langchain/libs/community/tests/integration_tests/retrievers/test_embedchain.py
Kai Kugler df234fb171
community[patch]: Fixing embedchain document mapping (#18255)
- **Description:** The current embedchain implementation seems to handle
document metadata differently than done in the current implementation of
langchain and a KeyError is thrown. I would love for someone else to
test this...

---------

Co-authored-by: KKUGLER <kai.kugler@mercedes-benz.com>
Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Deshraj Yadav <deshraj@gatech.edu>
2024-02-29 14:54:37 -08:00

47 lines
1.2 KiB
Python

"""Integration test for Embedchain."""
import os
from typing import Any
from unittest.mock import patch
import pytest
from langchain_core.documents import Document
from langchain_community.retrievers.embedchain import EmbedchainRetriever
try:
from embedchain import Pipeline
except ImportError:
pytest.skip("Requires embedchain", allow_module_level=True)
os.environ["OPENAI_API_KEY"] = "sk-xxxx"
context_value = [
{
"context": "this document is about John",
"metadata": {
"source": "source#1",
"doc_id": 123,
},
},
]
@pytest.mark.requires("embedchain")
@patch.object(Pipeline, "search", return_value=context_value)
@patch.object(Pipeline, "add", return_value=123)
def test_embedchain_retriever(mock_add: Any, mock_search: Any) -> None:
retriever = EmbedchainRetriever.create()
texts = [
"This document is about John",
]
for text in texts:
retriever.add_texts(text)
docs = retriever.get_relevant_documents("doc about john")
assert len(docs) == 1
for doc in docs:
assert isinstance(doc, Document)
assert doc.page_content
assert doc.metadata
assert len(list(doc.metadata.items())) > 0