fix(providers): fall back to configured models when models endpoint fetch fails (#7530)

Signed-off-by: Pete Gonzalez <4673363+octogonz@users.noreply.github.com>
Signed-off-by: Douwe Osinga <douwe@squareup.com>
Co-authored-by: Pete Gonzalez <octogonz@users.noreply.github.com>
Co-authored-by: Douwe Osinga <douwe@squareup.com>

Author: octogonz

crates/goose/src/providers/anthropic.rs

@@ -55,6 +55,7 @@ pub struct AnthropicProvider {
     model: ModelConfig,
     supports_streaming: bool,
     name: String,
+    custom_models: Option<Vec<String>>,
 }
 
 impl AnthropicProvider {
@@ -80,6 +81,7 @@ impl AnthropicProvider {
             model,
             supports_streaming: true,
             name: ANTHROPIC_PROVIDER_NAME.to_string(),
+            custom_models: None,
         })
     }
 
@@ -119,11 +121,18 @@ impl AnthropicProvider {
             ));
         }
 
+        let custom_models = if !config.models.is_empty() {
+            Some(config.models.iter().map(|m| m.name.clone()).collect())
+        } else {
+            None
+        };
+
         Ok(Self {
             api_client,
             model,
             supports_streaming,
             name: config.name.clone(),
+            custom_models,
         })
     }
 
@@ -139,6 +148,42 @@ impl AnthropicProvider {
 
         headers
     }
+
+    async fn fetch_models_from_api(&self) -> Result<Vec<String>, ProviderError> {
+        let response = self.api_client.request(None, "v1/models").api_get().await?;
+
+        if response.status == StatusCode::NOT_FOUND {
+            let msg = response
+                .payload
+                .as_ref()
+                .and_then(|p| p.get("error").and_then(|e| e.get("message")))
+                .and_then(|m| m.as_str())
+                .unwrap_or("models endpoint not found")
+                .to_string();
+            return Err(ProviderError::EndpointNotFound(msg));
+        }
+
+        if response.status != StatusCode::OK {
+            return Err(map_http_error_to_provider_error(
+                response.status,
+                response.payload,
+            ));
+        }
+
+        let json = response.payload.unwrap_or_default();
+        let arr = json.get("data").and_then(|v| v.as_array()).ok_or_else(|| {
+            ProviderError::RequestFailed(
+                "Missing 'data' array in Anthropic models response".to_string(),
+            )
+        })?;
+
+        let mut models: Vec<String> = arr
+            .iter()
+            .filter_map(|m| m.get("id").and_then(|v| v.as_str()).map(str::to_string))
+            .collect();
+        models.sort();
+        Ok(models)
+    }
 }
 
 impl ProviderDef for AnthropicProvider {
@@ -194,28 +239,22 @@ impl Provider for AnthropicProvider {
     }
 
     async fn fetch_supported_models(&self) -> Result<Vec<String>, ProviderError> {
-        let response = self.api_client.request(None, "v1/models").api_get().await?;
-
-        if response.status != StatusCode::OK {
-            return Err(map_http_error_to_provider_error(
-                response.status,
-                response.payload,
-            ));
+        if let Some(custom_models) = &self.custom_models {
+            match self.fetch_models_from_api().await {
+                Ok(models) => return Ok(models),
+                Err(e) if e.is_endpoint_not_found() => {
+                    tracing::debug!(
+                        "Models endpoint not implemented for provider '{}' ({}), using predefined list",
+                        self.name,
+                        e
+                    );
+                    return Ok(custom_models.clone());
+                }
+                Err(e) => return Err(e),
+            }
         }
 
-        let json = response.payload.unwrap_or_default();
-        let arr = json.get("data").and_then(|v| v.as_array()).ok_or_else(|| {
-            ProviderError::RequestFailed(
-                "Missing 'data' array in Anthropic models response".to_string(),
-            )
-        })?;
-
-        let mut models: Vec<String> = arr
-            .iter()
-            .filter_map(|m| m.get("id").and_then(|v| v.as_str()).map(str::to_string))
-            .collect();
-        models.sort();
-        Ok(models)
+        self.fetch_models_from_api().await
     }
 
     async fn stream(

crates/goose/src/providers/errors.rs

@@ -34,6 +34,9 @@ pub enum ProviderError {
     #[error("Unsupported operation: {0}")]
     NotImplemented(String),
 
+    #[error("Endpoint not found (404): {0}")]
+    EndpointNotFound(String),
+
     #[error("Credits exhausted: {details}")]
     CreditsExhausted {
         details: String,
@@ -53,9 +56,14 @@ impl ProviderError {
             ProviderError::ExecutionError(_) => "execution",
             ProviderError::UsageError(_) => "usage",
             ProviderError::NotImplemented(_) => "not_implemented",
+            ProviderError::EndpointNotFound(_) => "endpoint_not_found",
             ProviderError::CreditsExhausted { .. } => "credits_exhausted",
         }
     }
+
+    pub fn is_endpoint_not_found(&self) -> bool {
+        matches!(self, ProviderError::EndpointNotFound(_))
+    }
 }
 
 fn is_network_error(err: &reqwest::Error) -> bool {

crates/goose/src/providers/openai.rs

@@ -65,6 +65,7 @@ pub struct OpenAiProvider {
     custom_headers: Option<HashMap<String, String>>,
     supports_streaming: bool,
     name: String,
+    custom_models: Option<Vec<String>>,
     skip_canonical_filtering: bool,
 }
 
@@ -127,6 +128,7 @@ impl OpenAiProvider {
             custom_headers,
             supports_streaming: true,
             name: OPEN_AI_PROVIDER_NAME.to_string(),
+            custom_models: None,
             skip_canonical_filtering: false,
         })
     }
@@ -142,6 +144,7 @@ impl OpenAiProvider {
             custom_headers: None,
             supports_streaming: true,
             name: OPEN_AI_PROVIDER_NAME.to_string(),
+            custom_models: None,
             skip_canonical_filtering: false,
         }
     }
@@ -212,6 +215,12 @@ impl OpenAiProvider {
             api_client = api_client.with_headers(header_map)?;
         }
 
+        let custom_models = if !config.models.is_empty() {
+            Some(config.models.iter().map(|m| m.name.clone()).collect())
+        } else {
+            None
+        };
+
         Ok(Self {
             api_client,
             base_path,
@@ -221,6 +230,7 @@ impl OpenAiProvider {
             custom_headers: config.headers,
             supports_streaming: config.supports_streaming.unwrap_or(true),
             name: config.name.clone(),
+            custom_models,
             skip_canonical_filtering: config.skip_canonical_filtering,
         })
     }
@@ -314,6 +324,40 @@ impl OpenAiProvider {
             fallback.to_string()
         }
     }
+
+    async fn fetch_models_from_api(&self) -> Result<Vec<String>, ProviderError> {
+        let models_path =
+            Self::map_base_path(&self.base_path, "models", OPEN_AI_DEFAULT_MODELS_PATH);
+        let response = self
+            .api_client
+            .request(None, &models_path)
+            .response_get()
+            .await?;
+
+        if response.status() == StatusCode::NOT_FOUND {
+            let body = response.text().await.unwrap_or_default();
+            return Err(ProviderError::EndpointNotFound(body));
+        }
+
+        let json = handle_response_openai_compat(response).await?;
+        if let Some(err_obj) = json.get("error") {
+            let msg = err_obj
+                .get("message")
+                .and_then(|v| v.as_str())
+                .unwrap_or("unknown error");
+            return Err(ProviderError::Authentication(msg.to_string()));
+        }
+
+        let data = json.get("data").and_then(|v| v.as_array()).ok_or_else(|| {
+            ProviderError::UsageError("Missing data field in JSON response".into())
+        })?;
+        let mut models: Vec<String> = data
+            .iter()
+            .filter_map(|m| m.get("id").and_then(|v| v.as_str()).map(str::to_string))
+            .collect();
+        models.sort();
+        Ok(models)
+    }
 }
 
 impl ProviderDef for OpenAiProvider {
@@ -384,31 +428,22 @@ impl Provider for OpenAiProvider {
     }
 
     async fn fetch_supported_models(&self) -> Result<Vec<String>, ProviderError> {
-        let models_path =
-            Self::map_base_path(&self.base_path, "models", OPEN_AI_DEFAULT_MODELS_PATH);
-        let response = self
-            .api_client
-            .request(None, &models_path)
-            .response_get()
-            .await?;
-        let json = handle_response_openai_compat(response).await?;
-        if let Some(err_obj) = json.get("error") {
-            let msg = err_obj
-                .get("message")
-                .and_then(|v| v.as_str())
-                .unwrap_or("unknown error");
-            return Err(ProviderError::Authentication(msg.to_string()));
+        if let Some(custom_models) = &self.custom_models {
+            match self.fetch_models_from_api().await {
+                Ok(models) => return Ok(models),
+                Err(e) if e.is_endpoint_not_found() => {
+                    tracing::debug!(
+                        "Models endpoint not implemented for provider '{}' ({}), using predefined list",
+                        self.name,
+                        e
+                    );
+                    return Ok(custom_models.clone());
+                }
+                Err(e) => return Err(e),
+            }
         }
 
-        let data = json.get("data").and_then(|v| v.as_array()).ok_or_else(|| {
-            ProviderError::UsageError("Missing data field in JSON response".into())
-        })?;
-        let mut models: Vec<String> = data
-            .iter()
-            .filter_map(|m| m.get("id").and_then(|v| v.as_str()).map(str::to_string))
-            .collect();
-        models.sort();
-        Ok(models)
+        self.fetch_models_from_api().await
     }
 
     fn supports_embeddings(&self) -> bool {
@@ -635,6 +670,7 @@ mod tests {
             custom_headers: None,
             supports_streaming: true,
             name: name.to_string(),
+            custom_models: None,
             skip_canonical_filtering: false,
         }
     }

crates/goose/src/providers/openai_compatible.rs

@@ -299,6 +299,18 @@ mod tests {
         "ServerError"
         ; "500 server error"
     )]
+    #[test_case(
+        StatusCode::NOT_FOUND,
+        None,
+        "RequestFailed"
+        ; "404 not found"
+    )]
+    #[test_case(
+        StatusCode::NOT_FOUND,
+        Some(json!({"error": {"message": "model not available"}})),
+        "RequestFailed"
+        ; "404 with error payload"
+    )]
     fn http_status_maps_to_expected_error(
         status: StatusCode,
         payload: Option<Value>,
@@ -312,6 +324,7 @@ mod tests {
             "Authentication" => "auth",
             "ContextLengthExceeded" => "context_length",
             "ServerError" => "server",
+            "RequestFailed" => "request",
             other => panic!("Unknown variant: {other}"),
         };
         assert_eq!(