Fix/native tracing (#87)

<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **New Features**
* Added Langfuse tracing auto-configuration for evaluation requests when
credentials are provided.
* Docker builds now support AUTOMATED_MODE as an optional build argument
(default: enabled) for flexible build-time control.

* **Documentation**
* Added deployment type reference guide to Docker documentation
outlining DevTools and Agent Server configurations.

<sub>✏️ Tip: You can customize this high-level summary in your review
settings.</sub>
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

Author: Daedaelius

agent-server/nodejs/src/api-server.js

@@ -593,26 +593,33 @@ class APIServer {
       // 1. Try tier-specific endpoint (e.g., main_model.endpoint)
       // 2. Fall back to top-level endpoint (e.g., model.endpoint)
       // 3. Fall back to LITELLM_ENDPOINT env var (for litellm provider)
-      const getEndpoint = (tierConfig) => {
-        const explicitEndpoint = tierConfig?.endpoint || requestBody.model.endpoint;
+      // @param {Object} resolvedConfig - Config after extractModelTierConfig (has defaults applied)
+      // @param {Object} rawTierConfig - Original tier config from request (may be undefined)
+      const getEndpoint = (resolvedConfig, rawTierConfig) => {
+        const explicitEndpoint = rawTierConfig?.endpoint || requestBody.model.endpoint;
         if (explicitEndpoint) return explicitEndpoint;
-        // Use env var default for litellm provider
-        if (tierConfig?.provider === 'litellm') return defaultLiteLLMEndpoint;
+        // Use env var default for litellm provider (check resolved config for provider)
+        if (resolvedConfig?.provider === 'litellm') return defaultLiteLLMEndpoint;
         return undefined;
       };
 
+      // Extract tier configs first so getEndpoint can use resolved provider
+      const mainConfig = this.extractModelTierConfig('main', requestBody.model.main_model, defaults);
+      const miniConfig = this.extractModelTierConfig('mini', requestBody.model.mini_model, defaults);
+      const nanoConfig = this.extractModelTierConfig('nano', requestBody.model.nano_model, defaults);
+
       return {
         main_model: {
-          ...this.extractModelTierConfig('main', requestBody.model.main_model, defaults),
-          endpoint: getEndpoint(requestBody.model.main_model)
+          ...mainConfig,
+          endpoint: getEndpoint(mainConfig, requestBody.model.main_model)
         },
         mini_model: {
-          ...this.extractModelTierConfig('mini', requestBody.model.mini_model, defaults),
-          endpoint: getEndpoint(requestBody.model.mini_model)
+          ...miniConfig,
+          endpoint: getEndpoint(miniConfig, requestBody.model.mini_model)
         },
         nano_model: {
-          ...this.extractModelTierConfig('nano', requestBody.model.nano_model, defaults),
-          endpoint: getEndpoint(requestBody.model.nano_model)
+          ...nanoConfig,
+          endpoint: getEndpoint(nanoConfig, requestBody.model.nano_model)
         }
       };
     }

docker/Dockerfile

@@ -47,11 +47,18 @@ RUN git remote add upstream https://github.com/BrowserOperator/browser-operator-
 RUN git fetch upstream
 RUN git checkout upstream/main
 
-# Force automated mode (matches parent Dockerfile.devtools approach - rock-solid)
-RUN sed -i 's/AUTOMATED_MODE: false/AUTOMATED_MODE: true/' \
-    front_end/panels/ai_chat/core/BuildConfig.ts || true
-
-# Build Browser Operator version with current changes
+# Copy local LLM changes on top of the upstream code
+# This allows iterative development without breaking BUILD.gn compatibility
+COPY front_end/panels/ai_chat/LLM /workspace/devtools/devtools-frontend/front_end/panels/ai_chat/LLM
+
+# AUTOMATED_MODE: Default true for API mode (Type 2/3). Override with --build-arg AUTOMATED_MODE=false for Type 1.
+ARG AUTOMATED_MODE=true
+RUN if [ "$AUTOMATED_MODE" = "true" ]; then \
+      sed -i 's/AUTOMATED_MODE: false/AUTOMATED_MODE: true/' \
+      front_end/panels/ai_chat/core/BuildConfig.ts; \
+    fi
+
+# Build Browser Operator version with local changes
 RUN npm run build
 
 # ==============================================================================

docker/README.md

@@ -2,6 +2,10 @@
 
 This directory contains Docker configuration files for building and running the Browser Operator DevTools Frontend with integrated Agent Server in a containerized environment.
 
+> **Deployment Types:** This directory supports **Type 1** (DevTools only) and **Type 2** (DevTools + Agent Server).
+> For **Type 3** (full dockerized browser), see the [web-agent](https://github.com/BrowserOperator/web-agent) repository.
+> Quick reference: [CLAUDE.md](../CLAUDE.md)
+
 ## Overview
 
 The Docker setup uses a multi-stage build process:

front_end/panels/ai_chat/evaluation/remote/EvaluationAgent.ts

@@ -11,7 +11,7 @@ import { ToolRegistry, ConfigurableAgentTool } from '../../agent_framework/Confi
 import { AgentService } from '../../core/AgentService.js';
 import { AIChatPanel } from '../../ui/AIChatPanel.js';
 import { createLogger } from '../../core/Logger.js';
-import { createTracingProvider, withTracingContext, isTracingEnabled, getTracingConfig } from '../../tracing/TracingConfig.js';
+import { createTracingProvider, withTracingContext, isTracingEnabled, getTracingConfig, setTracingConfig, refreshTracingProvider } from '../../tracing/TracingConfig.js';
 import { AgentDescriptorRegistry, type AgentDescriptor } from '../../core/AgentDescriptorRegistry.js';
 import '../../core/BaseOrchestratorAgent.js';
 import type { TracingProvider, TracingContext } from '../../tracing/TracingProvider.js';
@@ -433,9 +433,37 @@ export class EvaluationAgent {
       hasTracing: !!params.tracing,
       tracingKeys: Object.keys(requestTracing),
       sessionId: requestTracing.session_id,
-      traceId: requestTracing.trace_id
+      traceId: requestTracing.trace_id,
+      hasLangfuseCredentials: !!(requestTracing.langfuse_endpoint && requestTracing.langfuse_public_key && requestTracing.langfuse_secret_key)
     });
 
+    // Auto-configure Langfuse tracing from request if credentials provided and not already enabled
+    if (requestTracing.langfuse_endpoint &&
+        requestTracing.langfuse_public_key &&
+        requestTracing.langfuse_secret_key &&
+        !isTracingEnabled()) {
+      logger.info('Auto-configuring DevTools Langfuse tracing from request', {
+        endpoint: requestTracing.langfuse_endpoint,
+        hasPublicKey: true,
+        hasSecretKey: true
+      });
+
+      setTracingConfig({
+        provider: 'langfuse',
+        endpoint: requestTracing.langfuse_endpoint,
+        publicKey: requestTracing.langfuse_public_key,
+        secretKey: requestTracing.langfuse_secret_key
+      });
+
+      // Refresh the tracing provider to pick up new configuration
+      await refreshTracingProvider();
+
+      // Update this instance's tracing provider
+      this.tracingProvider = createTracingProvider();
+
+      logger.info('DevTools Langfuse tracing configured successfully from request');
+    }
+
     // Create a trace for this evaluation - use tracing from request if available
     const traceId = requestTracing.trace_id || `eval-${params.evaluationId}-${Date.now()}`;
     const sessionId = requestTracing.session_id || `eval-session-${Date.now()}`;

front_end/panels/ai_chat/evaluation/remote/EvaluationProtocol.ts

@@ -113,6 +113,11 @@ export interface EvaluationParams {
     category?: string;
     tags?: string[];
     trace_name?: string;
+    // Langfuse credentials for auto-configuration
+    // When provided, DevTools will auto-configure Langfuse tracing if not already enabled
+    langfuse_endpoint?: string;
+    langfuse_public_key?: string;
+    langfuse_secret_key?: string;
   };
 }