Pinecone serverless from existing index

Question

from flask import Flask, render_template, jsonify, request
from src.helper import download_hugging_face_embeddings
# from langchain.vectorstores import Pinecone
import pinecone
from langchain.prompts import PromptTemplate
from langchain.llms import CTransformers
from langchain.chains import RetrievalQA
from dotenv import load_dotenv
from src.prompt import *
import os
from pinecone import Pinecone,ServerlessSpec
from langchain_pinecone import PineconeVectorStore

app = Flask(__name__)

load_dotenv()

PINECONE_API_KEY = os.environ.get('PINECONE_API_KEY')
PINECONE_API_ENV = os.environ.get('PINECONE_API_ENV')


embeddings = download_hugging_face_embeddings()

#Initializing the Pinecone
# pinecone.init(api_key=PINECONE_API_KEY,
#               environment=PINECONE_API_ENV)
pc = Pinecone(
        api_key=os.environ.get("PINECONE_API_KEY")
    )
index_name="chatbot"

#Loading the index
# docsearch=pc.from_existing_index(index_name, embeddings)
docsearch = Pinecone.from_existing_index(index_name, embeddings)

PROMPT=PromptTemplate(template=prompt_template, input_variables=["context", "question"])

chain_type_kwargs={"prompt": PROMPT}

llm=CTransformers(model="model/llama-2-7b-chat.ggmlv3.q4_0.bin",
                  model_type="llama",
                  config={'max_new_tokens':512,
                          'temperature':0.8})


qa=RetrievalQA.from_chain_type(
    llm=llm, 
    chain_type="stuff", 
    retriever=docsearch.as_retriever(search_kwargs={'k': 2}),
    return_source_documents=True, 
    chain_type_kwargs=chain_type_kwargs)



@app.route("/")
def index():
    return render_template('chat.html')



@app.route("/get", methods=["GET", "POST"])
def chat():
    msg = request.form["msg"]
    input = msg
    print(input)
    result=qa({"query": input})
    print("Response : ", result["result"])
    return str(result["result"])



if __name__ == '__main__':
    app.run(host="0.0.0.0", port= 8080, debug= True)

Why am I getting this error ? Traceback (most recent call last): File "C:\final_year_chatbot\End-to-end-Medical-Chatbot-using-Llama2-main\app.py", line 34, in docsearch = Pinecone.from_existing_index(index_name, embeddings) AttributeError: type object 'Pinecone' has no attribute 'from_existing_index'

I am trying to run this app.py but I am getting this error

Samyak Khetan · Accepted Answer · 2024-05-15 15:24:45Z

0

I think your code was supposed to work for an earlier version of pinecone. I faced a similar issue and this code works for me:

from pinecone import Pinecone
from pinecone import ServerlessSpec
from langchain_pinecone import PineconeVectorStore
import os

# initialize connection to pinecone (get API key at app.pinecone.io)
api_key = PINECONE_API_KEY
# configure client
pc = Pinecone(api_key=api_key)

os.environ['PINECONE_API_KEY'] = PINECONE_API_KEY
index_name="chatbot"
index = pc.Index(index_name)
PineconeVectorStore(index_name=index_name,embedding=embeddings)

vectorstore_from_docs = PineconeVectorStore.from_documents(
    text_chunks,
    index_name=index_name,
    embedding=embeddings
)

# index.describe_index_stats()
vectorstore = PineconeVectorStore.from_existing_index(index_name=index_name, embedding=embeddings)
qa=RetrievalQA.from_chain_type(
    llm=llm, 
    chain_type="stuff", 
    retriever=vectorstore.as_retriever(search_kwargs={'k': 2}),
    return_source_documents=True, 
    chain_type_kwargs=chain_type_kwargs)

answered May 15, 2024 at 15:24

Samyak Khetan

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2 Comments

Garima Srivastava Over a year ago

Hi thanks for answering but I'm getting this error now:NameError: name 'text_chunks' is not defined

Samyak Khetan Over a year ago

Here's how I defined it for one of my projects:

def load_pdf(data):     loader = DirectoryLoader(data,                              glob="*pdf",                              loader_cls=PyPDFLoader)     documents = loader.load()     return documents extracted_data=load_pdf("data/") def text_split(extracted_data):     text_splitter=RecursiveCharacterTextSplitter(chunk_size=500, chunk_overlap = 20)     text_chunks=text_splitter.split_documents(extracted_data)     return text_chunks text_chunks=text_split(extracted_data)

Rookie · Accepted Answer · 2024-11-20 09:56:04Z

0

AttributeError: type object 'Pinecone' has no attribute 'from_existing_index'.

This happenes when there are two Pinecones that you installed when importing from langchain.vectorstore and also pinecone itself. so I the method so called 'from_existing_index' only exist in Pinecone from langchain. so when import from langchain ... use this:: 'from langchain.vectorstores import Pinecode as Pi' and then use Pi when you are trying to access the attribute 'from_existing_index'

I hope you understood it.

answered Nov 20, 2024 at 9:56

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