LangChain Integration

pip install flexorch-sdk langchain langchain-openai

from flexorch_sdk import FlexOrch, FlexOrchRetriever

client = FlexOrch()  # reads FLEXORCH_API_KEY from env

retriever = FlexOrchRetriever(
    client,
    quality_threshold="B",   # include A and B grade chunks
    pii_masked=True,          # only return PII-safe chunks
    top_k=5,
    mode="hybrid",            # auto | semantic | hybrid | structured
    document_type="invoice",  # optional filter
    language="tr",            # optional ISO 639-1 filter
)

docs = retriever.invoke("invoices over 10000 EUR")

for doc in docs:
    print(doc.page_content[:100])
    print(doc.metadata)

from flexorch_sdk import FlexOrch, FlexOrchRetriever
from langchain.chains import RetrievalQA
from langchain_openai import ChatOpenAI

client = FlexOrch()
retriever = FlexOrchRetriever(client, quality_threshold="B", mode="hybrid")

qa = RetrievalQA.from_chain_type(
    llm=ChatOpenAI(model="gpt-4o-mini"),
    retriever=retriever,
    return_source_documents=True,
)

result = qa.invoke("What is the payment term on invoice FTR-2024-001?")
print(result["result"])

for doc in result["source_documents"]:
    print(doc.metadata["quality_grade"], doc.page_content[:60])

from langchain_core.prompts import ChatPromptTemplate
from langchain_core.output_parsers import StrOutputParser
from langchain_core.runnables import RunnablePassthrough
from langchain_openai import ChatOpenAI

prompt = ChatPromptTemplate.from_template(
    "Answer the question based only on the context below.\n\n"
    "Context: {context}\n\nQuestion: {question}"
)

def format_docs(docs):
    return "\n\n".join(doc.page_content for doc in docs)

chain = (
    {"context": retriever | format_docs, "question": RunnablePassthrough()}
    | prompt
    | ChatOpenAI(model="gpt-4o-mini")
    | StrOutputParser()
)

print(chain.invoke("Total amount on the March invoices?"))

# German contracts — grade A only
retriever_de = FlexOrchRetriever(
    client,
    quality_threshold="A",
    document_type="sales_proposal",
    language="de",
    top_k=10,
)

# Turkish payroll — grade B+, PII masked
retriever_tr = FlexOrchRetriever(
    client,
    quality_threshold="B",
    pii_masked=True,
    document_type="payroll",
    language="tr",
)

docs = await retriever.aget_relevant_documents("payment terms")