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fix: vertexai authentication via service account (#2863)

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* fix: vertexai authentication via service account

* [autofix.ci] apply automated fixes

* fix: remove debugging print

---------

Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: anovazzi1 <otavio2204@gmail.com>
This commit is contained in:
Nicolò Boschi 2024-07-22 14:05:18 +02:00 • committed by GitHub
commit ff592d7714
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GPG key ID: B5690EEEBB952194
16 changed files with 107 additions and 296 deletions
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17
src/backend/base/langflow/base/models/model.py
View file

@ -1,13 +1,16 @@
import json
import warnings
from abc import abstractmethod
from typing import Optional, Union
from typing import Optional, Union, List
from langchain_core.language_models.llms import LLM
from langchain_core.messages import AIMessage, BaseMessage, HumanMessage, SystemMessage
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.custom import Component
from langflow.field_typing import LanguageModel
from langflow.inputs import MessageInput, MessageTextInput
from langflow.inputs.inputs import InputTypes, BoolInput
from langflow.schema.message import Message
from langflow.template.field.base import Output
@ -17,6 +20,17 @@ class LCModelComponent(Component):
description: str = "Model Description"
trace_type = "llm"
_base_inputs: List[InputTypes] = [
MessageInput(name="input_value", display_name="Input"),
MessageTextInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
]
outputs = [
Output(display_name="Text", name="text_output", method="text_response"),
Output(display_name="Language Model", name="model_output", method="build_model"),
@ -142,6 +156,7 @@ class LCModelComponent(Component):
messages.append(input_value.to_lc_message())
else:
messages.append(HumanMessage(content=input_value))
inputs: Union[list, dict] = messages or {}
try:
runnable = runnable.with_config( # type: ignore

101
src/backend/base/langflow/components/embeddings/VertexAIEmbeddings.py
View file

@ -1,6 +1,6 @@
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import Embeddings
from langflow.io import BoolInput, DictInput, FileInput, FloatInput, IntInput, MessageTextInput, Output
from langflow.io import BoolInput, FileInput, FloatInput, IntInput, MessageTextInput, Output
class VertexAIEmbeddingsComponent(LCModelComponent):
@ -13,81 +13,22 @@ class VertexAIEmbeddingsComponent(LCModelComponent):
FileInput(
name="credentials",
display_name="Credentials",
info="JSON credentials file. Leave empty to fallback to environment variables",
value="",
file_types=["json"], # Removed the dot
),
DictInput(
name="instance",
display_name="Instance",
advanced=True,
),
MessageTextInput(
name="location",
display_name="Location",
value="us-central1",
advanced=True,
),
IntInput(
name="max_output_tokens",
display_name="Max Output Tokens",
value=128,
),
IntInput(
name="max_retries",
display_name="Max Retries",
value=6,
advanced=True,
),
MessageTextInput(
name="model_name",
display_name="Model Name",
value="textembedding-gecko",
),
IntInput(
name="n",
display_name="N",
value=1,
advanced=True,
),
MessageTextInput(
name="project",
display_name="Project",
advanced=True,
),
IntInput(
name="request_parallelism",
display_name="Request Parallelism",
value=5,
advanced=True,
),
MessageTextInput(
name="stop",
display_name="Stop",
advanced=True,
),
BoolInput(
name="streaming",
display_name="Streaming",
value=False,
advanced=True,
),
FloatInput(
name="temperature",
display_name="Temperature",
value=0.0,
),
IntInput(
name="top_k",
display_name="Top K",
value=40,
advanced=True,
),
FloatInput(
name="top_p",
display_name="Top P",
value=0.95,
advanced=True,
file_types=["json"],
),
MessageTextInput(name="location", display_name="Location", advanced=True),
MessageTextInput(name="project", display_name="Project", info="The project ID.", advanced=True),
IntInput(name="max_output_tokens", display_name="Max Output Tokens", advanced=True),
IntInput(name="max_retries", display_name="Max Retries", value=1, advanced=True),
MessageTextInput(name="model_name", display_name="Model Name", value="textembedding-gecko"),
IntInput(name="n", display_name="N", value=1, advanced=True),
IntInput(name="request_parallelism", value=5, display_name="Request Parallelism", advanced=True),
MessageTextInput(name="stop_sequences", display_name="Stop", advanced=True, is_list=True),
BoolInput(name="streaming", display_name="Streaming", value=False, advanced=True),
FloatInput(name="temperature", value=0.0, display_name="Temperature"),
IntInput(name="top_k", display_name="Top K", advanced=True),
FloatInput(name="top_p", display_name="Top P", value=0.95, advanced=True),
]
outputs = [
@ -102,9 +43,15 @@ class VertexAIEmbeddingsComponent(LCModelComponent):
"Please install the langchain-google-vertexai package to use the VertexAIEmbeddings component."
)
from google.oauth2 import service_account
if self.credentials:
gcloud_credentials = service_account.Credentials.from_service_account_file(self.credentials)
else:
# will fallback to environment variable or inferred from gcloud CLI
gcloud_credentials = None
return VertexAIEmbeddings(
instance=self.instance,
credentials=self.credentials,
credentials=gcloud_credentials,
location=self.location,
max_output_tokens=self.max_output_tokens,
max_retries=self.max_retries,
@ -112,7 +59,7 @@ class VertexAIEmbeddingsComponent(LCModelComponent):
n=self.n,
project=self.project,
request_parallelism=self.request_parallelism,
stop=self.stop,
stop=self.stop_sequences or None,
streaming=self.streaming,
temperature=self.temperature,
top_k=self.top_k,

13
src/backend/base/langflow/components/models/AmazonBedrockModel.py
View file

@ -1,10 +1,9 @@
from langchain_aws import ChatBedrock
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.inputs import MessageTextInput
from langflow.io import BoolInput, DictInput, DropdownInput, MessageInput
from langflow.io import DictInput, DropdownInput
class AmazonBedrockComponent(LCModelComponent):
@ -13,8 +12,7 @@ class AmazonBedrockComponent(LCModelComponent):
icon = "Amazon"
name = "AmazonBedrockModel"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
DropdownInput(
name="model_id",
display_name="Model ID",
@ -57,13 +55,6 @@ class AmazonBedrockComponent(LCModelComponent):
MessageTextInput(name="region_name", display_name="Region Name", value="us-east-1"),
DictInput(name="model_kwargs", display_name="Model Kwargs", advanced=True, is_list=True),
MessageTextInput(name="endpoint_url", display_name="Endpoint URL", advanced=True),
MessageTextInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

13
src/backend/base/langflow/components/models/AnthropicModel.py
View file

@ -1,10 +1,9 @@
from langchain_anthropic.chat_models import ChatAnthropic
from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput
from langflow.io import DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput
class AnthropicModelComponent(LCModelComponent):
@ -13,8 +12,7 @@ class AnthropicModelComponent(LCModelComponent):
icon = "Anthropic"
name = "AnthropicModel"
inputs = [
MessageTextInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
IntInput(
name="max_tokens",
display_name="Max Tokens",
@ -46,13 +44,6 @@ class AnthropicModelComponent(LCModelComponent):
advanced=True,
info="Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.",
),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True, value=False),
MessageTextInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
MessageTextInput(
name="prefill",
display_name="Prefill",

13
src/backend/base/langflow/components/models/AzureOpenAIModel.py
View file

@ -1,9 +1,8 @@
from langchain_openai import AzureChatOpenAI
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.inputs import MessageTextInput
from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
from langflow.io import DropdownInput, FloatInput, IntInput, SecretStrInput
class AzureChatOpenAIComponent(LCModelComponent):
@ -26,7 +25,7 @@ class AzureChatOpenAIComponent(LCModelComponent):
"2024-05-13",
]
inputs = [
inputs = LCModelComponent._base_inputs + [
MessageTextInput(
name="azure_endpoint",
display_name="Azure Endpoint",
@ -48,14 +47,6 @@ class AzureChatOpenAIComponent(LCModelComponent):
advanced=True,
info="The maximum number of tokens to generate. Set to 0 for unlimited tokens.",
),
MessageInput(name="input_value", display_name="Input"),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
advanced=True,
info="System message to pass to the model.",
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

21
src/backend/base/langflow/components/models/BaiduQianfanChatModel.py
View file

@ -1,10 +1,9 @@
from langchain_community.chat_models.baidu_qianfan_endpoint import QianfanChatEndpoint
from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing.constants import LanguageModel
from langflow.io import BoolInput, DropdownInput, FloatInput, MessageTextInput, SecretStrInput
from langflow.io import DropdownInput, FloatInput, MessageTextInput, SecretStrInput
class QianfanChatEndpointComponent(LCModelComponent):
@ -14,11 +13,7 @@ class QianfanChatEndpointComponent(LCModelComponent):
icon = "BaiduQianfan"
name = "BaiduQianfanChatModel"
inputs = [
MessageTextInput(
name="input_value",
display_name="Input",
),
inputs = LCModelComponent._base_inputs + [
DropdownInput(
name="model",
display_name="Model Name",
@ -72,18 +67,6 @@ class QianfanChatEndpointComponent(LCModelComponent):
display_name="Endpoint",
info="Endpoint of the Qianfan LLM, required if custom model used.",
),
BoolInput(
name="stream",
display_name="Stream",
info=STREAM_INFO_TEXT,
advanced=True,
),
MessageTextInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

13
src/backend/base/langflow/components/models/CohereModel.py
View file

@ -1,10 +1,9 @@
from langchain_cohere import ChatCohere
from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.io import BoolInput, FloatInput, MessageInput, SecretStrInput, StrInput
from langflow.io import FloatInput, SecretStrInput
class CohereComponent(LCModelComponent):
@ -14,7 +13,7 @@ class CohereComponent(LCModelComponent):
icon = "Cohere"
name = "CohereModel"
inputs = [
inputs = LCModelComponent._base_inputs + [
SecretStrInput(
name="cohere_api_key",
display_name="Cohere API Key",
@ -23,14 +22,6 @@ class CohereComponent(LCModelComponent):
value="COHERE_API_KEY",
),
FloatInput(name="temperature", display_name="Temperature", value=0.75),
MessageInput(name="input_value", display_name="Input"),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

13
src/backend/base/langflow/components/models/GoogleGenerativeAIModel.py
View file

@ -1,9 +1,8 @@
from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
from langflow.inputs import DropdownInput, FloatInput, IntInput, SecretStrInput
class GoogleGenerativeAIComponent(LCModelComponent):
@ -12,8 +11,7 @@ class GoogleGenerativeAIComponent(LCModelComponent):
icon = "GoogleGenerativeAI"
name = "GoogleGenerativeAIModel"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
IntInput(
name="max_output_tokens",
display_name="Max Output Tokens",
@ -38,19 +36,12 @@ class GoogleGenerativeAIComponent(LCModelComponent):
advanced=True,
),
FloatInput(name="temperature", display_name="Temperature", value=0.1),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
IntInput(
name="n",
display_name="N",
info="Number of chat completions to generate for each prompt. Note that the API may not return the full n completions if duplicates are generated.",
advanced=True,
),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
IntInput(
name="top_k",
display_name="Top K",

22
src/backend/base/langflow/components/models/GroqModel.py
View file

@ -1,11 +1,10 @@
from langchain_groq import ChatGroq
from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.groq_constants import MODEL_NAMES
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput
from langflow.io import DropdownInput, FloatInput, IntInput, MessageTextInput, SecretStrInput
class GroqModel(LCModelComponent):
@ -14,7 +13,7 @@ class GroqModel(LCModelComponent):
icon = "Groq"
name = "GroqModel"
inputs = [
inputs = LCModelComponent._base_inputs + [
SecretStrInput(
name="groq_api_key",
display_name="Groq API Key",
@ -50,23 +49,6 @@ class GroqModel(LCModelComponent):
info="The name of the model to use.",
options=MODEL_NAMES,
),
MessageTextInput(
name="input_value",
display_name="Input",
info="The input to the model.",
),
BoolInput(
name="stream",
display_name="Stream",
info=STREAM_INFO_TEXT,
advanced=True,
),
MessageTextInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

13
src/backend/base/langflow/components/models/HuggingFaceModel.py
View file

@ -1,10 +1,9 @@
from langchain_community.chat_models.huggingface import ChatHuggingFace
from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.io import BoolInput, DictInput, DropdownInput, MessageInput, SecretStrInput, StrInput
from langflow.io import DictInput, DropdownInput, SecretStrInput, StrInput
class HuggingFaceEndpointsComponent(LCModelComponent):
@ -13,8 +12,7 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
icon = "HuggingFace"
name = "HuggingFaceModel"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
SecretStrInput(name="endpoint_url", display_name="Endpoint URL", password=True),
StrInput(
name="model_id",
@ -28,13 +26,6 @@ class HuggingFaceEndpointsComponent(LCModelComponent):
),
SecretStrInput(name="huggingfacehub_api_token", display_name="API token", password=True),
DictInput(name="model_kwargs", display_name="Model Keyword Arguments", advanced=True),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

13
src/backend/base/langflow/components/models/Maritalk.py
View file

@ -1,10 +1,9 @@
from langchain_community.chat_models import ChatMaritalk
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.field_typing.range_spec import RangeSpec
from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
from langflow.inputs import DropdownInput, FloatInput, IntInput, SecretStrInput
class MaritalkModelComponent(LCModelComponent):
@ -12,8 +11,7 @@ class MaritalkModelComponent(LCModelComponent):
description = "Generates text using Maritalk LLMs."
icon = "Maritalk"
name = "Maritalk"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
IntInput(
name="max_tokens",
display_name="Max Tokens",
@ -35,13 +33,6 @@ class MaritalkModelComponent(LCModelComponent):
advanced=False,
),
FloatInput(name="temperature", display_name="Temperature", value=0.1, range_spec=RangeSpec(min=0, max=1)),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, value=False, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

13
src/backend/base/langflow/components/models/MistralModel.py
View file

@ -1,10 +1,9 @@
from langchain_mistralai import ChatMistralAI
from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
from langflow.io import BoolInput, DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
class MistralAIModelComponent(LCModelComponent):
@ -13,8 +12,7 @@ class MistralAIModelComponent(LCModelComponent):
icon = "MistralAI"
name = "MistralModel"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
IntInput(
name="max_tokens",
display_name="Max Tokens",
@ -51,13 +49,6 @@ class MistralAIModelComponent(LCModelComponent):
advanced=False,
),
FloatInput(name="temperature", display_name="Temperature", advanced=False, value=0.5),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
IntInput(name="max_retries", display_name="Max Retries", advanced=True, value=5),
IntInput(name="timeout", display_name="Timeout", advanced=True, value=60),
IntInput(name="max_concurrent_requests", display_name="Max Concurrent Requests", advanced=True, value=3),

13
src/backend/base/langflow/components/models/NvidiaModel.py
View file

@ -1,9 +1,8 @@
from typing import Any
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.inputs import BoolInput, DropdownInput, FloatInput, IntInput, MessageInput, SecretStrInput, StrInput
from langflow.inputs import DropdownInput, FloatInput, IntInput, SecretStrInput, StrInput
from langflow.schema.dotdict import dotdict
@ -12,8 +11,7 @@ class NVIDIAModelComponent(LCModelComponent):
description = "Generates text using NVIDIA LLMs."
icon = "NVIDIA"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
IntInput(
name="max_tokens",
display_name="Max Tokens",
@ -42,13 +40,6 @@ class NVIDIAModelComponent(LCModelComponent):
value="NVIDIA_API_KEY",
),
FloatInput(name="temperature", display_name="Temperature", value=0.1),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
IntInput(
name="seed",
display_name="Seed",

20
src/backend/base/langflow/components/models/OllamaModel.py
View file

@ -3,10 +3,9 @@ from typing import Any
import httpx
from langchain_community.chat_models import ChatOllama
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, MessageInput, StrInput
from langflow.io import BoolInput, DictInput, DropdownInput, FloatInput, IntInput, StrInput
class ChatOllamaComponent(LCModelComponent):
@ -68,7 +67,7 @@ class ChatOllamaComponent(LCModelComponent):
except Exception as e:
raise ValueError("Could not retrieve models. Please, make sure Ollama is running.") from e
inputs = [
inputs = LCModelComponent._base_inputs + [
StrInput(
name="base_url",
display_name="Base URL",
@ -204,21 +203,6 @@ class ChatOllamaComponent(LCModelComponent):
info="Template to use for generating text.",
advanced=True,
),
MessageInput(
name="input_value",
display_name="Input",
),
BoolInput(
name="stream",
display_name="Stream",
info=STREAM_INFO_TEXT,
),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]

12
src/backend/base/langflow/components/models/OpenAIModel.py
View file

@ -4,7 +4,6 @@ from functools import reduce
from langchain_openai import ChatOpenAI
from pydantic.v1 import SecretStr
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.base.models.openai_constants import MODEL_NAMES
from langflow.field_typing import LanguageModel
@ -14,7 +13,6 @@ from langflow.inputs import (
DropdownInput,
FloatInput,
IntInput,
MessageInput,
SecretStrInput,
StrInput,
)
@ -26,8 +24,7 @@ class OpenAIModelComponent(LCModelComponent):
icon = "OpenAI"
name = "OpenAIModel"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
IntInput(
name="max_tokens",
display_name="Max Tokens",
@ -65,13 +62,6 @@ class OpenAIModelComponent(LCModelComponent):
value="OPENAI_API_KEY",
),
FloatInput(name="temperature", display_name="Temperature", value=0.1),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
IntInput(
name="seed",
display_name="Seed",

93
src/backend/base/langflow/components/models/VertexAiModel.py
View file

@ -1,9 +1,7 @@
from langchain_google_vertexai import ChatVertexAI
from langflow.base.constants import STREAM_INFO_TEXT
from langflow.base.models.model import LCModelComponent
from langflow.field_typing import LanguageModel
from langflow.io import BoolInput, FileInput, FloatInput, IntInput, MessageInput, MultilineInput, StrInput
from langflow.inputs import MessageTextInput
from langflow.io import BoolInput, FileInput, FloatInput, IntInput, StrInput
class ChatVertexAIComponent(LCModelComponent):
@ -12,64 +10,57 @@ class ChatVertexAIComponent(LCModelComponent):
icon = "VertexAI"
name = "VertexAiModel"
inputs = [
MessageInput(name="input_value", display_name="Input"),
inputs = LCModelComponent._base_inputs + [
FileInput(
name="credentials",
display_name="Credentials",
info="Path to the JSON file containing the credentials.",
info="JSON credentials file. Leave empty to fallback to environment variables",
file_types=["json"],
advanced=True,
),
StrInput(name="project", display_name="Project", info="The project ID."),
MultilineInput(
name="examples",
display_name="Examples",
info="Examples to pass to the model.",
advanced=True,
),
StrInput(name="location", display_name="Location", value="us-central1", advanced=True),
IntInput(
name="max_output_tokens",
display_name="Max Output Tokens",
value=128,
advanced=True,
),
StrInput(name="model_name", display_name="Model Name", value="gemini-1.5-pro"),
FloatInput(name="temperature", display_name="Temperature", value=0.0),
IntInput(name="top_k", display_name="Top K", value=40, advanced=True),
MessageTextInput(name="model_name", display_name="Model Name", value="gemini-1.5-pro"),
StrInput(name="project", display_name="Project", info="The project ID.", advanced=True),
StrInput(name="location", display_name="Location", advanced=True),
IntInput(name="max_output_tokens", display_name="Max Output Tokens", advanced=True),
IntInput(name="max_retries", display_name="Max Retries", value=1, advanced=True),
FloatInput(name="temperature", value=0.0, display_name="Temperature"),
IntInput(name="top_k", display_name="Top K", advanced=True),
FloatInput(name="top_p", display_name="Top P", value=0.95, advanced=True),
BoolInput(name="verbose", display_name="Verbose", value=False, advanced=True),
BoolInput(name="stream", display_name="Stream", info=STREAM_INFO_TEXT, advanced=True),
StrInput(
name="system_message",
display_name="System Message",
info="System message to pass to the model.",
advanced=True,
),
]
def build_model(self) -> LanguageModel: # type: ignore[type-var]
credentials = self.credentials
location = self.location
max_output_tokens = self.max_output_tokens
model_name = self.model_name
project = self.project
temperature = self.temperature
top_k = self.top_k
top_p = self.top_p
verbose = self.verbose
def build_model(self) -> LanguageModel:
try:
from langchain_google_vertexai import ChatVertexAI
except ImportError:
raise ImportError(
"Please install the langchain-google-vertexai package to use the VertexAIEmbeddings component."
)
location = self.location or None
if self.credentials:
from google.oauth2 import service_account
from google.cloud import aiplatform
output = ChatVertexAI(
credentials = service_account.Credentials.from_service_account_file(self.credentials)
project = self.project or credentials.project_id
# ChatVertexAI sometimes skip manual credentials initialization
aiplatform.init(
project=project,
location=location,
credentials=credentials,
)
else:
project = self.project or None
credentials = None
return ChatVertexAI(
credentials=credentials,
location=location,
max_output_tokens=max_output_tokens,
model_name=model_name,
project=project,
temperature=temperature,
top_k=top_k,
top_p=top_p,
verbose=verbose,
max_output_tokens=self.max_output_tokens,
max_retries=self.max_retries,
model_name=self.model_name,
temperature=self.temperature,
top_k=self.top_k,
top_p=self.top_p,
verbose=self.verbose,
)
return output # type: ignore