merge fix

src/backend/base/langflow/alembic/versions/006b3990db50_add_unique_constraints.py

@@ -26,13 +26,13 @@ def upgrade() -> None:
     flow_constraints = inspector.get_unique_constraints("flow")
     user_constraints = inspector.get_unique_constraints("user")
     try:
-        if not any(constraint["name"] == "uq_apikey_id" for constraint in api_key_constraints):
+        if not any(constraint["column_names"] == ["id"] for constraint in api_key_constraints):
             with op.batch_alter_table("apikey", schema=None) as batch_op:
                 batch_op.create_unique_constraint("uq_apikey_id", ["id"])
-        if not any(constraint["name"] == "uq_flow_id" for constraint in flow_constraints):
+        if not any(constraint["column_names"] == ["id"] for constraint in flow_constraints):
             with op.batch_alter_table("flow", schema=None) as batch_op:
                 batch_op.create_unique_constraint("uq_flow_id", ["id"])
-        if not any(constraint["name"] == "uq_user_id" for constraint in user_constraints):
+        if not any(constraint["column_names"] == ["id"] for constraint in user_constraints):
             with op.batch_alter_table("user", schema=None) as batch_op:
                 batch_op.create_unique_constraint("uq_user_id", ["id"])
     except Exception as e:

src/backend/base/langflow/base/io/chat.py

@@ -2,6 +2,7 @@ import warnings
 from typing import Optional, Union
 
 from langflow.field_typing import Text
+from langflow.helpers.record import records_to_text
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.memory import add_messages
 from langflow.schema import Record
@@ -21,6 +22,7 @@ class ChatComponent(CustomComponent):
             "sender": {
                 "options": ["Machine", "User"],
                 "display_name": "Sender Type",
+                "advanced": True,
             },
             "sender_name": {"display_name": "Sender Name"},
             "session_id": {
@@ -31,6 +33,13 @@ class ChatComponent(CustomComponent):
             "return_record": {
                 "display_name": "Return Record",
                 "info": "Return the message as a record containing the sender, sender_name, and session_id.",
+                "advanced": True,
+            },
+            "record_template": {
+                "display_name": "Record Template",
+                "multiline": True,
+                "info": "In case of Message being a Record, this template will be used to convert it to text.",
+                "advanced": True,
             },
         }
 
@@ -74,9 +83,10 @@ class ChatComponent(CustomComponent):
         self,
         sender: Optional[str] = "User",
         sender_name: Optional[str] = "User",
-        input_value: Optional[str] = None,
+        input_value: Optional[Union[str, Record]] = None,
         session_id: Optional[str] = None,
         return_record: Optional[bool] = False,
+        record_template: Optional[str] = "Text: {text}\nData: {data}",
     ) -> Union[Text, Record]:
         input_value_record: Optional[Record] = None
         if return_record:
@@ -94,6 +104,8 @@ class ChatComponent(CustomComponent):
                         "session_id": session_id,
                     },
                 )
+        elif isinstance(input_value, Record):
+            input_value = records_to_text(template=record_template, records=input_value)
         if not input_value:
             input_value = ""
         if return_record and input_value_record:

src/backend/base/langflow/base/io/text.py

@@ -1,18 +1,28 @@
-from typing import Optional
+from typing import Optional, Union
 
 from langflow.field_typing import Text
+from langflow.helpers.record import records_to_text
 from langflow.interface.custom.custom_component import CustomComponent
+from langflow.schema.schema import Record
 
 
 class TextComponent(CustomComponent):
     display_name = "Text Component"
     description = "Used to pass text to the next component."
 
-    field_config = {
-        "input_value": {"display_name": "Value", "multiline": True},
-    }
+    def build_config(self):
+        return {
+            "input_value": {"display_name": "Value", "input_types": ["Record"], "info": "Text or Record to be passed."},
+            "record_template": {"display_name": "Record Template", "multiline": True},
+        }
 
-    def build(self, input_value: Optional[str] = "") -> Text:
+    def build(
+        self,
+        input_value: Optional[Union[Text, Record]] = "",
+        record_template: Optional[str] = "Text: {text}\nData: {data}",
+    ) -> Text:
+        if isinstance(input_value, Record):
+            input_value = records_to_text(template=record_template, records=input_value)
         self.status = input_value
         if not input_value:
             input_value = ""

src/backend/base/langflow/components/__init__.py

@@ -1,18 +1,17 @@
 __all__ = [
     "agents",
     "chains",
-    "data",
     "documentloaders",
     "embeddings",
     "experimental",
-    "helpers",
     "inputs",
     "memories",
     "model_specs",
-    "models",
     "outputs",
     "retrievers",
     "textsplitters",
     "toolkits",
+    "tools",
+    "vectorsearch",
     "vectorstores",
 ]

src/backend/base/langflow/components/agents/__init__.py

@@ -5,6 +5,7 @@ from .OpenAIConversationalAgent import ConversationalAgent
 from .SQLAgent import SQLAgentComponent
 from .VectorStoreAgent import VectorStoreAgentComponent
 from .VectorStoreRouterAgent import VectorStoreRouterAgentComponent
+from .XMLAgent import XMLAgentComponent
 
 __all__ = [
     "AgentInitializerComponent",
@@ -14,4 +15,5 @@ __all__ = [
     "SQLAgentComponent",
     "VectorStoreAgentComponent",
     "VectorStoreRouterAgentComponent",
+    "XMLAgentComponent",
 ]

src/backend/base/langflow/components/data/APIRequest.py

@@ -10,11 +10,11 @@ from langflow.schema import Record
 
 class APIRequest(CustomComponent):
     display_name: str = "API Request"
-    description: str = "Make an HTTP request to the given URL."
+    description: str = "Make HTTP requests given one or more URLs."
     output_types: list[str] = ["Record"]
     documentation: str = "https://docs.langflow.org/components/utilities#api-request"
     field_config = {
-        "urls": {"display_name": "URLs", "info": "The URLs to make the request to."},
+        "urls": {"display_name": "URLs", "info": "URLs to make requests to."},
         "method": {
             "display_name": "Method",
             "info": "The HTTP method to use.",

src/backend/base/langflow/components/data/Directory.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class DirectoryComponent(CustomComponent):
     display_name = "Directory"
-    description = "Load Text Files from a Directory and Convert Them to Records."
+    description = "Recursively load files from a directory."
 
     def build_config(self) -> Dict[str, Any]:
         return {

src/backend/base/langflow/components/data/File.py

@@ -1,4 +1,5 @@
-from typing import Any, Dict, List
+from pathlib import Path
+from typing import Any, Dict
 
 from langflow.base.data.utils import TEXT_FILE_TYPES, parse_text_file_to_record
 from langflow.interface.custom.custom_component import CustomComponent
@@ -7,12 +8,12 @@ from langflow.schema import Record
 
 class FileComponent(CustomComponent):
     display_name = "Files"
-    description = "Read Text Files"
+    description = "A generic file loader."
 
     def build_config(self) -> Dict[str, Any]:
         return {
-            "paths": {
-                "display_name": "Paths",
+            "path": {
+                "display_name": "Path",
                 "field_type": "file",
                 "file_types": TEXT_FILE_TYPES,
                 "info": f"Supported file types: {', '.join(TEXT_FILE_TYPES)}",
@@ -26,7 +27,8 @@ class FileComponent(CustomComponent):
 
     def load_file(self, path: str, silent_errors: bool = False) -> Record:
         resolved_path = self.resolve_path(path)
-        extension = resolved_path.split(".")[-1]
+        path_obj = Path(resolved_path)
+        extension = path_obj.suffix[1:].lower()
         if extension == "doc":
             raise ValueError("doc files are not supported. Please save as .docx")
         if extension not in TEXT_FILE_TYPES:
@@ -37,9 +39,9 @@ class FileComponent(CustomComponent):
 
     def build(
         self,
-        paths: List[str],
+        path: str,
         silent_errors: bool = False,
-    ) -> List[Record]:
-        records = [self.load_file(path, silent_errors) for path in paths]
-        self.status = records
-        return records
+    ) -> Record:
+        record = self.load_file(path, silent_errors)
+        self.status = record
+        return record

src/backend/base/langflow/components/data/FileLoader.py

@@ -1,117 +0,0 @@
-from typing import List
-
-from langflow.interface.custom.custom_component import CustomComponent
-from langflow.schema import Record
-from langflow.utils.constants import LOADERS_INFO
-
-
-class FileLoaderComponent(CustomComponent):
-    display_name: str = "File Loader"
-    description: str = "Generic File Loader"
-
-    def build_config(self):
-        loader_options = ["Automatic"] + [loader_info["name"] for loader_info in LOADERS_INFO]
-
-        file_types = []
-        suffixes = []
-
-        for loader_info in LOADERS_INFO:
-            if "allowedTypes" in loader_info:
-                file_types.extend(loader_info["allowedTypes"])
-                suffixes.extend([f".{ext}" for ext in loader_info["allowedTypes"]])
-
-        return {
-            "file_path": {
-                "display_name": "File Path",
-                "required": True,
-                "field_type": "file",
-                "file_types": [
-                    "json",
-                    "txt",
-                    "csv",
-                    "jsonl",
-                    "html",
-                    "htm",
-                    "conllu",
-                    "enex",
-                    "msg",
-                    "pdf",
-                    "srt",
-                    "eml",
-                    "md",
-                    "mdx",
-                    "pptx",
-                    "docx",
-                ],
-                "suffixes": [
-                    ".json",
-                    ".txt",
-                    ".csv",
-                    ".jsonl",
-                    ".html",
-                    ".htm",
-                    ".conllu",
-                    ".enex",
-                    ".msg",
-                    ".pdf",
-                    ".srt",
-                    ".eml",
-                    ".md",
-                    ".mdx",
-                    ".pptx",
-                    ".docx",
-                ],
-                # "file_types" : file_types,
-                # "suffixes": suffixes,
-            },
-            "loader": {
-                "display_name": "Loader",
-                "is_list": True,
-                "required": True,
-                "options": loader_options,
-                "value": "Automatic",
-            },
-            "code": {"show": False},
-        }
-
-    def build(self, file_path: str, loader: str) -> List[Record]:
-        file_type = file_path.split(".")[-1]
-
-        # Map the loader to the correct loader class
-        selected_loader_info = None
-        for loader_info in LOADERS_INFO:
-            if loader_info["name"] == loader:
-                selected_loader_info = loader_info
-                break
-
-        if selected_loader_info is None and loader != "Automatic":
-            raise ValueError(f"Loader {loader} not found in the loader info list")
-
-        if loader == "Automatic":
-            # Determine the loader based on the file type
-            default_loader_info = None
-            for info in LOADERS_INFO:
-                if "defaultFor" in info and file_type in info["defaultFor"]:
-                    default_loader_info = info
-                    break
-
-            if default_loader_info is None:
-                raise ValueError(f"No default loader found for file type: {file_type}")
-
-            selected_loader_info = default_loader_info
-        if isinstance(selected_loader_info, dict):
-            loader_import: str = selected_loader_info["import"]
-        else:
-            raise ValueError(f"Loader info for {loader} is not a dict\nLoader info:\n{selected_loader_info}")
-        module_name, class_name = loader_import.rsplit(".", 1)
-
-        try:
-            # Import the loader class
-            loader_module = __import__(module_name, fromlist=[class_name])
-            loader_instance = getattr(loader_module, class_name)
-        except ImportError as e:
-            raise ValueError(f"Loader {loader} could not be imported\nLoader info:\n{selected_loader_info}") from e
-
-        result = loader_instance(file_path=file_path)
-        docs = result.load()
-        return self.to_records(docs)

src/backend/base/langflow/components/data/URL.py

@@ -8,7 +8,7 @@ from langflow.schema import Record
 
 class URLComponent(CustomComponent):
     display_name = "URL"
-    description = "Load URLs and convert them to records."
+    description = "Fetch text content given one or more URLs."
 
     def build_config(self) -> Dict[str, Any]:
         return {
@@ -22,4 +22,5 @@ class URLComponent(CustomComponent):
         loader = WebBaseLoader(web_paths=urls)
         docs = loader.load()
         records = self.to_records(docs)
+        self.status = records
         return records

src/backend/base/langflow/components/data/__init__.py

@@ -1,7 +1,7 @@
 from .APIRequest import APIRequest
 from .Directory import DirectoryComponent
 from .File import FileComponent
-from .FileLoader import FileLoaderComponent
+
 from .URL import URLComponent
 
-__all__ = ["APIRequest", "DirectoryComponent", "FileComponent", "FileLoaderComponent", "URLComponent"]
+__all__ = ["APIRequest", "DirectoryComponent", "FileComponent", "URLComponent"]

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

@@ -2,7 +2,7 @@ from typing import Optional
 
 from langchain_community.embeddings.cohere import CohereEmbeddings
 
-from langflow.interface.custom.custom_component import CustomComponent
+from langflow.custom import CustomComponent
 
 
 class CohereEmbeddingsComponent(CustomComponent):

src/backend/base/langflow/components/experimental/__init__.py

@@ -1,23 +1,27 @@
 from .ClearMessageHistory import ClearMessageHistoryComponent
 from .ExtractDataFromRecord import ExtractKeyFromRecordComponent
-from .Listen import ListenComponent
+from .FlowTool import FlowToolComponent
 from .ListFlows import ListFlowsComponent
+from .Listen import ListenComponent
 from .MergeRecords import MergeRecordsComponent
 from .Notify import NotifyComponent
+from .PythonFunction import PythonFunctionComponent
 from .RunFlow import RunFlowComponent
 from .RunnableExecutor import RunnableExecComponent
 from .SQLExecutor import SQLExecutorComponent
+from .SubFlow import SubFlowComponent
 
 __all__ = [
     "ClearMessageHistoryComponent",
     "ExtractKeyFromRecordComponent",
-    "ListenComponent",
+    "FlowToolComponent",
     "ListFlowsComponent",
+    "ListenComponent",
     "MergeRecordsComponent",
-    "MessageHistoryComponent",
     "NotifyComponent",
+    "PythonFunctionComponent",
     "RunFlowComponent",
     "RunnableExecComponent",
     "SQLExecutorComponent",
-    "TextToRecordComponent",
+    "SubFlowComponent",
 ]

src/backend/base/langflow/components/helpers/CreateRecord.py

@@ -2,16 +2,16 @@ from langflow.interface.custom.custom_component import CustomComponent
 from langflow.schema import Record
 
 
-class TextToRecordComponent(CustomComponent):
-    display_name = "Text to Record"
-    description = "A component to create a record from Text."
+class CreateRecordComponent(CustomComponent):
+    display_name = "Create Record"
+    description = "A component to create a record."
     beta: bool = True
 
     def build_config(self):
         return {
             "data": {
                 "display_name": "Data",
-                "info": "The data to convert to a record.",
+                "info": "Data to contruct the record.",
                 "input_types": ["Text"],
             }
         }

src/backend/base/langflow/components/helpers/DocumentToRecord.py

@@ -7,8 +7,8 @@ from langflow.schema import Record
 
 
 class DocumentToRecordComponent(CustomComponent):
-    display_name = "Documents to Records"
-    description = "Convert documents to records."
+    display_name = "Documents To Records"
+    description = "Convert LangChain Documents into Records."
 
     field_config = {
         "documents": {"display_name": "Documents"},

src/backend/base/langflow/components/helpers/IDGenerator.py

@@ -6,7 +6,7 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 class UUIDGeneratorComponent(CustomComponent):
     documentation: str = "http://docs.langflow.org/components/custom"
-    display_name = "Unique ID Generator"
+    display_name = "ID Generator"
     description = "Generates a unique ID."
 
     def update_build_config(

src/backend/base/langflow/components/helpers/MessageHistory.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class MessageHistoryComponent(CustomComponent):
     display_name = "Message History"
-    description = "Used to retrieve stored messages."
+    description = "Used to retrieve stored chat messages."
     beta: bool = True
 
     def build_config(self):
@@ -30,7 +30,7 @@ class MessageHistoryComponent(CustomComponent):
 
     def build(
         self,
-        sender: Optional[str] = None,
+        sender: Optional[str] = "Machine",
         sender_name: Optional[str] = None,
         session_id: Optional[str] = None,
         n_messages: int = 5,

src/backend/base/langflow/components/helpers/RecordsToText.py

@@ -4,9 +4,9 @@ from langflow.interface.custom.custom_component import CustomComponent
 from langflow.schema import Record
 
 
-class RecordsAsTextComponent(CustomComponent):
-    display_name = "Records to Text"
-    description = "Converts Records into single piece of text using a template."
+class RecordsToTextComponent(CustomComponent):
+    display_name = "Records To Text"
+    description = "Convert Records into plain text using a pre-defined template."
 
     def build_config(self):
         return {

src/backend/base/langflow/components/helpers/UpdateRecord.py

@@ -4,7 +4,7 @@ from langflow.schema import Record
 
 class UpdateRecordComponent(CustomComponent):
     display_name = "Update Record"
-    description = "Updates a record with new data."
+    description = "Updates a Record with new data. Akin to a Python dictionary update."
 
     def build_config(self):
         return {

src/backend/base/langflow/components/helpers/__init__.py

@@ -2,8 +2,6 @@ from .CustomComponent import Component
 from .DocumentToRecord import DocumentToRecordComponent
 from .IDGenerator import UUIDGeneratorComponent
 from .MessageHistory import MessageHistoryComponent
-from .PythonFunction import PythonFunctionComponent
-from .RecordsAsText import RecordsAsTextComponent
 from .TextToRecord import TextToRecordComponent
 from .UpdateRecord import UpdateRecordComponent
 
@@ -13,7 +11,7 @@ __all__ = [
     "DocumentToRecordComponent",
     "UUIDGeneratorComponent",
     "PythonFunctionComponent",
-    "RecordsAsTextComponent",
+    "RecordsToTextComponent",
     "TextToRecordComponent",
     "MessageHistoryComponent",
 ]

src/backend/base/langflow/components/inputs/ChatInput.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class ChatInput(ChatComponent):
     display_name = "Chat Input"
-    description = "Used to get user input from the chat."
+    description = "Capture user inputs from the chat interface."
     icon = "ChatInput"
 
     def build(

src/backend/base/langflow/components/inputs/JSONInput.py

@@ -1,30 +0,0 @@
-import ast
-import json
-
-from langflow.custom import CustomComponent
-from langflow.schema import Record
-
-
-class JSONInputComponent(CustomComponent):
-    display_name = "JSON Input"
-    description = "Load a JSON object as input."
-
-    def build_config(self):
-        return {
-            "json_str": {
-                "display_name": "JSON String",
-                "multiline": True,
-                "info": "The JSON string to load.",
-            }
-        }
-
-    def build(self, json_str: str) -> Record:
-        try:
-            data = json.loads(json_str)
-        except json.JSONDecodeError:
-            try:
-                data = ast.literal_eval(json_str)
-            except (SyntaxError, ValueError):
-                raise ValueError("Invalid JSON string.")
-        record = Record(data=data)
-        return record

src/backend/base/langflow/components/inputs/Prompt.py

@@ -6,7 +6,7 @@ from langflow.interface.custom.custom_component import CustomComponent
 
 class PromptComponent(CustomComponent):
     display_name: str = "Prompt"
-    description: str = "A component for creating prompts using templates"
+    description: str = "A component for creating prompt templates using dynamic variables."
     icon = "terminal-square"
 
     def build_config(self):

src/backend/base/langflow/components/inputs/TextInput.py

@@ -6,7 +6,21 @@ from langflow.field_typing import Text
 
 class TextInput(TextComponent):
     display_name = "Text Input"
-    description = "Used to pass text input to the next component."
+    description = "Capture Text or Record and send text inputs."
 
-    def build(self, input_value: Optional[str] = "") -> Text:
-        return super().build(input_value=input_value)
+    def build_config(self):
+        return {
+            "input_value": {
+                "display_name": "Value",
+                "input_types": ["Record"],
+                "info": "Text or Record to be passed as input.",
+            },
+            "record_template": {"display_name": "Record Template", "multiline": True},
+        }
+
+    def build(
+        self,
+        input_value: Optional[str] = "",
+        record_template: Optional[str] = "{text}",
+    ) -> Text:
+        return super().build(input_value=input_value, record_template=record_template)

src/backend/base/langflow/components/inputs/__init__.py

@@ -2,4 +2,4 @@ from .ChatInput import ChatInput
 from .Prompt import PromptComponent
 from .TextInput import TextInput
 
-__all__ = ["ChatInput", "TextInput", "PromptComponent"]
+__all__ = ["ChatInput", "PromptComponent", "TextInput"]

src/backend/base/langflow/components/model_specs/CTransformersSpecs.py

@@ -1,33 +0,0 @@
-from typing import Dict, Optional
-
-from langchain_community.llms.ctransformers import CTransformers
-
-from langflow.interface.custom.custom_component import CustomComponent
-
-
-class CTransformersComponent(CustomComponent):
-    display_name = "CTransformers"
-    description = "C Transformers LLM models"
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/ctransformers"
-
-    def build_config(self):
-        return {
-            "model": {"display_name": "Model", "required": True},
-            "model_file": {
-                "display_name": "Model File",
-                "required": False,
-                "field_type": "file",
-                "file_types": [".bin"],
-            },
-            "model_type": {"display_name": "Model Type", "required": True},
-            "config": {
-                "display_name": "Config",
-                "advanced": True,
-                "required": False,
-                "field_type": "dict",
-                "value": '{"top_k":40,"top_p":0.95,"temperature":0.8,"repetition_penalty":1.1,"last_n_tokens":64,"seed":-1,"max_new_tokens":256,"stop":"","stream":"False","reset":"True","batch_size":8,"threads":-1,"context_length":-1,"gpu_layers":0}',
-            },
-        }
-
-    def build(self, model: str, model_file: str, model_type: str, config: Optional[Dict] = None) -> CTransformers:
-        return CTransformers(model=model, model_file=model_file, model_type=model_type, config=config)  # type: ignore

src/backend/base/langflow/components/model_specs/ChatAnthropicSpecs.py

@@ -3,8 +3,8 @@ from typing import Callable, Optional, Union
 from langchain_community.chat_models.anthropic import ChatAnthropic
 from pydantic.v1.types import SecretStr
 
+from langflow.custom import CustomComponent
 from langflow.field_typing import BaseLanguageModel
-from langflow.interface.custom.custom_component import CustomComponent
 
 
 class ChatAnthropicComponent(CustomComponent):
@@ -20,31 +20,48 @@ class ChatAnthropicComponent(CustomComponent):
                 "field_type": "str",
                 "password": True,
             },
-            "anthropic_api_url": {
-                "display_name": "Anthropic API URL",
-                "field_type": "str",
-            },
             "model_kwargs": {
                 "display_name": "Model Kwargs",
                 "field_type": "dict",
                 "advanced": True,
             },
+            "model_name": {
+                "display_name": "Model Name",
+                "field_type": "str",
+                "advanced": False,
+                "required": False,
+                "options": ["claude-3-opus-20240229", "claude-3-sonnet-20240229", "claude-3-haiku-20240307"],
+            },
             "temperature": {
                 "display_name": "Temperature",
                 "field_type": "float",
             },
+            "max_tokens": {
+                "display_name": "Max Tokens",
+                "field_type": "int",
+                "advanced": False,
+                "required": False,
+            },
+            "top_k": {"display_name": "Top K", "field_type": "int", "advanced": True},
+            "top_p": {"display_name": "Top P", "field_type": "float", "advanced": True},
         }
 
     def build(
         self,
         anthropic_api_key: str,
-        anthropic_api_url: Optional[str] = None,
         model_kwargs: dict = {},
+        model_name: str = "claude-3-opus-20240229",
         temperature: Optional[float] = None,
+        max_tokens: Optional[int] = 1024,
+        top_k: Optional[int] = None,
+        top_p: Optional[float] = None,
     ) -> Union[BaseLanguageModel, Callable]:
         return ChatAnthropic(
             anthropic_api_key=SecretStr(anthropic_api_key),
-            anthropic_api_url=anthropic_api_url,
             model_kwargs=model_kwargs,
+            model_name=model_name,
             temperature=temperature,
+            max_tokens=max_tokens,  # type: ignore
+            top_k=top_k,
+            top_p=top_p,
         )

src/backend/base/langflow/components/model_specs/LlamaCppSpecs.py

@@ -1,131 +0,0 @@
-from typing import Any, Dict, List, Optional
-
-from langchain_community.llms.llamacpp import LlamaCpp
-
-from langflow.interface.custom.custom_component import CustomComponent
-
-
-class LlamaCppComponent(CustomComponent):
-    display_name = "LlamaCpp"
-    description = "llama.cpp model."
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/llamacpp"
-
-    def build_config(self):
-        return {
-            "grammar": {"display_name": "Grammar", "advanced": True},
-            "cache": {"display_name": "Cache", "advanced": True},
-            "client": {"display_name": "Client", "advanced": True},
-            "echo": {"display_name": "Echo", "advanced": True},
-            "f16_kv": {"display_name": "F16 KV", "advanced": True},
-            "grammar_path": {"display_name": "Grammar Path", "advanced": True},
-            "last_n_tokens_size": {"display_name": "Last N Tokens Size", "advanced": True},
-            "logits_all": {"display_name": "Logits All", "advanced": True},
-            "logprobs": {"display_name": "Logprobs", "advanced": True},
-            "lora_base": {"display_name": "Lora Base", "advanced": True},
-            "lora_path": {"display_name": "Lora Path", "advanced": True},
-            "max_tokens": {"display_name": "Max Tokens", "advanced": True},
-            "metadata": {"display_name": "Metadata", "advanced": True},
-            "model_kwargs": {"display_name": "Model Kwargs", "advanced": True},
-            "model_path": {
-                "display_name": "Model Path",
-                "field_type": "file",
-                "file_types": [".bin"],
-                "required": True,
-            },
-            "n_batch": {"display_name": "N Batch", "advanced": True},
-            "n_ctx": {"display_name": "N Ctx", "advanced": True},
-            "n_gpu_layers": {"display_name": "N GPU Layers", "advanced": True},
-            "n_parts": {"display_name": "N Parts", "advanced": True},
-            "n_threads": {"display_name": "N Threads", "advanced": True},
-            "repeat_penalty": {"display_name": "Repeat Penalty", "advanced": True},
-            "rope_freq_base": {"display_name": "Rope Freq Base", "advanced": True},
-            "rope_freq_scale": {"display_name": "Rope Freq Scale", "advanced": True},
-            "seed": {"display_name": "Seed", "advanced": True},
-            "stop": {"display_name": "Stop", "advanced": True},
-            "streaming": {"display_name": "Streaming", "advanced": True},
-            "suffix": {"display_name": "Suffix", "advanced": True},
-            "tags": {"display_name": "Tags", "advanced": True},
-            "temperature": {"display_name": "Temperature"},
-            "top_k": {"display_name": "Top K", "advanced": True},
-            "top_p": {"display_name": "Top P", "advanced": True},
-            "use_mlock": {"display_name": "Use Mlock", "advanced": True},
-            "use_mmap": {"display_name": "Use Mmap", "advanced": True},
-            "verbose": {"display_name": "Verbose", "advanced": True},
-            "vocab_only": {"display_name": "Vocab Only", "advanced": True},
-        }
-
-    def build(
-        self,
-        model_path: str,
-        grammar: Optional[str] = None,
-        cache: Optional[bool] = None,
-        client: Optional[Any] = None,
-        echo: Optional[bool] = False,
-        f16_kv: bool = True,
-        grammar_path: Optional[str] = None,
-        last_n_tokens_size: Optional[int] = 64,
-        logits_all: bool = False,
-        logprobs: Optional[int] = None,
-        lora_base: Optional[str] = None,
-        lora_path: Optional[str] = None,
-        max_tokens: Optional[int] = 256,
-        metadata: Optional[Dict] = None,
-        model_kwargs: Dict = {},
-        n_batch: Optional[int] = 8,
-        n_ctx: int = 512,
-        n_gpu_layers: Optional[int] = 1,
-        n_parts: int = -1,
-        n_threads: Optional[int] = 1,
-        repeat_penalty: Optional[float] = 1.1,
-        rope_freq_base: float = 10000.0,
-        rope_freq_scale: float = 1.0,
-        seed: int = -1,
-        stop: Optional[List[str]] = [],
-        streaming: bool = True,
-        suffix: Optional[str] = "",
-        tags: Optional[List[str]] = [],
-        temperature: Optional[float] = 0.8,
-        top_k: Optional[int] = 40,
-        top_p: Optional[float] = 0.95,
-        use_mlock: bool = False,
-        use_mmap: Optional[bool] = True,
-        verbose: bool = True,
-        vocab_only: bool = False,
-    ) -> LlamaCpp:
-        return LlamaCpp(
-            model_path=model_path,
-            grammar=grammar,
-            cache=cache,
-            client=client,
-            echo=echo,
-            f16_kv=f16_kv,
-            grammar_path=grammar_path,
-            last_n_tokens_size=last_n_tokens_size,
-            logits_all=logits_all,
-            logprobs=logprobs,
-            lora_base=lora_base,
-            lora_path=lora_path,
-            max_tokens=max_tokens,
-            metadata=metadata,
-            model_kwargs=model_kwargs,
-            n_batch=n_batch,
-            n_ctx=n_ctx,
-            n_gpu_layers=n_gpu_layers,
-            n_parts=n_parts,
-            n_threads=n_threads,
-            repeat_penalty=repeat_penalty,
-            rope_freq_base=rope_freq_base,
-            rope_freq_scale=rope_freq_scale,
-            seed=seed,
-            stop=stop,
-            streaming=streaming,
-            suffix=suffix,
-            tags=tags,
-            temperature=temperature,
-            top_k=top_k,
-            top_p=top_p,
-            use_mlock=use_mlock,
-            use_mmap=use_mmap,
-            verbose=verbose,
-            vocab_only=vocab_only,
-        )

src/backend/base/langflow/components/model_specs/__init__.py

@@ -4,7 +4,6 @@ from .AnthropicSpecs import AnthropicComponent
 from .AzureChatOpenAISpecs import AzureChatOpenAISpecsComponent
 from .BaiduQianfanChatEndpointsSpecs import QianfanChatEndpointComponent
 from .BaiduQianfanLLMEndpointsSpecs import QianfanLLMEndpointComponent
-from .CTransformersSpecs import CTransformersComponent
 from .ChatAnthropicSpecs import ChatAnthropicComponent
 from .ChatLiteLLMSpecs import ChatLiteLLMComponent
 from .ChatOllamaEndpointSpecs import ChatOllamaComponent
@@ -13,7 +12,6 @@ from .ChatVertexAISpecs import ChatVertexAIComponent
 from .CohereSpecs import CohereComponent
 from .GoogleGenerativeAISpecs import GoogleGenerativeAIComponent
 from .HuggingFaceEndpointsSpecs import HuggingFaceEndpointsComponent
-from .LlamaCppSpecs import LlamaCppComponent
 from .OllamaLLMSpecs import OllamaLLM
 from .VertexAISpecs import VertexAIComponent
 
@@ -24,7 +22,6 @@ __all__ = [
     "AzureChatOpenAISpecsComponent",
     "QianfanChatEndpointComponent",
     "QianfanLLMEndpointComponent",
-    "CTransformersComponent",
     "ChatAnthropicComponent",
     "ChatLiteLLMComponent",
     "ChatOllamaComponent",
@@ -33,7 +30,6 @@ __all__ = [
     "CohereComponent",
     "GoogleGenerativeAIComponent",
     "HuggingFaceEndpointsComponent",
-    "LlamaCppComponent",
     "OllamaLLM",
     "VertexAIComponent",
 ]

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

@@ -10,31 +10,50 @@ class AmazonBedrockComponent(LCModelComponent):
     display_name: str = "Amazon Bedrock"
     description: str = "Generate text using LLM model from Amazon Bedrock."
     icon = "Amazon"
+    field_order = [
+        "model_id",
+        "credentials_profile_name",
+        "region_name",
+        "model_kwargs",
+        "endpoint_url",
+        "cache",
+        "stream",
+        "input_value",
+        "system_message",
+    ]
 
     def build_config(self):
         return {
             "model_id": {
                 "display_name": "Model Id",
                 "options": [
-                    "ai21.j2-grande-instruct",
-                    "ai21.j2-jumbo-instruct",
-                    "ai21.j2-mid",
-                    "ai21.j2-mid-v1",
-                    "ai21.j2-ultra",
-                    "ai21.j2-ultra-v1",
-                    "anthropic.claude-instant-v1",
-                    "anthropic.claude-v1",
+                    "amazon.titan-text-express-v1",
+                    "amazon.titan-text-lite-v1",
+                    "amazon.titan-embed-text-v1",
+                    "amazon.titan-embed-image-v1",
+                    "amazon.titan-image-generator-v1",
                     "anthropic.claude-v2",
+                    "anthropic.claude-v2:1",
+                    "anthropic.claude-3-sonnet-20240229-v1:0",
+                    "anthropic.claude-3-haiku-20240307-v1:0",
+                    "anthropic.claude-instant-v1",
+                    "ai21.j2-mid-v1",
+                    "ai21.j2-ultra-v1",
                     "cohere.command-text-v14",
+                    "cohere.command-light-text-v14",
+                    "cohere.embed-english-v3",
+                    "cohere.embed-multilingual-v3",
+                    "meta.llama2-13b-chat-v1",
+                    "meta.llama2-70b-chat-v1",
+                    "mistral.mistral-7b-instruct-v0:2",
+                    "mistral.mixtral-8x7b-instruct-v0:1",
                 ],
             },
             "credentials_profile_name": {"display_name": "Credentials Profile Name"},
-            "streaming": {"display_name": "Streaming", "field_type": "bool"},
             "endpoint_url": {"display_name": "Endpoint URL"},
             "region_name": {"display_name": "Region Name"},
             "model_kwargs": {"display_name": "Model Kwargs"},
             "cache": {"display_name": "Cache"},
-            "code": {"advanced": True},
             "input_value": {"display_name": "Input"},
             "system_message": {"display_name": "System Message", "info": "System message to pass to the model."},
             "stream": {
@@ -52,7 +71,6 @@ class AmazonBedrockComponent(LCModelComponent):
         region_name: Optional[str] = None,
         model_kwargs: Optional[dict] = None,
         endpoint_url: Optional[str] = None,
-        streaming: bool = False,
         cache: Optional[bool] = None,
         stream: bool = False,
     ) -> Text:
@@ -63,7 +81,7 @@ class AmazonBedrockComponent(LCModelComponent):
                 region_name=region_name,
                 model_kwargs=model_kwargs,
                 endpoint_url=endpoint_url,
-                streaming=streaming,
+                streaming=stream,
                 cache=cache,
             )  # type: ignore
         except Exception as e:

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

@@ -17,15 +17,17 @@ class AnthropicLLM(LCModelComponent):
             "model": {
                 "display_name": "Model Name",
                 "options": [
+                    "claude-3-opus-20240229",
+                    "claude-3-sonnet-20240229",
+                    "claude-3-haiku-20240307",
                     "claude-2.1",
                     "claude-2.0",
                     "claude-instant-1.2",
                     "claude-instant-1",
-                    # Add more models as needed
                 ],
                 "info": "https://python.langchain.com/docs/integrations/chat/anthropic",
                 "required": True,
-                "value": "claude-2.1",
+                "value": "claude-3-opus-20240229",
             },
             "anthropic_api_key": {
                 "display_name": "Anthropic API Key",
@@ -43,8 +45,8 @@ class AnthropicLLM(LCModelComponent):
                 "field_type": "float",
                 "value": 0.7,
             },
-            "api_endpoint": {
-                "display_name": "API Endpoint",
+            "anthropic_api_url": {
+                "display_name": "Anthropic API URL",
                 "info": "Endpoint of the Anthropic API. Defaults to 'https://api.anthropic.com' if not specified.",
             },
             "code": {"show": False},
@@ -67,12 +69,12 @@ class AnthropicLLM(LCModelComponent):
         anthropic_api_key: Optional[str] = None,
         max_tokens: Optional[int] = None,
         temperature: Optional[float] = None,
-        api_endpoint: Optional[str] = None,
+        anthropic_api_url: Optional[str] = None,
         stream: bool = False,
     ) -> Text:
         # Set default API endpoint if not provided
-        if not api_endpoint:
-            api_endpoint = "https://api.anthropic.com"
+        if not anthropic_api_url:
+            anthropic_api_url = "https://api.anthropic.com"
 
         try:
             output = ChatAnthropic(
@@ -80,7 +82,7 @@ class AnthropicLLM(LCModelComponent):
                 anthropic_api_key=(SecretStr(anthropic_api_key) if anthropic_api_key else None),
                 max_tokens_to_sample=max_tokens,  # type: ignore
                 temperature=temperature,
-                anthropic_api_url=api_endpoint,
+                anthropic_api_url=anthropic_api_url,
             )
         except Exception as e:
             raise ValueError("Could not connect to Anthropic API.") from e

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

@@ -8,7 +8,7 @@ from langflow.field_typing import Text
 
 
 class AzureChatOpenAIComponent(LCModelComponent):
-    display_name: str = "AzureOpenAI"
+    display_name: str = "Azure OpenAI"
     description: str = "Generate text using LLM model from Azure OpenAI."
     documentation: str = "https://python.langchain.com/docs/integrations/llms/azure_openai"
     beta = False

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

@@ -8,7 +8,7 @@ from langflow.field_typing import Text
 
 
 class QianfanChatEndpointComponent(LCModelComponent):
-    display_name: str = "QianfanChat"
+    display_name: str = "Qianfan"
     description: str = (
         "Generate text using Baidu Qianfan chat models. Get more detail from "
         "https://python.langchain.com/docs/integrations/chat/baidu_qianfan_endpoint."

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

@@ -1,59 +0,0 @@
-from typing import Dict, Optional
-
-from langchain_community.llms.ctransformers import CTransformers
-
-from langflow.base.models.model import LCModelComponent
-from langflow.field_typing import Text
-
-
-class CTransformersComponent(LCModelComponent):
-    display_name = "CTransformers"
-    description = "Generate text using CTransformers LLM models"
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/ctransformers"
-
-    def build_config(self):
-        return {
-            "model": {"display_name": "Model", "required": True},
-            "model_file": {
-                "display_name": "Model File",
-                "required": False,
-                "field_type": "file",
-                "file_types": [".bin"],
-            },
-            "model_type": {"display_name": "Model Type", "required": True},
-            "config": {
-                "display_name": "Config",
-                "advanced": True,
-                "required": False,
-                "field_type": "dict",
-                "value": '{"top_k":40,"top_p":0.95,"temperature":0.8,"repetition_penalty":1.1,"last_n_tokens":64,"seed":-1,"max_new_tokens":256,"stop":"","stream":"False","reset":"True","batch_size":8,"threads":-1,"context_length":-1,"gpu_layers":0}',
-            },
-            "input_value": {"display_name": "Input"},
-            "stream": {
-                "display_name": "Stream",
-                "info": "Stream the response from the model.",
-            },
-            "system_message": {
-                "display_name": "System Message",
-                "info": "System message to pass to the model.",
-            },
-        }
-
-    def build(
-        self,
-        model: str,
-        model_file: str,
-        input_value: Text,
-        model_type: str,
-        stream: bool = False,
-        config: Optional[Dict] = None,
-    ) -> Text:
-        output = CTransformers(
-            client=None,
-            model=model,
-            model_file=model_file,
-            model_type=model_type,
-            config=config,  # noqa
-        )
-
-        return self.get_result(runnable=output, stream=stream, input_value=input_value)

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

@@ -1,148 +0,0 @@
-from typing import Any, Dict, List, Optional
-
-from langchain_community.llms.llamacpp import LlamaCpp
-
-from langflow.base.models.model import LCModelComponent
-from langflow.field_typing import Text
-
-
-class LlamaCppComponent(LCModelComponent):
-    display_name = "LlamaCpp"
-    description = "Generate text using llama.cpp model."
-    documentation = "https://python.langchain.com/docs/modules/model_io/models/llms/integrations/llamacpp"
-
-    def build_config(self):
-        return {
-            "grammar": {"display_name": "Grammar", "advanced": True},
-            "cache": {"display_name": "Cache", "advanced": True},
-            "client": {"display_name": "Client", "advanced": True},
-            "echo": {"display_name": "Echo", "advanced": True},
-            "f16_kv": {"display_name": "F16 KV", "advanced": True},
-            "grammar_path": {"display_name": "Grammar Path", "advanced": True},
-            "last_n_tokens_size": {
-                "display_name": "Last N Tokens Size",
-                "advanced": True,
-            },
-            "logits_all": {"display_name": "Logits All", "advanced": True},
-            "logprobs": {"display_name": "Logprobs", "advanced": True},
-            "lora_base": {"display_name": "Lora Base", "advanced": True},
-            "lora_path": {"display_name": "Lora Path", "advanced": True},
-            "max_tokens": {"display_name": "Max Tokens", "advanced": True},
-            "metadata": {"display_name": "Metadata", "advanced": True},
-            "model_kwargs": {"display_name": "Model Kwargs", "advanced": True},
-            "model_path": {
-                "display_name": "Model Path",
-                "field_type": "file",
-                "file_types": [".bin"],
-                "required": True,
-            },
-            "n_batch": {"display_name": "N Batch", "advanced": True},
-            "n_ctx": {"display_name": "N Ctx", "advanced": True},
-            "n_gpu_layers": {"display_name": "N GPU Layers", "advanced": True},
-            "n_parts": {"display_name": "N Parts", "advanced": True},
-            "n_threads": {"display_name": "N Threads", "advanced": True},
-            "repeat_penalty": {"display_name": "Repeat Penalty", "advanced": True},
-            "rope_freq_base": {"display_name": "Rope Freq Base", "advanced": True},
-            "rope_freq_scale": {"display_name": "Rope Freq Scale", "advanced": True},
-            "seed": {"display_name": "Seed", "advanced": True},
-            "stop": {"display_name": "Stop", "advanced": True},
-            "streaming": {"display_name": "Streaming", "advanced": True},
-            "suffix": {"display_name": "Suffix", "advanced": True},
-            "tags": {"display_name": "Tags", "advanced": True},
-            "temperature": {"display_name": "Temperature"},
-            "top_k": {"display_name": "Top K", "advanced": True},
-            "top_p": {"display_name": "Top P", "advanced": True},
-            "use_mlock": {"display_name": "Use Mlock", "advanced": True},
-            "use_mmap": {"display_name": "Use Mmap", "advanced": True},
-            "verbose": {"display_name": "Verbose", "advanced": True},
-            "vocab_only": {"display_name": "Vocab Only", "advanced": True},
-            "input_value": {"display_name": "Input"},
-            "stream": {
-                "display_name": "Stream",
-                "info": "Stream the response from the model.",
-            },
-            "system_message": {
-                "display_name": "System Message",
-                "info": "System message to pass to the model.",
-            },
-        }
-
-    def build(
-        self,
-        model_path: str,
-        input_value: Text,
-        grammar: Optional[str] = None,
-        cache: Optional[bool] = None,
-        client: Optional[Any] = None,
-        echo: Optional[bool] = False,
-        f16_kv: bool = True,
-        grammar_path: Optional[str] = None,
-        last_n_tokens_size: Optional[int] = 64,
-        logits_all: bool = False,
-        logprobs: Optional[int] = None,
-        lora_base: Optional[str] = None,
-        lora_path: Optional[str] = None,
-        max_tokens: Optional[int] = 256,
-        metadata: Optional[Dict] = None,
-        model_kwargs: Dict = {},
-        n_batch: Optional[int] = 8,
-        n_ctx: int = 512,
-        n_gpu_layers: Optional[int] = 1,
-        n_parts: int = -1,
-        n_threads: Optional[int] = 1,
-        repeat_penalty: Optional[float] = 1.1,
-        rope_freq_base: float = 10000.0,
-        rope_freq_scale: float = 1.0,
-        seed: int = -1,
-        stop: Optional[List[str]] = [],
-        streaming: bool = True,
-        suffix: Optional[str] = "",
-        tags: Optional[List[str]] = [],
-        temperature: Optional[float] = 0.8,
-        top_k: Optional[int] = 40,
-        top_p: Optional[float] = 0.95,
-        use_mlock: bool = False,
-        use_mmap: Optional[bool] = True,
-        verbose: bool = True,
-        vocab_only: bool = False,
-        stream: bool = False,
-    ) -> Text:
-        output = LlamaCpp(
-            model_path=model_path,
-            grammar=grammar,
-            cache=cache,
-            client=client,
-            echo=echo,
-            f16_kv=f16_kv,
-            grammar_path=grammar_path,
-            last_n_tokens_size=last_n_tokens_size,
-            logits_all=logits_all,
-            logprobs=logprobs,
-            lora_base=lora_base,
-            lora_path=lora_path,
-            max_tokens=max_tokens,
-            metadata=metadata,
-            model_kwargs=model_kwargs,
-            n_batch=n_batch,
-            n_ctx=n_ctx,
-            n_gpu_layers=n_gpu_layers,
-            n_parts=n_parts,
-            n_threads=n_threads,
-            repeat_penalty=repeat_penalty,
-            rope_freq_base=rope_freq_base,
-            rope_freq_scale=rope_freq_scale,
-            seed=seed,
-            stop=stop,
-            streaming=streaming,
-            suffix=suffix,
-            tags=tags,
-            temperature=temperature,
-            top_k=top_k,
-            top_p=top_p,
-            use_mlock=use_mlock,
-            use_mmap=use_mmap,
-            verbose=verbose,
-            vocab_only=vocab_only,
-        )
-
-        return self.get_result(runnable=output, stream=stream, input_value=input_value)

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

@@ -13,7 +13,7 @@ from langflow.field_typing import Text
 
 
 class ChatOllamaComponent(LCModelComponent):
-    display_name = "ChatOllama"
+    display_name = "Ollama"
     description = "Generate text using Local LLM for chat with Ollama."
     icon = "Ollama"
 

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

@@ -7,7 +7,7 @@ from langflow.field_typing import Text
 
 
 class ChatVertexAIComponent(LCModelComponent):
-    display_name = "ChatVertexAI"
+    display_name = "Vertex AI"
     description = "Generate text using Vertex AI Chat large language models API."
     icon = "VertexAI"
 

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

@@ -2,11 +2,9 @@ from .AmazonBedrockModel import AmazonBedrockComponent
 from .AnthropicModel import AnthropicLLM
 from .AzureOpenAIModel import AzureChatOpenAIComponent
 from .BaiduQianfanChatModel import QianfanChatEndpointComponent
-from .CTransformersModel import CTransformersComponent
 from .CohereModel import CohereComponent
 from .GoogleGenerativeAIModel import GoogleGenerativeAIComponent
 from .HuggingFaceModel import HuggingFaceEndpointsComponent
-from .LlamaCppModel import LlamaCppComponent
 from .OllamaModel import ChatOllamaComponent
 from .OpenAIModel import OpenAIModelComponent
 from .VertexAiModel import ChatVertexAIComponent
@@ -16,11 +14,9 @@ __all__ = [
     "AnthropicLLM",
     "AzureChatOpenAIComponent",
     "QianfanChatEndpointComponent",
-    "CTransformersComponent",
     "CohereComponent",
     "GoogleGenerativeAIComponent",
     "HuggingFaceEndpointsComponent",
-    "LlamaCppComponent",
     "ChatOllamaComponent",
     "OpenAIModelComponent",
     "ChatVertexAIComponent",

src/backend/base/langflow/components/outputs/ChatOutput.py

@@ -7,7 +7,7 @@ from langflow.schema import Record
 
 class ChatOutput(ChatComponent):
     display_name = "Chat Output"
-    description = "Used to send a message to the chat."
+    description = "Used to send a chat message."
     icon = "ChatOutput"
 
     def build(
@@ -17,6 +17,7 @@ class ChatOutput(ChatComponent):
         input_value: Optional[str] = None,
         session_id: Optional[str] = None,
         return_record: Optional[bool] = False,
+        record_template: Optional[str] = "{text}",
     ) -> Union[Text, Record]:
         return super().build(
             sender=sender,
@@ -24,4 +25,5 @@ class ChatOutput(ChatComponent):
             input_value=input_value,
             session_id=session_id,
             return_record=return_record,
+            record_template=record_template,
         )

src/backend/base/langflow/components/outputs/TextOutput.py

@@ -6,11 +6,17 @@ from langflow.field_typing import Text
 
 class TextOutput(TextComponent):
     display_name = "Text Output"
-    description = "Used to pass text output to the next component."
+    description = "Used to send a text output."
 
-    field_config = {
-        "input_value": {"display_name": "Value"},
-    }
+    def build_config(self):
+        return {
+            "input_value": {
+                "display_name": "Value",
+                "input_types": ["Record"],
+                "info": "Text or Record to be passed as output.",
+            },
+            "record_template": {"display_name": "Record Template", "multiline": True},
+        }
 
-    def build(self, input_value: Optional[Text] = "") -> Text:
-        return super().build(input_value=input_value)
+    def build(self, input_value: Optional[Text] = "", record_template: str = "{text}") -> Text:
+        return super().build(input_value=input_value, record_template=record_template)

src/backend/base/langflow/components/retrievers/__init__.py

@@ -2,10 +2,12 @@ from .AmazonKendra import AmazonKendraRetrieverComponent
 from .MetalRetriever import MetalRetrieverComponent
 from .MultiQueryRetriever import MultiQueryRetrieverComponent
 from .VectaraSelfQueryRetriver import VectaraSelfQueryRetriverComponent
+from .VectorStoreRetriever import VectoStoreRetrieverComponent
 
 __all__ = [
     "AmazonKendraRetrieverComponent",
     "MetalRetrieverComponent",
     "MultiQueryRetrieverComponent",
     "VectaraSelfQueryRetriverComponent",
+    "VectoStoreRetrieverComponent",
 ]

src/backend/base/langflow/components/tools/__init__.py

@@ -0,0 +1,5 @@
+from .RetrieverTool import RetrieverToolComponent
+from .SearchAPITool import SearchApiToolComponent
+from .SearchApi import SearchApi
+
+__all__ = ["RetrieverToolComponent", "SearchApiToolComponent", "SearchApi"]

src/backend/base/langflow/components/vectorsearch/AstraDBSearch.py

@@ -23,51 +23,73 @@ class AstraDBSearchComponent(LCVectorStoreComponent):
                 "info": "Input value to search",
             },
             "embedding": {"display_name": "Embedding", "info": "Embedding to use"},
-            "collection_name": {"display_name": "Collection Name", "info": "Collection name"},
-            "token": {"display_name": "Token", "info": "Token to use", "password": True},
-            "api_endpoint": {"display_name": "API Endpoint", "info": "API Endpoint to use"},
-            "namespace": {"display_name": "Namespace", "info": "Namespace to use", "advanced": True},
-            "metric": {"display_name": "Metric", "info": "Metric to use", "advanced": True},
-            "batch_size": {"display_name": "Batch Size", "info": "Batch size to use", "advanced": True},
+            "collection_name": {
+                "display_name": "Collection Name",
+                "info": "The name of the collection within AstraDB where the vectors will be stored.",
+            },
+            "token": {
+                "display_name": "Token",
+                "info": "Authentication token for accessing AstraDB.",
+                "password": True,
+            },
+            "api_endpoint": {
+                "display_name": "API Endpoint",
+                "info": "API endpoint URL for the AstraDB service.",
+            },
+            "namespace": {
+                "display_name": "Namespace",
+                "info": "Optional namespace within AstraDB to use for the collection.",
+                "advanced": True,
+            },
+            "metric": {
+                "display_name": "Metric",
+                "info": "Optional distance metric for vector comparisons in the vector store.",
+                "advanced": True,
+            },
+            "batch_size": {
+                "display_name": "Batch Size",
+                "info": "Optional number of records to process in a single batch.",
+                "advanced": True,
+            },
             "bulk_insert_batch_concurrency": {
                 "display_name": "Bulk Insert Batch Concurrency",
-                "info": "Bulk Insert Batch Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations.",
                 "advanced": True,
             },
             "bulk_insert_overwrite_concurrency": {
                 "display_name": "Bulk Insert Overwrite Concurrency",
-                "info": "Bulk Insert Overwrite Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations that overwrite existing records.",
                 "advanced": True,
             },
             "bulk_delete_concurrency": {
                 "display_name": "Bulk Delete Concurrency",
-                "info": "Bulk Delete Concurrency to use",
+                "info": "Optional concurrency level for bulk delete operations.",
                 "advanced": True,
             },
             "setup_mode": {
                 "display_name": "Setup Mode",
-                "info": "Setup mode for the vector store",
+                "info": "Configuration mode for setting up the vector store, with options like “Sync”, “Async”, or “Off”.",
                 "options": ["Sync", "Async", "Off"],
                 "advanced": True,
             },
             "pre_delete_collection": {
                 "display_name": "Pre Delete Collection",
-                "info": "Pre delete collection",
+                "info": "Boolean flag to determine whether to delete the collection before creating a new one.",
                 "advanced": True,
             },
             "metadata_indexing_include": {
                 "display_name": "Metadata Indexing Include",
-                "info": "Metadata Indexing Include",
+                "info": "Optional list of metadata fields to include in the indexing.",
                 "advanced": True,
             },
             "metadata_indexing_exclude": {
                 "display_name": "Metadata Indexing Exclude",
-                "info": "Metadata Indexing Exclude",
+                "info": "Optional list of metadata fields to exclude from the indexing.",
                 "advanced": True,
             },
             "collection_indexing_policy": {
                 "display_name": "Collection Indexing Policy",
-                "info": "Collection Indexing Policy",
+                "info": "Optional dictionary defining the indexing policy for the collection.",
                 "advanced": True,
             },
         }
@@ -77,9 +99,9 @@ class AstraDBSearchComponent(LCVectorStoreComponent):
         embedding: Embeddings,
         collection_name: str,
         input_value: Text,
+        token: str,
+        api_endpoint: str,
         search_type: str = "Similarity",
-        token: Optional[str] = None,
-        api_endpoint: Optional[str] = None,
         namespace: Optional[str] = None,
         metric: Optional[str] = None,
         batch_size: Optional[int] = None,

src/backend/base/langflow/components/vectorsearch/__init__.py

@@ -0,0 +1,25 @@
+from .AstraDBSearch import AstraDBSearchComponent
+from .ChromaSearch import ChromaSearchComponent
+from .FAISSSearch import FAISSSearchComponent
+from .MongoDBAtlasVectorSearch import MongoDBAtlasSearchComponent
+from .PineconeSearch import PineconeSearchComponent
+from .QdrantSearch import QdrantSearchComponent
+from .RedisSearch import RedisSearchComponent
+from .SupabaseVectorStoreSearch import SupabaseSearchComponent
+from .VectaraSearch import VectaraSearchComponent
+from .WeaviateSearch import WeaviateSearchVectorStore
+from .pgvectorSearch import PGVectorSearchComponent
+
+__all__ = [
+    "AstraDBSearchComponent",
+    "ChromaSearchComponent",
+    "FAISSSearchComponent",
+    "MongoDBAtlasSearchComponent",
+    "PineconeSearchComponent",
+    "QdrantSearchComponent",
+    "RedisSearchComponent",
+    "SupabaseSearchComponent",
+    "VectaraSearchComponent",
+    "WeaviateSearchVectorStore",
+    "PGVectorSearchComponent",
+]

src/backend/base/langflow/components/vectorstores/AstraDB.py

@@ -16,53 +16,78 @@ class AstraDBVectorStoreComponent(CustomComponent):
 
     def build_config(self):
         return {
-            "inputs": {"display_name": "Inputs", "info": "Inputs to AstraDB"},
+            "inputs": {
+                "display_name": "Inputs",
+                "info": "Optional list of records to be processed and stored in the vector store.",
+            },
             "embedding": {"display_name": "Embedding", "info": "Embedding to use"},
-            "collection_name": {"display_name": "Collection Name", "info": "Collection name"},
-            "token": {"display_name": "Token", "info": "Token to use", "password": True},
-            "api_endpoint": {"display_name": "API Endpoint", "info": "API Endpoint to use"},
-            "namespace": {"display_name": "Namespace", "info": "Namespace to use", "advanced": True},
-            "metric": {"display_name": "Metric", "info": "Metric to use", "advanced": True},
-            "batch_size": {"display_name": "Batch Size", "info": "Batch size to use", "advanced": True},
+            "collection_name": {
+                "display_name": "Collection Name",
+                "info": "The name of the collection within AstraDB where the vectors will be stored.",
+            },
+            "token": {
+                "display_name": "Token",
+                "info": "Authentication token for accessing AstraDB.",
+                "password": True,
+            },
+            "api_endpoint": {
+                "display_name": "API Endpoint",
+                "info": "API endpoint URL for the AstraDB service.",
+            },
+            "namespace": {
+                "display_name": "Namespace",
+                "info": "Optional namespace within AstraDB to use for the collection.",
+                "advanced": True,
+            },
+            "metric": {
+                "display_name": "Metric",
+                "info": "Optional distance metric for vector comparisons in the vector store.",
+                "advanced": True,
+            },
+            "batch_size": {
+                "display_name": "Batch Size",
+                "info": "Optional number of records to process in a single batch.",
+                "advanced": True,
+            },
             "bulk_insert_batch_concurrency": {
                 "display_name": "Bulk Insert Batch Concurrency",
-                "info": "Bulk Insert Batch Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations.",
                 "advanced": True,
             },
             "bulk_insert_overwrite_concurrency": {
                 "display_name": "Bulk Insert Overwrite Concurrency",
-                "info": "Bulk Insert Overwrite Concurrency to use",
+                "info": "Optional concurrency level for bulk insert operations that overwrite existing records.",
                 "advanced": True,
             },
             "bulk_delete_concurrency": {
                 "display_name": "Bulk Delete Concurrency",
-                "info": "Bulk Delete Concurrency to use",
+                "info": "Optional concurrency level for bulk delete operations.",
                 "advanced": True,
             },
             "setup_mode": {
                 "display_name": "Setup Mode",
-                "info": "Setup mode for the vector store",
+                "info": "Configuration mode for setting up the vector store, with options like “Sync”, “Async”, or “Off”.",
                 "options": ["Sync", "Async", "Off"],
                 "advanced": True,
             },
             "pre_delete_collection": {
                 "display_name": "Pre Delete Collection",
-                "info": "Pre delete collection",
+                "info": "Boolean flag to determine whether to delete the collection before creating a new one.",
                 "advanced": True,
             },
             "metadata_indexing_include": {
                 "display_name": "Metadata Indexing Include",
-                "info": "Metadata Indexing Include",
+                "info": "Optional list of metadata fields to include in the indexing.",
                 "advanced": True,
             },
             "metadata_indexing_exclude": {
                 "display_name": "Metadata Indexing Exclude",
-                "info": "Metadata Indexing Exclude",
+                "info": "Optional list of metadata fields to exclude from the indexing.",
                 "advanced": True,
             },
             "collection_indexing_policy": {
                 "display_name": "Collection Indexing Policy",
-                "info": "Collection Indexing Policy",
+                "info": "Optional dictionary defining the indexing policy for the collection.",
                 "advanced": True,
             },
         }
@@ -70,17 +95,17 @@ class AstraDBVectorStoreComponent(CustomComponent):
     def build(
         self,
         embedding: Embeddings,
+        token: str,
+        api_endpoint: str,
         collection_name: str,
         inputs: Optional[List[Record]] = None,
-        token: Optional[str] = None,
-        api_endpoint: Optional[str] = None,
         namespace: Optional[str] = None,
         metric: Optional[str] = None,
         batch_size: Optional[int] = None,
         bulk_insert_batch_concurrency: Optional[int] = None,
         bulk_insert_overwrite_concurrency: Optional[int] = None,
         bulk_delete_concurrency: Optional[int] = None,
-        setup_mode: str = "Sync",
+        setup_mode: str = "Async",
         pre_delete_collection: bool = False,
         metadata_indexing_include: Optional[List[str]] = None,
         metadata_indexing_exclude: Optional[List[str]] = None,

src/backend/base/langflow/components/vectorstores/__init__.py

@@ -1,44 +1,26 @@
+from .AstraDB import AstraDBVectorStoreComponent
 from .Chroma import ChromaComponent
-from .ChromaSearch import ChromaSearchComponent
 from .FAISS import FAISSComponent
-from .FAISSSearch import FAISSSearchComponent
 from .MongoDBAtlasVector import MongoDBAtlasComponent
-from .MongoDBAtlasVectorSearch import MongoDBAtlasSearchComponent
 from .Pinecone import PineconeComponent
-from .PineconeSearch import PineconeSearchComponent
 from .Qdrant import QdrantComponent
-from .QdrantSearch import QdrantSearchComponent
 from .Redis import RedisComponent
-from .RedisSearch import RedisSearchComponent
 from .SupabaseVectorStore import SupabaseComponent
-from .SupabaseVectorStoreSearch import SupabaseSearchComponent
 from .Vectara import VectaraComponent
-from .VectaraSearch import VectaraSearchComponent
 from .Weaviate import WeaviateVectorStoreComponent
-from .WeaviateSearch import WeaviateSearchVectorStore
 from .pgvector import PGVectorComponent
-from .pgvectorSearch import PGVectorSearchComponent
 
 __all__ = [
+    "AstraDBVectorStoreComponent",
     "ChromaComponent",
-    "ChromaSearchComponent",
     "FAISSComponent",
-    "FAISSSearchComponent",
     "MongoDBAtlasComponent",
-    "MongoDBAtlasSearchComponent",
     "PineconeComponent",
-    "PineconeSearchComponent",
     "QdrantComponent",
-    "QdrantSearchComponent",
     "RedisComponent",
-    "RedisSearchComponent",
     "SupabaseComponent",
-    "SupabaseSearchComponent",
     "VectaraComponent",
-    "VectaraSearchComponent",
     "WeaviateVectorStoreComponent",
-    "WeaviateSearchVectorStore",
     "base",
     "PGVectorComponent",
-    "PGVectorSearchComponent",
 ]

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

@@ -237,10 +237,28 @@ class CodeParser:
 
     def parse_return_statement(self, node: ast.FunctionDef) -> bool:
         """
-        Parses the return statement of a function or method node.
+        Parses the return statement of a function or method node, including nested returns.
         """
 
-        return any(isinstance(n, ast.Return) for n in node.body)
+        def has_return(node):
+            if isinstance(node, ast.Return):
+                return True
+            elif isinstance(node, ast.If):
+                return any(has_return(child) for child in node.body) or any(has_return(child) for child in node.orelse)
+            elif isinstance(node, ast.Try):
+                return (
+                    any(has_return(child) for child in node.body)
+                    or any(has_return(child) for child in node.handlers)
+                    or any(has_return(child) for child in node.finalbody)
+                )
+            elif isinstance(node, (ast.For, ast.While)):
+                return any(has_return(child) for child in node.body) or any(has_return(child) for child in node.orelse)
+            elif isinstance(node, ast.With):
+                return any(has_return(child) for child in node.body)
+            else:
+                return False
+
+        return any(has_return(child) for child in node.body)
 
     def parse_assign(self, stmt):
         """

src/backend/base/langflow/interface/initialize/utils.py

@@ -32,6 +32,8 @@ def check_tools_in_params(params: Dict):
 
 def instantiate_from_template(class_object, params: Dict):
     from_template_params = {"template": params.pop("prompt", params.pop("template", ""))}
+
+    from_template_params.update(params)
     if not from_template_params.get("template"):
         raise ValueError("Prompt template is required")
     return class_object.from_template(**from_template_params)

src/backend/base/langflow/interface/llms/base.py

@@ -4,6 +4,7 @@ from loguru import logger
 
 from langflow.interface.base import LangChainTypeCreator
 from langflow.interface.custom_lists import llm_type_to_cls_dict
+from langflow.services.deps import get_settings_service
 from langflow.template.frontend_node.llms import LLMFrontendNode
 from langflow.utils.util import build_template_from_class
 
@@ -33,10 +34,11 @@ class LLMCreator(LangChainTypeCreator):
             return None
 
     def to_list(self) -> List[str]:
+        settings_service = get_settings_service()
         return [
             llm.__name__
             for llm in self.type_to_loader_dict.values()
-            # if llm.__name__ in settings_service.settings.LLMS or settings_service.settings.DEV
+            if llm.__name__ in settings_service.settings.LLMS or settings_service.settings.DEV
         ]
 
 

src/backend/langflow/version/version.py

@@ -1,7 +1,7 @@
 from importlib import metadata
 
 try:
-    __version__ = metadata.version(__package__)
+    __version__ = metadata.version("langflow")
 except metadata.PackageNotFoundError:
     __version__ = ""
 del metadata

src/frontend/package-lock.json

@@ -55,7 +55,7 @@
         "react-cookie": "^4.1.1",
         "react-dom": "^18.2.0",
         "react-error-boundary": "^4.0.11",
-        "react-icons": "^4.10.1",
+        "react-icons": "^5.0.1",
         "react-laag": "^2.0.5",
         "react-markdown": "^8.0.7",
         "react-router-dom": "^6.15.0",
@@ -9363,9 +9363,9 @@
       }
     },
     "node_modules/react-icons": {
-      "version": "4.12.0",
-      "resolved": "https://registry.npmjs.org/react-icons/-/react-icons-4.12.0.tgz",
-      "integrity": "sha512-IBaDuHiShdZqmfc/TwHu6+d6k2ltNCf3AszxNmjJc1KUfXdEeRJOKyNvLmAHaarhzGmTSVygNdyu8/opXv2gaw==",
+      "version": "5.0.1",
+      "resolved": "https://registry.npmjs.org/react-icons/-/react-icons-5.0.1.tgz",
+      "integrity": "sha512-WqLZJ4bLzlhmsvme6iFdgO8gfZP17rfjYEJ2m9RsZjZ+cc4k1hTzknEz63YS1MeT50kVzoa1Nz36f4BEx+Wigw==",
       "peerDependencies": {
         "react": "*"
       }

src/frontend/package.json

@@ -50,7 +50,7 @@
     "react-cookie": "^4.1.1",
     "react-dom": "^18.2.0",
     "react-error-boundary": "^4.0.11",
-    "react-icons": "^4.10.1",
+    "react-icons": "^5.0.1",
     "react-laag": "^2.0.5",
     "react-markdown": "^8.0.7",
     "react-router-dom": "^6.15.0",

src/frontend/src/CustomNodes/GenericNode/index.tsx

@@ -211,10 +211,12 @@ export default function GenericNode({
     }
   }, [validationStatus, validationStatus?.params]);
 
-  // const showNode = data.showNode ?? true;
-
   const [showNode, setShowNode] = useState(data.showNode ?? true);
 
+  useEffect(() => {
+    setShowNode(data.showNode ?? true);
+  }, [data.showNode]);
+
   const nameEditable = true;
 
   const emojiRegex = /\p{Emoji}/u;
@@ -438,7 +440,7 @@ export default function GenericNode({
                             event.preventDefault();
                           }}
                           data-testid={"title-" + data.node?.display_name}
-                          className="generic-node-tooltip-div text-primary"
+                          className="generic-node-tooltip-div cursor-text text-primary"
                         >
                           {data.node?.display_name}
                         </div>

src/frontend/src/components/DropdownButtonComponent/index.tsx

@@ -13,6 +13,8 @@ export default function DropdownButton({
   firstButtonName,
   onFirstBtnClick,
   options,
+  plusButton = false,
+  dropdownOptions = true,
 }: dropdownButtonPropsType): JSX.Element {
   const [showOptions, setShowOptions] = useState<boolean>(false);
 
@@ -23,28 +25,33 @@ export default function DropdownButton({
           <Button
             id="new-project-btn"
             variant="primary"
-            className="relative pr-10"
+            className={"relative" + dropdownOptions ? "" : " pr-10"}
             onClick={(event) => {
               event.stopPropagation();
               event.preventDefault();
               onFirstBtnClick();
             }}
           >
+            {plusButton && (
+              <IconComponent name="Plus" className="main-page-nav-button" />
+            )}
             {firstButtonName}
-            <div
-              className="absolute right-2 items-center text-muted-foreground"
-              onClick={(event) => {
-                event.stopPropagation();
-                event.preventDefault();
-                setShowOptions(!showOptions);
-              }}
-            >
-              {!showOptions ? (
-                <IconComponent name="ChevronDown" />
-              ) : (
-                <IconComponent name="ChevronUp" />
-              )}
-            </div>
+            {dropdownOptions && (
+              <div
+                className="absolute right-2 items-center text-muted-foreground"
+                onClick={(event) => {
+                  event.stopPropagation();
+                  event.preventDefault();
+                  setShowOptions(!showOptions);
+                }}
+              >
+                {!showOptions ? (
+                  <IconComponent name="ChevronDown" />
+                ) : (
+                  <IconComponent name="ChevronUp" />
+                )}
+              </div>
+            )}
           </Button>
         </DropdownMenuTrigger>
         <DropdownMenuContent

src/frontend/src/components/IOview/index.tsx

@@ -120,7 +120,7 @@ export default function IOView({
       {/* TODO ADAPT TO ALL TYPES OF INPUTS AND OUTPUTS */}
       <BaseModal.Header description={CHAT_FORM_DIALOG_SUBTITLE}>
         <div className="flex items-center">
-          <span className="pr-2">Chat</span>
+          <span className="pr-2">Interaction Panel</span>
           <IconComponent
             name="prompts"
             className="h-6 w-6 pl-1 text-foreground"

src/frontend/src/components/headerComponent/index.tsx

@@ -1,5 +1,6 @@
 import { useContext, useEffect } from "react";
-import { FaDiscord, FaGithub, FaTwitter } from "react-icons/fa";
+import { FaDiscord, FaGithub } from "react-icons/fa";
+import { RiTwitterXFill } from "react-icons/ri";
 import { Link, useLocation, useNavigate, useParams } from "react-router-dom";
 import AlertDropdown from "../../alerts/alertDropDown";
 import { USER_PROJECTS_HEADER } from "../../constants/constants";
@@ -127,7 +128,7 @@ export default function Header(): JSX.Element {
             rel="noreferrer"
             className="text-muted-foreground"
           >
-            <FaTwitter className="side-bar-button-size" />
+            <RiTwitterXFill className="side-bar-button-size" />
           </a>
           <a
             href="https://discord.gg/EqksyE2EX9"

src/frontend/src/components/inputComponent/index.tsx

@@ -99,12 +99,16 @@ export default function InputComponent({
                 type="text"
                 onBlur={onInputLostFocus}
                 value={
-                  selectedOption !== "" || !onChange ? selectedOption : value
+                  (selectedOption !== "" || !onChange) && setSelectedOption
+                    ? selectedOption
+                    : value
                 }
                 autoFocus={autoFocus}
                 disabled={disabled}
                 onClick={() => {
-                  (selectedOption !== "" || !onChange) && setShowOptions(true);
+                  (selectedOption !== "" || !onChange) &&
+                    setSelectedOption &&
+                    setShowOptions(true);
                 }}
                 required={required}
                 className={classNames(
@@ -115,8 +119,12 @@ export default function InputComponent({
                     ? " text-clip password "
                     : "",
                   editNode ? " input-edit-node " : "",
-                  password && selectedOption === "" && editNode ? "pr-8" : "",
-                  password && selectedOption === "" && !editNode ? "pr-10" : "",
+                  password && setSelectedOption ? "pr-16" : "",
+                  (!password && setSelectedOption) ||
+                    (password && !setSelectedOption)
+                    ? "pr-8"
+                    : "",
+
                   className!
                 )}
                 placeholder={password && editNode ? "Key" : placeholder}
@@ -179,18 +187,32 @@ export default function InputComponent({
                           setShowOptions(false);
                         }}
                       >
-                        <div className="flex w-full items-center justify-between">
+                        <div className="group flex w-full items-center justify-between">
                           <div className="flex items-center">
-                            <ForwardedIconComponent
-                              name="Check"
+                            <div
                               className={cn(
-                                "mr-2 h-4 w-4 text-primary",
+                                "relative mr-2 h-4 w-4",
                                 selectedOption === option
                                   ? "opacity-100"
                                   : "opacity-0"
                               )}
-                              aria-hidden="true"
-                            />
+                            >
+                              <div className="absolute opacity-100 transition-all group-hover:opacity-0">
+                                <ForwardedIconComponent
+                                  name="Check"
+                                  className="mr-2 h-4 w-4 text-primary"
+                                  aria-hidden="true"
+                                />
+                              </div>
+                              <div className="absolute opacity-0 transition-all group-hover:opacity-100">
+                                <ForwardedIconComponent
+                                  name="X"
+                                  className="mr-2 h-4 w-4 text-status-red"
+                                  aria-hidden="true"
+                                />
+                              </div>
+                            </div>
+
                             {option}
                           </div>
                           {optionButton && optionButton(option)}
@@ -206,10 +228,12 @@ export default function InputComponent({
           <div
             className={cn(
               "pointer-events-auto absolute inset-y-0 h-full w-full cursor-pointer",
-              selectedOption !== "" || !onChange ? "" : "hidden"
+              (selectedOption !== "" || !onChange) && setSelectedOption
+                ? ""
+                : "hidden"
             )}
             onClick={
-              selectedOption !== "" || !onChange
+              (selectedOption !== "" || !onChange) && setSelectedOption
                 ? (e) => {
                     setShowOptions((old) => !old);
                     e.preventDefault();
@@ -221,30 +245,32 @@ export default function InputComponent({
         </>
       )}
 
-      <span
-        className={cn(
-          password && selectedOption === "" ? "right-8" : "right-0",
-          "absolute inset-y-0 flex items-center pr-2.5"
-        )}
-      >
-        <button
-          onClick={() => {
-            setShowOptions(!showOptions);
-          }}
+      {setSelectedOption && (
+        <span
           className={cn(
-            selectedOption !== ""
-              ? "text-medium-indigo"
-              : "text-muted-foreground",
-            "hover:text-accent-foreground"
+            password && selectedOption === "" ? "right-8" : "right-0",
+            "absolute inset-y-0 flex items-center pr-2.5"
           )}
         >
-          <ForwardedIconComponent
-            name={optionsIcon}
-            className={"h-4 w-4"}
-            aria-hidden="true"
-          />
-        </button>
-      </span>
+          <button
+            onClick={() => {
+              setShowOptions(!showOptions);
+            }}
+            className={cn(
+              selectedOption !== ""
+                ? "text-medium-indigo"
+                : "text-muted-foreground",
+              "hover:text-accent-foreground"
+            )}
+          >
+            <ForwardedIconComponent
+              name={optionsIcon}
+              className={"h-4 w-4"}
+              aria-hidden="true"
+            />
+          </button>
+        </span>
+      )}
 
       {password && selectedOption === "" && (
         <button

src/frontend/src/constants/constants.ts

@@ -107,7 +107,7 @@ export const CODE_DIALOG_SUBTITLE =
  * @constant
  */
 export const CHAT_FORM_DIALOG_SUBTITLE =
-  "Set up the input variables defined in prompt templates. Interact with agents and chains.";
+  "Adjust or overwrite input values, inspect outputs or interact through the chat console.";
 
 /**
  * The base text for subtitle of Edit Node Dialog
@@ -732,12 +732,12 @@ export const PRIORITY_SIDEBAR_ORDER = [
   "saved_components",
   "inputs",
   "outputs",
-  "prompts",
   "data",
   "prompt",
   "models",
+  "vectorstores",
+  "vectorsearch",
   "helpers",
-  "experimental",
 ];
 export const NATIVE_CATEGORIES = [
   "inputs",

src/frontend/src/modals/formModal/chatInput/index.tsx

@@ -33,7 +33,7 @@ export default function ChatInput({
     <div className="relative">
       <Textarea
         onKeyDown={(event) => {
-          if (event.key === "Enter" && !lockChat && !event.shiftKey) {
+          if (event.key === "Enter" && !event.nativeEvent.isComposing && !lockChat && !event.shiftKey) {
             sendMessage();
           }
         }}

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

@@ -5,7 +5,6 @@ import ShadTooltip from "../../../../components/ShadTooltipComponent";
 import IconComponent from "../../../../components/genericIconComponent";
 import { Input } from "../../../../components/ui/input";
 import { Separator } from "../../../../components/ui/separator";
-import { PRIORITY_SIDEBAR_ORDER } from "../../../../constants/constants";
 import ExportModal from "../../../../modals/exportModal";
 import ShareModal from "../../../../modals/shareModal";
 import useAlertStore from "../../../../stores/alertStore";
@@ -282,35 +281,7 @@ export default function ExtraSidebar(): JSX.Element {
                     </div>
                   </div>
                 )}
-                {index === PRIORITY_SIDEBAR_ORDER.length - 1 && (
-                  <>
-                    <a
-                      target={"_blank"}
-                      href="https://langflow.store"
-                      className="components-disclosure-arrangement"
-                    >
-                      <div className="flex gap-4">
-                        {/* BUG ON THIS ICON */}
-                        <SparklesIcon
-                          strokeWidth={1.5}
-                          className="w-[22px] text-primary"
-                        />
 
-                        <span className="components-disclosure-title">
-                          Discover More
-                        </span>
-                      </div>
-                      <div className="components-disclosure-div">
-                        <div>
-                          <LinkIcon className="h-4 w-4 text-foreground" />
-                        </div>
-                      </div>
-                    </a>
-                    <div className="p-2 px-4 text-sm font-semibold" key={index}>
-                      Legacy Components
-                    </div>
-                  </>
-                )}
                 <DisclosureComponent
                   openDisc={
                     getFilterEdge.length !== 0 || search.length !== 0
@@ -371,6 +342,32 @@ export default function ExtraSidebar(): JSX.Element {
                       ))}
                   </div>
                 </DisclosureComponent>
+                {index === Object.keys(dataFilter).length - 1 && (
+                  <>
+                    <a
+                      target={"_blank"}
+                      href="https://langflow.store"
+                      className="components-disclosure-arrangement"
+                    >
+                      <div className="flex gap-4">
+                        {/* BUG ON THIS ICON */}
+                        <SparklesIcon
+                          strokeWidth={1.5}
+                          className="w-[22px] text-primary"
+                        />
+
+                        <span className="components-disclosure-title">
+                          Discover More
+                        </span>
+                      </div>
+                      <div className="components-disclosure-div">
+                        <div>
+                          <LinkIcon className="h-4 w-4 text-foreground" />
+                        </div>
+                      </div>
+                    </a>
+                  </>
+                )}
               </>
             ) : (
               <div key={index}></div>

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

@@ -85,7 +85,9 @@ export default function NodeToolbarComponent({
   const [showModalAdvanced, setShowModalAdvanced] = useState(false);
   const [showconfirmShare, setShowconfirmShare] = useState(false);
   const [showOverrideModal, setShowOverrideModal] = useState(false);
-  const [flowComponent, setFlowComponent] = useState<FlowType>();
+  const [flowComponent, setFlowComponent] = useState<FlowType>(
+    createFlowComponent(cloneDeep(data), version)
+  );
 
   const openInNewTab = (url) => {
     window.open(url, "_blank", "noreferrer");
@@ -285,7 +287,13 @@ export default function NodeToolbarComponent({
         event.preventDefault();
         setShowconfirmShare((state) => !state);
       }
-      if (selected && (event.ctrlKey || event.metaKey) && event.key === "q") {
+
+      if (
+        selected &&
+        (event.ctrlKey || event.metaKey) &&
+        event.shiftKey &&
+        event.key === "Q"
+      ) {
         event.preventDefault();
         if (isMinimal) {
           setShowState((show) => !show);
@@ -341,6 +349,10 @@ export default function NodeToolbarComponent({
           title: `${data.id} docs is not available at the moment.`,
         });
       }
+      if (selected && (event.ctrlKey || event.metaKey) && event.key === "j") {
+        event.preventDefault();
+        downloadNode(flowComponent!);
+      }
     }
 
     document.addEventListener("keydown", onKeyDown);
@@ -499,15 +511,17 @@ export default function NodeToolbarComponent({
                   />
                 </SelectItem>
               )}
-              {!hasStore && (
+              {(!hasStore || !hasApiKey || !validApiKey) && (
                 <SelectItem value={"Download"}>
-                  <div className="flex">
-                    <IconComponent
-                      name="Download"
-                      className="relative top-0.5 mr-2 h-4 w-4"
-                    />{" "}
-                    Download{" "}
-                  </div>{" "}
+                  <ToolbarSelectItem
+                    value="Download"
+                    shift={false}
+                    isMac={navigator.userAgent.toUpperCase().includes("MAC")}
+                    icon="Download"
+                    styleObj={{ iconClasses: "relative top-0.5 mr-2 h-4 w-4" }}
+                    keyboardKey={"J"}
+                    dataTestId={"Dowload-button-nodeToolbar"}
+                  />
                 </SelectItem>
               )}
               <SelectItem
@@ -525,24 +539,14 @@ export default function NodeToolbarComponent({
               </SelectItem>
               {isMinimal && (
                 <SelectItem value={"show"}>
-                  <div className="flex">
-                    <IconComponent
-                      name={showNode ? "Minimize2" : "Maximize2"}
-                      className="relative top-0.5 mr-2 h-4 w-4"
-                    />
-                    {showNode ? "Minimize" : "Expand"}
-                    {navigator.userAgent.toUpperCase().includes("MAC") ? (
-                      <IconComponent
-                        name="Command"
-                        className="absolute right-[1.25rem] top-[0.65em] h-3.5 w-3.5 stroke-2"
-                      ></IconComponent>
-                    ) : (
-                      <span className="absolute right-[1.30rem] top-[0.40em] stroke-2">
-                        Ctrl +{" "}
-                      </span>
-                    )}
-                    <span className="absolute right-2 top-[0.46em]">Q</span>
-                  </div>
+                  <ToolbarSelectItem
+                    icon={showNode ? "Minimize2" : "Maximize2"}
+                    value={showNode ? "Minimize" : "Expand"}
+                    isMac={navigator.userAgent.toUpperCase().includes("MAC")}
+                    shift={true}
+                    keyboardKey={"Q"}
+                    dataTestId={"minimize-button-nodeToolbar"}
+                  />
                 </SelectItem>
               )}
               {isGroup && (

src/frontend/src/pages/MainPage/index.tsx

@@ -105,6 +105,8 @@ export default function HomePage(): JSX.Element {
             firstButtonName="New Project"
             onFirstBtnClick={() => setOpenModal(true)}
             options={dropdownOptions}
+            plusButton={true}
+            dropdownOptions={false}
           />
         </div>
       }

src/frontend/src/stores/darkStore.tsx

@@ -4,7 +4,7 @@ import { DarkStoreType } from "../types/zustand/dark";
 
 const startedStars = Number(window.localStorage.getItem("githubStars")) ?? 0;
 
-export const useDarkStore = create<DarkStoreType>((set) => ({
+export const useDarkStore = create<DarkStoreType>((set, get) => ({
   dark: JSON.parse(window.localStorage.getItem("isDark")!) ?? false,
   stars: startedStars,
   version: "",
@@ -15,14 +15,23 @@ export const useDarkStore = create<DarkStoreType>((set) => ({
     });
   },
   refreshStars: () => {
-    if (window.localStorage.getItem("githubStars") !== null) {
-      set(() => ({ stars: startedStars }));
-      return;
+    let lastUpdated = window.localStorage.getItem("githubStarsLastUpdated");
+    let diff = 0;
+    // check if lastUpdated actually exists
+    if (lastUpdated !== null) {
+      diff = Math.abs(new Date().getTime() - new Date(lastUpdated).getTime());
     }
 
-    getRepoStars("logspace-ai", "langflow").then((res) => {
-      window.localStorage.setItem("githubStars", res.toString());
-      set(() => ({ stars: res }));
-    });
+    // if lastUpdated is null or the difference is greater than 2 hours
+    if (lastUpdated === null || diff > 7200000) {
+      getRepoStars("logspace-ai", "langflow").then((res) => {
+        window.localStorage.setItem("githubStars", res.toString());
+        window.localStorage.setItem(
+          "githubStarsLastUpdated",
+          new Date().toString()
+        );
+        set(() => ({ stars: res, lastUpdated: new Date() }));
+      });
+    }
   },
 }));

src/frontend/src/types/components/index.ts

@@ -689,6 +689,8 @@ export type dropdownButtonPropsType = {
   firstButtonName: string;
   onFirstBtnClick: () => void;
   options: Array<{ name: string; onBtnClick: () => void }>;
+  plusButton?: boolean;
+  dropdownOptions?: boolean;
 };
 
 export type IOInputProps = {

src/frontend/src/utils/buildUtils.ts

@@ -119,6 +119,8 @@ export async function buildVertices({
       try {
         onValidateNodes(verticesOrderResponse.verticesToRun);
       } catch (e) {
+        useFlowStore.getState().setIsBuilding(false);
+
         return;
       }
     }

src/frontend/src/utils/reactflowUtils.ts

@@ -1170,7 +1170,7 @@ export function downloadNode(NodeFLow: FlowType) {
     type: "application/json",
   });
   element.href = URL.createObjectURL(file);
-  element.download = `${NodeFLow.name}.json`;
+  element.download = `${NodeFLow?.name??"node"}.json`;
   element.click();
 }
 

src/frontend/src/utils/styleUtils.ts

@@ -236,6 +236,7 @@ export const nodeColors: { [char: string]: string } = {
   embeddings: "#42BAA7",
   documentloaders: "#7AAE42",
   vectorstores: "#AA8742",
+  vectorsearch: "#AA8742",
   textsplitters: "#B47CB5",
   toolkits: "#DB2C2C",
   wrappers: "#E6277A",
@@ -248,6 +249,7 @@ export const nodeColors: { [char: string]: string } = {
   retrievers: "#e6b25a",
   unknown: "#9CA3AF",
   custom_components: "#ab11ab",
+  Record:"#31a3cc"
 };
 
 export const nodeNames: { [char: string]: string } = {
@@ -267,6 +269,7 @@ export const nodeNames: { [char: string]: string } = {
   embeddings: "Embeddings",
   documentloaders: "Loaders",
   vectorstores: "Vector Stores",
+  vectorsearch: "Vector Search",
   toolkits: "Toolkits",
   wrappers: "Wrappers",
   textsplitters: "Text Splitters",
@@ -369,6 +372,7 @@ export const nodeIconsLucide: iconsType = {
   saved_components: GradientSave,
   documentloaders: Paperclip,
   vectorstores: Layers,
+  vectorsearch: Search,
   toolkits: Package2,
   textsplitters: Scissors,
   wrappers: Gift,
@@ -387,7 +391,6 @@ export const nodeIconsLucide: iconsType = {
   Trash2,
   Boxes,
   Network,
-  X,
   XCircle,
   Info,
   CheckCircle2,

src/frontend/tests/end-to-end/assets/ChatTest.json

@@ -0,0 +1,358 @@
+{
+  "id": "3f5e860d-1676-4fba-9d86-06db9f51e43a",
+  "data": {
+    "nodes": [
+      {
+        "id": "ChatInput-7hPDT",
+        "type": "genericNode",
+        "position": {
+          "x": 687,
+          "y": 41.9375
+        },
+        "data": {
+          "type": "ChatInput",
+          "node": {
+            "template": {
+              "code": {
+                "type": "code",
+                "required": true,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatInput(ChatComponent):\n    display_name = \"Chat Input\"\n    description = \"Used to get user input from the chat.\"\n    icon = \"ChatInput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"User\",\n        sender_name: Optional[str] = \"User\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "code",
+                "advanced": true,
+                "dynamic": true,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "input_value": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "input_value",
+                "display_name": "Message",
+                "advanced": false,
+                "input_types": ["Text"],
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "return_record": {
+                "type": "bool",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "return_record",
+                "display_name": "Return Record",
+                "advanced": false,
+                "dynamic": false,
+                "info": "Return the message as a record containing the sender, sender_name, and session_id.",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "sender": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": true,
+                "show": true,
+                "multiline": false,
+                "value": "User",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "options": ["Machine", "User"],
+                "name": "sender",
+                "display_name": "Sender Type",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "sender_name": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": "User",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "sender_name",
+                "display_name": "Sender Name",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "session_id": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "session_id",
+                "display_name": "Session ID",
+                "advanced": true,
+                "dynamic": false,
+                "info": "If provided, the message will be stored in the memory.",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "_type": "CustomComponent"
+            },
+            "description": "Used to get user input from the chat.",
+            "icon": "ChatInput",
+            "base_classes": ["Text", "object", "str", "Record"],
+            "display_name": "Chat Input",
+            "documentation": "",
+            "custom_fields": {
+              "sender": null,
+              "sender_name": null,
+              "input_value": null,
+              "session_id": null,
+              "return_record": null
+            },
+            "output_types": ["Text", "Record"],
+            "field_formatters": {},
+            "frozen": false,
+            "field_order": [],
+            "beta": false
+          },
+          "id": "ChatInput-7hPDT"
+        },
+        "selected": false,
+        "width": 384,
+        "height": 569,
+        "positionAbsolute": {
+          "x": 687,
+          "y": 41.9375
+        },
+        "dragging": false
+      },
+      {
+        "id": "ChatOutput-4sm9Z",
+        "type": "genericNode",
+        "position": {
+          "x": 4.939451516507972,
+          "y": 103.3695231904992
+        },
+        "data": {
+          "type": "ChatOutput",
+          "node": {
+            "template": {
+              "code": {
+                "type": "code",
+                "required": true,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "value": "from typing import Optional, Union\n\nfrom langflow.base.io.chat import ChatComponent\nfrom langflow.field_typing import Text\nfrom langflow.schema import Record\n\n\nclass ChatOutput(ChatComponent):\n    display_name = \"Chat Output\"\n    description = \"Used to send a message to the chat.\"\n    icon = \"ChatOutput\"\n\n    def build(\n        self,\n        sender: Optional[str] = \"Machine\",\n        sender_name: Optional[str] = \"AI\",\n        input_value: Optional[str] = None,\n        session_id: Optional[str] = None,\n        return_record: Optional[bool] = False,\n    ) -> Union[Text, Record]:\n        return super().build(\n            sender=sender,\n            sender_name=sender_name,\n            input_value=input_value,\n            session_id=session_id,\n            return_record=return_record,\n        )\n",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "code",
+                "advanced": true,
+                "dynamic": true,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "input_value": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": true,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "input_value",
+                "display_name": "Message",
+                "advanced": false,
+                "input_types": ["Text"],
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "return_record": {
+                "type": "bool",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "return_record",
+                "display_name": "Return Record",
+                "advanced": false,
+                "dynamic": false,
+                "info": "Return the message as a record containing the sender, sender_name, and session_id.",
+                "load_from_db": false,
+                "title_case": false
+              },
+              "sender": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": true,
+                "show": true,
+                "multiline": false,
+                "value": "Machine",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "options": ["Machine", "User"],
+                "name": "sender",
+                "display_name": "Sender Type",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "sender_name": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "value": "AI",
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "sender_name",
+                "display_name": "Sender Name",
+                "advanced": false,
+                "dynamic": false,
+                "info": "",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "session_id": {
+                "type": "str",
+                "required": false,
+                "placeholder": "",
+                "list": false,
+                "show": true,
+                "multiline": false,
+                "fileTypes": [],
+                "file_path": "",
+                "password": false,
+                "name": "session_id",
+                "display_name": "Session ID",
+                "advanced": true,
+                "dynamic": false,
+                "info": "If provided, the message will be stored in the memory.",
+                "load_from_db": false,
+                "title_case": false,
+                "input_types": ["Text"]
+              },
+              "_type": "CustomComponent"
+            },
+            "description": "Used to send a message to the chat.",
+            "icon": "ChatOutput",
+            "base_classes": ["Text", "object", "str", "Record"],
+            "display_name": "Chat Output",
+            "documentation": "",
+            "custom_fields": {
+              "sender": null,
+              "sender_name": null,
+              "input_value": null,
+              "session_id": null,
+              "return_record": null
+            },
+            "output_types": ["Text", "Record"],
+            "field_formatters": {},
+            "frozen": false,
+            "field_order": [],
+            "beta": false
+          },
+          "id": "ChatOutput-4sm9Z"
+        },
+        "selected": true,
+        "width": 384,
+        "height": 569,
+        "positionAbsolute": {
+          "x": 4.939451516507972,
+          "y": 103.3695231904992
+        },
+        "dragging": false
+      }
+    ],
+    "edges": [
+      {
+        "source": "ChatOutput-4sm9Z",
+        "sourceHandle": "{œbaseClassesœ:[œTextœ,œobjectœ,œstrœ,œRecordœ],œdataTypeœ:œChatOutputœ,œidœ:œChatOutput-4sm9Zœ}",
+        "target": "ChatInput-7hPDT",
+        "targetHandle": "{œfieldNameœ:œinput_valueœ,œidœ:œChatInput-7hPDTœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}",
+        "data": {
+          "targetHandle": {
+            "fieldName": "input_value",
+            "id": "ChatInput-7hPDT",
+            "inputTypes": ["Text"],
+            "type": "str"
+          },
+          "sourceHandle": {
+            "baseClasses": ["Text", "object", "str", "Record"],
+            "dataType": "ChatOutput",
+            "id": "ChatOutput-4sm9Z"
+          }
+        },
+        "style": {
+          "stroke": "#555"
+        },
+        "className": "stroke-gray-900 stroke-connection",
+        "id": "reactflow__edge-ChatOutput-4sm9Z{œbaseClassesœ:[œTextœ,œobjectœ,œstrœ,œRecordœ],œdataTypeœ:œChatOutputœ,œidœ:œChatOutput-4sm9Zœ}-ChatInput-7hPDT{œfieldNameœ:œinput_valueœ,œidœ:œChatInput-7hPDTœ,œinputTypesœ:[œTextœ],œtypeœ:œstrœ}"
+      }
+    ],
+    "viewport": {
+      "x": 316.78239920440234,
+      "y": 182.84104875768622,
+      "zoom": 0.6070974421975234
+    }
+  },
+  "description": "flow to test ChatInput and output",
+  "name": "ChatITest",
+  "last_tested_version": "1.0.0a0",
+  "is_component": false
+}

src/frontend/tests/end-to-end/chat_io.spec.ts

@@ -0,0 +1,46 @@
+import { test } from "@playwright/test";
+import { readFileSync } from "fs";
+test.beforeEach(async ({ page }) => {
+  // await page.waitForTimeout(20000);
+  // test.setTimeout(120000);
+});
+test("chat_io_teste", async ({ page }) => {
+  await page.goto("/");
+  await page.locator("span").filter({ hasText: "My Collection" }).isVisible();
+  // Read your file into a buffer.
+  const jsonContent = readFileSync(
+    "tests/end-to-end/assets/ChatTest.json",
+    "utf-8"
+  );
+
+  // Create the DataTransfer and File
+  const dataTransfer = await page.evaluateHandle((data) => {
+    const dt = new DataTransfer();
+    // Convert the buffer to a hex array
+    const file = new File([data], "ChatTest.json", {
+      type: "application/json",
+    });
+    dt.items.add(file);
+    return dt;
+  }, jsonContent);
+
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await page.waitForTimeout(2000);
+
+  await page.getByTestId("blank-flow").click();
+  await page.waitForTimeout(2000);
+
+  // Now dispatch
+  await page.dispatchEvent(
+    '//*[@id="react-flow-id"]/div[1]/div[1]/div',
+    "drop",
+    {
+      dataTransfer,
+    }
+  );
+  await page.getByLabel("fit view").click();
+  await page.getByText("Run", { exact: true }).click();
+  await page.getByPlaceholder("Send a message...").click();
+  await page.getByPlaceholder("Send a message...").fill("teste");
+  await page.getByRole("button").nth(1).click();
+});

src/frontend/tests/end-to-end/codeAreaModalComponent.spec.ts

@@ -25,86 +25,31 @@ test("CodeAreaModalComponent", async ({ page }) => {
   await page.getByTestId("code-button-modal").click();
 
   let value = await page.locator('//*[@id="codeValue"]').inputValue();
-
-  if (
-    value !=
-    'def python_function(text: str) -> str:    """This is a default python function that returns the input text"""    return text'
-  ) {
-    expect(false).toBeTruthy();
-  }
-
+  const code =
+    'def python_function(text: str) -> str:\n    """This is a default python function that returns the input text"""\n    return text';
+  const wCode =
+    'def python_function(text: str) -> st:    """This is a default python function that returns the input text"""    return text';
+  const assertCode =
+    'def python_function(text: str) -> str:    """This is a default python function that returns the input text"""    return text';
+  await page
+    .locator("#CodeEditor div")
+    .filter({ hasText: "def python_function(text: str" })
+    .nth(1)
+    .click();
+  await page.locator("textarea").press("Control+a");
+  await page.locator("textarea").fill(wCode);
   await page.locator('//*[@id="checkAndSaveBtn"]').click();
-
-  await page.getByTestId("div-generic-node").click();
-
-  await page.getByTestId("more-options-modal").click();
-  await page.getByTestId("edit-button-modal").click();
-
-  await page.locator('//*[@id="showdescription"]').click();
+  await page.waitForTimeout(1000);
   expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showname"]').click();
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeFalsy();
-
-  await page.locator('//*[@id="showreturn_direct"]').click();
-  expect(
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showdescription"]').click();
-  expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
+    await page.getByText("invalid syntax (<unknown>, line 1)").isVisible()
   ).toBeTruthy();
-
-  await page.locator('//*[@id="showname"]').click();
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeTruthy();
-
-  await page.locator('//*[@id="showreturn_direct"]').click();
-  expect(
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
-  ).toBeTruthy();
-
-  await page.locator('//*[@id="showdescription"]').click();
-  expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showname"]').click();
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeFalsy();
-
-  await page.locator('//*[@id="showreturn_direct"]').click();
-  expect(
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
-  ).toBeFalsy();
-
-  await page.locator('//*[@id="showdescription"]').click();
-  expect(
-    await page.locator('//*[@id="showdescription"]').isChecked()
-  ).toBeTruthy();
-
-  await page.locator('//*[@id="showname"]').click();
-  expect(await page.locator('//*[@id="showname"]').isChecked()).toBeTruthy();
-
-  await page.locator('//*[@id="showreturn_direct"]').click();
-  expect(
-    await page.locator('//*[@id="showreturn_direct"]').isChecked()
-  ).toBeTruthy();
-
-  await page.locator('//*[@id="saveChangesBtn"]').click();
-
-  const plusButtonLocator = page.locator('//*[@id="code-input-0"]');
-  const elementCount = await plusButtonLocator.count();
-  if (elementCount === 0) {
-    expect(true).toBeTruthy();
-
-    await page.getByTestId("more-options-modal").click();
-    await page.getByTestId("edit-button-modal").click();
-
-    await page.locator('//*[@id="saveChangesBtn"]').click();
-
-    await page.getByTestId("div-generic-node").click();
-    await page.getByTestId("code-button-modal").click();
-  }
+  await page.locator("textarea").press("Control+a");
+  await page.locator("textarea").fill(wCode);
+  await page.locator("textarea").fill(code);
+  await page.locator('//*[@id="checkAndSaveBtn"]').click();
+  expect(await page.getByText("Code is ready to run").isVisible()).toBeTruthy();
+  await page.getByTestId("code-button-modal").click();
+  expect(await page.locator('//*[@id="codeValue"]').inputValue()).toBe(
+    assertCode
+  );
 });

src/frontend/tests/end-to-end/curl_api_generation.spec.ts

@@ -0,0 +1,17 @@
+import { expect, test } from "@playwright/test";
+
+test("curl_api_generation", async ({ page, context }) => {
+  await page.goto("/");
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  await page.getByRole("heading", { name: "Data Ingestion" }).click();
+  await page.waitForTimeout(2000);
+  await page.getByText("API", { exact: true }).click();
+  await page.getByRole("tab", { name: "cURL" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent = await handle.jsonValue();
+  expect(clipboardContent.length).toBeGreaterThan(0);
+});

src/frontend/tests/end-to-end/python_api_generation.spec.ts

@@ -0,0 +1,17 @@
+import { expect, test } from "@playwright/test";
+
+test("python_api_generation", async ({ page, context }) => {
+  await page.goto("/");
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  await page.getByRole("heading", { name: "Data Ingestion" }).click();
+  await page.waitForTimeout(2000);
+  await page.getByText("API", { exact: true }).click();
+  await page.getByRole("tab", { name: "Python API" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent = await handle.jsonValue();
+  expect(clipboardContent.length).toBeGreaterThan(0);
+});

src/frontend/tests/end-to-end/tweaks_test.spec.ts

@@ -0,0 +1,38 @@
+import { expect, test } from "@playwright/test";
+
+test("curl_api_generation", async ({ page, context }) => {
+  await page.goto("/");
+  await page.locator('//*[@id="new-project-btn"]').click();
+  await context.grantPermissions(["clipboard-read", "clipboard-write"]);
+  await page.getByRole("heading", { name: "Data Ingestion" }).click();
+  await page.waitForTimeout(2000);
+  await page.getByText("API", { exact: true }).click();
+  await page.getByRole("tab", { name: "cURL" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent = await handle.jsonValue();
+  const oldValue = clipboardContent;
+  expect(clipboardContent.length).toBeGreaterThan(0);
+  await page.getByRole("tab", { name: "Tweaks" }).click();
+  await page
+    .getByRole("heading", { name: "URL" })
+    .locator("div")
+    .first()
+    .click();
+  await page.getByRole("textbox", { name: "Type something..." }).click();
+  await page
+    .getByRole("textbox", { name: "Type something..." })
+    .press("Control+a");
+  await page.getByRole("textbox", { name: "Type something..." }).fill("teste");
+  await page.getByRole("tab", { name: "cURL" }).click();
+  await page.getByRole("button", { name: "Copy Code" }).click();
+  const handle2 = await page.evaluateHandle(() =>
+    navigator.clipboard.readText()
+  );
+  const clipboardContent2 = await handle2.jsonValue();
+  const newValue = clipboardContent2;
+  expect(oldValue).not.toBe(newValue);
+  expect(clipboardContent2.length).toBeGreaterThan(clipboardContent.length);
+});