Retriever-2
Sat 17 May 2025
!python --version
Python 3.12.4
from constants import OPENAI_API_KEY
!pip show langchain-openai | grep "Version:"
Version: 0.2.9
import os
os.environ["OPENAI_API_KEY"] = OPENAI_API_KEY
from langchain_openai import ChatOpenAI
model = ChatOpenAI(model="gpt-4o-mini")
from langchain_community.vectorstores import FAISS
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate
from langchain_core.runnables import RunnablePassthrough
from langchain_openai import OpenAIEmbeddings
template = """Answer the question based only on the following context:
{context}
Question: {question}
"""
prompt = ChatPromptTemplate.from_template(template)
vectorstore = FAISS.from_texts(
["harrison worked at kensho", "harrison likes spicy food"],
embedding=OpenAIEmbeddings(),
)
retriever = vectorstore.as_retriever()
chunks = [chunk for chunk in retriever.stream("where did harrison work?")]
chunks
[[Document(metadata={}, page_content='harrison worked at kensho'),
Document(metadata={}, page_content='harrison likes spicy food')]]
Score: 10
Category: langchain