Merge branch 'main' into fix/RemoveGlobalVariables

.github/workflows/typescript_test.yml

@@ -29,8 +29,30 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        shardIndex: [1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15]
-        shardTotal: [15]
+        shardIndex:
+          [
+            1,
+            2,
+            3,
+            4,
+            5,
+            6,
+            7,
+            8,
+            9,
+            10,
+            11,
+            12,
+            13,
+            14,
+            15,
+            16,
+            17,
+            18,
+            19,
+            20,
+          ]
+        shardTotal: [20]
     env:
       OPENAI_API_KEY: ${{ inputs.openai_api_key || secrets.OPENAI_API_KEY }}
       STORE_API_KEY: ${{ inputs.store_api_key || secrets.STORE_API_KEY }}
@@ -123,6 +145,7 @@ jobs:
   merge-reports:
     needs: setup-and-test
     runs-on: ubuntu-latest
+    if: always()
     steps:
       - name: Checkout code
         uses: actions/checkout@v4

pyproject.toml

@@ -192,6 +192,7 @@ line-length = 120
 [tool.mypy]
 plugins = ["pydantic.mypy"]
 follow_imports = "silent"
+disable_error_code = ["type-var"]
 
 [build-system]
 requires = ["poetry-core"]

src/backend/base/langflow/api/v1/api_key.py

@@ -71,6 +71,7 @@ def save_store_api_key(
         # Encrypt the API key
         encrypted = auth_utils.encrypt_api_key(api_key, settings_service=settings_service)
         current_user.store_api_key = encrypted
+        db.add(current_user)
         db.commit()
         return {"detail": "API Key saved"}
     except Exception as e:

src/backend/base/langflow/api/v1/flows.py

@@ -293,19 +293,25 @@ async def upload_file(
     session: Session = Depends(get_session),
     file: UploadFile = File(...),
     current_user: User = Depends(get_current_active_user),
+    folder_id: UUID | None = None,
 ):
     """Upload flows from a file."""
     contents = await file.read()
     data = orjson.loads(contents)
+    response_list = []
     if "flows" in data:
         flow_list = FlowListCreate(**data)
     else:
         flow_list = FlowListCreate(flows=[FlowCreate(**data)])
     # Now we set the user_id for all flows
     for flow in flow_list.flows:
         flow.user_id = current_user.id
+        if folder_id:
+            flow.folder_id = folder_id
+        response = create_flow(session=session, flow=flow, current_user=current_user)
+        response_list.append(response)
 
-    return create_flows(session=session, flow_list=flow_list, current_user=current_user)
+    return response_list
 
 
 @router.get("/download/", response_model=FlowListRead, status_code=200)

src/backend/base/langflow/base/models/model.py

@@ -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 @@ def get_chat_result(
                         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

src/backend/base/langflow/components/embeddings/VertexAIEmbeddings.py

@@ -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 = [
@@ -102,17 +43,23 @@ def build_embeddings(self) -> Embeddings:
                 "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,
             model_name=self.model_name,
             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,

src/backend/base/langflow/components/models/AmazonBedrockModel.py

@@ -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]

src/backend/base/langflow/components/models/AnthropicModel.py

@@ -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",

src/backend/base/langflow/components/models/AzureOpenAIModel.py

@@ -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]