Add OpenAI/LiteLLM provider support with settings UI

- Add openai/ provider module with translator, client, convert, request/response translators - Add shared provider/ types (ConversationMessage, MessageRole, ProviderConfig enum) - Wire OpenAI-compatible provider dispatch alongside Bedrock in response_stream.rs - Add ai.openai.* settings (enabled, base_url, api_key, model, models) - Add OpenAI/LiteLLM settings page with model fetch, picker, and config UI - Extend model menu items and llms.rs to surface LiteLLM models - Update WARP.md with OpenAI provider architecture docs
2026-06-17 14:14:40 -05:00
parent 59cfd0e2f5
commit 5ea378a38d
32 changed files with 2442 additions and 137 deletions
@@ -0,0 +1,272 @@
+use serde_json::json;
+
+use crate::ai::openai::convert::build_openai_request;
+use crate::ai::provider::types::{
+    ContentPart, ConversationMessage, MessageContent, MessageRole, ToolDefinition,
+};
+
+#[test]
+fn test_simple_text_message_conversion() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::User,
+        content: MessageContent::Text("Hello world".to_string()),
+    }];
+
+    let request = build_openai_request(messages, None, vec![], 1024, None, "test-model");
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs.len(), 1);
+    assert_eq!(msgs[0]["role"], "user");
+    assert_eq!(msgs[0]["content"], "Hello world");
+    assert_eq!(request["model"], "test-model");
+    assert_eq!(request["max_tokens"], 1024);
+    assert_eq!(request["stream"], true);
+}
+
+#[test]
+fn test_system_prompt_placement() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::User,
+        content: MessageContent::Text("Hi".to_string()),
+    }];
+
+    let request = build_openai_request(
+        messages,
+        Some("You are a helpful assistant.".to_string()),
+        vec![],
+        1024,
+        None,
+        "test-model",
+    );
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs.len(), 2);
+    assert_eq!(msgs[0]["role"], "system");
+    assert_eq!(msgs[0]["content"], "You are a helpful assistant.");
+    assert_eq!(msgs[1]["role"], "user");
+}
+
+#[test]
+fn test_assistant_tool_use_conversion() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::Assistant,
+        content: MessageContent::ToolUse {
+            tool_use_id: "call_123".to_string(),
+            name: "run_shell_command".to_string(),
+            input: json!({"command": "ls -la"}),
+        },
+    }];
+
+    let request = build_openai_request(messages, None, vec![], 1024, None, "test-model");
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs.len(), 1);
+    assert_eq!(msgs[0]["role"], "assistant");
+    assert!(msgs[0]["content"].is_null());
+
+    let tool_calls = msgs[0]["tool_calls"].as_array().unwrap();
+    assert_eq!(tool_calls.len(), 1);
+    assert_eq!(tool_calls[0]["id"], "call_123");
+    assert_eq!(tool_calls[0]["type"], "function");
+    assert_eq!(tool_calls[0]["function"]["name"], "run_shell_command");
+    assert_eq!(
+        tool_calls[0]["function"]["arguments"],
+        json!({"command": "ls -la"}).to_string()
+    );
+}
+
+#[test]
+fn test_tool_result_conversion() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::User,
+        content: MessageContent::ToolResult {
+            tool_use_id: "call_123".to_string(),
+            content: "file1.txt\nfile2.txt".to_string(),
+            is_error: false,
+        },
+    }];
+
+    let request = build_openai_request(messages, None, vec![], 1024, None, "test-model");
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs.len(), 1);
+    assert_eq!(msgs[0]["role"], "tool");
+    assert_eq!(msgs[0]["tool_call_id"], "call_123");
+    assert_eq!(msgs[0]["content"], "file1.txt\nfile2.txt");
+}
+
+#[test]
+fn test_tool_result_error_conversion() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::User,
+        content: MessageContent::ToolResult {
+            tool_use_id: "call_456".to_string(),
+            content: "command not found".to_string(),
+            is_error: true,
+        },
+    }];
+
+    let request = build_openai_request(messages, None, vec![], 1024, None, "test-model");
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs[0]["role"], "tool");
+    assert_eq!(msgs[0]["content"], "[ERROR] command not found");
+}
+
+#[test]
+fn test_multipart_assistant_message() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::Assistant,
+        content: MessageContent::MultiPart(vec![
+            ContentPart::Text("I'll run that command for you.".to_string()),
+            ContentPart::ToolUse {
+                tool_use_id: "call_abc".to_string(),
+                name: "run_shell_command".to_string(),
+                input: json!({"command": "pwd"}),
+            },
+        ]),
+    }];
+
+    let request = build_openai_request(messages, None, vec![], 1024, None, "test-model");
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs.len(), 1);
+    assert_eq!(msgs[0]["role"], "assistant");
+    assert_eq!(msgs[0]["content"], "I'll run that command for you.");
+
+    let tool_calls = msgs[0]["tool_calls"].as_array().unwrap();
+    assert_eq!(tool_calls.len(), 1);
+    assert_eq!(tool_calls[0]["id"], "call_abc");
+    assert_eq!(tool_calls[0]["function"]["name"], "run_shell_command");
+}
+
+#[test]
+fn test_multipart_user_message_with_tool_results() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::User,
+        content: MessageContent::MultiPart(vec![
+            ContentPart::ToolResult {
+                tool_use_id: "call_1".to_string(),
+                content: "result 1".to_string(),
+                is_error: false,
+            },
+            ContentPart::ToolResult {
+                tool_use_id: "call_2".to_string(),
+                content: "result 2".to_string(),
+                is_error: false,
+            },
+        ]),
+    }];
+
+    let request = build_openai_request(messages, None, vec![], 1024, None, "test-model");
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs.len(), 2);
+    assert_eq!(msgs[0]["role"], "tool");
+    assert_eq!(msgs[0]["tool_call_id"], "call_1");
+    assert_eq!(msgs[1]["role"], "tool");
+    assert_eq!(msgs[1]["tool_call_id"], "call_2");
+}
+
+#[test]
+fn test_tool_definitions_conversion() {
+    let tools = vec![
+        ToolDefinition {
+            name: "run_shell_command".to_string(),
+            description: "Runs a shell command".to_string(),
+            input_schema: json!({
+                "type": "object",
+                "properties": {
+                    "command": {"type": "string"}
+                },
+                "required": ["command"]
+            }),
+        },
+        ToolDefinition {
+            name: "read_files".to_string(),
+            description: "Reads files from disk".to_string(),
+            input_schema: json!({
+                "type": "object",
+                "properties": {
+                    "files": {"type": "array", "items": {"type": "string"}}
+                }
+            }),
+        },
+    ];
+
+    let request = build_openai_request(vec![], None, tools, 1024, None, "test-model");
+
+    let tool_defs = request["tools"].as_array().unwrap();
+    assert_eq!(tool_defs.len(), 2);
+    assert_eq!(tool_defs[0]["type"], "function");
+    assert_eq!(tool_defs[0]["function"]["name"], "run_shell_command");
+    assert_eq!(
+        tool_defs[0]["function"]["description"],
+        "Runs a shell command"
+    );
+    assert_eq!(tool_defs[0]["function"]["parameters"]["type"], "object");
+    assert_eq!(tool_defs[1]["function"]["name"], "read_files");
+}
+
+#[test]
+fn test_temperature_handling() {
+    let messages = vec![ConversationMessage {
+        role: MessageRole::User,
+        content: MessageContent::Text("test".to_string()),
+    }];
+
+    // Temperature absent when None
+    let request = build_openai_request(messages.clone(), None, vec![], 1024, None, "test-model");
+    assert!(request.get("temperature").is_none());
+
+    // Temperature present when Some
+    let request = build_openai_request(messages, None, vec![], 1024, Some(0.7), "test-model");
+    assert!(request.get("temperature").is_some());
+}
+
+#[test]
+fn test_full_conversation_roundtrip() {
+    let messages = vec![
+        ConversationMessage {
+            role: MessageRole::User,
+            content: MessageContent::Text("List files".to_string()),
+        },
+        ConversationMessage {
+            role: MessageRole::Assistant,
+            content: MessageContent::ToolUse {
+                tool_use_id: "call_1".to_string(),
+                name: "run_shell_command".to_string(),
+                input: json!({"command": "ls"}),
+            },
+        },
+        ConversationMessage {
+            role: MessageRole::User,
+            content: MessageContent::ToolResult {
+                tool_use_id: "call_1".to_string(),
+                content: "file1.rs\nfile2.rs".to_string(),
+                is_error: false,
+            },
+        },
+        ConversationMessage {
+            role: MessageRole::Assistant,
+            content: MessageContent::Text("Here are the files: file1.rs and file2.rs".to_string()),
+        },
+    ];
+
+    let request = build_openai_request(
+        messages,
+        Some("You are Galaxy AI.".to_string()),
+        vec![],
+        4096,
+        None,
+        "claude-sonnet",
+    );
+
+    let msgs = request["messages"].as_array().unwrap();
+    assert_eq!(msgs.len(), 5); // system + 4 conversation messages
+    assert_eq!(msgs[0]["role"], "system");
+    assert_eq!(msgs[1]["role"], "user");
+    assert_eq!(msgs[2]["role"], "assistant");
+    assert_eq!(msgs[3]["role"], "tool");
+    assert_eq!(msgs[4]["role"], "assistant");
+}