From 34754c09df44be9400d81c522fe9d54e36804cb5 Mon Sep 17 00:00:00 2001 From: Tyler Hutcherson Date: Thu, 15 Feb 2024 22:03:39 -0500 Subject: [PATCH] update vectorizer tests and docs --- redisvl/utils/vectorize/text/cohere.py | 2 +- tests/integration/test_vectorizers.py | 7 +++++-- 2 files changed, 6 insertions(+), 3 deletions(-) diff --git a/redisvl/utils/vectorize/text/cohere.py b/redisvl/utils/vectorize/text/cohere.py index 8990cae5..7eadd658 100644 --- a/redisvl/utils/vectorize/text/cohere.py +++ b/redisvl/utils/vectorize/text/cohere.py @@ -38,7 +38,7 @@ class CohereTextVectorizer(BaseVectorizer): ) doc_embeddings = cohere.embed_many( texts=["your document text", "more document text"], - input_type="search_documents" + input_type="search_document" ) """ diff --git a/tests/integration/test_vectorizers.py b/tests/integration/test_vectorizers.py index 59b094db..9a3c1288 100644 --- a/tests/integration/test_vectorizers.py +++ b/tests/integration/test_vectorizers.py @@ -43,7 +43,10 @@ def vectorizer(request): @pytest.mark.skipif(skip_vectorizer_test, reason="Skipping vectorizer tests") def test_vectorizer_embed(vectorizer): text = "This is a test sentence." - embedding = vectorizer.embed(text) + if isinstance(vectorizer, CohereTextVectorizer): + embedding = vectorizer.embed(text, input_type="search_document") + else: + embedding = vectorizer.embed(text) assert isinstance(embedding, list) assert len(embedding) == vectorizer.dims @@ -77,7 +80,7 @@ def test_vectorizer_bad_input(vectorizer): @pytest.fixture(params=[OpenAITextVectorizer]) -def avectorizer(request, openai_key): +def avectorizer(request): # Here we use actual models for integration test if request.param == OpenAITextVectorizer: return request.param()