[BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

Description

@braintrust-bot

Summary

The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

What is missing

BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

if (chatModelinstanceofOpenAiChatModeloaiModel) {
aiServices.chatModel(wrap(openTelemetry, oaiModel));
} else {
log.warn("unsupported model: {}. LLM calls will not be instrumented",
chatModel.getClass().getName());
}

The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

The most impactful missing model providers are:

LangChain4j model classProvider
AnthropicChatModelAnthropic Claude
GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
MistralAiChatModel / MistralAiStreamingChatModelMistral AI

Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

Braintrust docs status

Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

Upstream sources

  • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
  • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
  • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

Local files inspected

  • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
  • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
  • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

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      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all
       blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
      }
      } catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
      })();
      (function(){
      try {
      var __m = "github.com";
      var __re = new RegExp('^' + "github\\.com" + '
      
      Skip to content

      [BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

      Description

      @braintrust-bot

      Summary

      The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

      Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

      What is missing

      BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

      if (chatModelinstanceofOpenAiChatModeloaiModel) {
      aiServices.chatModel(wrap(openTelemetry, oaiModel));
      } else {
      log.warn("unsupported model: {}. LLM calls will not be instrumented",
      chatModel.getClass().getName());
      }

      The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

      The most impactful missing model providers are:

      LangChain4j model classProvider
      AnthropicChatModelAnthropic Claude
      GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
      VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
      AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
      MistralAiChatModel / MistralAiStreamingChatModelMistral AI

      Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

      Braintrust docs status

      Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

      Upstream sources

      • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
      • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
      • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

      Local files inspected

      • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
      • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
      • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

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          , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix"); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
          Skip to content

          [BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

          Description

          @braintrust-bot

          Summary

          The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

          Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

          What is missing

          BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

          if (chatModelinstanceofOpenAiChatModeloaiModel) {
          aiServices.chatModel(wrap(openTelemetry, oaiModel));
          } else {
          log.warn("unsupported model: {}. LLM calls will not be instrumented",
          chatModel.getClass().getName());
          }

          The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

          The most impactful missing model providers are:

          LangChain4j model classProvider
          AnthropicChatModelAnthropic Claude
          GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
          VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
          AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
          MistralAiChatModel / MistralAiStreamingChatModelMistral AI

          Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

          Braintrust docs status

          Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

          Upstream sources

          • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
          • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
          • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

          Local files inspected

          • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
          • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
          • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

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            No type

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            No projects

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              No milestone

              Relationships

              None yet

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              No branches or pull requests

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              , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms"); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
              Skip to content

              [BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

              Description

              @braintrust-bot

              Summary

              The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

              Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

              What is missing

              BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

              if (chatModelinstanceofOpenAiChatModeloaiModel) {
              aiServices.chatModel(wrap(openTelemetry, oaiModel));
              } else {
              log.warn("unsupported model: {}. LLM calls will not be instrumented",
              chatModel.getClass().getName());
              }

              The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

              The most impactful missing model providers are:

              LangChain4j model classProvider
              AnthropicChatModelAnthropic Claude
              GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
              VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
              AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
              MistralAiChatModel / MistralAiStreamingChatModelMistral AI

              Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

              Braintrust docs status

              Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

              Upstream sources

              • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
              • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
              • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

              Local files inspected

              • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
              • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
              • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

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                  No milestone

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                  None yet

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                  No branches or pull requests

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                  , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links"); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
                  Skip to content

                  [BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

                  Description

                  @braintrust-bot

                  Summary

                  The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

                  Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

                  What is missing

                  BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

                  if (chatModelinstanceofOpenAiChatModeloaiModel) {
                  aiServices.chatModel(wrap(openTelemetry, oaiModel));
                  } else {
                  log.warn("unsupported model: {}. LLM calls will not be instrumented",
                  chatModel.getClass().getName());
                  }

                  The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

                  The most impactful missing model providers are:

                  LangChain4j model classProvider
                  AnthropicChatModelAnthropic Claude
                  GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
                  VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
                  AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
                  MistralAiChatModel / MistralAiStreamingChatModelMistral AI

                  Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

                  Braintrust docs status

                  Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

                  Upstream sources

                  • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
                  • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
                  • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

                  Local files inspected

                  • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
                  • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
                  • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

                  Metadata

                  Metadata

                  Assignees

                  No one assigned

                    Labels

                    No labels
                    No labels

                    Type

                    No type

                    Projects

                    No projects

                      Milestone

                      No milestone

                      Relationships

                      None yet

                      Development

                      No branches or pull requests

                      Issue actions

                      , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default"); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
                      Skip to content

                      [BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

                      Description

                      @braintrust-bot

                      Summary

                      The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

                      Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

                      What is missing

                      BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

                      if (chatModelinstanceofOpenAiChatModeloaiModel) {
                      aiServices.chatModel(wrap(openTelemetry, oaiModel));
                      } else {
                      log.warn("unsupported model: {}. LLM calls will not be instrumented",
                      chatModel.getClass().getName());
                      }

                      The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

                      The most impactful missing model providers are:

                      LangChain4j model classProvider
                      AnthropicChatModelAnthropic Claude
                      GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
                      VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
                      AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
                      MistralAiChatModel / MistralAiStreamingChatModelMistral AI

                      Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

                      Braintrust docs status

                      Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

                      Upstream sources

                      • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
                      • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
                      • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

                      Local files inspected

                      • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
                      • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
                      • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

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                          , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers"); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
                          Skip to content

                          [BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

                          Description

                          @braintrust-bot

                          Summary

                          The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

                          Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

                          What is missing

                          BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

                          if (chatModelinstanceofOpenAiChatModeloaiModel) {
                          aiServices.chatModel(wrap(openTelemetry, oaiModel));
                          } else {
                          log.warn("unsupported model: {}. LLM calls will not be instrumented",
                          chatModel.getClass().getName());
                          }

                          The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

                          The most impactful missing model providers are:

                          LangChain4j model classProvider
                          AnthropicChatModelAnthropic Claude
                          GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
                          VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
                          AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
                          MistralAiChatModel / MistralAiStreamingChatModelMistral AI

                          Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

                          Braintrust docs status

                          Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

                          Upstream sources

                          • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
                          • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
                          • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

                          Local files inspected

                          • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
                          • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
                          • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

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                              None yet

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                              No branches or pull requests

                              Issue actions

                              , 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode"); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
                              Skip to content

                              [BOT ISSUE] LangChain4j instrumentation only supports OpenAI-backed chat models #60

                              Description

                              @braintrust-bot

                              Summary

                              The LangChain4j instrumentation only wraps OpenAiChatModel and OpenAiStreamingChatModel. All other LangChain4j model providers — including Anthropic, Google Gemini, Azure OpenAI, and Mistral — are explicitly skipped with a warning, producing no LLM-level span data for those calls.

                              Unlike the Spring AI integration (where unsupported providers can fall through to direct SDK auto-instrumentation, e.g. the GenAI module intercepts Client$Builder.build()), LangChain4j model providers use their own internal HTTP clients rather than the upstream SDK clients. This means no other auto-instrumentation module catches these calls.

                              What is missing

                              BraintrustLangchain.wrap(OpenTelemetry, AiServices) (lines 36-51) performs instanceof checks against only two model classes:

                              if (chatModelinstanceofOpenAiChatModeloaiModel) {
                              aiServices.chatModel(wrap(openTelemetry, oaiModel));
                              } else {
                              log.warn("unsupported model: {}. LLM calls will not be instrumented",
                              chatModel.getClass().getName());
                              }

                              The auto-instrumentation module (LangchainInstrumentationModule) similarly only registers ByteBuddy advice for OpenAiChatModel$OpenAiChatModelBuilder.build() and OpenAiStreamingChatModel$OpenAiStreamingChatModelBuilder.build().

                              The most impactful missing model providers are:

                              LangChain4j model classProvider
                              AnthropicChatModelAnthropic Claude
                              GoogleAiGeminiChatModel / GoogleAiGeminiStreamingChatModelGoogle Gemini
                              VertexAiGeminiChatModel / VertexAiGeminiStreamingChatModelGoogle Vertex AI
                              AzureOpenAiChatModel / AzureOpenAiStreamingChatModelAzure OpenAI
                              MistralAiChatModel / MistralAiStreamingChatModelMistral AI

                              Since the existing OpenAI instrumentation works by wrapping LangChain4j's internal HttpClient interface (extracted via reflection from the model's internal client), the same pattern could apply to other providers — each uses the same dev.langchain4j.http.client.HttpClient interface internally.

                              Braintrust docs status

                              Braintrust docs do not have a LangChain4j-specific page. The Java SDK is listed as supported for OpenAI, Anthropic, and Gemini providers at https://www.braintrust.dev/docs/integrations/ai-providers, but LangChain4j as a framework integration is not_found in docs.

                              Upstream sources

                              • LangChain4j supports 20+ model providers as first-party integrations: https://github.com/langchain4j/langchain4j
                              • LangChain4j model provider modules: langchain4j-anthropic, langchain4j-google-ai-gemini, langchain4j-vertex-ai-gemini, langchain4j-azure-open-ai, langchain4j-mistral-ai, etc.
                              • All LangChain4j model providers use their own dev.langchain4j.http.client.HttpClient internally (not the upstream provider SDK), so upstream SDK auto-instrumentation does not cover them.

                              Local files inspected

                              • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/BraintrustLangchain.java — lines 36-51 (instanceof check limits to OpenAI only), lines 88-152 (OpenAI-specific wrapping via internal HttpClient)
                              • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/auto/LangchainInstrumentationModule.java — lines 55-68, 85-100 (auto-instrumentation only targets OpenAI builders)
                              • braintrust-sdk/instrumentation/langchain_1_8_0/src/main/java/dev/braintrust/instrumentation/langchain/v1_8_0/WrappedHttpClient.java — the HTTP client wrapper that could be reused for other providers

                              Metadata

                              Metadata

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                              No one assigned

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                                No projects

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                                  No milestone

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                                  None yet

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                                  No branches or pull requests

                                  Issue actions