Google GenAI: grounding metadata from Google Search not captured in span output #153

Closed
Bug
#155
Closed
Google GenAI: grounding metadata from Google Search not captured in span output#153
Bug
#155
Assignees
AbhiPrasad
Labels
bot-automationintegration: google_genai

Description

@braintrust-bot
braintrust-bot
bot
opened on Mar 26, 2026

Gap

When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.

Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.

What is missing

The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:

  • grounding_chunks — the actual search result snippets used by the model
  • grounding_supports — which parts of the response are supported by which chunks
  • search_entry_point — the rendered search widget URL
  • web_search_queries — the queries the model issued to Google Search

The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.

Braintrust docs status

not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.

Upstream sources

  • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
  • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
  • Grounding is GA for Gemini 1.5 and 2.0 models

Local files inspected

  • py/src/braintrust/wrappers/google_genai/__init__.py:
    • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
    • _serialize_tools() — serializes tool declarations (including google_search) for span input
    • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
  • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
  • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata

Metadata

Metadata

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Labels

bot-automationintegration: google_genai

Type

Bug

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("// 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
    Google GenAI: grounding metadata from Google Search not captured in span output #153
    Closed
    Bug
    #155
    Closed
    Google GenAI: grounding metadata from Google Search not captured in span output#153
    Bug
    #155
    Assignees
    AbhiPrasad
    Labels
    bot-automationintegration: google_genai
    Description
    @braintrust-bot
    braintrust-bot
    bot
    opened on Mar 26, 2026
    Gap
    When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.
    Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.
    What is missing
    The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:
    • grounding_chunks — the actual search result snippets used by the model
    • grounding_supports — which parts of the response are supported by which chunks
    • search_entry_point — the rendered search widget URL
    • web_search_queries — the queries the model issued to Google Search
    The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.
    Braintrust docs status
    not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.
    Upstream sources
    • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
    • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
    • Grounding is GA for Gemini 1.5 and 2.0 models
    Local files inspected
    • py/src/braintrust/wrappers/google_genai/__init__.py:

      • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
      • _serialize_tools() — serializes tool declarations (including google_search) for span input
      • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
    • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
    • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata
    Metadata
    Metadata
    Assignees
    Labels
    bot-automationintegration: google_genai
    Type
    Bug
    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("// 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
      Google GenAI: grounding metadata from Google Search not captured in span output #153
      Closed
      Bug
      #155
      Closed
      Google GenAI: grounding metadata from Google Search not captured in span output#153
      Bug
      #155
      Assignees
      AbhiPrasad
      Labels
      bot-automationintegration: google_genai
      Description
      @braintrust-bot
      braintrust-bot
      bot
      opened on Mar 26, 2026
      Gap
      When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.
      Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.
      What is missing
      The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:
      • grounding_chunks — the actual search result snippets used by the model
      • grounding_supports — which parts of the response are supported by which chunks
      • search_entry_point — the rendered search widget URL
      • web_search_queries — the queries the model issued to Google Search
      The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.
      Braintrust docs status
      not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.
      Upstream sources
      • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
      • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
      • Grounding is GA for Gemini 1.5 and 2.0 models
      Local files inspected
      • py/src/braintrust/wrappers/google_genai/__init__.py:

        • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
        • _serialize_tools() — serializes tool declarations (including google_search) for span input
        • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
      • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
      • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata
      Metadata
      Metadata
      Assignees
      Labels
      bot-automationintegration: google_genai
      Type
      Bug
      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("// 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
        Google GenAI: grounding metadata from Google Search not captured in span output #153
        Closed
        Bug
        #155
        Closed
        Google GenAI: grounding metadata from Google Search not captured in span output#153
        Bug
        #155
        Assignees
        AbhiPrasad
        Labels
        bot-automationintegration: google_genai
        Description
        @braintrust-bot
        braintrust-bot
        bot
        opened on Mar 26, 2026
        Gap
        When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.
        Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.
        What is missing
        The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:
        • grounding_chunks — the actual search result snippets used by the model
        • grounding_supports — which parts of the response are supported by which chunks
        • search_entry_point — the rendered search widget URL
        • web_search_queries — the queries the model issued to Google Search
        The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.
        Braintrust docs status
        not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.
        Upstream sources
        • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
        • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
        • Grounding is GA for Gemini 1.5 and 2.0 models
        Local files inspected
        • py/src/braintrust/wrappers/google_genai/__init__.py:

          • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
          • _serialize_tools() — serializes tool declarations (including google_search) for span input
          • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
        • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
        • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata
        Metadata
        Metadata
        Assignees
        Labels
        bot-automationintegration: google_genai
        Type
        Bug
        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("// 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
          Google GenAI: grounding metadata from Google Search not captured in span output #153
          Closed
          Bug
          #155
          Closed
          Google GenAI: grounding metadata from Google Search not captured in span output#153
          Bug
          #155
          Assignees
          AbhiPrasad
          Labels
          bot-automationintegration: google_genai
          Description
          @braintrust-bot
          braintrust-bot
          bot
          opened on Mar 26, 2026
          Gap
          When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.
          Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.
          What is missing
          The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:
          • grounding_chunks — the actual search result snippets used by the model
          • grounding_supports — which parts of the response are supported by which chunks
          • search_entry_point — the rendered search widget URL
          • web_search_queries — the queries the model issued to Google Search
          The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.
          Braintrust docs status
          not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.
          Upstream sources
          • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
          • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
          • Grounding is GA for Gemini 1.5 and 2.0 models
          Local files inspected
          • py/src/braintrust/wrappers/google_genai/__init__.py:

            • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
            • _serialize_tools() — serializes tool declarations (including google_search) for span input
            • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
          • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
          • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata
          Metadata
          Metadata
          Assignees
          Labels
          bot-automationintegration: google_genai
          Type
          Bug
          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
            Google GenAI: grounding metadata from Google Search not captured in span output #153
            Closed
            Bug
            #155
            Closed
            Google GenAI: grounding metadata from Google Search not captured in span output#153
            Bug
            #155
            Assignees
            AbhiPrasad
            Labels
            bot-automationintegration: google_genai
            Description
            @braintrust-bot
            braintrust-bot
            bot
            opened on Mar 26, 2026
            Gap
            When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.
            Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.
            What is missing
            The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:
            • grounding_chunks — the actual search result snippets used by the model
            • grounding_supports — which parts of the response are supported by which chunks
            • search_entry_point — the rendered search widget URL
            • web_search_queries — the queries the model issued to Google Search
            The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.
            Braintrust docs status
            not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.
            Upstream sources
            • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
            • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
            • Grounding is GA for Gemini 1.5 and 2.0 models
            Local files inspected
            • py/src/braintrust/wrappers/google_genai/__init__.py:

              • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
              • _serialize_tools() — serializes tool declarations (including google_search) for span input
              • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
            • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
            • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata
            Metadata
            Metadata
            Assignees
            Labels
            bot-automationintegration: google_genai
            Type
            Bug
            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("// 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
              Google GenAI: grounding metadata from Google Search not captured in span output #153
              Closed
              Bug
              #155
              Closed
              Google GenAI: grounding metadata from Google Search not captured in span output#153
              Bug
              #155
              Assignees
              AbhiPrasad
              Labels
              bot-automationintegration: google_genai
              Description
              @braintrust-bot
              braintrust-bot
              bot
              opened on Mar 26, 2026
              Gap
              When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.
              Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.
              What is missing
              The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:
              • grounding_chunks — the actual search result snippets used by the model
              • grounding_supports — which parts of the response are supported by which chunks
              • search_entry_point — the rendered search widget URL
              • web_search_queries — the queries the model issued to Google Search
              The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.
              Braintrust docs status
              not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.
              Upstream sources
              • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
              • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
              • Grounding is GA for Gemini 1.5 and 2.0 models
              Local files inspected
              • py/src/braintrust/wrappers/google_genai/__init__.py:

                • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
                • _serialize_tools() — serializes tool declarations (including google_search) for span input
                • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
              • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
              • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata
              Metadata
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              Labels
              bot-automationintegration: google_genai
              Type
              Bug
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, '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); }
})();
})();

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                Google GenAI: grounding metadata from Google Search not captured in span output #153
                Closed
                Bug
                #155
                Closed
                Google GenAI: grounding metadata from Google Search not captured in span output#153
                Bug
                #155
                Assignees
                AbhiPrasad
                Labels
                bot-automationintegration: google_genai
                Description
                @braintrust-bot
                braintrust-bot
                bot
                opened on Mar 26, 2026
                Gap
                When Gemini models use Google Search grounding (via the google_search tool), the response includes a grounding_metadata field containing search results, citations, search queries, and search entry points. This metadata is silently dropped from the span output — only the model's text response is captured.
                Google Search grounding is one of Gemini's key differentiating features, allowing models to ground their responses in real-time web data. Without capturing the grounding metadata, users cannot verify which search results the model used, audit citation accuracy, or debug grounding quality.
                What is missing
                The grounding_metadata field on GenerateContentResponse.candidates[].grounding_metadata should be extracted and logged in the span output. This includes:
                • grounding_chunks — the actual search result snippets used by the model
                • grounding_supports — which parts of the response are supported by which chunks
                • search_entry_point — the rendered search widget URL
                • web_search_queries — the queries the model issued to Google Search
                The tool declarations (google_search) pass through _serialize_tools() in the input, but the grounding results on the response side are not extracted.
                Braintrust docs status
                not_found — the Gemini integration page documents generate_content, streaming, function calling, structured outputs, thinking tokens, and context caching, but does not mention grounding or Google Search integration.
                Upstream sources
                • Google GenAI grounding guide: https://ai.google.dev/gemini-api/docs/grounding
                • google.genai.types.GroundingMetadata — contains grounding_chunks, grounding_supports, search_entry_point, web_search_queries
                • Grounding is GA for Gemini 1.5 and 2.0 models
                Local files inspected
                • py/src/braintrust/wrappers/google_genai/__init__.py:

                  • _gc_process_result() — processes non-streaming results; extracts text, usage_metadata, and content.parts but not grounding_metadata
                  • _serialize_tools() — serializes tool declarations (including google_search) for span input
                  • Zero references to grounding_metadata, grounding_chunks, grounding_supports, search_entry_point, or web_search_queries
                • py/src/braintrust/wrappers/test_google_genai.py — no grounding-related test cases
                • py/src/braintrust/integrations/adk/tracing.py — the ADK integration also does not extract grounding metadata
                Metadata
                Metadata
                Assignees
                Labels
                bot-automationintegration: google_genai
                Type
                Bug
                Projects
                No projects
                  Milestone
                  No milestone
                  Relationships
                  None yet
                  Development
                  No branches or pull requests
                  Issue actions