Merge branch 'logspace-ai:dev' into Add-Ollama-LLM

.github/workflows/pre-release.yml

@@ -8,6 +8,7 @@ on:
       - dev
     paths:
       - "pyproject.toml"
+  workflow_dispatch:
 
 env:
   POETRY_VERSION: "1.5.1"
@@ -40,7 +41,7 @@ jobs:
           generateReleaseNotes: true
           prerelease: true
           tag: v${{ steps.check-version.outputs.version }}
-          commit: main
+          commit: dev
       - name: Publish to PyPI
         env:
           POETRY_PYPI_TOKEN_PYPI: ${{ secrets.PYPI_API_TOKEN }}

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "langflow"
-version = "0.6.3a5"
+version = "0.6.3"
 description = "A Python package with a built-in web application"
 authors = ["Logspace <contact@logspace.ai>"]
 maintainers = [

src/backend/langflow/api/v1/chat.py

@@ -1,19 +1,15 @@
 import time
 
-from fastapi import (APIRouter, Depends, HTTPException, Query, WebSocket,
+from fastapi import APIRouter, Depends, HTTPException, Query, WebSocket, WebSocketException, status
-                     WebSocketException, status)
 from fastapi.responses import StreamingResponse
 from langflow.api.utils import build_input_keys_response, format_elapsed_time
-from langflow.api.v1.schemas import (BuildStatus, BuiltResponse, InitResponse,
+from langflow.api.v1.schemas import BuildStatus, BuiltResponse, InitResponse, StreamData
-                                     StreamData)
 from langflow.graph.graph.base import Graph
-from langflow.services.auth.utils import (get_current_active_user,
+from langflow.services.auth.utils import get_current_active_user, get_current_user_by_jwt
-                                          get_current_user_by_jwt)
 from langflow.services.cache.service import BaseCacheService
 from langflow.services.cache.utils import update_build_status
 from langflow.services.chat.service import ChatService
-from langflow.services.deps import (get_cache_service, get_chat_service,
+from langflow.services.deps import get_cache_service, get_chat_service, get_session
-                                    get_session)
 from loguru import logger
 from sqlmodel import Session
 

src/backend/langflow/api/v1/endpoints.py

@@ -1,5 +1,5 @@
 from http import HTTPStatus
-from typing import Annotated, List, Optional, Union
+from typing import Annotated, Any, List, Optional, Union
 
 import sqlalchemy as sa
 from fastapi import APIRouter, Body, Depends, HTTPException, UploadFile, status
@@ -16,7 +16,7 @@ from langflow.api.v1.schemas import (
 )
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.interface.custom.directory_reader import DirectoryReader
-from langflow.interface.custom.utils import build_custom_component_template, create_and_validate_component
+from langflow.interface.custom.utils import build_custom_component_template
 from langflow.processing.process import process_graph_cached, process_tweaks
 from langflow.services.auth.utils import api_key_security, get_current_active_user
 from langflow.services.cache.utils import save_uploaded_file
@@ -49,7 +49,7 @@ async def process_graph_data(
     task_service: "TaskService" = Depends(get_task_service),
     sync: bool = True,
 ):
-    task_result = None
+    task_result: Any = None
     task_status = None
     if tweaks:
         try:
@@ -270,7 +270,7 @@ async def custom_component(
     raw_code: CustomComponentCode,
     user: User = Depends(get_current_active_user),
 ):
-    component = create_and_validate_component(raw_code.code)
+    component = CustomComponent(code=raw_code.code)
 
     built_frontend_node = build_custom_component_template(component, user_id=user.id)
 
@@ -289,7 +289,6 @@ async def reload_custom_component(path: str, user: User = Depends(get_current_ac
             raise ValueError(content)
 
         extractor = CustomComponent(code=content)
-        extractor.validate()
         return build_custom_component_template(extractor, user_id=user.id)
     except Exception as exc:
         raise HTTPException(status_code=400, detail=str(exc))
@@ -300,7 +299,7 @@ async def custom_component_update(
     raw_code: CustomComponentCode,
     user: User = Depends(get_current_active_user),
 ):
-    component = create_and_validate_component(raw_code.code)
+    component = CustomComponent(code=raw_code.code)
 
     component_node = build_custom_component_template(component, user_id=user.id, update_field=raw_code.field)
     # Update the field

src/backend/langflow/components/agents/AgentInitializer.py

@@ -1,7 +1,6 @@
-from typing import Callable, List, Union
+from typing import Callable, List, Optional, Union
 
 from langchain.agents import AgentExecutor, AgentType, initialize_agent, types
-
 from langflow import CustomComponent
 from langflow.field_typing import BaseChatMemory, BaseLanguageModel, Tool
 
@@ -20,12 +19,19 @@ class AgentInitializerComponent(CustomComponent):
             "memory": {"display_name": "Memory"},
             "tools": {"display_name": "Tools"},
             "llm": {"display_name": "Language Model"},
+            "code": {"advanced": True},
         }
 
     def build(
-        self, agent: str, llm: BaseLanguageModel, memory: BaseChatMemory, tools: List[Tool], max_iterations: int
+        self,
+        agent: str,
+        llm: BaseLanguageModel,
+        tools: List[Tool],
+        max_iterations: int,
+        memory: Optional[BaseChatMemory] = None,
     ) -> Union[AgentExecutor, Callable]:
         agent = AgentType(agent)
+        if memory:
             return initialize_agent(
                 tools=tools,
                 llm=llm,
@@ -35,3 +41,12 @@ class AgentInitializerComponent(CustomComponent):
                 handle_parsing_errors=True,
                 max_iterations=max_iterations,
             )
+        else:
+            return initialize_agent(
+                tools=tools,
+                llm=llm,
+                agent=agent,
+                return_intermediate_steps=True,
+                handle_parsing_errors=True,
+                max_iterations=max_iterations,
+            )

src/backend/langflow/components/llms/AzureChatOpenAI.py

@@ -3,6 +3,7 @@ from langflow import CustomComponent
 from langchain.llms.base import BaseLanguageModel
 from langchain.chat_models.azure_openai import AzureChatOpenAI
 
+
 class AzureChatOpenAIComponent(CustomComponent):
     display_name: str = "AzureChatOpenAI"
     description: str = "LLM model from Azure OpenAI."
@@ -28,7 +29,7 @@ class AzureChatOpenAIComponent(CustomComponent):
             "azure_endpoint": {
                 "display_name": "Azure Endpoint",
                 "required": True,
-                "info": "Your Azure endpoint, including the resource.. Example: `https://example-resource.azure.openai.com/`"
+                "info": "Your Azure endpoint, including the resource.. Example: `https://example-resource.azure.openai.com/`",
             },
             "azure_deployment": {
                 "display_name": "Deployment Name",
@@ -40,11 +41,7 @@ class AzureChatOpenAIComponent(CustomComponent):
                 "required": True,
                 "advanced": True,
             },
-            "api_key": {
+            "api_key": {"display_name": "API Key", "required": True, "password": True},
-                "display_name": "API Key",
-                "required": True,
-                "password": True
-            },
             "temperature": {
                 "display_name": "Temperature",
                 "value": 0.7,
@@ -71,8 +68,6 @@ class AzureChatOpenAIComponent(CustomComponent):
         temperature: float = 0.7,
         max_tokens: Optional[int] = 1000,
     ) -> BaseLanguageModel:
-
-
         return AzureChatOpenAI(
             model=model,
             azure_endpoint=azure_endpoint,
@@ -80,5 +75,5 @@ class AzureChatOpenAIComponent(CustomComponent):
             api_version=api_version,
             api_key=api_key,
             temperature=temperature,
-            max_tokens=max_tokens
+            max_tokens=max_tokens,
         )

src/backend/langflow/components/vectorstores/Weaviate.py

@@ -12,18 +12,29 @@ from langchain.embeddings.base import Embeddings
 class WeaviateVectorStore(CustomComponent):
     display_name: str = "Weaviate"
     description: str = "Implementation of Vector Store using Weaviate"
-    documentation = (
+    documentation = "https://python.langchain.com/docs/integrations/vectorstores/weaviate"
-        "https://python.langchain.com/docs/integrations/vectorstores/weaviate"
-    )
     beta = True
     field_config = {
         "url": {"display_name": "Weaviate URL", "value": "http://localhost:8080"},
-        "api_key": { "display_name": "API Key", "password": True,"required": False, },
+        "api_key": {
-        "index_name": {"display_name": "Index name","required": False,},
+            "display_name": "API Key",
-        "text_key": {"display_name": "Text Key","required": False,  "advanced": True, "value": "text"},
+            "password": True,
+            "required": False,
+        },
+        "index_name": {
+            "display_name": "Index name",
+            "required": False,
+        },
+        "text_key": {"display_name": "Text Key", "required": False, "advanced": True, "value": "text"},
         "documents": {"display_name": "Documents", "is_list": True},
         "embedding": {"display_name": "Embedding"},
-        "attributes": {"display_name": "Attributes", "required": False, "is_list": True, "field_type": "str", "advanced": True},
+        "attributes": {
+            "display_name": "Attributes",
+            "required": False,
+            "is_list": True,
+            "field_type": "str",
+            "advanced": True,
+        },
         "search_by_text": {"display_name": "Search By Text", "field_type": "bool", "advanced": True},
         "code": {"show": False},
     }

src/backend/langflow/interface/agents/custom.py

@@ -1,6 +1,6 @@
-from typing import Any, List, Optional
+from typing import Any, Optional
 
-from langchain.agents import AgentExecutor, AgentType, Tool, ZeroShotAgent, initialize_agent
+from langchain.agents import AgentExecutor, ZeroShotAgent
 from langchain.agents.agent_toolkits import (
     SQLDatabaseToolkit,
     VectorStoreInfo,
@@ -15,7 +15,6 @@ from langchain.agents.agent_toolkits.vectorstore.prompt import ROUTER_PREFIX as
 from langchain.agents.mrkl.prompt import FORMAT_INSTRUCTIONS
 from langchain.base_language import BaseLanguageModel
 from langchain.chains.llm import LLMChain
-from langchain.memory.chat_memory import BaseChatMemory
 from langchain.sql_database import SQLDatabase
 from langchain.tools.sql_database.prompt import QUERY_CHECKER
 from langchain_experimental.agents.agent_toolkits.pandas.prompt import PREFIX as PANDAS_PREFIX

src/backend/langflow/interface/custom/code_parser/code_parser.py

@@ -6,8 +6,7 @@ from typing import Any, Dict, List, Type, Union
 
 from cachetools import TTLCache, cachedmethod, keys
 from fastapi import HTTPException
-from langflow.interface.custom.schema import (CallableCodeDetails,
+from langflow.interface.custom.schema import CallableCodeDetails, ClassCodeDetails
-                                              ClassCodeDetails)
 
 
 class CodeSyntaxError(HTTPException):

src/backend/langflow/interface/custom/custom_component/custom_component.py

@@ -5,10 +5,11 @@ from uuid import UUID
 import yaml
 from cachetools import TTLCache, cachedmethod
 from fastapi import HTTPException
+
 from langflow.interface.custom.code_parser.utils import (
     extract_inner_type_from_generic_alias,
-    extract_union_types_from_generic_alias)
+    extract_union_types_from_generic_alias,
-from langflow.interface.custom.directory_reader import DirectoryReader
+)
 from langflow.services.database.models.flow import Flow
 from langflow.services.database.utils import session_getter
 from langflow.services.deps import get_credential_service, get_db_service
@@ -46,34 +47,6 @@ class CustomComponent(Component):
     def build_config(self):
         return self.field_config
 
-    def _class_template_validation(self, code: str):
-        TYPE_HINT_LIST = ["Optional", "Prompt", "PromptTemplate", "LLMChain"]
-
-        if not code:
-            raise HTTPException(
-                status_code=400,
-                detail={
-                    "error": self.ERROR_CODE_NULL,
-                    "traceback": "",
-                },
-            )
-
-        reader = DirectoryReader("", False)
-
-        for type_hint in TYPE_HINT_LIST:
-            if reader._is_type_hint_used_in_args(type_hint, code) and not reader._is_type_hint_imported(
-                type_hint, code
-            ):
-                error_detail = {
-                    "error": "Type hint Error",
-                    "traceback": f"Type hint '{type_hint}' is used but not imported in the code.",
-                }
-                raise HTTPException(status_code=400, detail=error_detail)
-        return True
-
-    def validate(self) -> bool:
-        return self._class_template_validation(self.code) if self.code else False
-
     @property
     def tree(self):
         return self.get_code_tree(self.code or "")
@@ -206,8 +179,7 @@ class CustomComponent(Component):
         return validate.create_function(self.code, self.function_entrypoint_name)
 
     async def load_flow(self, flow_id: str, tweaks: Optional[dict] = None) -> Any:
-        from langflow.processing.process import (build_sorted_vertices,
+        from langflow.processing.process import build_sorted_vertices, process_tweaks
-                                                 process_tweaks)
 
         db_service = get_db_service()
         with session_getter(db_service) as session:

src/backend/langflow/interface/custom/directory_reader/directory_reader.py

@@ -65,12 +65,13 @@ class DirectoryReader:
 
     def filter_loaded_components(self, data: dict, with_errors: bool) -> dict:
         from langflow.interface.custom.utils import build_component
+
         items = [
             {
                 "name": menu["name"],
                 "path": menu["path"],
                 "components": [
-                    (*build_component(component),component)
+                    (*build_component(component), component)
                     for component in menu["components"]
                     if (component["error"] if with_errors else not component["error"])
                 ],

src/backend/langflow/interface/custom/directory_reader/utils.py

@@ -1,6 +1,5 @@
 from langflow.interface.custom.directory_reader import DirectoryReader
-from langflow.template.frontend_node.custom_components import \
+from langflow.template.frontend_node.custom_components import CustomComponentFrontendNode
-    CustomComponentFrontendNode
 from loguru import logger
 
 
@@ -79,7 +78,6 @@ def create_invalid_component_template(component, component_name):
         display_name=f"ERROR - {component_name}",
     )
 
-
     component_frontend_node.error = component.get("error", None)
     field = component_frontend_node.template.get_field("code")
     field.value = component_code

src/backend/langflow/interface/custom/utils.py

@@ -7,18 +7,20 @@ from typing import Any, Dict, List, Optional, Union
 from uuid import UUID
 
 from fastapi import HTTPException
+from loguru import logger
+
 from langflow.field_typing.range_spec import RangeSpec
 from langflow.interface.custom.code_parser.utils import extract_inner_type
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.interface.custom.directory_reader.utils import (
-    build_custom_component_list_from_path, determine_component_name,
+    build_custom_component_list_from_path,
-    merge_nested_dicts_with_renaming)
+    determine_component_name,
+    merge_nested_dicts_with_renaming,
+)
 from langflow.interface.importing.utils import eval_custom_component_code
 from langflow.template.field.base import TemplateField
-from langflow.template.frontend_node.custom_components import \
+from langflow.template.frontend_node.custom_components import CustomComponentFrontendNode
-    CustomComponentFrontendNode
 from langflow.utils.util import get_base_classes
-from loguru import logger
 
 
 def add_output_types(frontend_node: CustomComponentFrontendNode, return_types: List[str]):
@@ -174,9 +176,7 @@ def get_field_dict(field: Union[TemplateField, dict]):
     return field
 
 
-def run_build_config(
+def run_build_config(custom_component: CustomComponent, user_id: Optional[Union[str, UUID]] = None, update_field=None):
-    custom_component: CustomComponent, user_id: Optional[Union[str, UUID]] = None, update_field=None
-):
     """Build the field configuration for a custom component"""
 
     try:
@@ -311,7 +311,6 @@ def create_component_template(component):
     component_output_types = component["output_types"]
 
     component_extractor = CustomComponent(code=component_code)
-    component_extractor.validate()
 
     component_template = build_custom_component_template(component_extractor)
     component_template["output_types"] = component_output_types
@@ -343,12 +342,6 @@ def build_custom_components(settings_service):
     return custom_components_from_file
 
 
-def create_and_validate_component(code: str) -> CustomComponent:
-    component = CustomComponent(code=code)
-    component.validate()
-    return component
-
-
 def update_field_dict(field_dict):
     """Update the field dictionary by calling options() or value() if they are callable"""
     if "options" in field_dict and callable(field_dict["options"]):
@@ -378,6 +371,3 @@ def build_component(component):
     component_name = determine_component_name(component)
     component_template = create_component_template(component)
     return component_name, component_template
-
-
-

src/backend/langflow/interface/types.py

@@ -1,9 +1,7 @@
-
 from cachetools import LRUCache, cached
 from langflow.interface.agents.base import agent_creator
 from langflow.interface.chains.base import chain_creator
-from langflow.interface.custom.directory_reader.utils import \
+from langflow.interface.custom.directory_reader.utils import merge_nested_dicts_with_renaming
-    merge_nested_dicts_with_renaming
 from langflow.interface.custom.utils import build_custom_components
 from langflow.interface.document_loaders.base import documentloader_creator
 from langflow.interface.embeddings.base import embedding_creator
@@ -70,5 +68,3 @@ def get_all_types_dict(settings_service):
     native_components = build_langchain_types_dict()
     custom_components_from_file = build_custom_components(settings_service)
     return merge_nested_dicts_with_renaming(native_components, custom_components_from_file)
-
-

src/backend/langflow/processing/process.py

@@ -5,6 +5,7 @@ from langchain.agents import AgentExecutor
 from langchain.chains.base import Chain
 from langchain.schema import AgentAction, Document
 from langchain.vectorstores.base import VectorStore
+from langchain_core.messages import AIMessage
 from langchain_core.runnables.base import Runnable
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.interface.run import build_sorted_vertices, get_memory_key, update_memory_keys
@@ -105,10 +106,23 @@ def get_build_result(data_graph, session_id):
     return build_sorted_vertices(data_graph)
 
 
-def process_inputs(inputs: Optional[dict], artifacts: Dict[str, Any]) -> dict:
+def process_inputs(
+    inputs: Optional[Union[dict, List[dict]]] = None, artifacts: Optional[Dict[str, Any]] = None
+) -> Union[dict, List[dict]]:
     if inputs is None:
         inputs = {}
+    if artifacts is None:
+        artifacts = {}
 
+    if isinstance(inputs, dict):
+        inputs = update_inputs_dict(inputs, artifacts)
+    elif isinstance(inputs, List):
+        inputs = [update_inputs_dict(inp, artifacts) for inp in inputs]
+
+    return inputs
+
+
+def update_inputs_dict(inputs: dict, artifacts: Dict[str, Any]) -> dict:
     for key, value in artifacts.items():
         if key == "repr":
             continue
@@ -125,6 +139,11 @@ async def process_runnable(runnable: Runnable, inputs: Union[dict, List[dict]]):
         result = await runnable.ainvoke(inputs)
     else:
         raise ValueError(f"Runnable {runnable} does not support inputs of type {type(inputs)}")
+    # Check if the result is a list of AIMessages
+    if isinstance(result, list) and all(isinstance(r, AIMessage) for r in result):
+        result = [r.content for r in result]
+    elif isinstance(result, AIMessage):
+        result = result.content
     return result
 
 

src/backend/langflow/utils/validate.py

@@ -2,7 +2,7 @@ import ast
 import contextlib
 import importlib
 from types import FunctionType
-from typing import Dict
+from typing import Dict, List, Optional, Union
 
 from langflow.field_typing.constants import CUSTOM_COMPONENT_SUPPORTED_TYPES
 
@@ -260,14 +260,13 @@ def get_default_imports(code_string):
     """
     Returns a dictionary of default imports for the dynamic class constructor.
     """
-    typing_module = importlib.import_module("typing")
-    default_imports = {
-        "Optional": typing_module.Optional,
-        "List": typing_module.List,
-        "Dict": typing_module.Dict,
-        "Union": typing_module.Union,
-    }
 
+    default_imports = {
+        "Optional": Optional,
+        "List": List,
+        "Dict": Dict,
+        "Union": Union,
+    }
     langflow_imports = list(CUSTOM_COMPONENT_SUPPORTED_TYPES.keys())
     necessary_imports = find_names_in_code(code_string, langflow_imports)
     langflow_module = importlib.import_module("langflow.field_typing")

src/backend/langflow/worker.py

@@ -1,14 +1,13 @@
-from typing import TYPE_CHECKING, Any, Dict, Optional
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Union
 
 from asgiref.sync import async_to_sync
 from celery.exceptions import SoftTimeLimitExceeded  # type: ignore
-from loguru import logger
-from rich import print
-
 from langflow.core.celery_app import celery_app
 from langflow.processing.process import Result, generate_result, process_inputs
 from langflow.services.deps import get_session_service
 from langflow.services.manager import initialize_session_service
+from loguru import logger
+from rich import print
 
 if TYPE_CHECKING:
     from langflow.graph.vertex.base import Vertex
@@ -35,7 +34,7 @@ def build_vertex(self, vertex: "Vertex") -> "Vertex":
 @celery_app.task(acks_late=True)
 def process_graph_cached_task(
     data_graph: Dict[str, Any],
-    inputs: Optional[dict] = None,
+    inputs: Optional[Union[dict, List[dict]]] = None,
     clear_cache=False,
     session_id=None,
 ) -> Dict[str, Any]:

src/frontend/src/pages/FlowPage/components/extraSidebarComponent/index.tsx

@@ -231,7 +231,7 @@ export default function ExtraSidebar(): JSX.Element {
   return (
     <div className="side-bar-arrangement">
       <div className="side-bar-buttons-arrangement">
-        {hasStore && (
+        {hasStore && validApiKey && (
           <ShadTooltip
             content={
               !hasApiKey || !validApiKey
@@ -263,7 +263,7 @@ export default function ExtraSidebar(): JSX.Element {
             </button>
           </ShadTooltip>
         </div>
-        {!hasStore && ExportMemo}
+        {(!hasApiKey || !validApiKey) && ExportMemo}
         <ShadTooltip content={"Code"} side="top">
           <div className="side-bar-button">
             {flow && flow.data && (

src/frontend/src/utils/styleUtils.ts

@@ -129,12 +129,12 @@ import { NotionIcon } from "../icons/Notion";
 import { OpenAiIcon } from "../icons/OpenAi";
 import { PineconeIcon } from "../icons/Pinecone";
 import { QDrantIcon } from "../icons/QDrant";
-import { WeaviateIcon } from "../icons/Weaviate";
 import { SearxIcon } from "../icons/Searx";
 import { ShareIcon } from "../icons/Share";
 import { Share2Icon } from "../icons/Share2";
 import SvgSlackIcon from "../icons/Slack/SlackIcon";
 import { VertexAIIcon } from "../icons/VertexAI";
+import { WeaviateIcon } from "../icons/Weaviate";
 import SvgWikipedia from "../icons/Wikipedia/Wikipedia";
 import SvgWolfram from "../icons/Wolfram/Wolfram";
 import { HackerNewsIcon } from "../icons/hackerNews";

tests/test_custom_component.py

@@ -3,14 +3,10 @@ import types
 from uuid import uuid4
 
 import pytest
-from fastapi import HTTPException
 from langflow.interface.custom.base import CustomComponent
-from langflow.interface.custom.code_parser.code_parser import (CodeParser,
+from langflow.interface.custom.code_parser.code_parser import CodeParser, CodeSyntaxError
-                                                               CodeSyntaxError)
+from langflow.interface.custom.custom_component.component import Component, ComponentCodeNullError
-from langflow.interface.custom.custom_component.component import (
+from langflow.interface.custom.utils import build_custom_component_template
-    Component, ComponentCodeNullError)
-from langflow.interface.custom.utils import (build_custom_component_template,
-                                             create_and_validate_component)
 from langflow.services.database.models.flow import Flow, FlowCreate
 
 code_default = """
@@ -368,16 +364,6 @@ def test_component_get_code_tree_syntax_error():
         component.get_code_tree(component.code)
 
 
-def test_custom_component_class_template_validation_no_code():
-    """
-    Test the _class_template_validation method of the CustomComponent class
-    raises the HTTPException when the code is None.
-    """
-    custom_component = CustomComponent(code=None, function_entrypoint_name="build")
-    with pytest.raises(HTTPException):
-        custom_component._class_template_validation(custom_component.code)
-
-
 def test_custom_component_get_code_tree_syntax_error():
     """
     Test the get_code_tree method of the CustomComponent class
@@ -535,12 +521,12 @@ def test_build_config_field_value_keys(component):
 
 
 def test_create_and_validate_component_valid_code(test_component_code):
-    component = create_and_validate_component(test_component_code)
+    component = CustomComponent(code=test_component_code)
     assert isinstance(component, CustomComponent)
 
 
 def test_build_langchain_template_custom_component_valid_code(test_component_code):
-    component = create_and_validate_component(test_component_code)
+    component = CustomComponent(code=test_component_code)
     frontend_node = build_custom_component_template(component)
     assert isinstance(frontend_node, dict)
     template = frontend_node["template"]
@@ -554,7 +540,7 @@ def test_build_langchain_template_custom_component_valid_code(test_component_cod
 
 
 def test_build_langchain_template_custom_component_templatefield(test_component_with_templatefield_code):
-    component = create_and_validate_component(test_component_with_templatefield_code)
+    component = CustomComponent(code=test_component_with_templatefield_code)
     frontend_node = build_custom_component_template(component)
     assert isinstance(frontend_node, dict)
     template = frontend_node["template"]