),
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"kimi-k2.5".to_string(),
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"Kimi K2.5 (latest flagship, recommended)".to_string(),
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),
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(
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"kimi-k2-thinking".to_string(),
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"Kimi K2 Thinking (deep reasoning + tool use)".to_string(),
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),
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(
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"kimi-k2-0905-preview".to_string(),
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"Kimi K2 0905 Preview (strong coding)".to_string(),
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),
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(
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"kimi-thinking-preview".to_string(),
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"Kimi Thinking Preview (deep reasoning)".to_string(),
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),
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],
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"glm" | "zai" => vec![
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(
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"glm-4.7".to_string(),
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"GLM-4.7 (latest flagship)".to_string(),
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),
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("glm-5".to_string(), "GLM-5 (high reasoning)".to_string()),
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(
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"glm-4-plus".to_string(),
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"GLM-4 Plus (stable baseline)".to_string(),
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"glm-4.7".to_string(),
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"GLM-4.7 (strong general-purpose quality)".to_string(),
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),
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(
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"glm-4.5-air".to_string(),
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"GLM-4.5 Air (lower latency)".to_string(),
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),
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],
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"minimax" => vec![
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@ -730,12 +770,12 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
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"MiniMax M2.5 (latest flagship)".to_string(),
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),
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(
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"MiniMax-M2.1".to_string(),
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"MiniMax M2.1 (strong coding/reasoning)".to_string(),
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"MiniMax-M2.5-highspeed".to_string(),
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"MiniMax M2.5 High-Speed (fast)".to_string(),
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),
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(
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"MiniMax-M2.1-lightning".to_string(),
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"MiniMax M2.1 Lightning (fast)".to_string(),
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"MiniMax-M2.1".to_string(),
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"MiniMax M2.1 (strong coding/reasoning)".to_string(),
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),
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],
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"qwen" => vec![
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@ -752,6 +792,42 @@ fn curated_models_for_provider(provider_name: &str) -> Vec<(String, String)> {
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"Qwen Turbo (fast and cost-efficient)".to_string(),
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),
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],
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"nvidia" | "nvidia-nim" | "build.nvidia.com" => vec![
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(
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"meta/llama-3.3-70b-instruct".to_string(),
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"Llama 3.3 70B Instruct (balanced default)".to_string(),
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),
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(
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"deepseek-ai/deepseek-v3.2".to_string(),
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"DeepSeek V3.2 (reasoning + coding)".to_string(),
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),
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(
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"google/gemma-3-27b-it".to_string(),
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"Gemma 3 27B IT (cost-efficient)".to_string(),
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),
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(
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"meta/llama-3.1-405b-instruct".to_string(),
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"Llama 3.1 405B Instruct (max quality)".to_string(),
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),
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],
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"astrai" => vec![
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(
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"anthropic/claude-sonnet-4.6".to_string(),
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"Claude Sonnet 4.6 (balanced default)".to_string(),
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),
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(
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"openai/gpt-5.2".to_string(),
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"GPT-5.2 (latest flagship)".to_string(),
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),
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(
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"deepseek/deepseek-v3.2".to_string(),
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"DeepSeek V3.2 (agentic + affordable)".to_string(),
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),
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(
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"z-ai/glm-5".to_string(),
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"GLM-5 (high reasoning)".to_string(),
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),
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],
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"ollama" => vec![
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(
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"llama3.2".to_string(),
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@ -797,9 +873,49 @@ fn supports_live_model_fetch(provider_name: &str) -> bool {
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| "gemini"
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| "ollama"
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| "astrai"
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| "venice"
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| "fireworks"
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| "cohere"
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| "moonshot"
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| "glm"
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| "zai"
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| "qwen"
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| "nvidia"
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| "nvidia-nim"
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| "build.nvidia.com"
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)
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}
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fn models_endpoint_for_provider(provider_name: &str) -> Option<&'static str> {
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match provider_name {
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"qwen-intl" => Some("https://dashscope-intl.aliyuncs.com/compatible-mode/v1/models"),
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"dashscope-us" => Some("https://dashscope-us.aliyuncs.com/compatible-mode/v1/models"),
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"moonshot-cn" | "kimi-cn" => Some("https://api.moonshot.cn/v1/models"),
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"glm-cn" | "bigmodel" => Some("https://open.bigmodel.cn/api/paas/v4/models"),
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"zai-cn" | "z.ai-cn" => Some("https://open.bigmodel.cn/api/coding/paas/v4/models"),
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_ => match canonical_provider_name(provider_name) {
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"openai" => Some("https://api.openai.com/v1/models"),
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"venice" => Some("https://api.venice.ai/api/v1/models"),
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"groq" => Some("https://api.groq.com/openai/v1/models"),
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"mistral" => Some("https://api.mistral.ai/v1/models"),
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"deepseek" => Some("https://api.deepseek.com/v1/models"),
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"xai" => Some("https://api.x.ai/v1/models"),
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"together-ai" => Some("https://api.together.xyz/v1/models"),
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"fireworks" => Some("https://api.fireworks.ai/inference/v1/models"),
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"cohere" => Some("https://api.cohere.com/compatibility/v1/models"),
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"moonshot" => Some("https://api.moonshot.ai/v1/models"),
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"glm" => Some("https://api.z.ai/api/paas/v4/models"),
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"zai" => Some("https://api.z.ai/api/coding/paas/v4/models"),
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"qwen" => Some("https://dashscope.aliyuncs.com/compatible-mode/v1/models"),
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"nvidia" | "nvidia-nim" | "build.nvidia.com" => {
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Some("https://integrate.api.nvidia.com/v1/models")
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}
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"astrai" => Some("https://as-trai.com/v1/models"),
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_ => None,
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},
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}
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}
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fn build_model_fetch_client() -> Result<reqwest::blocking::Client> {
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reqwest::blocking::Client::builder()
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.timeout(Duration::from_secs(8))
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@ -882,15 +998,21 @@ fn parse_ollama_model_ids(payload: &Value) -> Vec<String> {
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normalize_model_ids(ids)
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}
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fn fetch_openai_compatible_models(endpoint: &str, api_key: Option<&str>) -> Result<Vec<String>> {
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let Some(api_key) = api_key else {
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return Ok(Vec::new());
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};
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fn fetch_openai_compatible_models(
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endpoint: &str,
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api_key: Option<&str>,
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allow_unauthenticated: bool,
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) -> Result<Vec<String>> {
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let client = build_model_fetch_client()?;
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let payload: Value = client
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.get(endpoint)
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.bearer_auth(api_key)
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let mut request = client.get(endpoint);
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if let Some(api_key) = api_key {
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request = request.bearer_auth(api_key);
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} else if !allow_unauthenticated {
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bail!("model fetch requires API key for endpoint {endpoint}");
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}
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let payload: Value = request
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.send()
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.and_then(reqwest::blocking::Response::error_for_status)
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.with_context(|| format!("model fetch failed: GET {endpoint}"))?
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@ -919,7 +1041,7 @@ fn fetch_openrouter_models(api_key: Option<&str>) -> Result<Vec<String>> {
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fn fetch_anthropic_models(api_key: Option<&str>) -> Result<Vec<String>> {
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let Some(api_key) = api_key else {
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return Ok(Vec::new());
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bail!("Anthropic model fetch requires API key or OAuth token");
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};
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let client = build_model_fetch_client()?;
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@ -954,7 +1076,7 @@ fn fetch_anthropic_models(api_key: Option<&str>) -> Result<Vec<String>> {
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fn fetch_gemini_models(api_key: Option<&str>) -> Result<Vec<String>> {
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let Some(api_key) = api_key else {
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return Ok(Vec::new());
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bail!("Gemini model fetch requires API key");
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};
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let client = build_model_fetch_client()?;
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@ -984,6 +1106,7 @@ fn fetch_ollama_models() -> Result<Vec<String>> {
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}
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fn fetch_live_models_for_provider(provider_name: &str, api_key: &str) -> Result<Vec<String>> {
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let requested_provider_name = provider_name;
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let provider_name = canonical_provider_name(provider_name);
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let api_key = if api_key.trim().is_empty() {
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std::env::var(provider_env_var(provider_name))
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@ -1006,25 +1129,6 @@ fn fetch_live_models_for_provider(provider_name: &str, api_key: &str) -> Result<
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let models = match provider_name {
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"openrouter" => fetch_openrouter_models(api_key.as_deref())?,
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"openai" => {
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fetch_openai_compatible_models("https://api.openai.com/v1/models", api_key.as_deref())?
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}
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"groq" => fetch_openai_compatible_models(
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"https://api.groq.com/openai/v1/models",
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api_key.as_deref(),
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)?,
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"mistral" => {
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fetch_openai_compatible_models("https://api.mistral.ai/v1/models", api_key.as_deref())?
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}
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"deepseek" => fetch_openai_compatible_models(
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"https://api.deepseek.com/v1/models",
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api_key.as_deref(),
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)?,
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"xai" => fetch_openai_compatible_models("https://api.x.ai/v1/models", api_key.as_deref())?,
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"together-ai" => fetch_openai_compatible_models(
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"https://api.together.xyz/v1/models",
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api_key.as_deref(),
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)?,
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"anthropic" => fetch_anthropic_models(api_key.as_deref())?,
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"gemini" => fetch_gemini_models(api_key.as_deref())?,
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"ollama" => {
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|
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@ -1046,10 +1150,15 @@ fn fetch_live_models_for_provider(provider_name: &str, api_key: &str) -> Result<
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]
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}
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}
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"astrai" => {
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fetch_openai_compatible_models("https://as-trai.com/v1/models", api_key.as_deref())?
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_ => {
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if let Some(endpoint) = models_endpoint_for_provider(requested_provider_name) {
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let allow_unauthenticated =
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allows_unauthenticated_model_fetch(requested_provider_name);
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fetch_openai_compatible_models(endpoint, api_key.as_deref(), allow_unauthenticated)?
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} else {
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Vec::new()
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}
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}
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_ => Vec::new(),
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};
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Ok(models)
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@ -1719,167 +1828,12 @@ fn setup_provider(workspace_dir: &Path) -> Result<(String, String, String, Optio
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// ── Model selection ──
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let canonical_provider = canonical_provider_name(provider_name);
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let models: Vec<(&str, &str)> = match canonical_provider {
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"openrouter" => vec![
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(
|
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"anthropic/claude-sonnet-4",
|
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"Claude Sonnet 4 (balanced, recommended)",
|
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),
|
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(
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"anthropic/claude-3.5-sonnet",
|
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"Claude 3.5 Sonnet (fast, affordable)",
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),
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("openai/gpt-4o", "GPT-4o (OpenAI flagship)"),
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("openai/gpt-4o-mini", "GPT-4o Mini (fast, cheap)"),
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(
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"google/gemini-2.0-flash-001",
|
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"Gemini 2.0 Flash (Google, fast)",
|
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),
|
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(
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"meta-llama/llama-3.3-70b-instruct",
|
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"Llama 3.3 70B (open source)",
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),
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("deepseek/deepseek-chat", "DeepSeek Chat (affordable)"),
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],
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"anthropic" => vec![
|
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(
|
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"claude-sonnet-4-20250514",
|
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"Claude Sonnet 4 (balanced, recommended)",
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),
|
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("claude-3-5-sonnet-20241022", "Claude 3.5 Sonnet (fast)"),
|
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(
|
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"claude-3-5-haiku-20241022",
|
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"Claude 3.5 Haiku (fastest, cheapest)",
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),
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],
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"openai" => vec![
|
||||
("gpt-4o", "GPT-4o (flagship)"),
|
||||
("gpt-4o-mini", "GPT-4o Mini (fast, cheap)"),
|
||||
("o1-mini", "o1-mini (reasoning)"),
|
||||
],
|
||||
"openai-codex" => vec![
|
||||
("gpt-5-codex", "GPT-5 Codex (recommended)"),
|
||||
("o4-mini", "o4-mini (fallback)"),
|
||||
],
|
||||
"venice" => vec![
|
||||
("llama-3.3-70b", "Llama 3.3 70B (default, fast)"),
|
||||
("claude-opus-45", "Claude Opus 4.5 via Venice (strongest)"),
|
||||
("llama-3.1-405b", "Llama 3.1 405B (largest open source)"),
|
||||
],
|
||||
"groq" => vec![
|
||||
(
|
||||
"llama-3.3-70b-versatile",
|
||||
"Llama 3.3 70B (fast, recommended)",
|
||||
),
|
||||
("llama-3.1-8b-instant", "Llama 3.1 8B (instant)"),
|
||||
("mixtral-8x7b-32768", "Mixtral 8x7B (32K context)"),
|
||||
],
|
||||
"mistral" => vec![
|
||||
("mistral-large-latest", "Mistral Large (flagship)"),
|
||||
("codestral-latest", "Codestral (code-focused)"),
|
||||
("mistral-small-latest", "Mistral Small (fast, cheap)"),
|
||||
],
|
||||
"deepseek" => vec![
|
||||
("deepseek-chat", "DeepSeek Chat (V3, recommended)"),
|
||||
("deepseek-reasoner", "DeepSeek Reasoner (R1)"),
|
||||
],
|
||||
"xai" => vec![
|
||||
("grok-3", "Grok 3 (flagship)"),
|
||||
("grok-3-mini", "Grok 3 Mini (fast)"),
|
||||
],
|
||||
"perplexity" => vec![
|
||||
("sonar-pro", "Sonar Pro (search + reasoning)"),
|
||||
("sonar", "Sonar (search, fast)"),
|
||||
],
|
||||
"fireworks" => vec![
|
||||
(
|
||||
"accounts/fireworks/models/llama-v3p3-70b-instruct",
|
||||
"Llama 3.3 70B",
|
||||
),
|
||||
(
|
||||
"accounts/fireworks/models/mixtral-8x22b-instruct",
|
||||
"Mixtral 8x22B",
|
||||
),
|
||||
],
|
||||
"together-ai" => vec![
|
||||
(
|
||||
"meta-llama/Meta-Llama-3.1-70B-Instruct-Turbo",
|
||||
"Llama 3.1 70B Turbo",
|
||||
),
|
||||
(
|
||||
"meta-llama/Meta-Llama-3.1-8B-Instruct-Turbo",
|
||||
"Llama 3.1 8B Turbo",
|
||||
),
|
||||
("mistralai/Mixtral-8x22B-Instruct-v0.1", "Mixtral 8x22B"),
|
||||
],
|
||||
"nvidia" | "nvidia-nim" | "build.nvidia.com" => vec![
|
||||
("deepseek-ai/DeepSeek-R1", "DeepSeek R1 (reasoning)"),
|
||||
("meta/llama-3.1-70b-instruct", "Llama 3.1 70B Instruct"),
|
||||
("mistralai/Mistral-7B-Instruct-v0.3", "Mistral 7B Instruct"),
|
||||
("meta/llama-3.1-405b-instruct", "Llama 3.1 405B Instruct"),
|
||||
],
|
||||
"cohere" => vec![
|
||||
("command-r-plus", "Command R+ (flagship)"),
|
||||
("command-r", "Command R (fast)"),
|
||||
],
|
||||
"kimi-code" => vec![
|
||||
(
|
||||
"kimi-for-coding",
|
||||
"Kimi for Coding (official coding-agent model)",
|
||||
),
|
||||
("kimi-k2.5", "Kimi K2.5 (general coding endpoint model)"),
|
||||
],
|
||||
"moonshot" => vec![
|
||||
("moonshot-v1-128k", "Moonshot V1 128K"),
|
||||
("moonshot-v1-32k", "Moonshot V1 32K"),
|
||||
],
|
||||
"glm" | "zai" => vec![
|
||||
("glm-5", "GLM-5 (latest)"),
|
||||
("glm-4-plus", "GLM-4 Plus (flagship)"),
|
||||
("glm-4-flash", "GLM-4 Flash (fast)"),
|
||||
],
|
||||
"minimax" => MINIMAX_ONBOARD_MODELS.to_vec(),
|
||||
"qwen" => vec![
|
||||
("qwen-plus", "Qwen Plus (balanced default)"),
|
||||
("qwen-max", "Qwen Max (highest quality)"),
|
||||
("qwen-turbo", "Qwen Turbo (fast and cost-efficient)"),
|
||||
],
|
||||
"ollama" => vec![
|
||||
("llama3.2", "Llama 3.2 (recommended local)"),
|
||||
("mistral", "Mistral 7B"),
|
||||
("codellama", "Code Llama"),
|
||||
("phi3", "Phi-3 (small, fast)"),
|
||||
],
|
||||
"gemini" | "google" | "google-gemini" => vec![
|
||||
("gemini-2.0-flash", "Gemini 2.0 Flash (fast, recommended)"),
|
||||
(
|
||||
"gemini-2.0-flash-lite",
|
||||
"Gemini 2.0 Flash Lite (fastest, cheapest)",
|
||||
),
|
||||
("gemini-1.5-pro", "Gemini 1.5 Pro (best quality)"),
|
||||
("gemini-1.5-flash", "Gemini 1.5 Flash (balanced)"),
|
||||
],
|
||||
"astrai" => vec![
|
||||
("auto", "Auto — Astrai best execution routing (recommended)"),
|
||||
("gpt-4o", "GPT-4o (OpenAI via Astrai)"),
|
||||
(
|
||||
"claude-sonnet-4.5",
|
||||
"Claude Sonnet 4.5 (Anthropic via Astrai)",
|
||||
),
|
||||
("deepseek-v3", "DeepSeek V3 (best value via Astrai)"),
|
||||
("llama-3.3-70b", "Llama 3.3 70B (open source via Astrai)"),
|
||||
],
|
||||
_ => vec![("default", "Default model")],
|
||||
};
|
||||
let mut model_options: Vec<(String, String)> = curated_models_for_provider(canonical_provider);
|
||||
|
||||
let mut model_options: Vec<(String, String)> = models
|
||||
.into_iter()
|
||||
.map(|(model_id, label)| (model_id.to_string(), label.to_string()))
|
||||
.collect();
|
||||
let mut live_options: Option<Vec<(String, String)>> = None;
|
||||
|
||||
if supports_live_model_fetch(provider_name) {
|
||||
let can_fetch_without_key = matches!(provider_name, "openrouter" | "ollama");
|
||||
let can_fetch_without_key = allows_unauthenticated_model_fetch(provider_name);
|
||||
let has_api_key = !api_key.trim().is_empty()
|
||||
|| std::env::var(provider_env_var(provider_name))
|
||||
.ok()
|
||||
|
|
@ -4663,7 +4617,12 @@ mod tests {
|
|||
|
||||
#[test]
|
||||
fn default_model_for_provider_uses_latest_defaults() {
|
||||
assert_eq!(
|
||||
default_model_for_provider("openrouter"),
|
||||
"anthropic/claude-sonnet-4.6"
|
||||
);
|
||||
assert_eq!(default_model_for_provider("openai"), "gpt-5.2");
|
||||
assert_eq!(default_model_for_provider("openai-codex"), "gpt-5-codex");
|
||||
assert_eq!(
|
||||
default_model_for_provider("anthropic"),
|
||||
"claude-sonnet-4-5-20250929"
|
||||
|
|
@ -4680,6 +4639,16 @@ mod tests {
|
|||
default_model_for_provider("google-gemini"),
|
||||
"gemini-2.5-pro"
|
||||
);
|
||||
assert_eq!(default_model_for_provider("venice"), "zai-org-glm-5");
|
||||
assert_eq!(default_model_for_provider("moonshot"), "kimi-k2.5");
|
||||
assert_eq!(
|
||||
default_model_for_provider("nvidia-nim"),
|
||||
"meta/llama-3.3-70b-instruct"
|
||||
);
|
||||
assert_eq!(
|
||||
default_model_for_provider("astrai"),
|
||||
"anthropic/claude-sonnet-4.6"
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
|
@ -4708,6 +4677,31 @@ mod tests {
|
|||
assert!(ids.contains(&"gpt-5-mini".to_string()));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn curated_models_for_glm_removes_deprecated_flash_plus_aliases() {
|
||||
let ids: Vec<String> = curated_models_for_provider("glm")
|
||||
.into_iter()
|
||||
.map(|(id, _)| id)
|
||||
.collect();
|
||||
|
||||
assert!(ids.contains(&"glm-5".to_string()));
|
||||
assert!(ids.contains(&"glm-4.7".to_string()));
|
||||
assert!(ids.contains(&"glm-4.5-air".to_string()));
|
||||
assert!(!ids.contains(&"glm-4-plus".to_string()));
|
||||
assert!(!ids.contains(&"glm-4-flash".to_string()));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn curated_models_for_openai_codex_include_codex_family() {
|
||||
let ids: Vec<String> = curated_models_for_provider("openai-codex")
|
||||
.into_iter()
|
||||
.map(|(id, _)| id)
|
||||
.collect();
|
||||
|
||||
assert!(ids.contains(&"gpt-5-codex".to_string()));
|
||||
assert!(ids.contains(&"gpt-5.2-codex".to_string()));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn curated_models_for_openrouter_use_valid_anthropic_id() {
|
||||
let ids: Vec<String> = curated_models_for_provider("openrouter")
|
||||
|
|
@ -4715,7 +4709,33 @@ mod tests {
|
|||
.map(|(id, _)| id)
|
||||
.collect();
|
||||
|
||||
assert!(ids.contains(&"anthropic/claude-sonnet-4.5".to_string()));
|
||||
assert!(ids.contains(&"anthropic/claude-sonnet-4.6".to_string()));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn curated_models_for_moonshot_drop_deprecated_aliases() {
|
||||
let ids: Vec<String> = curated_models_for_provider("moonshot")
|
||||
.into_iter()
|
||||
.map(|(id, _)| id)
|
||||
.collect();
|
||||
|
||||
assert!(ids.contains(&"kimi-k2.5".to_string()));
|
||||
assert!(ids.contains(&"kimi-k2-thinking".to_string()));
|
||||
assert!(!ids.contains(&"kimi-latest".to_string()));
|
||||
assert!(!ids.contains(&"kimi-thinking-preview".to_string()));
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn allows_unauthenticated_model_fetch_for_public_catalogs() {
|
||||
assert!(allows_unauthenticated_model_fetch("openrouter"));
|
||||
assert!(allows_unauthenticated_model_fetch("venice"));
|
||||
assert!(allows_unauthenticated_model_fetch("nvidia"));
|
||||
assert!(allows_unauthenticated_model_fetch("nvidia-nim"));
|
||||
assert!(allows_unauthenticated_model_fetch("build.nvidia.com"));
|
||||
assert!(allows_unauthenticated_model_fetch("astrai"));
|
||||
assert!(allows_unauthenticated_model_fetch("ollama"));
|
||||
assert!(!allows_unauthenticated_model_fetch("openai"));
|
||||
assert!(!allows_unauthenticated_model_fetch("deepseek"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
|
@ -4739,7 +4759,11 @@ mod tests {
|
|||
assert!(supports_live_model_fetch("together"));
|
||||
assert!(supports_live_model_fetch("ollama"));
|
||||
assert!(supports_live_model_fetch("astrai"));
|
||||
assert!(!supports_live_model_fetch("venice"));
|
||||
assert!(supports_live_model_fetch("venice"));
|
||||
assert!(supports_live_model_fetch("glm-cn"));
|
||||
assert!(supports_live_model_fetch("qwen-intl"));
|
||||
assert!(!supports_live_model_fetch("minimax-cn"));
|
||||
assert!(!supports_live_model_fetch("unknown-provider"));
|
||||
}
|
||||
|
||||
#[test]
|
||||
|
|
@ -4778,6 +4802,40 @@ mod tests {
|
|||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn models_endpoint_for_provider_handles_region_aliases() {
|
||||
assert_eq!(
|
||||
models_endpoint_for_provider("glm-cn"),
|
||||
Some("https://open.bigmodel.cn/api/paas/v4/models")
|
||||
);
|
||||
assert_eq!(
|
||||
models_endpoint_for_provider("zai-cn"),
|
||||
Some("https://open.bigmodel.cn/api/coding/paas/v4/models")
|
||||
);
|
||||
assert_eq!(
|
||||
models_endpoint_for_provider("qwen-intl"),
|
||||
Some("https://dashscope-intl.aliyuncs.com/compatible-mode/v1/models")
|
||||
);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn models_endpoint_for_provider_supports_additional_openai_compatible_providers() {
|
||||
assert_eq!(
|
||||
models_endpoint_for_provider("venice"),
|
||||
Some("https://api.venice.ai/api/v1/models")
|
||||
);
|
||||
assert_eq!(
|
||||
models_endpoint_for_provider("cohere"),
|
||||
Some("https://api.cohere.com/compatibility/v1/models")
|
||||
);
|
||||
assert_eq!(
|
||||
models_endpoint_for_provider("moonshot"),
|
||||
Some("https://api.moonshot.ai/v1/models")
|
||||
);
|
||||
assert_eq!(models_endpoint_for_provider("perplexity"), None);
|
||||
assert_eq!(models_endpoint_for_provider("unknown-provider"), None);
|
||||
}
|
||||
|
||||
#[test]
|
||||
fn parse_openai_model_ids_supports_data_array_payload() {
|
||||
let payload = json!({
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue