Pinecone
Use Pinecone vector database
Configuration
Generate Embeddings
Operation
Generate Embeddings
API Key*
••••••••
Model
multilingual-e5-large
Text Inputs*
[{"text": "Your text here"}]
Generate Embeddings (
pinecone_generate_embeddings)Generate embeddings from text using Pinecone's hosted models
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
model | string | Yes | Model to use for generating embeddings |
inputs | array | Yes | Array of text inputs to generate embeddings for |
apiKey | string | Yes | Pinecone API key |
Output
| Parameter | Type | Description |
|---|---|---|
data | array | Generated embeddings data with values and vector type |
model | string | Model used for generating embeddings |
vector_type | string | Type of vector generated (dense/sparse) |
usage | object | Usage statistics for embeddings generation |
Upsert Text
Operation
Upsert Text
API Key*
••••••••
Index Host*
https://index-name-abc123.svc.project-id.pinecone.io
Namespace*
default
Records*
{"_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"}
Upsert Text (
pinecone_upsert_text)Insert or update text records in a Pinecone index
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
indexHost | string | Yes | Full Pinecone index host URL |
namespace | string | Yes | Namespace to upsert records into |
records | array | Yes | Record or array of records to upsert, each containing _id, text, and optional metadata |
apiKey | string | Yes | Pinecone API key |
Output
| Parameter | Type | Description |
|---|---|---|
statusText | string | Status of the upsert operation |
upsertedCount | number | Number of records successfully upserted |
Search With Text
Operation
Search With Text
API Key*
••••••••
Index Host*
https://index-name-abc123.svc.project-id.pinecone.io
Namespace*
default
Search Query*
Enter text to search for
Top K Results
10
Fields to Return
["category", "text"]
Filter
{"category": "product"}
Rerank Options
{"model": "bge-reranker-v2-m3", "rank_fields": ["text"], "top_n": 2}
Search With Text (
pinecone_search_text)Search for similar text in a Pinecone index
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
indexHost | string | Yes | Full Pinecone index host URL |
namespace | string | No | Namespace to search in |
searchQuery | string | Yes | Text to search for |
topK | string | No | Number of results to return |
fields | array | No | Fields to return in the results |
filter | object | No | Filter to apply to the search |
rerank | object | No | Reranking parameters |
apiKey | string | Yes | Pinecone API key |
Output
| Parameter | Type | Description |
|---|---|---|
matches | array | Search results with ID, score, and metadata |
usage | object | Usage statistics including tokens, read units, and rerank units |
Search With Vector
Operation
Search With Vector
API Key*
••••••••
Index Host*
https://index-name-abc123.svc.project-id.pinecone.io
Namespace*
default
Query Vector*
[0.1, 0.2, 0.3, ...]
Top K Results
10
Options
Options
Search With Vector (
pinecone_search_vector)Search for similar vectors in a Pinecone index
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
indexHost | string | Yes | Full Pinecone index host URL |
namespace | string | No | Namespace to search in |
vector | array | Yes | Vector to search for |
topK | number | No | Number of results to return |
filter | object | No | Filter to apply to the search |
includeValues | boolean | No | Include vector values in response |
includeMetadata | boolean | No | Include metadata in response |
apiKey | string | Yes | Pinecone API key |
Output
| Parameter | Type | Description |
|---|---|---|
matches | array | Vector search results with ID, score, values, and metadata |
namespace | string | Namespace where the search was performed |
Fetch Vectors
Operation
Fetch Vectors
API Key*
••••••••
Index Host*
https://index-name-abc123.svc.project-id.pinecone.io
Namespace*
Namespace
Vector IDs*
["vec1", "vec2"]
Fetch Vectors (
pinecone_fetch)Fetch vectors by ID from a Pinecone index
Input
| Parameter | Type | Required | Description |
|---|---|---|---|
indexHost | string | Yes | Full Pinecone index host URL |
ids | array | Yes | Array of vector IDs to fetch |
namespace | string | No | Namespace to fetch vectors from |
apiKey | string | Yes | Pinecone API key |
Output
| Parameter | Type | Description |
|---|---|---|
matches | array | Fetched vectors with ID, values, metadata, and score |
data | array | Vector data with values and vector type |
usage | object | Usage statistics including total read units |
Usage Instructions
Integrate Pinecone into the workflow. Can generate embeddings, upsert text, search with text, fetch vectors, and search with vectors.
Notes
- Category:
tools - Type:
pinecone