fix(ai-sdk): Add conversion to opentelemetry semantic convention

packages/ai-semantic-conventions/src/SemanticAttributes.ts

@@ -39,6 +39,15 @@ export const SpanAttributes = {
     "gen_ai.usage.cache_creation_input_tokens",
   GEN_AI_USAGE_CACHE_READ_INPUT_TOKENS: "gen_ai.usage.cache_read_input_tokens",
   GEN_AI_USAGE_REASONING_TOKENS: "gen_ai.usage.reasoning_tokens",
+  GEN_AI_OPERATION_NAME: "gen_ai.operation.name",
+  GEN_AI_PROVIDER_NAME: "gen_ai.provider.name",
+  GEN_AI_TOOL_NAME: "gen_ai.tool.name",
+  GEN_AI_TOOL_CALL_ID: "gen_ai.tool.call.id",
+  GEN_AI_TOOL_CALL_ARGUMENTS: "gen_ai.tool.call.arguments",
+  GEN_AI_TOOL_CALL_RESULT: "gen_ai.tool.call.result",
+  GEN_AI_RESPONSE_ID: "gen_ai.response.id",
+  GEN_AI_RESPONSE_FINISH_REASONS: "gen_ai.response.finish_reasons",
+  GEN_AI_CONVERSATION_ID: "gen_ai.conversation.id",
 
   GEN_AI_AGENT_NAME: "gen_ai.agent.name",
 

packages/traceloop-sdk/src/lib/tracing/ai-sdk-transformations.ts

@@ -310,7 +310,43 @@ const transformPrompts = (attributes: Record<string, any>): void => {
   if (AI_PROMPT in attributes) {
     try {
       const promptData = JSON.parse(attributes[AI_PROMPT] as string);
-      if (promptData.prompt && typeof promptData.prompt === "string") {
+
+      // Handle case where promptData has a "messages" array
+      if (promptData.messages && Array.isArray(promptData.messages)) {
+        const messages = promptData.messages;
+        const inputMessages: any[] = [];
+
+        messages.forEach(
+          (msg: { role: string; content: any }, index: number) => {
+            const processedContent = processMessageContent(msg.content);
+            const contentKey = `${SpanAttributes.LLM_PROMPTS}.${index}.content`;
+            attributes[contentKey] = processedContent;
+            attributes[`${SpanAttributes.LLM_PROMPTS}.${index}.role`] =
+              msg.role;
+
+            // Add to OpenTelemetry standard gen_ai.input.messages format
+            inputMessages.push({
+              role: msg.role,
+              parts: [
+                {
+                  type: TYPE_TEXT,
+                  content: processedContent,
+                },
+              ],
+            });
+          },
+        );
+
+        // Set the OpenTelemetry standard input messages attribute
+        if (inputMessages.length > 0) {
+          attributes[SpanAttributes.LLM_INPUT_MESSAGES] =
+            JSON.stringify(inputMessages);
+        }
+
+        delete attributes[AI_PROMPT];
+      }
+      // Handle case where promptData has a "prompt" string
+      else if (promptData.prompt && typeof promptData.prompt === "string") {
         attributes[`${SpanAttributes.LLM_PROMPTS}.0.content`] =
           promptData.prompt;
         attributes[`${SpanAttributes.LLM_PROMPTS}.0.role`] = ROLE_USER;
@@ -432,6 +468,10 @@ const transformVendor = (attributes: Record<string, any>): void => {
     // Find matching vendor prefix in mapping
     let mappedVendor = null;
     if (typeof vendor === "string" && vendor.length > 0) {
+      // Extract base provider name for OpenTelemetry standard (e.g., "openai" from "openai.chat")
+      const providerName = vendor.split(".")[0];
+      attributes[SpanAttributes.GEN_AI_PROVIDER_NAME] = providerName;
+
       for (const prefix of Object.keys(VENDOR_MAPPING)) {
         if (vendor.startsWith(prefix)) {
           mappedVendor = VENDOR_MAPPING[prefix];
@@ -445,6 +485,109 @@ const transformVendor = (attributes: Record<string, any>): void => {
   }
 };
 
+const transformOperationName = (
+  attributes: Record<string, any>,
+  spanName?: string,
+): void => {
+  if (!spanName) return;
+
+  let operationName: string | undefined;
+  if (
+    spanName.includes("generateText") ||
+    spanName.includes("streamText") ||
+    spanName.includes("generateObject") ||
+    spanName.includes("streamObject")
+  ) {
+    operationName = "chat";
+  } else if (spanName === "ai.toolCall" || spanName.endsWith(".tool")) {
+    operationName = "execute_tool";
+  }
+
+  if (operationName) {
+    attributes[SpanAttributes.GEN_AI_OPERATION_NAME] = operationName;
+  }
+};
+
+const transformModelId = (attributes: Record<string, any>): void => {
+  const AI_MODEL_ID = "ai.model.id";
+  if (AI_MODEL_ID in attributes) {
+    attributes[SpanAttributes.LLM_REQUEST_MODEL] = attributes[AI_MODEL_ID];
+    delete attributes[AI_MODEL_ID];
+  }
+};
+
+const transformFinishReason = (attributes: Record<string, any>): void => {
+  const AI_RESPONSE_FINISH_REASON = "ai.response.finishReason";
+  if (AI_RESPONSE_FINISH_REASON in attributes) {
+    const finishReason = attributes[AI_RESPONSE_FINISH_REASON];
+    // Convert to array format for OTel standard
+    attributes[SpanAttributes.GEN_AI_RESPONSE_FINISH_REASONS] = Array.isArray(
+      finishReason,
+    )
+      ? finishReason
+      : [finishReason];
+    delete attributes[AI_RESPONSE_FINISH_REASON];
+  }
+};
+
+const transformToolCallAttributes = (attributes: Record<string, any>): void => {
+  // Transform tool name
+  if ("ai.toolCall.name" in attributes) {
+    attributes[SpanAttributes.GEN_AI_TOOL_NAME] =
+      attributes["ai.toolCall.name"];
+    // Keep ai.toolCall.name for now, will be deleted in transformToolCalls
+  }
+
+  // Transform tool call ID
+  if ("ai.toolCall.id" in attributes) {
+    attributes[SpanAttributes.GEN_AI_TOOL_CALL_ID] =
+      attributes["ai.toolCall.id"];
+    delete attributes["ai.toolCall.id"];
+  }
+
+  // Transform tool arguments (keep both OTel and Traceloop versions)
+  if ("ai.toolCall.args" in attributes) {
+    attributes[SpanAttributes.GEN_AI_TOOL_CALL_ARGUMENTS] =
+      attributes["ai.toolCall.args"];
+    // Don't delete yet - transformToolCalls will handle entity input/output
+  }
+
+  // Transform tool result (keep both OTel and Traceloop versions)
+  if ("ai.toolCall.result" in attributes) {
+    attributes[SpanAttributes.GEN_AI_TOOL_CALL_RESULT] =
+      attributes["ai.toolCall.result"];
+    // Don't delete yet - transformToolCalls will handle entity input/output
+  }
+};
+
+const transformConversationId = (attributes: Record<string, any>): void => {
+  // Check for conversation/session ID in metadata
+  const conversationId = attributes["ai.telemetry.metadata.conversationId"];
+  const sessionId = attributes["ai.telemetry.metadata.sessionId"];
+
+  if (conversationId) {
+    attributes[SpanAttributes.GEN_AI_CONVERSATION_ID] = conversationId;
+  } else if (sessionId) {
+    attributes[SpanAttributes.GEN_AI_CONVERSATION_ID] = sessionId;
+  }
+};
+
+const transformResponseMetadata = (attributes: Record<string, any>): void => {
+  const AI_RESPONSE_MODEL = "ai.response.model";
+  const AI_RESPONSE_ID = "ai.response.id";
+
+  if (AI_RESPONSE_MODEL in attributes) {
+    attributes[SpanAttributes.LLM_RESPONSE_MODEL] =
+      attributes[AI_RESPONSE_MODEL];
+    delete attributes[AI_RESPONSE_MODEL];
+  }
+
+  if (AI_RESPONSE_ID in attributes) {
+    attributes[SpanAttributes.GEN_AI_RESPONSE_ID] = attributes[AI_RESPONSE_ID];
+    delete attributes[AI_RESPONSE_ID];
+  }
+};
+
 const transformTelemetryMetadata = (
   attributes: Record<string, any>,
   spanName?: string,
@@ -525,6 +668,8 @@ export const transformLLMSpans = (
   attributes: Record<string, any>,
   spanName?: string,
 ): void => {
+  transformOperationName(attributes, spanName);
+  transformModelId(attributes);
   transformResponseText(attributes);
   transformResponseObject(attributes);
   transformResponseToolCalls(attributes);
@@ -533,8 +678,12 @@ export const transformLLMSpans = (
   transformPromptTokens(attributes);
   transformCompletionTokens(attributes);
   transformProviderMetadata(attributes);
+  transformFinishReason(attributes);
+  transformResponseMetadata(attributes);
   calculateTotalTokens(attributes);
-  transformVendor(attributes);
+  transformVendor(attributes); // Also sets GEN_AI_PROVIDER_NAME
+  transformConversationId(attributes);
+  transformToolCallAttributes(attributes);
   transformTelemetryMetadata(attributes, spanName);
 };
 
@@ -556,6 +705,7 @@ const transformToolCalls = (span: ReadableSpan): void => {
     const toolName = span.attributes["ai.toolCall.name"];
     if (toolName) {
       span.attributes[SpanAttributes.TRACELOOP_ENTITY_NAME] = toolName;
+      delete span.attributes["ai.toolCall.name"];
     }
   }
 };