feat(providers): add Vercel AI Gateway (vercel-ai-gateway)

12th provider. API-key via AI_GATEWAY_API_KEY, Bearer, OpenAI listing + ChatCompletions, Passthrough dialect. Second wire-metadata provider but takes the enrichment path instead: Vercel serves context under context_window, which WireModel ignores (reads context_length), so wire_serves_metadata=false + restrict_to_enriched pulls context/limits from the models.dev "vercel" snapshot (302/306 live ids match snapshot keys byte-for-byte, so restrict keeps essentially the whole catalog). /models is public (200 for any key), so login validation targets /credits (key_validation_path) which 401s on a bad bearer — avoids false-accepting invalid keys against the public listing. Tests: e2e proves enrichment-wins (wire context_window=999 distinct from enrichment context=400000, asserts 400000) and non-vacuous tool_call restriction; validation test proves /credits (not /models) is hit. Registry at 15 (ordinal/VARIANT_COUNT/ALL), 4 auth arrays + 16-row picker.
2026-07-21 15:03:43 -04:00
parent 9ee40b13d0
commit 193d16f6d5
4 changed files with 195 additions and 14 deletions
@@ -1897,6 +1897,103 @@ mod tests {
        );
    }

+    /// Vercel-cycle e2e: the gateway lists creator/model ids (matching the
+    /// models.dev "vercel" keys); enrichment supplies context (the wire uses
+    /// `context_window`, not the WireModel `context_length`); the restriction
+    /// drops non-chat types; slashed id; Passthrough dialect.
+    #[tokio::test(flavor = "multi_thread")]
+    #[serial_test::serial]
+    async fn vercel_gateway_enriches_restricts_and_maps_passthrough() {
+        let platform_server = wiremock::MockServer::start().await;
+        wiremock::Mock::given(wiremock::matchers::method("GET"))
+            .and(wiremock::matchers::path("/models"))
+            .respond_with(wiremock::ResponseTemplate::new(200).set_body_json(
+                // Vercel serves context under `context_window` (ignored by
+                // WireModel) — enrichment supplies the real context.
+                serde_json::json!({ "data": [
+                    // A DISTINCT (wrong) context_window that WireModel ignores —
+                    // so asserting the enrichment value below proves the source.
+                    { "id": "openai/gpt-5.5", "object": "model",
+                      "type": "language", "context_window": 999 },
+                    { "id": "voyage/rerank-2.5", "object": "model", "type": "embedding" }
+                ]}),
+            ))
+            .expect(1)
+            .mount(&platform_server)
+            .await;
+        let modelsdev_server = wiremock::MockServer::start().await;
+        wiremock::Mock::given(wiremock::matchers::method("GET"))
+            .and(wiremock::matchers::path("/api.json"))
+            .respond_with(wiremock::ResponseTemplate::new(200).set_body_json(
+                serde_json::json!({ "vercel": { "models": {
+                    "openai/gpt-5.5": {
+                        "limit": {"context": 400000, "output": 128000},
+                        "tool_call": true
+                    },
+                    "voyage/rerank-2.5": { "limit": {"context": 32000} }
+                }}}),
+            ))
+            .expect(1)
+            .mount(&modelsdev_server)
+            .await;
+        let cache_dir = tempfile::tempdir().unwrap();
+        let _base = kigi_test_support::EnvGuard::set(
+            kigi_models::VERCEL_BASE_URL_ENV,
+            platform_server.uri(),
+        );
+        let _mdev = kigi_test_support::EnvGuard::set(
+            crate::agent::enrichment_fetch::MODELS_DEV_URL_ENV,
+            format!("{}/api.json", modelsdev_server.uri()),
+        );
+        let _mdev_cache = kigi_test_support::EnvGuard::set(
+            crate::agent::enrichment_fetch::MODELS_DEV_CACHE_DIR_ENV,
+            cache_dir.path(),
+        );
+        let endpoints = crate::agent::config::EndpointsConfig::default();
+        let keys = crate::agent::models::PlatformApiKeys::test_single(
+            kigi_models::PlatformId::Vercel,
+            "vg-1",
+        );
+        let result = tokio::task::spawn_blocking(move || {
+            fetch_platform_models_blocking(&endpoints, None, &keys)
+        })
+        .await
+        .unwrap()
+        .expect("fetch must succeed");
+        assert_eq!(
+            result
+                .models
+                .iter()
+                .map(|m| m.id.as_deref().unwrap_or_default())
+                .collect::<Vec<_>>(),
+            vec!["vercel-ai-gateway/openai/gpt-5.5"],
+            "rerank (not tool-calling) dropped; creator/model id kept under the platform key"
+        );
+        let entry = &result.models[0];
+        assert_eq!(
+            entry.context_window.get(),
+            400_000,
+            "context comes from enrichment (wire used context_window, not context_length)"
+        );
+        assert_eq!(entry.max_completion_tokens, Some(128_000));
+        assert_eq!(
+            entry.model, "openai/gpt-5.5",
+            "the creator/model id rides the wire"
+        );
+        let model_entry = crate::agent::config::ModelEntry::from_config_entry(entry);
+        let creds = crate::agent::config::ResolvedCredentials {
+            api_key: Some("vg-1".into()),
+            base_url: entry.base_url.clone(),
+            auth_type: kigi_chat_state::AuthType::ApiKey,
+            auth_scheme: Default::default(),
+        };
+        let cfg = crate::agent::config::sampling_config_for_model(&model_entry, creds, None);
+        assert_eq!(
+            cfg.chat_compat,
+            kigi_sampling_types::ChatCompat::Passthrough
+        );
+    }
+
    #[test]
    fn get_env_keys_parses_strings_and_rejects_non_strings() {
        use crate::agent::config::EnvKeys;