docsearch = Pinecone.from_texts([t.page_content for t in text_chunks], embedding, index_name="testforpractical")
I got below error
PineconeConfigurationError: You haven't specified an Api-Key.
and i tried another method:
from langchain_openai import OpenAIEmbeddings
from langchain.vectorstores import Pinecone
from pinecone import Pinecone as PineconeClient
import os
model_name = 'text-embedding-ada-002'
embedding = OpenAIEmbeddings(
model= "gpt-3.5-turbo",
openai_api_key="-------"
)
PINECONE_API_KEY = os.environ.get('PINECONE_API_KEY', '----')
PINECONE_API_ENV = os.environ.get('PINECONE_API_ENV', '-----')
Create a Pinecone instance with the API key and environment
pinecone_instance = PineconeClient(api_key=PINECONE_API_KEY, environment=PINECONE_API_ENV)
index_name = "testforpractical"
Create a PineconeVectorStore instance with the Pinecone instance and index name
docsearch = Pinecone.from_texts(
[t.page_content for t in text_chunks],
embedding,
index_name=index_name,
pinecone_index=pinecone_instance
)
and got another error as :
PineconeConfigurationError
PineconeConfigurationError: You haven't specified an Api-Key.
but i have specified all api key that of open ai and of pinecode both .
I was unable to solve this error since yesterday. So can anyone help me with this ?
Hi @home.rajnishadhikari, thanks for posting. For starters, please ensure that you are using v3.0.0 or newer of the Pinecone Python client. Once upgraded, you can initialize the Pinecone client using pc = Pinecone(api_key='YOUR_API_KEY') (docs).
When importing the LangChain package, you need to ensure you are using the most up-to-date package as well. The package langchain.vectorstores.Pinecone that you are using is deprecated. Instead you should be using from langchain_pinecone import PineconeVectorStore (docs).
from langchain_pinecone import PineconeVectorStore
docsearch = PineconeStore.from_texts([t.page_content for t in text_chunks], embeddings, index_name = index_name)
Getting the error:
“PineconeConfigurationError: You haven’t specified an Api-Key.”
Hi there, sharing my experience that may help someone,
Working with Pinecone in Google Colab: A Note on Environment Variables
When using Pinecone for vector storage within your Langchain project running on Google Colab, you may encounter the same error as setting environment variables for credentials with google.userdata.
The Challenge:
The google.userdata method is not suitable for assigning environment variables to objects used within your code. This leads to “PineconeConfigurationError: You haven’t specified an Api-Key.
The Solution:
To effectively manage your Pinecone API key or other credentials in Google Colab, leverage the os.environ method:
import os
# Set your Pinecone API key (replace with your actual key)
os.environ["PINECONE_API_KEY"] = "YOUR_PINECONE_API_KEY"
# Now, use this environment variable when initializing Pinecone:
from langchain_pinecone import Pinecone
pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"])
Followed the Langchain-pinecone documentation. But still i get the error
Traceback (most recent call last):
File "/Users/roopeshbharatwajkr/PycharmProjects/chainlit/embedding1.py", line 124, in <module>
Cert_in_AI_vectorstore = process_data(load_data("/Users/roopeshbharatwajkr/DLI/Data /Cert_in_AI_Final/"), "Cert_in_AI")
File "/Users/roopeshbharatwajkr/PycharmProjects/chainlit/embedding1.py", line 112, in process_data
vectorstore = PineconeVectorStore.from_texts(
File "/Users/roopeshbharatwajkr/anaconda3/envs/Python3_9/lib/python3.9/site-packages/langchain_pinecone/vectorstores.py", line 453, in from_texts
pinecone_index = cls.get_pinecone_index(index_name, pool_threads)
File "/Users/roopeshbharatwajkr/anaconda3/envs/Python3_9/lib/python3.9/site-packages/langchain_pinecone/vectorstores.py", line 386, in get_pinecone_index
client = PineconeClient(
File "/Users/roopeshbharatwajkr/anaconda3/envs/Python3_9/lib/python3.9/site-packages/pinecone/control/pinecone.py", line 205, in __init__
self.config = PineconeConfig.build(
File "/Users/roopeshbharatwajkr/anaconda3/envs/Python3_9/lib/python3.9/site-packages/pinecone/config/pinecone_config.py", line 29, in build
return ConfigBuilder.build(
File "/Users/roopeshbharatwajkr/anaconda3/envs/Python3_9/lib/python3.9/site-packages/pinecone/config/config.py", line 58, in build
raise PineconeConfigurationError("You haven't specified an Api-Key.")
pinecone.exceptions.exceptions.PineconeConfigurationError: You haven't specified an Api-Key.
Process finished with exit code 1
raise PineconeConfigurationError(“You haven’t specified an Api-Key.”)
pinecone.exceptions.exceptions.PineconeConfigurationError: You haven’t specified an Api-Key.
This is the Error and i tried to change my dependency all my previous version to new but still its not working
# --- Process Data ---
model_name = 'text-embedding-3-large'
embeddings = OpenAIEmbeddings(model=model_name, openai_api_key=OPENAI_API_KEY)
print('embeddings',embeddings)
pc = Pinecone(api_key=PINECONE_KEY)
index = pc.Index(PINECONE_INDEX_NAME)
Cert_in_AI_vectorstore = PineconeVectorStore.from_texts(
texts=[doc["text"] for doc in documents],
embedding=embeddings,
index_name=index,
namespace="Cert_in_AI",
metadatas=[{"source": doc["source"]} for doc in documents]
)
print('Cert_in_AI_vectorstore',Cert_in_AI_vectorstore)
Diploma_in_AI_chain = 0 # Placeholder for later
# --- Conversational Chain Setup ---
llm = ChatOpenAI(model='gpt-4o-mini', api_key=OPENAI_API_KEY)
memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
Cert_in_AI_chain = ConversationalRetrievalChain.from_llm(
llm=llm, retriever=Cert_in_AI_vectorstore.as_retriever(), memory=memory
)
import os
# Set your Pinecone API key (replace with your actual key)
os.environ["PINECONE_API_KEY"] = "YOUR_PINECONE_API_KEY"
# Now, use this environment variable when initializing Pinecone:
from langchain_pinecone import Pinecone
pc = Pinecone(api_key=os.environ["PINECONE_API_KEY"])