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fix: issue with dynamic inputs when selecting model (#4538)

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Eric Hare 2024-11-12 11:58:41 -08:00 • committed by GitHub
commit 1dfa160385
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2 changed files with 56 additions and 44 deletions
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82
src/backend/base/langflow/components/vectorstores/astradb.py
View file

@ -210,6 +210,13 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
), ),
] ]
def del_fields(self, build_config, field_list):
for field in field_list:
if field in build_config:
del build_config[field]
return build_config
def insert_in_dict(self, build_config, field_name, new_parameters): def insert_in_dict(self, build_config, field_name, new_parameters):
# Insert the new key-value pair after the found key # Insert the new key-value pair after the found key
for new_field_name, new_parameter in new_parameters.items(): for new_field_name, new_parameter in new_parameters.items():
@ -234,31 +241,30 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None): def update_build_config(self, build_config: dict, field_value: str, field_name: str | None = None):
if field_name == "embedding_service": if field_name == "embedding_service":
if field_value == "Astra Vectorize": if field_value == "Astra Vectorize":
for field in ["embedding"]: self.del_fields(build_config, ["embedding"])
if field in build_config:
del build_config[field]
new_parameter = DropdownInput( new_parameter = DropdownInput(
name="provider", name="embedding_provider",
display_name="Vectorize Provider", display_name="Embedding Provider",
options=self.VECTORIZE_PROVIDERS_MAPPING.keys(), options=self.VECTORIZE_PROVIDERS_MAPPING.keys(),
value="", value="",
required=True, required=True,
real_time_refresh=True, real_time_refresh=True,
).to_dict() ).to_dict()
self.insert_in_dict(build_config, "embedding_service", {"provider": new_parameter}) self.insert_in_dict(build_config, "embedding_service", {"embedding_provider": new_parameter})
else: else:
for field in [ self.del_fields(
"provider", build_config,
"z_00_model_name", [
"embedding_provider",
"model",
"z_01_model_parameters", "z_01_model_parameters",
"z_02_api_key_name", "z_02_api_key_name",
"z_03_provider_api_key", "z_03_provider_api_key",
"z_04_authentication", "z_04_authentication",
]: ],
if field in build_config: )
del build_config[field]
new_parameter = HandleInput( new_parameter = HandleInput(
name="embedding", name="embedding",
@ -269,32 +275,35 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
self.insert_in_dict(build_config, "embedding_service", {"embedding": new_parameter}) self.insert_in_dict(build_config, "embedding_service", {"embedding": new_parameter})
elif field_name == "provider": elif field_name == "embedding_provider":
for field in [ self.del_fields(
"z_00_model_name", build_config,
"z_01_model_parameters", ["model", "z_01_model_parameters", "z_02_api_key_name", "z_03_provider_api_key", "z_04_authentication"],
"z_02_api_key_name", )
"z_03_provider_api_key",
"z_04_authentication",
]:
if field in build_config:
del build_config[field]
model_options = self.VECTORIZE_PROVIDERS_MAPPING[field_value][1] model_options = self.VECTORIZE_PROVIDERS_MAPPING[field_value][1]
new_parameter_0 = DropdownInput( new_parameter = DropdownInput(
name="z_00_model_name", name="model",
display_name="Model Name", display_name="Model",
info="The embedding model to use for the selected provider. Each provider has a different set of " info="The embedding model to use for the selected provider. Each provider has a different set of "
"models available (full list at " "models available (full list at "
"https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\n\n" "https://docs.datastax.com/en/astra-db-serverless/databases/embedding-generation.html):\n\n"
f"{', '.join(model_options)}", f"{', '.join(model_options)}",
options=model_options, options=model_options,
placeholder="Select a model", value=None,
value=model_options[0],
required=True, required=True,
real_time_refresh=True,
).to_dict() ).to_dict()
self.insert_in_dict(build_config, "embedding_provider", {"model": new_parameter})
elif field_name == "model":
self.del_fields(
build_config,
["z_01_model_parameters", "z_02_api_key_name", "z_03_provider_api_key", "z_04_authentication"],
)
new_parameter_1 = DictInput( new_parameter_1 = DictInput(
name="z_01_model_parameters", name="z_01_model_parameters",
display_name="Model Parameters", display_name="Model Parameters",
@ -303,12 +312,13 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
new_parameter_2 = MessageTextInput( new_parameter_2 = MessageTextInput(
name="z_02_api_key_name", name="z_02_api_key_name",
display_name="API Key name", display_name="API Key Name",
info="The name of the embeddings provider API key stored on Astra. " info="The name of the embeddings provider API key stored on Astra. "
"If set, it will override the 'ProviderKey' in the authentication parameters.", "If set, it will override the 'ProviderKey' in the authentication parameters.",
).to_dict() ).to_dict()
new_parameter_3 = SecretStrInput( new_parameter_3 = SecretStrInput(
load_from_db=False,
name="z_03_provider_api_key", name="z_03_provider_api_key",
display_name="Provider API Key", display_name="Provider API Key",
info="An alternative to the Astra Authentication that passes an API key for the provider " info="An alternative to the Astra Authentication that passes an API key for the provider "
@ -319,15 +329,14 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
new_parameter_4 = DictInput( new_parameter_4 = DictInput(
name="z_04_authentication", name="z_04_authentication",
display_name="Authentication parameters", display_name="Authentication Parameters",
is_list=True, is_list=True,
).to_dict() ).to_dict()
self.insert_in_dict( self.insert_in_dict(
build_config, build_config,
"provider", "model",
{ {
"z_00_model_name": new_parameter_0,
"z_01_model_parameters": new_parameter_1, "z_01_model_parameters": new_parameter_1,
"z_02_api_key_name": new_parameter_2, "z_02_api_key_name": new_parameter_2,
"z_03_provider_api_key": new_parameter_3, "z_03_provider_api_key": new_parameter_3,
@ -339,8 +348,8 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
def build_vectorize_options(self, **kwargs): def build_vectorize_options(self, **kwargs):
for attribute in [ for attribute in [
"provider", "embedding_provider",
"z_00_model_name", "model",
"z_01_model_parameters", "z_01_model_parameters",
"z_02_api_key_name", "z_02_api_key_name",
"z_03_provider_api_key", "z_03_provider_api_key",
@ -350,8 +359,10 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
setattr(self, attribute, None) setattr(self, attribute, None)
# Fetch values from kwargs if any self.* attributes are None # Fetch values from kwargs if any self.* attributes are None
provider_value = self.VECTORIZE_PROVIDERS_MAPPING.get(self.provider, [None])[0] or kwargs.get("provider") provider_value = self.VECTORIZE_PROVIDERS_MAPPING.get(self.embedding_provider, [None])[0] or kwargs.get(
model_name = self.z_00_model_name or kwargs.get("z_00_model_name") "embedding_provider"
)
model_name = self.model or kwargs.get("model")
authentication = {**(self.z_04_authentication or kwargs.get("z_04_authentication", {}))} authentication = {**(self.z_04_authentication or kwargs.get("z_04_authentication", {}))}
parameters = self.z_01_model_parameters or kwargs.get("z_01_model_parameters", {}) parameters = self.z_01_model_parameters or kwargs.get("z_01_model_parameters", {})
@ -414,6 +425,7 @@ class AstraVectorStoreComponent(LCVectorStoreComponent):
), ),
"collection_embedding_api_key": dict_options.get("collection_embedding_api_key"), "collection_embedding_api_key": dict_options.get("collection_embedding_api_key"),
} }
try: try:
vector_store = AstraDBVectorStore( vector_store = AstraDBVectorStore(
collection_name=self.collection_name, collection_name=self.collection_name,

10
src/backend/tests/integration/components/astra/test_astra_component.py
View file

@ -99,7 +99,7 @@ def test_astra_vectorize():
store = None store = None
try: try:
options = {"provider": "nvidia", "modelName": "NV-Embed-QA"} options = {"provider": "nvidia", "modelName": "NV-Embed-QA"}
options_comp = {"provider": "nvidia", "z_00_model_name": "NV-Embed-QA"} options_comp = {"embedding_provider": "nvidia", "model": "NV-Embed-QA"}
store = AstraDBVectorStore( store = AstraDBVectorStore(
collection_name=VECTORIZE_COLLECTION, collection_name=VECTORIZE_COLLECTION,
@ -150,8 +150,8 @@ def test_astra_vectorize_with_provider_api_key():
} }
options_comp = { options_comp = {
"provider": "openai", "embedding_provider": "openai",
"z_00_model_name": "text-embedding-3-small", "model": "text-embedding-3-small",
"z_01_model_parameters": {}, "z_01_model_parameters": {},
"z_03_provider_api_key": "openai", "z_03_provider_api_key": "openai",
"z_04_authentication": {}, "z_04_authentication": {},
@ -206,8 +206,8 @@ def test_astra_vectorize_passes_authentication():
"authentication": {"providerKey": "openai"}, "authentication": {"providerKey": "openai"},
} }
options_comp = { options_comp = {
"provider": "openai", "embedding_provider": "openai",
"z_00_model_name": "text-embedding-3-small", "model": "text-embedding-3-small",
"z_01_model_parameters": {}, "z_01_model_parameters": {},
"z_04_authentication": {"providerKey": "openai"}, "z_04_authentication": {"providerKey": "openai"},
} }