Atención al Cliente Autónoma 24/7

from langchain.chains import RetrievalQA
from langchain.vectorstores import Pinecone
from langchain_anthropic import ChatAnthropic

# Setup RAG chain
llm = ChatAnthropic(model="claude-3-5-sonnet-20241022")
vectorstore = Pinecone.from_existing_index("docs")

qa_chain = RetrievalQA.from_chain_type(
    llm=llm,
    retriever=vectorstore.as_retriever(
        search_kwargs={"k": 5}  # Top 5 relevant docs
    ),
    return_source_documents=True
)

# Process user query
result = qa_chain({"query": user_question})
answer = result["result"]
sources = result["source_documents"]

# Decision: responder o escalar
if confidence_score(answer) > 0.8:
    return answer
else:
    escalate_to_human(context=sources)