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Use Pinecone vector database
Store, search, and retrieve vector embeddings using Pinecone's specialized vector database. Generate embeddings from text and perform semantic similarity searches with customizable filtering options.
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Options: Generate Embeddings, Upsert Text, Search With Text, Search With Vector
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Condition: operation = "generate"
Options: multilingual-e5-large, llama-text-embed-v2, pinecone-sparse-english-v0
Placeholder: [{"text": "Your text here"}]
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Condition: operation = "generate"
Placeholder: https://index-name-abc123.svc.project-id.pinecone.io
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Condition: operation = "upsert_text"
Placeholder: default
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Condition: operation = "upsert_text"
Placeholder: {"_id": "rec1", "text": "Apple's first product, the Apple I, was released in 1976.", "category": "product"} {"_id": "rec2", "chunk_text": "Apples are a great source of dietary fiber.", "category": "nutrition"}
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Condition: operation = "upsert_text"
Placeholder: https://index-name-abc123.svc.project-id.pinecone.io
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Condition: operation = "search_text"
Placeholder: default
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Condition: operation = "search_text"
Placeholder: Enter text to search for
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Condition: operation = "search_text"
Placeholder: 10
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Condition: operation = "search_text"
Placeholder: ["category", "text"]
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Condition: operation = "search_text"
Placeholder: {"category": "product"}
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Condition: operation = "search_text"
Placeholder: {"model": "bge-reranker-v2-m3", "rank_fields": ["text"], "top_n": 2}
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Condition: operation = "search_text"
Placeholder: https://index-name-abc123.svc.project-id.pinecone.io
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Condition: operation = "fetch"
Placeholder: Namespace
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Condition: operation = "fetch"
Placeholder: ["vec1", "vec2"]
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Condition: operation = "fetch"
Placeholder: https://index-name-abc123.svc.project-id.pinecone.io
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Condition: operation = "search_vector"
Placeholder: default
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Condition: operation = "search_vector"
Placeholder: [0.1, 0.2, 0.3, ...]
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Condition: operation = "search_vector"
Placeholder: 10
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Condition: operation = "search_vector"
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Condition: operation = "search_vector"
Options: Include Values, Include Metadata
Placeholder: Your Pinecone API key
Layout: full
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Primary response type:
{
"matches": "json",
"upsertedCount": "number",
"data": "json",
"model": "string",
"vector_type": "string",
"usage": "json"
}