Periya-Retriever
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")
# https://python.langchain.com/docs/how_to/passthrough/
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 ChatOpenAI, OpenAIEmbeddings
vectorstore = FAISS.from_texts(
["harrison worked at kensho"], embedding=OpenAIEmbeddings()
)
retriever = vectorstore.as_retriever()
template = """Answer the question based only on the following context:
{context}
Question: {question}
"""
prompt = ChatPromptTemplate.from_template(template)
model = ChatOpenAI()
retrieval_chain = (
{"context": retriever, "question": RunnablePassthrough()}
| prompt
| model
| StrOutputParser()
)
retrieval_chain.invoke("where did harrison work?")
'Harrison worked at Kensho.'
Score: 5
Category: langchain