create_embeddings.py

import pinecone
from langchain_google_genai import GoogleGenerativeAIEmbeddings
from paragraphs2 import podcasts
import uuid
google_embeddings = GoogleGenerativeAIEmbeddings(
    model="models/embedding-001",  # Correct model name
    google_api_key="AIzaSyANNRKfEb-YnVIBaSAq6hQ38XpxxGwvaws"  # Your API key
)

# Initialize Pinecone instance
pc = pinecone.Pinecone(
    api_key="4a80f293-ae6d-489a-a7d8-33ea3fcdd26b"  # Your Pinecone API key
)

# Define the Pinecone index name (make sure it exists in your Pinecone dashboard)
index_name = "iocl2"
index = pc.Index(index_name)

def create_embedding(variable):
    try:
        content=variable.get("description")
        url=variable.get("url")
        tag=variable.get("tag")
        updated_url=""
        if isinstance(url,list):
            updated_url=",".join(url)
        else:
            updated_url=url

        embedding=google_embeddings.embed_query(content)
        vectors=[]
        vectors.append({
            'id': str(uuid.uuid4()),
            'values': embedding,
            'metadata': {
                'chunk': content,
                "url":updated_url,
                "tag":tag
            }
        })
        index.upsert(vectors)
        print(f"inserted : {updated_url}")
    except Exception as e:
        print(f"error occured {e}")


create_embedding(podcasts)