descriptions

Author: antonpirker

docs/platforms/python/tracing/instrumentation/custom-instrumentation/agents-module.mdx

@@ -85,11 +85,11 @@ This span wraps the execution of a tool.
     - `gen_ai.request.presence_penalty`: Model configuration
     - `gen_ai.request.temperature`: Model configuration
     - `gen_ai.request.top_p`:  Model configuration
-    - `gen_ai.tool.description`:
-    - `gen_ai.tool.input`: \{"max":10\}
-    - `gen_ai.tool.name:`: "random_number"
-    - `gen_ai.tool.output`:
-    - `gen_ai.tool.type`:
+    - `gen_ai.tool.description`: Description of the tool executed
+    - `gen_ai.tool.input`: Input that was given to the executed too. (Example: \{"max":10\})
+    - `gen_ai.tool.name:`: Name of the tool executed. (Example: "random_number")
+    - `gen_ai.tool.output`: The output from the tool.
+    - `gen_ai.tool.type`: The type of the tools. Can be `function`, `extension`, `datastore`
 
 ### AI Client Span
 
@@ -98,20 +98,16 @@ This span wraps the request to an LLM.
 - `span.op` = `"gen_ai.{gen_ai.operation.name}"` (Example: `"gen_ai.chat"`)
 - `span.name` = `"{gen_ai.operation.name} {model.name}"` (Example: `"chat gpt-4o-mini"`)
 - Span attributes:
-  - `gen_ai.request.available_tools`
+  - `gen_ai.request.available_tools`: Array of objects describing the available tools.
+  - `gen_ai.request.messages`: Array of objects describing the messages sent to the LLM (Each object has the format `{ role:"", content:""}` where role can be `user`, `assistant`, or `system` and `content` can either be a string or an array of objects.)
+  - `gen_ai.response.tool_calls`: Array of objects returned from the LLM with information about what tools need to be called.
   - `gen_ai.request.frequency_penalty`
   - `gen_ai.request.max_tokens`
-  - `gen_ai.request.messages`
-  - `gen_ai.request.model`
   - `gen_ai.request.presence_penalty`
   - `gen_ai.request.temperature`
   - `gen_ai.request.top_p`
-  - `gen_ai.response.tool_calls`
-  - `gen_ai.system`
-  - `gen_ai.system.message`
-  - `gen_ai.usage.input_tokens`
-  - `gen_ai.usage.input_tokens.cached`
-  - `gen_ai.usage.output_tokens`
-  - `gen_ai.usage.output_tokens.reasoning`
-  - `gen_ai.usage.total_tokens`
-  - `gen_ai.user.message`
+  - `gen_ai.usage.input_tokens`: Input tokens used for the request. (excluding cached tokens)
+  - `gen_ai.usage.input_tokens.cached`: Cached input tokens used for the request.
+  - `gen_ai.usage.output_tokens`: Output tokens used for the request.
+  - `gen_ai.usage.output_tokens.reasoning` Tokens used for reasoning.
+  - `gen_ai.usage.total_tokens`: Total number of tokens used in the request.

src/instrumentation.ts

@@ -1,37 +1,37 @@
 import * as Sentry from '@sentry/nextjs';
 
-export function register() {
-  if (process.env.NEXT_RUNTIME === 'nodejs') {
-    Sentry.init({
-      dsn: process.env.SENTRY_DSN,
-      tracesSampleRate: 1,
-      debug: false,
-      environment: process.env.NODE_ENV === 'development' ? 'development' : undefined,
-      spotlight: process.env.NODE_ENV === 'development',
-    });
-  }
+// export function register() {
+//   if (process.env.NEXT_RUNTIME === 'nodejs') {
+//     Sentry.init({
+//       dsn: process.env.SENTRY_DSN,
+//       tracesSampleRate: 1,
+//       debug: false,
+//       environment: process.env.NODE_ENV === 'development' ? 'development' : undefined,
+//       spotlight: process.env.NODE_ENV === 'development',
+//     });
+//   }
 
-  if (process.env.NEXT_RUNTIME === 'edge') {
-    Sentry.init({
-      dsn: process.env.SENTRY_DSN,
-      tracesSampleRate: 1,
-      debug: false,
-      environment: process.env.NODE_ENV === 'development' ? 'development' : undefined,
-      // temporary change for investigating edge middleware tx names
-      beforeSendTransaction(event) {
-        if (
-          event.transaction?.includes('middleware GET') &&
-          event.contexts?.trace?.data
-        ) {
-          event.contexts.trace.data = {
-            ...event.contexts.trace.data,
-            'sentry.source': 'custom',
-          };
-        }
-        return event;
-      },
-    });
-  }
-}
+//   if (process.env.NEXT_RUNTIME === 'edge') {
+//     Sentry.init({
+//       dsn: process.env.SENTRY_DSN,
+//       tracesSampleRate: 1,
+//       debug: false,
+//       environment: process.env.NODE_ENV === 'development' ? 'development' : undefined,
+//       // temporary change for investigating edge middleware tx names
+//       beforeSendTransaction(event) {
+//         if (
+//           event.transaction?.includes('middleware GET') &&
+//           event.contexts?.trace?.data
+//         ) {
+//           event.contexts.trace.data = {
+//             ...event.contexts.trace.data,
+//             'sentry.source': 'custom',
+//           };
+//         }
+//         return event;
+//       },
+//     });
+//   }
+// }
 
-export const onRequestError = Sentry.captureRequestError;
+// export const onRequestError = Sentry.captureRequestError;