feat: Add Prompt component to prompts/__init__.py

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

@@ -1,150 +1,115 @@
-from typing import Dict, List, Optional
-
 from langchain_openai.embeddings.base import OpenAIEmbeddings
-from pydantic.v1 import SecretStr
+from langflow.base.models.model import LCModelComponent
-
+from langflow.field_typing import Embeddings
-from langflow.custom import CustomComponent
+from langflow.inputs import (
-from langflow.field_typing import Embeddings, NestedDict
+    BoolInput,
+    DictInput,
+    FloatInput,
+    IntInput,
+    SecretStrInput,
+    StrInput,
+    DropdownInput
+)
+from langflow.template import Output
 
 
-class OpenAIEmbeddingsComponent(CustomComponent):
+class OpenAIEmbeddingsComponent(LCModelComponent):
     display_name = "OpenAI Embeddings"
     description = "Generate embeddings using OpenAI models."
+    icon = "OpenAI"
+    inputs = [
+        DictInput(
+            name="default_headers",
+            display_name="Default Headers",
+            advanced=True,
+            info="Default headers to use for the API request.",
+        ),
+        DictInput(
+            name="default_query",
+            display_name="Default Query",
+            advanced=True,
+            info="Default query parameters to use for the API request.",
+        ),
+        IntInput(name="chunk_size", display_name="Chunk Size", advanced=True, value=1000),
+        StrInput(name="client", display_name="Client", advanced=True),
+        StrInput(name="deployment", display_name="Deployment", advanced=True),
+        IntInput(
+            name="embedding_ctx_length",
+            display_name="Embedding Context Length",
+            advanced=True,
+            value=1536
+        ),
+        IntInput(name="max_retries", display_name="Max Retries", value=3, advanced=True),
+        DropdownInput(
+            name="model",
+            display_name="Model",
+            advanced=False,
+            options=[
+                "text-embedding-3-small",
+                "text-embedding-3-large",
+                "text-embedding-ada-002",
+            ],
+            value="text-embedding-3-small"
+        ),
+        DictInput(name="model_kwargs", display_name="Model Kwargs", advanced=True),
+        SecretStrInput(
+            name="openai_api_base", display_name="OpenAI API Base", advanced=True
+        ),
+        SecretStrInput(name="openai_api_key", display_name="OpenAI API Key"),
+        SecretStrInput(
+            name="openai_api_type", display_name="OpenAI API Type", advanced=True
+        ),
+        StrInput(
+            name="openai_api_version", display_name="OpenAI API Version", advanced=True
+        ),
+        StrInput(
+            name="openai_organization",
+            display_name="OpenAI Organization",
+            advanced=True,
+        ),
+        StrInput(name="openai_proxy", display_name="OpenAI Proxy", advanced=True),
+        FloatInput(
+            name="request_timeout", display_name="Request Timeout", advanced=True
+        ),
+        BoolInput(
+            name="show_progress_bar", display_name="Show Progress Bar", advanced=True
+        ),
+        BoolInput(name="skip_empty", display_name="Skip Empty", advanced=True),
+        StrInput(
+            name="tiktoken_model_name",
+            display_name="TikToken Model Name",
+            advanced=True,
+        ),
+        BoolInput(
+            name="tiktoken_enable", display_name="TikToken Enable", advanced=True
+        ),
+    ]
 
-    def build_config(self):
+    outputs = [
-        return {
+        Output(display_name="Embeddings", name="embeddings", method="build_embeddings"),
-            "allowed_special": {
+    ]
-                "display_name": "Allowed Special",
-                "advanced": True,
-                "field_type": "str",
-                "is_list": True,
-            },
-            "default_headers": {
-                "display_name": "Default Headers",
-                "advanced": True,
-                "field_type": "dict",
-            },
-            "default_query": {
-                "display_name": "Default Query",
-                "advanced": True,
-                "field_type": "NestedDict",
-            },
-            "disallowed_special": {
-                "display_name": "Disallowed Special",
-                "advanced": True,
-                "field_type": "str",
-                "is_list": True,
-            },
-            "chunk_size": {"display_name": "Chunk Size", "advanced": True},
-            "client": {"display_name": "Client", "advanced": True},
-            "deployment": {"display_name": "Deployment", "advanced": True},
-            "embedding_ctx_length": {
-                "display_name": "Embedding Context Length",
-                "advanced": True,
-            },
-            "max_retries": {"display_name": "Max Retries", "advanced": True},
-            "model": {
-                "display_name": "Model",
-                "advanced": False,
-                "options": [
-                    "text-embedding-3-small",
-                    "text-embedding-3-large",
-                    "text-embedding-ada-002",
-                ],
-            },
-            "model_kwargs": {"display_name": "Model Kwargs", "advanced": True},
-            "openai_api_base": {
-                "display_name": "OpenAI API Base",
-                "password": True,
-                "advanced": True,
-            },
-            "openai_api_key": {"display_name": "OpenAI API Key", "password": True},
-            "openai_api_type": {
-                "display_name": "OpenAI API Type",
-                "advanced": True,
-                "password": True,
-            },
-            "openai_api_version": {
-                "display_name": "OpenAI API Version",
-                "advanced": True,
-            },
-            "openai_organization": {
-                "display_name": "OpenAI Organization",
-                "advanced": True,
-            },
-            "openai_proxy": {"display_name": "OpenAI Proxy", "advanced": True},
-            "request_timeout": {"display_name": "Request Timeout", "advanced": True},
-            "show_progress_bar": {
-                "display_name": "Show Progress Bar",
-                "advanced": True,
-            },
-            "skip_empty": {"display_name": "Skip Empty", "advanced": True},
-            "tiktoken_model_name": {
-                "display_name": "TikToken Model Name",
-                "advanced": True,
-            },
-            "tiktoken_enable": {"display_name": "TikToken Enable", "advanced": True},
-            "dimensions": {
-                "display_name": "Dimensions",
-                "info": "The number of dimensions the resulting output embeddings should have. Only supported by certain models.",
-                "advanced": True,
-            },
-        }
-
-    def build(
-        self,
-        openai_api_key: str,
-        default_headers: Optional[Dict[str, str]] = None,
-        default_query: Optional[NestedDict] = {},
-        allowed_special: List[str] = [],
-        disallowed_special: List[str] = ["all"],
-        chunk_size: int = 1000,
-        deployment: str = "text-embedding-ada-002",
-        embedding_ctx_length: int = 8191,
-        max_retries: int = 6,
-        model: str = "text-embedding-ada-002",
-        model_kwargs: NestedDict = {},
-        openai_api_base: Optional[str] = None,
-        openai_api_type: Optional[str] = None,
-        openai_api_version: Optional[str] = None,
-        openai_organization: Optional[str] = None,
-        openai_proxy: Optional[str] = None,
-        request_timeout: Optional[float] = None,
-        show_progress_bar: bool = False,
-        skip_empty: bool = False,
-        tiktoken_enable: bool = True,
-        tiktoken_model_name: Optional[str] = None,
-        dimensions: Optional[int] = None,
-    ) -> Embeddings:
-        # This is to avoid errors with Vector Stores (e.g Chroma)
-        if disallowed_special == ["all"]:
-            disallowed_special = "all"  # type: ignore
-        if openai_api_key:
-            api_key = SecretStr(openai_api_key)
-        else:
-            api_key = None
 
+    def build_embeddings(self) -> Embeddings:
         return OpenAIEmbeddings(
-            tiktoken_enabled=tiktoken_enable,
+            tiktoken_enabled=self.tiktoken_enable,
-            default_headers=default_headers,
+            default_headers=self.default_headers,
-            default_query=default_query,
+            default_query=self.default_query,
-            allowed_special=set(allowed_special),
+            allowed_special="all",
             disallowed_special="all",
-            chunk_size=chunk_size,
+            chunk_size=self.chunk_size,
-            deployment=deployment,
+            deployment=self.deployment,
-            embedding_ctx_length=embedding_ctx_length,
+            embedding_ctx_length=self.embedding_ctx_length,
-            max_retries=max_retries,
+            max_retries=self.max_retries,
-            model=model,
+            model=self.model,
-            model_kwargs=model_kwargs,
+            model_kwargs=self.model_kwargs,
-            base_url=openai_api_base,
+            base_url=self.openai_api_base,
-            api_key=api_key,
+            api_key=self.openai_api_key,
-            openai_api_type=openai_api_type,
+            openai_api_type=self.openai_api_type,
-            api_version=openai_api_version,
+            api_version=self.openai_api_version,
-            organization=openai_organization,
+            organization=self.openai_organization,
-            openai_proxy=openai_proxy,
+            openai_proxy=self.openai_proxy,
-            timeout=request_timeout,
+            timeout=self.request_timeout,
-            show_progress_bar=show_progress_bar,
+            show_progress_bar=self.show_progress_bar,
-            skip_empty=skip_empty,
+            skip_empty=self.skip_empty,
-            tiktoken_model_name=tiktoken_model_name,
+            tiktoken_model_name=self.tiktoken_model_name,
-            dimensions=dimensions,
         )

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

@@ -12,7 +12,7 @@ class ParseDataComponent(Component):
 
     inputs = [
         HandleInput(
-            name="data", display_name="Data", info="The data to convert to text.", input_types=["Message", "Data"]
+            name="data", display_name="Data", info="The data to convert to text.", input_types=["Data"]
         ),
         MultilineInput(
             name="template",
@@ -27,7 +27,7 @@ class ParseDataComponent(Component):
 
     def parse_data_to_text(self) -> Text:
         data = self.data if isinstance(self.data, list) else [self.data]
-        template = self.template or "Text: {text}"
+        template = self.template
 
         result_string = data_to_text(template, data)
         self.status = result_string

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

@@ -0,0 +1,3 @@
+from .Prompt import Prompt
+
+__all__ = ["Prompt"]

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

@@ -57,30 +57,30 @@ def __getattr__(name: str) -> Any:
 
 
 __all__ = [
-    "NestedDict",
+    "AgentExecutor",
-    "Data",
-    "Tool",
-    "PromptTemplate",
-    "Chain",
     "BaseChatMemory",
-    "BaseLLM",
     "BaseLanguageModel",
+    "BaseLLM",
     "BaseLoader",
     "BaseMemory",
     "BaseOutputParser",
-    "BaseRetriever",
-    "VectorStore",
-    "Embeddings",
-    "TextSplitter",
-    "Document",
-    "AgentExecutor",
-    "Text",
-    "Object",
-    "Callable",
     "BasePromptTemplate",
+    "BaseRetriever",
+    "Callable",
+    "Chain",
     "ChatPromptTemplate",
-    "Prompt",
-    "RangeSpec",
-    "Input",
     "Code",
+    "Data",
+    "Document",
+    "Embeddings",
+    "Input",
+    "NestedDict",
+    "Object",
+    "Prompt",
+    "PromptTemplate",
+    "RangeSpec",
+    "Text",
+    "TextSplitter",
+    "Tool",
+    "VectorStore",
 ]

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

@@ -23,6 +23,11 @@ class HandleInput(BaseInputMixin, ListableInputMixin):
     field_type: Optional[SerializableFieldTypes] = FieldTypes.OTHER
 
 
+# class DataInput(HandleInput):
+#     input_types: list[str] = ["Data"]
+# ! Let's add this?
+
+
 class PromptInput(BaseInputMixin, ListableInputMixin):
     field_type: Optional[SerializableFieldTypes] = FieldTypes.PROMPT
 
@@ -38,29 +43,29 @@ class StrInput(BaseInputMixin, ListableInputMixin, DatabaseLoadMixin):  # noqa:
 class TextInput(StrInput):
     input_types: list[str] = ["Data", "Message", "Text"]
 
-    @field_validator("value")
+    # @field_validator("value")
-    @classmethod
+    # @classmethod
-    def validate_value(cls, v: Any, _info):
+    # def validate_value(cls, v: Any, _info):
-        value = None
+    #     value = None
-        if isinstance(v, str):
+    #     if isinstance(v, str):
-            value = v
+    #         value = v
-        elif isinstance(v, Message):
+    #     elif isinstance(v, Message):
-            value = v.text
+    #         value = v.text
-        elif isinstance(v, Data):
+    #     elif isinstance(v, Data):
-            if v.text_key in v.data:
+    #         if v.text_key in v.data:
-                value = v.data[v.text_key]
+    #             value = v.data[v.text_key]
-            else:
+    #         else:
-                keys = ", ".join(v.data.keys())
+    #             keys = ", ".join(v.data.keys())
-                input_name = _info.data["name"]
+    #             input_name = _info.data["name"]
-                raise ValueError(
+    #             raise ValueError(
-                    f"The input to '{input_name}' must contain the key '{v.text_key}'."
+    #                 f"The input to '{input_name}' must contain the key '{v.text_key}'."
-                    f"You can set `text_key` to one of the following keys: {keys} or set the value using another Component."
+    #                 f"You can set `text_key` to one of the following keys: {keys} or set the value using another Component."
-                )
+    #             )
-        else:
+    #     else:
-            raise ValueError(f"Invalid input type {type(v)}")
+    #         raise ValueError(f"Invalid input type {type(v)}")
-        if isinstance(value, str):
+    #     if isinstance(value, str):
-            return value
+    #         return value
-        raise ValueError(f"Invalid value type {type(value)}")
+    #     raise ValueError(f"Invalid value type {type(value)}")
 
 
 class MultilineInput(BaseInputMixin):
@@ -108,16 +113,17 @@ class FileInput(BaseInputMixin, ListableInputMixin, FileMixin):
 
 
 InputTypes = Union[
-    StrInput,
-    SecretStrInput,
-    IntInput,
-    FloatInput,
     BoolInput,
-    NestedDictInput,
+    # DataInput, # ! Let's add this
     DictInput,
     DropdownInput,
     FileInput,
-    PromptInput,
+    FloatInput,
-    MultilineInput,
     HandleInput,
+    IntInput,
+    MultilineInput,
+    NestedDictInput,
+    PromptInput,
+    SecretStrInput,
+    StrInput,
 ]

src/frontend/src/utils/styleUtils.ts

@@ -247,7 +247,6 @@ export const nodeColors: { [char: string]: string } = {
   models: "#ab11ab",
   model_specs: "#6344BE",
   chains: "#FE7500",
-  Document: "#7AAE42",
   list: "#9AAE42",
   agents: "#903BBE",
   tools: "#FF3434",
@@ -267,14 +266,18 @@ export const nodeColors: { [char: string]: string } = {
   experimental: "#E6277A",
   langchain_utilities: "#31A3CC",
   output_parsers: "#E6A627",
-  str: "#4367BF",
-  Text: "#4367BF",
-  retrievers: "#e6b25a",
-  unknown: "#9CA3AF",
   // custom_components: "#ab11ab",
-  Data: "#9CA3AF",
+  retrievers: "#e6b25a",
-  Message: "#4367BF",
+  //
-  BaseLanguageModel: "#ab11ab",
+  str: "#2563eb",
+  Text: "#2563eb",
+  unknown: "#9CA3AF",
+  Document: "#65a30d",
+  Data: "#dc2626",
+  Message: "#4f46e5",
+  Prompt: "#7c3aed",
+  Embeddings: "#10b981",
+  BaseLanguageModel: "#c026d3",
 };
 
 export const nodeNames: { [char: string]: string } = {