Allow using a custom model when using zed.dev (#14933)

Release Notes:

- N/A

crates/completion/src/cloud.rs

@@ -54,15 +54,15 @@ impl CloudCompletionProvider {
 
 impl LanguageModelCompletionProvider for CloudCompletionProvider {
     fn available_models(&self) -> Vec<LanguageModel> {
-        let mut custom_model = if let CloudModel::Custom(custom_model) = self.model.clone() {
-            Some(custom_model)
+        let mut custom_model = if matches!(self.model, CloudModel::Custom { .. }) {
+            Some(self.model.clone())
         } else {
             None
         };
         CloudModel::iter()
             .filter_map(move |model| {
-                if let CloudModel::Custom(_) = model {
-                    Some(CloudModel::Custom(custom_model.take()?))
+                if let CloudModel::Custom { .. } = model {
+                    custom_model.take()
                 } else {
                     Some(model)
                 }
@@ -117,9 +117,9 @@ impl LanguageModelCompletionProvider for CloudCompletionProvider {
                 // Can't find a tokenizer for Claude 3, so for now just use the same as OpenAI's as an approximation.
                 count_open_ai_tokens(request, cx.background_executor())
             }
-            LanguageModel::Cloud(CloudModel::Custom(model)) => {
+            LanguageModel::Cloud(CloudModel::Custom { name, .. }) => {
                 let request = self.client.request(proto::CountTokensWithLanguageModel {
-                    model,
+                    model: name,
                     messages: request
                         .messages
                         .iter()

crates/completion/src/open_ai.rs

@@ -241,6 +241,7 @@ pub fn count_open_ai_tokens(
                 | LanguageModel::Cloud(CloudModel::Claude3Opus)
                 | LanguageModel::Cloud(CloudModel::Claude3Sonnet)
                 | LanguageModel::Cloud(CloudModel::Claude3Haiku)
+                | LanguageModel::Cloud(CloudModel::Custom { .. })
                 | LanguageModel::OpenAi(OpenAiModel::Custom { .. }) => {
                     // Tiktoken doesn't yet support these models, so we manually use the
                     // same tokenizer as GPT-4.