729875f3a6
- Add AG Native DOM path: #conversation + .leading-relaxed.select-text - Keep Cascade path: [data-testid=conversation-view] + [data-step-index] - Register #632 in known-issues.md (SDK+DOM both blocked for AG Native) - Bump version 0.5.50 → 0.5.51 - Add DOM analysis helper scripts
110 lines
4.0 KiB
Python
110 lines
4.0 KiB
Python
"""Trace the DOM path from body to AI response container."""
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import json, os
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fpath = os.path.join(os.path.expanduser('~'), '.gemini', 'antigravity', 'bridge', 'dump_html_5.json')
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with open(fpath, 'r', encoding='utf-8-sig') as f:
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data = json.load(f)
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body = data.get('body', data.get('bodyTree', {}))
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def find_path_to_class(node, target_cls, path=None, depth=0):
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"""Find the DOM path down to a node with a matching class."""
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if path is None: path = []
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if not isinstance(node, dict): return []
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tag = node.get('tag', '')
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cls = node.get('cls', '')
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children = node.get('children', [])
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text = node.get('text', '')
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attrs = node.get('attrs', {})
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entry = {
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'depth': depth,
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'tag': tag,
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'cls': cls[:120],
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'children': len(children),
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'text': text[:60] if text else '',
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'attrs': {k:v[:40] for k,v in attrs.items() if k not in ('style',)}
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}
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if target_cls.lower() in cls.lower():
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return path + [entry]
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for i, child in enumerate(children):
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result = find_path_to_class(child, target_cls, path + [entry], depth+1)
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if result:
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return result
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return []
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# Find path to the AI response container
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print("=== PATH TO 'leading-relaxed select-text' ===")
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path = find_path_to_class(body, 'leading-relaxed select-text')
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for p in path:
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indent = ' ' * p['depth']
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print(f'{indent}[{p["tag"]}] cls="{p["cls"]}" children={p["children"]} {p["attrs"]}')
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if p['text']:
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print(f'{indent} text: "{p["text"]}"')
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# Now get the full subtree of the AI response container
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def get_subtree(node, target_cls, depth=0):
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if not isinstance(node, dict): return None
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cls = node.get('cls', '')
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if target_cls.lower() in cls.lower():
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return node
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for child in node.get('children', []):
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result = get_subtree(child, target_cls, depth+1)
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if result:
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return result
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return None
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print("\n=== AI RESPONSE CONTAINER SUBTREE ===")
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container = get_subtree(body, 'leading-relaxed select-text')
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if container:
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def print_tree(node, depth=0, max_depth=4):
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if not isinstance(node, dict) or depth > max_depth: return
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tag = node.get('tag','')
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cls = node.get('cls','')[:80]
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text = node.get('text','')
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children = node.get('children', [])
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indent = ' ' * depth
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line = f'{indent}[{tag}]'
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if cls: line += f' cls="{cls}"'
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line += f' children={len(children)}'
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if text: line += f' text="{text[:60]}"'
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print(line)
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for c in children:
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print_tree(c, depth+1, max_depth)
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print_tree(container, 0, 3)
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# Also search for the chat panel container - what wraps the entire conversation
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print("\n=== SEARCH FOR CHAT PANEL WRAPPERS ===")
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chat_patterns = ['chat', 'antigravity', 'gemini', 'panel', 'agentview', 'sidebar', 'conversation']
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for pat in chat_patterns:
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path = find_path_to_class(body, pat)
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if path:
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last = path[-1]
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print(f' Pattern "{pat}" found at depth={last["depth"]} [{last["tag"]}] cls="{last["cls"]}" children={last["children"]}')
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# Find the parent chain from body to the container - look by scanning ALL class names
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print("\n=== ALL UNIQUE CLASS NAMES (depth <= 12) ===")
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all_classes = set()
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def collect_classes(node, depth=0, max_depth=12):
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if not isinstance(node, dict) or depth > max_depth: return
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cls = node.get('cls', '')
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if cls:
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for c in cls.split():
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if len(c) > 3 and not c.startswith('{') and 'mtk' not in c:
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all_classes.add(c)
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for child in node.get('children', []):
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collect_classes(child, depth+1, max_depth)
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collect_classes(body)
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# Print classes sorted, grouped by potential relevance
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relevant = sorted([c for c in all_classes if any(k in c.lower() for k in
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['chat', 'message', 'response', 'agent', 'gemini', 'turn', 'model', 'user', 'bot', 'conversation', 'markdown', 'prose', 'text-', 'content'])])
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print("Relevant classes:")
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for c in relevant:
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print(f' {c}')
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