You can access the Pinecone Integration programmatically from your own applications by using the Apify API. You can also choose the language preference from below. To use the Apify API, you’ll need an Apify account and your API token, found in Integrations settings in Apify Console.

Python

JavaScript

CLI

OpenAPI

HTTP

MCP

1from apify_client import ApifyClient
2
3# Initialize the ApifyClient with your Apify API token
4# Replace '<YOUR_API_TOKEN>' with your token.
5client = ApifyClient("<YOUR_API_TOKEN>")
6
7# Prepare the Actor input
8run_input = {
9    "datasetFields": ["text"],
10    "dataUpdatesStrategy": "deltaUpdates",
11    "dataUpdatesPrimaryDatasetFields": ["url"],
12    "deltaUpdatesPrimaryDatasetFields": ["url"],
13}
14
15# Run the Actor and wait for it to finish
16run = client.actor("apify/pinecone-integration").call(run_input=run_input)
17
18# Fetch and print Actor results from the run's dataset (if there are any)
19print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
20for item in client.dataset(run["defaultDatasetId"]).iterate_items():
21    print(item)
22
23# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start

Pinecone Integration API in Python

The Apify API client for Python is the official library that allows you to use Pinecone Integration API in Python, providing convenience functions and automatic retries on errors.

Install the apify-client

$pip install apify-client

Other API clients include:

Pinecone Integration API in JavaScript

Pinecone Integration API through CLI

Pinecone Integration OpenAPI definition

Pinecone Integration API

Milvus Integration

apify/milvus-integration

This integration transfers data from Apify Actors to a Milvus/Zilliz database and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.5

OpenAI Vector Store Integration

jiri.spilka/openai-vector-store-integration

The Apify OpenAI Vector Store integration uploads data from Apify Actors to the OpenAI Vector Store linked to OpenAI Assistant.

Jiří Spilka

185

4.8

Pinecone GPT Chatbot

tri_angle/pinecone-gpt-chatbot

Pinecone GPT Chatbot combines OpenAI's GPT models with Pinecone's database to generate insightful responses. Its interactive chatbot interface presents precise and comprehensive answers to user queries. Benefit from semantic understanding, efficient workflows, and enriched knowledge integration!

Tri⟁angle

4.9

WCC Pinecone Integration

tri_angle/wcc-pinecone-integration

Crawl any website and store its content in your Pinecone vector database. Enhance the accuracy and reliability of your own AI Assistant with facts fetched from external sources or connect this integration to our Pinecone GPT Chatbot assistant available in Apify Store.

Tri⟁angle

151

3.2

Chroma Integration

apify/chroma-integration

This integration transfers data from Apify Actors to a Chroma and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.8

Weaviate Integration

apify/weaviate-integration

This integration transfers data from Apify Actors to a Weaviate and is a good starting point for a question-answering, search, or RAG use case.

Apify

4.7

PGVector Integration

apify/pgvector-integration

This integration transfers data from Apify Actors to a Postgres SQL database (with PGVector extension).

Apify

4.6

Qdrant Integration

apify/qdrant-integration

Transfer data from Apify Actors to a Qdrant vector database.

Apify

4.5

RAG Web Browser

apify/rag-web-browser

Web browser for OpenAI Assistants, RAG pipelines, or AI agents, similar to a web browser in ChatGPT. It queries Google Search, scrapes the top N pages, and returns their content as Markdown for further processing by an LLM. It can also scrape individual URLs. Supports Model Context Protocol (MCP).

Apify

5.3K

4.4

OpenSearch Integration

apify/opensearch-integration

Transfer data from Apify Actors to Amazon OpenSearch Service. This Actor is a good starting point for building question-answering systems, search functionality, or Retrieval-Augmented Generation (RAG) use cases.

Apify

4.4