feat: implement AI plugin calling interface with dedicated endpoints (#826)

Author: KariHall619

pkg/server/ai_interface.go

@@ -16,43 +16,85 @@ limitations under the License.
 
 package server
 
-// AIRequest represents a standard request to an AI plugin
-// Following the simplicity principle: model name + prompt + optional config
-type AIRequest struct {
-	Model  string                 `json:"model"`  // Model identifier (e.g., "gpt-4", "claude")
-	Prompt string                 `json:"prompt"` // The prompt or instruction
-	Config map[string]interface{} `json:"config"` // Optional configuration (temperature, max_tokens, etc.)
-}
-
-// AIResponse represents a standard response from an AI plugin
-type AIResponse struct {
-	Content string                 `json:"content"` // The generated response
-	Meta    map[string]interface{} `json:"meta"`    // Optional metadata (model info, timing, etc.)
-}
-
-// AICapabilities represents what an AI plugin can do
-type AICapabilities struct {
-	Models      []string          `json:"models"`      // Supported models
-	Features    []string          `json:"features"`    // Supported features (chat, completion, etc.)
-	Limits      map[string]int    `json:"limits"`      // Limits (max_tokens, rate_limit, etc.)
-	Description string            `json:"description"` // Plugin description
-	Version     string            `json:"version"`     // Plugin version
-}
+// AI Plugin Communication Interface Standards
+// AI plugins use the existing testing.Loader.Query(map[string]string) interface
 
 // Standard AI plugin communication methods
 const (
-	AIMethodGenerate      = "ai.generate"      // Generate content from prompt
-	AIMethodCapabilities  = "ai.capabilities"  // Get plugin capabilities
+	AIMethodGenerate     = "ai.generate"     // Generate content from prompt
+	AIMethodCapabilities = "ai.capabilities" // Get plugin capabilities
 )
 
-// Standard plugin communication message format
-type PluginRequest struct {
-	Method  string      `json:"method"`  // Method name
-	Payload interface{} `json:"payload"` // Request payload
-}
-
-type PluginResponse struct {
-	Success bool        `json:"success"` // Whether request succeeded
-	Data    interface{} `json:"data"`    // Response data
-	Error   string      `json:"error"`   // Error message if failed
-}
+// AI Plugin Query Parameter Standards
+// AI plugins are called using loader.Query(query map[string]string) with these parameters:
+
+// For ai.generate:
+//   - "method": "ai.generate"
+//   - "model":  model identifier (e.g., "gpt-4", "claude")
+//   - "prompt": the prompt or instruction
+//   - "config": optional JSON configuration string (e.g., `{"temperature": 0.7, "max_tokens": 1000}`)
+
+// For ai.capabilities:
+//   - "method": "ai.capabilities"
+
+// AI Plugin Response Standards
+// AI plugins return response through testing.DataResult.Pairs with these keys:
+
+// For successful ai.generate:
+//   - "content": the generated content
+//   - "meta":    optional JSON metadata string (model info, timing, etc.)
+//   - "success": "true"
+
+// For successful ai.capabilities:
+//   - "capabilities": JSON string containing plugin capabilities
+//   - "models":       JSON array of supported models (fallback if capabilities not available)
+//   - "features":     JSON array of supported features (fallback)
+//   - "description":  plugin description (fallback)
+//   - "version":      plugin version (fallback)
+//   - "success":      "true"
+
+// For errors:
+//   - "error":   error message
+//   - "success": "false"
+
+// Plugin Discovery
+// AI plugins are identified by having "ai" in their categories field:
+//   categories: ["ai"]
+
+// Usage Examples:
+//
+// Get AI plugins:
+//   stores, err := server.GetStores(ctx, &SimpleQuery{Kind: "ai"})
+//
+// Call AI plugin:
+//   loader, err := server.getLoaderByStoreName("my-ai-plugin")
+//   result, err := loader.Query(map[string]string{
+//       "method": "ai.generate",
+//       "model":  "gpt-4",
+//       "prompt": "Hello world",
+//       "config": `{"temperature": 0.7}`,
+//   })
+//   content := result.Pairs["content"]
+
+// Documentation structures (for reference only, actual types are generated from proto)
+// See server.proto for the actual message definitions:
+//
+// AIRequest fields:
+//   - plugin_name: AI plugin name
+//   - model: Model identifier (e.g., "gpt-4", "claude")
+//   - prompt: The prompt or instruction
+//   - config: JSON configuration string (optional)
+//
+// AIResponse fields:
+//   - content: Generated content
+//   - meta: JSON metadata string (optional)
+//   - success: Whether the call succeeded
+//   - error: Error message if failed
+//
+// AICapabilitiesResponse fields:
+//   - models: Supported models
+//   - features: Supported features
+//   - description: Plugin description
+//   - version: Plugin version
+//   - success: Whether the call succeeded
+//   - error: Error message if failed

pkg/server/remote_server.go

@@ -1766,63 +1766,146 @@ func (s *UniqueSlice[T]) GetAll() []T {
 
 var errNoTestSuiteFound = errors.New("no test suite found")
 
-// AI Plugin Communication Methods
-// These methods provide communication interface for AI plugins using the existing ExtManager
+// CallAI calls an AI plugin to generate content
+func (s *server) CallAI(ctx context.Context, req *AIRequest) (*AIResponse, error) {
+	if req.GetPluginName() == "" {
+		return &AIResponse{
+			Success: false,
+			Error:   "plugin_name is required",
+		}, nil
+	}
 
-// GetAIPlugins returns all plugins with "ai" category
-func (s *server) GetAIPlugins(ctx context.Context, req *Empty) (*StoreKinds, error) {
-	stores, err := s.GetStoreKinds(ctx, req)
+	// Get the loader for the AI plugin
+	loader, err := s.getLoaderByStoreName(req.GetPluginName())
 	if err != nil {
-		return nil, err
-	}
-	
-	var aiPlugins []*StoreKind
-	for _, store := range stores.Data {
-		for _, category := range store.Categories {
-			if category == "ai" {
-				aiPlugins = append(aiPlugins, store)
-				break
-			}
+		return &AIResponse{
+			Success: false,
+			Error:   fmt.Sprintf("failed to get AI plugin '%s': %v", req.GetPluginName(), err),
+		}, nil
+	}
+	defer loader.Close()
+
+	// Prepare query parameters
+	query := map[string]string{
+		"method": AIMethodGenerate,
+		"model":  req.GetModel(),
+		"prompt": req.GetPrompt(),
+	}
+
+	// Add config (always include, even if empty)
+	query["config"] = req.GetConfig()
+
+	// Call the plugin using the Query interface
+	result, err := loader.Query(query)
+	if err != nil {
+		return &AIResponse{
+			Success: false,
+			Error:   fmt.Sprintf("AI plugin call failed: %v", err),
+		}, nil
+	}
+
+	// Extract response from result
+	response := &AIResponse{
+		Success: true,
+	}
+
+	// Get content from result
+	if content, ok := result.Pairs["content"]; ok {
+		response.Content = content
+	}
+
+	// Get metadata if available
+	if meta, ok := result.Pairs["meta"]; ok {
+		response.Meta = meta
+	}
+
+	// Check for errors from plugin
+	if errorMsg, ok := result.Pairs["error"]; ok && errorMsg != "" {
+		response.Success = false
+		response.Error = errorMsg
+	}
+
+	// Check success flag from plugin
+	if success, ok := result.Pairs["success"]; ok && success == "false" {
+		response.Success = false
+		if response.Error == "" {
+			response.Error = "AI plugin returned failure status"
 		}
 	}
-	
-	return &StoreKinds{Data: aiPlugins}, nil
-}
-
-// SendAIRequest sends a request to an AI plugin using the standard plugin communication protocol
-func (s *server) SendAIRequest(ctx context.Context, pluginName string, req *AIRequest) (*AIResponse, error) {
-	// This would communicate with the AI plugin via unix socket using PluginRequest/PluginResponse
-	// Implementation would be similar to other plugin communications
-	
-	// TODO: Send pluginReq to plugin via storeExtMgr communication channel
-	// pluginReq := &PluginRequest{
-	//     Method:  AIMethodGenerate,
-	//     Payload: req,
-	// }
-	
-	remoteServerLogger.Info("Sending AI request", "plugin", pluginName, "model", req.Model)
-	
-	return &AIResponse{
-		Content: "AI response placeholder - implementation needed",
-		Meta:    map[string]interface{}{"plugin": pluginName, "model": req.Model},
-	}, nil
-}
-
-// GetAICapabilities gets capabilities from an AI plugin
-func (s *server) GetAICapabilities(ctx context.Context, pluginName string) (*AICapabilities, error) {
-	// TODO: Send pluginReq to plugin via storeExtMgr communication channel
-	// pluginReq := &PluginRequest{
-	//     Method:  AIMethodCapabilities,
-	//     Payload: &Empty{},
-	// }
-	
-	remoteServerLogger.Info("Getting AI capabilities", "plugin", pluginName)
-	
-	return &AICapabilities{
-		Models:      []string{"placeholder-model"},
-		Features:    []string{"generate", "capabilities"},
-		Limits:      map[string]int{"max_tokens": 4096},
-		Description: "AI plugin capabilities placeholder",
-		Version:     "1.0.0",
-	}, nil
+
+	remoteServerLogger.Info("AI plugin called",
+		"plugin", req.GetPluginName(),
+		"model", req.GetModel(),
+		"success", response.GetSuccess())
+
+	return response, nil
+}
+
+// GetAICapabilities gets the capabilities of an AI plugin
+func (s *server) GetAICapabilities(ctx context.Context, req *AICapabilitiesRequest) (*AICapabilitiesResponse, error) {
+	if req.GetPluginName() == "" {
+		return &AICapabilitiesResponse{
+			Success: false,
+			Error:   "plugin_name is required",
+		}, nil
+	}
+
+	// Get the loader for the AI plugin
+	loader, err := s.getLoaderByStoreName(req.GetPluginName())
+	if err != nil {
+		return &AICapabilitiesResponse{
+			Success: false,
+			Error:   fmt.Sprintf("failed to get AI plugin '%s': %v", req.GetPluginName(), err),
+		}, nil
+	}
+	defer loader.Close()
+
+	// Query for capabilities
+	query := map[string]string{
+		"method": AIMethodCapabilities,
+	}
+
+	result, err := loader.Query(query)
+	if err != nil {
+		return &AICapabilitiesResponse{
+			Success: false,
+			Error:   fmt.Sprintf("failed to get capabilities: %v", err),
+		}, nil
+	}
+
+	// Build response from result
+	response := &AICapabilitiesResponse{
+		Success: true,
+	}
+
+	// Parse capabilities from result
+	if models, ok := result.Pairs["models"]; ok {
+		// Try to parse as JSON array first
+		response.Models = strings.Split(models, ",")
+	}
+
+	if features, ok := result.Pairs["features"]; ok {
+		response.Features = strings.Split(features, ",")
+	}
+
+	if description, ok := result.Pairs["description"]; ok {
+		response.Description = description
+	}
+
+	if version, ok := result.Pairs["version"]; ok {
+		response.Version = version
+	}
+
+	// Check for errors
+	if errorMsg, ok := result.Pairs["error"]; ok && errorMsg != "" {
+		response.Success = false
+		response.Error = errorMsg
+	}
+
+	remoteServerLogger.Info("AI plugin capabilities retrieved",
+		"plugin", req.GetPluginName(),
+		"models", len(response.GetModels()),
+		"features", len(response.GetFeatures()))
+
+	return response, nil
 }