from langchain.chains import RetrievalQA
from langchain_community.llms import Ollama
from langchain_community.vectorstores import Chroma
from langchain_community.embeddings import HuggingFaceEmbeddings
llm = Ollama(model="llama3")
embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
vectorstore = Chroma(persist_directory="./chroma_db", embedding_function=embeddings)
qa_chain = RetrievalQA.from_chain_type(
llm=llm,
retriever=vectorstore.as_retriever(),
chain_type="stuff"
)
response = qa_chain.invoke("Как работает авторизация в этом проекте?")
print(response["result"])
from langchain.chains import RetrievalQA
from langchain_community.llms import Ollama
from langchain_community.vectorstores import Chroma
from langchain_community.embeddings import HuggingFaceEmbeddings
llm = Ollama(model="llama3")
embeddings = HuggingFaceEmbeddings(model_name="all-MiniLM-L6-v2")
vectorstore = Chroma(persist_directory="./chroma_db", embedding_function=embeddings)
qa_chain = RetrievalQA.from_chain_type(
llm=llm,
retriever=vectorstore.as_retriever(),
chain_type="stuff"
)
response = qa_chain.invoke("Как работает авторизация в этом проекте?")
print(response["result"])