language_models: Add images support for Ollama vision models (#31883)

Ollama supports vision to process input images. This PR adds support for
same. I have tested this with gemma3:4b and have attached the screenshot
of it working.

<img width="435" alt="image"
src="https://github.com/user-attachments/assets/5f17d742-0a37-4e6c-b4d8-05b750a0a158"
/>


Release Notes:

- Add image support for [Ollama vision models](https://ollama.com/search?c=vision)

crates/agent_settings/src/agent_settings.rs

@@ -372,6 +372,7 @@ impl AgentSettingsContent {
                                 None,
                                 None,
                                 Some(language_model.supports_tools()),
+                                Some(language_model.supports_images()),
                                 None,
                             )),
                             api_url,

crates/language_models/src/provider/ollama.rs

@@ -4,14 +4,11 @@ use futures::{Stream, TryFutureExt, stream};
 use gpui::{AnyView, App, AsyncApp, Context, Subscription, Task};
 use http_client::HttpClient;
 use language_model::{
-    AuthenticateError, LanguageModelCompletionError, LanguageModelCompletionEvent,
+    AuthenticateError, LanguageModel, LanguageModelCompletionError, LanguageModelCompletionEvent,
+    LanguageModelId, LanguageModelName, LanguageModelProvider, LanguageModelProviderId,
+    LanguageModelProviderName, LanguageModelProviderState, LanguageModelRequest,
     LanguageModelRequestTool, LanguageModelToolChoice, LanguageModelToolUse,
-    LanguageModelToolUseId, MessageContent, StopReason,
-};
-use language_model::{
-    LanguageModel, LanguageModelId, LanguageModelName, LanguageModelProvider,
-    LanguageModelProviderId, LanguageModelProviderName, LanguageModelProviderState,
-    LanguageModelRequest, RateLimiter, Role,
+    LanguageModelToolUseId, MessageContent, RateLimiter, Role, StopReason,
 };
 use ollama::{
     ChatMessage, ChatOptions, ChatRequest, ChatResponseDelta, KeepAlive, OllamaFunctionTool,
@@ -54,6 +51,8 @@ pub struct AvailableModel {
     pub keep_alive: Option<KeepAlive>,
     /// Whether the model supports tools
     pub supports_tools: Option<bool>,
+    /// Whether the model supports vision
+    pub supports_images: Option<bool>,
     /// Whether to enable think mode
     pub supports_thinking: Option<bool>,
 }
@@ -101,6 +100,7 @@ impl State {
                             None,
                             None,
                             Some(capabilities.supports_tools()),
+                            Some(capabilities.supports_vision()),
                             Some(capabilities.supports_thinking()),
                         );
                         Ok(ollama_model)
@@ -222,6 +222,7 @@ impl LanguageModelProvider for OllamaLanguageModelProvider {
                     max_tokens: model.max_tokens,
                     keep_alive: model.keep_alive.clone(),
                     supports_tools: model.supports_tools,
+                    supports_vision: model.supports_images,
                     supports_thinking: model.supports_thinking,
                 },
             );
@@ -277,30 +278,59 @@ pub struct OllamaLanguageModel {
 
 impl OllamaLanguageModel {
     fn to_ollama_request(&self, request: LanguageModelRequest) -> ChatRequest {
+        let supports_vision = self.model.supports_vision.unwrap_or(false);
+
         ChatRequest {
             model: self.model.name.clone(),
             messages: request
                 .messages
                 .into_iter()
-                .map(|msg| match msg.role {
-                    Role::User => ChatMessage::User {
-                        content: msg.string_contents(),
-                    },
-                    Role::Assistant => {
-                        let content = msg.string_contents();
-                        let thinking = msg.content.into_iter().find_map(|content| match content {
-                            MessageContent::Thinking { text, .. } if !text.is_empty() => Some(text),
-                            _ => None,
-                        });
-                        ChatMessage::Assistant {
-                            content,
-                            tool_calls: None,
-                            thinking,
+                .map(|msg| {
+                    let images = if supports_vision {
+                        msg.content
+                            .iter()
+                            .filter_map(|content| match content {
+                                MessageContent::Image(image) => Some(image.source.to_string()),
+                                _ => None,
+                            })
+                            .collect::<Vec<String>>()
+                    } else {
+                        vec![]
+                    };
+
+                    match msg.role {
+                        Role::User => ChatMessage::User {
+                            content: msg.string_contents(),
+                            images: if images.is_empty() {
+                                None
+                            } else {
+                                Some(images)
+                            },
+                        },
+                        Role::Assistant => {
+                            let content = msg.string_contents();
+                            let thinking =
+                                msg.content.into_iter().find_map(|content| match content {
+                                    MessageContent::Thinking { text, .. } if !text.is_empty() => {
+                                        Some(text)
+                                    }
+                                    _ => None,
+                                });
+                            ChatMessage::Assistant {
+                                content,
+                                tool_calls: None,
+                                images: if images.is_empty() {
+                                    None
+                                } else {
+                                    Some(images)
+                                },
+                                thinking,
+                            }
                         }
+                        Role::System => ChatMessage::System {
+                            content: msg.string_contents(),
+                        },
                     }
-                    Role::System => ChatMessage::System {
-                        content: msg.string_contents(),
-                    },
                 })
                 .collect(),
             keep_alive: self.model.keep_alive.clone().unwrap_or_default(),
@@ -339,7 +369,7 @@ impl LanguageModel for OllamaLanguageModel {
     }
 
     fn supports_images(&self) -> bool {
-        false
+        self.model.supports_vision.unwrap_or(false)
     }
 
     fn supports_tool_choice(&self, choice: LanguageModelToolChoice) -> bool {
@@ -437,7 +467,7 @@ fn map_to_language_model_completion_events(
             let mut events = Vec::new();
 
             match delta.message {
-                ChatMessage::User { content } => {
+                ChatMessage::User { content, images: _ } => {
                     events.push(Ok(LanguageModelCompletionEvent::Text(content)));
                 }
                 ChatMessage::System { content } => {
@@ -446,6 +476,7 @@ fn map_to_language_model_completion_events(
                 ChatMessage::Assistant {
                     content,
                     tool_calls,
+                    images: _,
                     thinking,
                 } => {
                     if let Some(text) = thinking {

crates/ollama/src/ollama.rs

@@ -38,6 +38,7 @@ pub struct Model {
     pub max_tokens: usize,
     pub keep_alive: Option<KeepAlive>,
     pub supports_tools: Option<bool>,
+    pub supports_vision: Option<bool>,
     pub supports_thinking: Option<bool>,
 }
 
@@ -68,6 +69,7 @@ impl Model {
         display_name: Option<&str>,
         max_tokens: Option<usize>,
         supports_tools: Option<bool>,
+        supports_vision: Option<bool>,
         supports_thinking: Option<bool>,
     ) -> Self {
         Self {
@@ -78,6 +80,7 @@ impl Model {
             max_tokens: max_tokens.unwrap_or_else(|| get_max_tokens(name)),
             keep_alive: Some(KeepAlive::indefinite()),
             supports_tools,
+            supports_vision,
             supports_thinking,
         }
     }
@@ -101,10 +104,14 @@ pub enum ChatMessage {
     Assistant {
         content: String,
         tool_calls: Option<Vec<OllamaToolCall>>,
+        #[serde(skip_serializing_if = "Option::is_none")]
+        images: Option<Vec<String>>,
         thinking: Option<String>,
     },
     User {
         content: String,
+        #[serde(skip_serializing_if = "Option::is_none")]
+        images: Option<Vec<String>>,
     },
     System {
         content: String,
@@ -221,6 +228,10 @@ impl ModelShow {
         self.capabilities.iter().any(|v| v == "tools")
     }
 
+    pub fn supports_vision(&self) -> bool {
+        self.capabilities.iter().any(|v| v == "vision")
+    }
+
     pub fn supports_thinking(&self) -> bool {
         self.capabilities.iter().any(|v| v == "thinking")
     }
@@ -468,6 +479,7 @@ mod tests {
             ChatMessage::Assistant {
                 content,
                 tool_calls,
+                images: _,
                 thinking,
             } => {
                 assert!(content.is_empty());
@@ -534,4 +546,70 @@ mod tests {
         assert!(result.capabilities.contains(&"tools".to_string()));
         assert!(result.capabilities.contains(&"completion".to_string()));
     }
+
+    #[test]
+    fn serialize_chat_request_with_images() {
+        let base64_image = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==";
+
+        let request = ChatRequest {
+            model: "llava".to_string(),
+            messages: vec![ChatMessage::User {
+                content: "What do you see in this image?".to_string(),
+                images: Some(vec![base64_image.to_string()]),
+            }],
+            stream: false,
+            keep_alive: KeepAlive::default(),
+            options: None,
+            think: None,
+            tools: vec![],
+        };
+
+        let serialized = serde_json::to_string(&request).unwrap();
+        assert!(serialized.contains("images"));
+        assert!(serialized.contains(base64_image));
+    }
+
+    #[test]
+    fn serialize_chat_request_without_images() {
+        let request = ChatRequest {
+            model: "llama3.2".to_string(),
+            messages: vec![ChatMessage::User {
+                content: "Hello, world!".to_string(),
+                images: None,
+            }],
+            stream: false,
+            keep_alive: KeepAlive::default(),
+            options: None,
+            think: None,
+            tools: vec![],
+        };
+
+        let serialized = serde_json::to_string(&request).unwrap();
+        assert!(!serialized.contains("images"));
+    }
+
+    #[test]
+    fn test_json_format_with_images() {
+        let base64_image = "iVBORw0KGgoAAAANSUhEUgAAAAEAAAABCAYAAAAfFcSJAAAADUlEQVR42mNk+M9QDwADhgGAWjR9awAAAABJRU5ErkJggg==";
+
+        let request = ChatRequest {
+            model: "llava".to_string(),
+            messages: vec![ChatMessage::User {
+                content: "What do you see?".to_string(),
+                images: Some(vec![base64_image.to_string()]),
+            }],
+            stream: false,
+            keep_alive: KeepAlive::default(),
+            options: None,
+            think: None,
+            tools: vec![],
+        };
+
+        let serialized = serde_json::to_string(&request).unwrap();
+
+        let parsed: serde_json::Value = serde_json::from_str(&serialized).unwrap();
+        let message_images = parsed["messages"][0]["images"].as_array().unwrap();
+        assert_eq!(message_images.len(), 1);
+        assert_eq!(message_images[0].as_str().unwrap(), base64_image);
+    }
 }