feat: auto-detect ollama models

src-tauri/src/commands/chat.rs

@@ -18,6 +18,12 @@ pub struct ProviderConfig {
 
 const MAX_TURNS: usize = 10;
 
+#[tauri::command]
+pub async fn get_ollama_models(base_url: Option<String>) -> Result<Vec<String>, String> {
+    let url = base_url.unwrap_or_else(|| "http://localhost:11434".to_string());
+    OllamaProvider::get_models(&url).await
+}
+
 #[tauri::command]
 pub async fn chat(
     messages: Vec<Message>,

src-tauri/src/lib.rs

@@ -20,7 +20,8 @@ pub fn run() {
             commands::fs::list_directory,
             commands::search::search_files,
             commands::shell::exec_shell,
-            commands::chat::chat
+            commands::chat::chat,
+            commands::chat::get_ollama_models
         ])
         .run(tauri::generate_context!())
         .expect("error while running tauri application");

src-tauri/src/llm/ollama.rs

@@ -13,6 +13,40 @@ impl OllamaProvider {
     pub fn new(base_url: String) -> Self {
         Self { base_url }
     }
+
+    pub async fn get_models(base_url: &str) -> Result<Vec<String>, String> {
+        let client = reqwest::Client::new();
+        let url = format!("{}/api/tags", base_url.trim_end_matches('/'));
+
+        let res = client
+            .get(&url)
+            .send()
+            .await
+            .map_err(|e| format!("Request failed: {}", e))?;
+
+        if !res.status().is_success() {
+            let status = res.status();
+            let text = res.text().await.unwrap_or_default();
+            return Err(format!("Ollama API error {}: {}", status, text));
+        }
+
+        let body: OllamaTagsResponse = res
+            .json()
+            .await
+            .map_err(|e| format!("Failed to parse response: {}", e))?;
+
+        Ok(body.models.into_iter().map(|m| m.name).collect())
+    }
+}
+
+#[derive(Deserialize)]
+struct OllamaTagsResponse {
+    models: Vec<OllamaModelTag>,
+}
+
+#[derive(Deserialize)]
+struct OllamaModelTag {
+    name: String,
 }
 
 // --- Request Types ---

src/components/Chat.tsx

@@ -9,8 +9,24 @@ export function Chat() {
   const [loading, setLoading] = useState(false);
   const [model, setModel] = useState("llama3.1"); // Default local model
   const [enableTools, setEnableTools] = useState(true);
+  const [availableModels, setAvailableModels] = useState<string[]>([]);
   const messagesEndRef = useRef<HTMLDivElement>(null);
 
+  useEffect(() => {
+    invoke<string[]>("get_ollama_models")
+      .then((models) => {
+        if (models.length > 0) {
+          setAvailableModels(models);
+          // If we have models and current one isn't valid, switch to first
+          if (!models.includes(model)) {
+            setModel(models[0]);
+          }
+        }
+      })
+      .catch((err) => console.error(err));
+    // eslint-disable-next-line react-hooks/exhaustive-deps
+  }, []);
+
   const scrollToBottom = () => {
     messagesEndRef.current?.scrollIntoView({ behavior: "smooth" });
   };
@@ -76,12 +92,26 @@ export function Chat() {
         }}
       >
         <label>Ollama Model:</label>
+        {availableModels.length > 0 ? (
+          <select
+            value={model}
+            onChange={(e) => setModel(e.target.value)}
+            style={{ padding: "5px" }}
+          >
+            {availableModels.map((m) => (
+              <option key={m} value={m}>
+                {m}
+              </option>
+            ))}
+          </select>
+        ) : (
           <input
             value={model}
             onChange={(e) => setModel(e.target.value)}
             placeholder="e.g. llama3, mistral"
             style={{ padding: "5px" }}
           />
+        )}
         <label
           style={{
             display: "flex",