merge dev into two_edges
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commit
fcf4512210
133 changed files with 2534 additions and 1507 deletions
160
tests/integration/astra/test_astra_component.py
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160
tests/integration/astra/test_astra_component.py
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import os
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import pytest
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from integration.utils import MockEmbeddings, check_env_vars
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from langflow.components.memories.AstraDBMessageReader import (
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AstraDBMessageReaderComponent,
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)
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from langflow.components.memories.AstraDBMessageWriter import (
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AstraDBMessageWriterComponent,
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)
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from langflow.components.vectorsearch.AstraDBSearch import AstraDBSearchComponent
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from langflow.components.vectorstores.AstraDB import AstraDBVectorStoreComponent
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from langflow.schema.record import Record
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from langchain_core.documents import Document
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COLLECTION = "test_basic"
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SEARCH_COLLECTION = "test_search"
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MEMORY_COLLECTION = "test_memory"
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@pytest.fixture()
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def astra_fixture(request):
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"""
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Sets up the astra collection and cleans up after
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"""
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try:
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from langchain_astradb import AstraDBVectorStore
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except ImportError:
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raise ImportError(
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"Could not import langchain Astra DB integration package. Please install it with `pip install langchain-astradb`."
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)
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store = AstraDBVectorStore(
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collection_name=request.param,
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embedding=MockEmbeddings(),
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api_endpoint=os.getenv("ASTRA_DB_API_ENDPOINT"),
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token=os.getenv("ASTRA_DB_APPLICATION_TOKEN"),
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)
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yield
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store.delete_collection()
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@pytest.mark.skipif(
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not check_env_vars("ASTRA_DB_APPLICATION_TOKEN", "ASTRA_DB_API_ENDPOINT"),
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reason="missing astra env vars",
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)
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@pytest.mark.parametrize("astra_fixture", [COLLECTION], indirect=True)
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def test_astra_setup(astra_fixture):
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application_token = os.getenv("ASTRA_DB_APPLICATION_TOKEN")
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api_endpoint = os.getenv("ASTRA_DB_API_ENDPOINT")
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embedding = MockEmbeddings()
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component = AstraDBVectorStoreComponent()
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component.build(
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token=application_token,
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api_endpoint=api_endpoint,
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collection_name=COLLECTION,
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embedding=embedding,
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)
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@pytest.mark.skipif(
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not check_env_vars("ASTRA_DB_APPLICATION_TOKEN", "ASTRA_DB_API_ENDPOINT"),
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reason="missing astra env vars",
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)
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@pytest.mark.parametrize("astra_fixture", [SEARCH_COLLECTION], indirect=True)
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def test_astra_embeds_and_search(astra_fixture):
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application_token = os.getenv("ASTRA_DB_APPLICATION_TOKEN")
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api_endpoint = os.getenv("ASTRA_DB_API_ENDPOINT")
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embedding = MockEmbeddings()
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documents = [Document(page_content="test1"), Document(page_content="test2")]
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records = [Record.from_document(d) for d in documents]
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component = AstraDBVectorStoreComponent()
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component.build(
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token=application_token,
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api_endpoint=api_endpoint,
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collection_name=SEARCH_COLLECTION,
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embedding=embedding,
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inputs=records,
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)
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component = AstraDBSearchComponent()
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records = component.build(
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token=application_token,
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api_endpoint=api_endpoint,
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collection_name=SEARCH_COLLECTION,
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embedding=embedding,
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input_value="test1",
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number_of_results=1,
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)
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assert len(records) == 1
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@pytest.mark.skipif(
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not check_env_vars("ASTRA_DB_APPLICATION_TOKEN", "ASTRA_DB_API_ENDPOINT"),
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reason="missing astra env vars",
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)
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def test_astra_memory():
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application_token = os.getenv("ASTRA_DB_APPLICATION_TOKEN")
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api_endpoint = os.getenv("ASTRA_DB_API_ENDPOINT")
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writer = AstraDBMessageWriterComponent()
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reader = AstraDBMessageReaderComponent()
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input_value = Record.from_document(
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Document(
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page_content="memory1",
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metadata={"session_id": 1, "sender": "human", "sender_name": "Bob"},
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)
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)
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writer.build(
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input_value=input_value,
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session_id=1,
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token=application_token,
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api_endpoint=api_endpoint,
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collection_name=MEMORY_COLLECTION,
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)
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# verify reading w/ same session id pulls the same record
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records = reader.build(
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session_id=1,
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token=application_token,
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api_endpoint=api_endpoint,
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collection_name=MEMORY_COLLECTION,
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)
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assert len(records) == 1
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assert isinstance(records[0], Record)
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content = records[0].get_text()
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assert content == "memory1"
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# verify reading w/ different session id does not pull the same record
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records = reader.build(
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session_id=2,
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token=application_token,
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api_endpoint=api_endpoint,
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collection_name=MEMORY_COLLECTION,
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)
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assert len(records) == 0
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# Cleanup store - doing here rather than fixture (see https://github.com/langchain-ai/langchain-datastax/pull/36)
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try:
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from langchain_astradb import AstraDBVectorStore
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except ImportError:
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raise ImportError(
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"Could not import langchain Astra DB integration package. Please install it with `pip install langchain-astradb`."
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)
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store = AstraDBVectorStore(
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collection_name=MEMORY_COLLECTION,
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embedding=MockEmbeddings(),
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api_endpoint=api_endpoint,
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token=application_token,
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)
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store.delete_collection()
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35
tests/integration/utils.py
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35
tests/integration/utils.py
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@ -0,0 +1,35 @@
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import os
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from typing import List
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from langflow.field_typing import Embeddings
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def check_env_vars(*vars):
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"""
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Check if all specified environment variables are set.
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Args:
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*vars (str): The environment variables to check.
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Returns:
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bool: True if all environment variables are set, False otherwise.
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"""
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return all(os.getenv(var) for var in vars)
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class MockEmbeddings(Embeddings):
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def __init__(self):
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self.embedded_documents = None
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self.embedded_query = None
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@staticmethod
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def mock_embedding(text: str):
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return [len(text) / 2, len(text) / 5, len(text) / 10]
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def embed_documents(self, texts: List[str]) -> List[List[float]]:
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self.embedded_documents = texts
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return [self.mock_embedding(text) for text in texts]
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def embed_query(self, text: str) -> List[float]:
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self.embedded_query = text
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return self.mock_embedding(text)
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@ -707,36 +707,36 @@ def test_run_flow_with_caching_invalid_input_format(client: TestClient, starter_
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assert response.status_code == status.HTTP_422_UNPROCESSABLE_ENTITY
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@pytest.mark.api_key_required
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def test_run_flow_with_session_id(client, starter_project, created_api_key):
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headers = {"x-api-key": created_api_key.api_key}
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flow_id = starter_project["id"]
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payload = {
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"input_value": "value1",
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"input_type": "text",
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"output_type": "text",
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"session_id": "test-session-id",
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}
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response = client.post(f"/api/v1/run/{flow_id}", json=payload, headers=headers)
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assert response.status_code == status.HTTP_404_NOT_FOUND
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data = response.json()
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assert {"detail": "Session test-session-id not found"} == data
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# @pytest.mark.api_key_required
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# def test_run_flow_with_session_id(client, starter_project, created_api_key):
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# headers = {"x-api-key": created_api_key.api_key}
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# flow_id = starter_project["id"]
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# payload = {
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# "input_value": "value1",
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# "input_type": "text",
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# "output_type": "text",
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# "session_id": "test-session-id",
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# }
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# response = client.post(f"/api/v1/run/{flow_id}", json=payload, headers=headers)
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# assert response.status_code == status.HTTP_404_NOT_FOUND
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# data = response.json()
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# assert {"detail": "Session test-session-id not found"} == data
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def test_run_flow_with_invalid_session_id(client, starter_project, created_api_key):
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headers = {"x-api-key": created_api_key.api_key}
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flow_id = starter_project["id"]
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payload = {
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"input_value": "value1",
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"input_type": "text",
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"output_type": "text",
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"session_id": "invalid-session-id",
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}
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response = client.post(f"/api/v1/run/{flow_id}", json=payload, headers=headers)
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assert response.status_code == status.HTTP_404_NOT_FOUND
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data = response.json()
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assert "detail" in data
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assert f"Session {payload['session_id']} not found" in data["detail"]
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# def test_run_flow_with_invalid_session_id(client, starter_project, created_api_key):
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# headers = {"x-api-key": created_api_key.api_key}
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# flow_id = starter_project["id"]
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# payload = {
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# "input_value": "value1",
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# "input_type": "text",
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# "output_type": "text",
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# "session_id": "invalid-session-id",
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# }
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# response = client.post(f"/api/v1/run/{flow_id}", json=payload, headers=headers)
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# assert response.status_code == status.HTTP_404_NOT_FOUND
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# data = response.json()
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# assert "detail" in data
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# assert f"Session {payload['session_id']} not found" in data["detail"]
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@pytest.mark.api_key_required
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0
tests/unit/__init__.py
Normal file
0
tests/unit/__init__.py
Normal file
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