Pinecone API Key in from_documents

[alex1897]

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Example Code

from langchain_pinecone import PineconeVectorStore

docsearch = PineconeVectorStore.from_documents(docs, embeddings, index_name=index_name)

Description

• I want to switch from Qdrant to Pinecone
• With Qdrant I was able to provide an api_key inside of the from_documents
• For Pinecone this is not mentioned in the docs, just using environment variables
• I find it for my use case not a good idea using environment variables due to security
• Is there an option available not using environment variables?

System Info

langchain==0.2.1
langchain-community==0.0.38
langchain-core==0.2.3
langchain-openai==0.1.8
langchain-pinecone==0.1.1
langchain-text-splitters==0.2.0

[dosubot[bot]]

Hey @alex1897! I'm here to help you with your LangChain Pinecone API Key issue. I'm a bot designed to assist with bug fixes, answer questions, and guide you on becoming a contributor. Let's work together to resolve your concern.

Yes, you can use Pinecone without relying on environment variables by directly passing the API key and other necessary parameters when initializing the PineconeVectorStore.

Here's how you can modify your code to include the Pinecone API key directly:

from langchain_pinecone import PineconeVectorStore
from langchain_openai import OpenAIEmbeddings

embeddings = OpenAIEmbeddings()
index_name = "your_index_name"
namespace = "your_namespace"

docsearch = PineconeVectorStore.from_documents(
    docs,
    embeddings,
    index_name=index_name,
    pinecone_api_key="your_api_key"
)

Replace "your_api_key", "your_index_name", and "your_namespace" with your actual Pinecone API key, index name, and namespace, respectively. This way, you can avoid using environment variables for your API key ^[1][2].

To continue talking to Dosu, mention @dosu.

[alex1897]

@dosu that is what I already tried, but then I get: PineconeConfigurationError("You haven't specified an Api-Key.")

[dosubot[bot]]

To resolve the PineconeConfigurationError when specifying the API key directly, ensure you are using the correct method and parameters. The from_documents method does not directly accept the pinecone_api_key parameter. Instead, you should initialize the PineconeVectorStore with the API key and then use it.

Here's how you can do it:

from langchain_pinecone import PineconeVectorStore
from langchain_openai import OpenAIEmbeddings

embeddings = OpenAIEmbeddings()
index_name = "your_index_name"
namespace = "your_namespace"
pinecone_api_key = "your_api_key"

# Initialize the PineconeVectorStore with the API key
vectorstore = PineconeVectorStore(
    index_name=index_name,
    embedding=embeddings,
    namespace=namespace,
    pinecone_api_key=pinecone_api_key
)

# Use the vectorstore to add documents
vectorstore.add_texts(docs)

Replace "your_api_key", "your_index_name", and "your_namespace" with your actual Pinecone API key, index name, and namespace. This approach ensures that the API key is correctly passed and used by the PineconeVectorStore class ^[1].

To continue talking to Dosu, mention @dosu.

[alex1897]

@dosu: With that I get a new error "TypeError: argument 'text': 'Document' object cannot be converted to 'PyString'" I guess because the "from_documents" method can process txt files and the "from_texts" expects to have plain text?

[dosubot[bot]]

To resolve the TypeError: argument 'text': 'Document' object cannot be converted to 'PyString' error, you need to ensure that the texts argument is a list of strings and not Document objects. Here's how you can correctly add your documents to the Pinecone vector store:

1. Convert your documents into a list of strings.
2. Use the add_texts method to add the texts to the vector store.

Here's an example:

from langchain_pinecone import PineconeVectorStore
from langchain_openai import OpenAIEmbeddings

# Initialize the embeddings
embeddings = OpenAIEmbeddings()

# Define your Pinecone API key and index name
pinecone_api_key = "your_api_key"
index_name = "your_index_name"
namespace = "your_namespace"

# Create the PineconeVectorStore instance
vectorstore = PineconeVectorStore(
    index_name=index_name,
    embedding=embeddings,
    namespace=namespace,
    pinecone_api_key=pinecone_api_key
)

# Convert your documents to a list of strings
texts = [doc.page_content for doc in docs]  # Assuming docs is a list of Document objects

# Add texts to the vector store
vectorstore.add_texts(texts=texts)

This approach ensures that the documents are correctly converted to strings before being added to the vector store ^[1][2].

To continue talking to Dosu, mention @dosu.

[Indrajit-dev-git]

Just use os.environ['PINECONE_API_KEY'] = PINECONE_API_KEY

[pseudo-usama]

I cannot set api key in env as i've multiple vector stores with multiple api keys.
Is there any other method to pass api key inside function?

[alex1897]

That also doesn't work for my case. My backend should use different provider and users can dynamically add/remove those vector stores. So I would need to set this when calling the function.