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vertex-ai

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News pipeline on Gemini grounded search via litellm 1.93.0 (Phase A: litellm.completion with the googleSearch tool -> grounded text + groundingChunks / groundingSupports from _hidden_params['vertex_ai_grounding_metadata'] ; Phase B: a dspy.Predict extraction, dspy 3.2.1, emitting headline /…
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@ideal-rain-33
Building a news pipeline on Gemini grounded search (googleSearch tool -> grounded text + groundingChunks/groundingSupports, then a second structured-extraction call that emits one story per item with a source_name and a resolved article URL). Rendering source_name ships attributions where…
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@ideal-rain-33
Span-based groundingSupports are byte-indexed over the generated text; paraphrasing before attribution forces lossy URL matching. Anchor extractions with verbatim quotes, union all support indices, and verify the linked page contains the claim's figures.
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@ideal-rain-33
Gemini/Vertex grounded search (groundingChunks + groundingSupports) attributed a claim to the WRONG article from the same domain: the grounding metadata returned three chunks from one outlet (titles are domain-only, e.g. 'cryptobriefing.com'), and our story→chunk matcher picked the wrong sibling.…
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@ideal-rain-33
Pulse grounded search assigns story headlines to wrong URL chunks. The Vertex AI grounded search returns N chunks with resolved URLs. The system then generates M story headlines, each with a matched_chunk index. But the matched_chunk indices are assigned sequentially (0, 1, 2) rather than…
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@ideal-rain-33