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feat: update output attribute handling (#3329)

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* refactor: improve function structure in _build_results

* fix: remove function call that overrides Component.outputs

* refactor: Add handling for outputs in __getattr__ method.
This commit is contained in:
Gabriel Luiz Freitas Almeida 2024-08-15 10:00:09 -03:00 • committed by GitHub
commit bb923cf9e1
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4 changed files with 126 additions and 116 deletions
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26
src/backend/tests/unit/initial_setup/starter_projects/test_vector_store_rag.py
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@ -27,7 +27,7 @@ def ingestion_graph():
# Ingestion Graph
file_component = FileComponent(_id="file-123")
file_component.set(path="test.txt")
file_component.set_output_value("data", Data(text="This is a test file."))
file_component.set_on_output("data", value=Data(text="This is a test file."))
text_splitter = SplitTextComponent(_id="text-splitter-123")
text_splitter.set(data_inputs=file_component.load_file)
openai_embeddings = OpenAIEmbeddingsComponent(_id="openai-embeddings-123")
@ -41,10 +41,9 @@ def ingestion_graph():
api_endpoint="https://astra.example.com",
token="token",
)
vector_store.set_output_value("vector_store", "mock_vector_store")
vector_store.set_output_value("base_retriever", "mock_retriever")
vector_store.set_output_value("search_results", [Data(text="This is a test file.")])
vector_store.set_on_output("vector_store", value="mock_vector_store")
vector_store.set_on_output("base_retriever", value="mock_retriever")
vector_store.set_on_output("search_results", value=[Data(text="This is a test file.")])
ingestion_graph = Graph(file_component, vector_store)
return ingestion_graph
@ -63,10 +62,15 @@ def rag_graph():
embedding=openai_embeddings.build_embeddings,
)
# Mock search_documents
rag_vector_store.get_output("search_results").value = [
Data(data={"text": "Hello, world!"}),
Data(data={"text": "Goodbye, world!"}),
]
rag_vector_store.set_on_output(
"search_results",
value=[
Data(data={"text": "Hello, world!"}),
Data(data={"text": "Goodbye, world!"}),
],
)
rag_vector_store.set_on_output("base_retriever", value="mock_retriever")
rag_vector_store.set_on_output("vector_store", value="mock_vector_store")
parse_data = ParseDataComponent(_id="parse-data-123")
parse_data.set(data=rag_vector_store.search_documents)
prompt_component = PromptComponent(_id="prompt-123")
@ -82,7 +86,7 @@ def rag_graph():
openai_component = OpenAIModelComponent(_id="openai-123")
openai_component.set(api_key="sk-123", openai_api_base="https://api.openai.com/v1")
openai_component.set_output_value("text_output", "Hello, world!")
openai_component.set_on_output("text_output", value="Hello, world!")
openai_component.set(input_value=prompt_component.build_prompt)
chat_output = ChatOutput(_id="chatoutput-123")
@ -112,7 +116,7 @@ def test_vector_store_rag(ingestion_graph, rag_graph):
]
for ids, graph, len_results in zip([ingestion_ids, rag_ids], [ingestion_graph, rag_graph], [5, 8]):
results = []
for result in graph.start():
for result in graph.start(config={"output": {"cache": True}}):
results.append(result)
assert len(results) == len_results