Merge branch 'zustand/io/migration' of personal:logspace-ai/langflow into zustand/io/migration

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

@@ -12,16 +12,29 @@ class TextComponent(CustomComponent):
 
     def build_config(self):
         return {
-            "input_value": {"display_name": "Value", "input_types": ["Record"], "info": "Text or Record to be passed."},
+            "input_value": {
-            "record_template": {"display_name": "Record Template", "multiline": True},
+                "display_name": "Value",
+                "input_types": ["Text", "Record"],
+                "info": "Text or Record to be passed.",
+            },
+            "record_template": {
+                "display_name": "Record Template",
+                "multiline": True,
+                "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
+                "advanced": True,
+            },
         }
 
     def build(
         self,
         input_value: Optional[Union[Text, Record]] = "",
-        record_template: Optional[str] = "Text: {text}\nData: {data}",
+        record_template: Optional[str] = "{text}",
     ) -> Text:
         if isinstance(input_value, Record):
+            if record_template == "":
+                # it should be dynamically set to the Record's .text_key value
+                # meaning, if text_key = "bacon", then record_template = "{bacon}"
+                record_template = "{" + input_value.text_key + "}"
             input_value = records_to_text(template=record_template, records=input_value)
         self.status = input_value
         if not input_value:

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

@@ -35,6 +35,8 @@ class LCModelComponent(CustomComponent):
         self, runnable: BaseChatModel, stream: bool, input_value: str, system_message: Optional[str] = None
     ):
         messages: list[Union[HumanMessage, SystemMessage]] = []
+        if not input_value and not system_message:
+            raise ValueError("The message you want to send to the model is empty.")
         if system_message:
             messages.append(SystemMessage(content=system_message))
         if input_value:

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

@@ -9,7 +9,7 @@ from langchain_core.documents import Document
 from langflow.interface.custom.custom_component import CustomComponent
 from langflow.schema import Record
 from langflow.field_typing import Text
-from langflow.utils.util import build_loader_repr_from_records, unescape_string
+from langflow.utils.util import unescape_string
 
 
 class SplitTextComponent(CustomComponent):
@@ -54,7 +54,6 @@ class SplitTextComponent(CustomComponent):
         chunk_overlap: Optional[int] = 200,
         recursive: bool = False,
     ) -> list[Record]:
-
         separators = [unescape_string(x) for x in separators]
 
         # Make sure chunk_size and chunk_overlap are ints

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

@@ -13,15 +13,20 @@ class TextInput(TextComponent):
         return {
             "input_value": {
                 "display_name": "Value",
-                "input_types": ["Record"],
+                "input_types": ["Text", "Record"],
                 "info": "Text or Record to be passed as input.",
             },
-            "record_template": {"display_name": "Record Template", "multiline": True},
+            "record_template": {
+                "display_name": "Record Template",
+                "multiline": True,
+                "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
+                "advanced": True,
+            },
         }
 
     def build(
         self,
         input_value: Optional[str] = "",
-        record_template: Optional[str] = "{text}",
+        record_template: Optional[str] = "",
     ) -> Text:
         return super().build(input_value=input_value, record_template=record_template)

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

@@ -16,8 +16,13 @@ class TextOutput(TextComponent):
                 "input_types": ["Record"],
                 "info": "Text or Record to be passed as output.",
             },
-            "record_template": {"display_name": "Record Template", "multiline": True},
+            "record_template": {
+                "display_name": "Record Template",
+                "multiline": True,
+                "info": "Template to convert Record to Text. If left empty, it will be dynamically set to the Record's text key.",
+                "advanced": True,
+            },
         }
 
-    def build(self, input_value: Optional[Text] = "", record_template: str = "{text}") -> Text:
+    def build(self, input_value: Optional[Text] = "", record_template: str = "") -> Text:
         return super().build(input_value=input_value, record_template=record_template)

src/backend/base/langflow/graph/graph/base.py

@@ -603,8 +603,7 @@ class Graph:
         # This is a hack to make sure that the LLM vertex is sent to
         # the toolkit vertex
         self._build_vertex_params()
-        # remove invalid vertices
+
-        self._validate_vertices()
         # Now that we have the vertices and edges
         # We need to map the vertices that are connected to
         # to ChatVertex instances
@@ -631,14 +630,6 @@ class Graph:
                 if isinstance(vertex, ToolkitVertex):
                     vertex.params["llm"] = llm_vertex
 
-    def _validate_vertices(self) -> None:
-        """Check that all vertices have edges"""
-        if len(self.vertices) == 1:
-            return
-        for vertex in self.vertices:
-            if not self._validate_vertex(vertex):
-                raise ValueError(f"{vertex.display_name} is not connected to any other components")
-
     def _validate_vertex(self, vertex: Vertex) -> bool:
         """Validates a vertex."""
         # All vertices that do not have edges are invalid

src/frontend/src/components/EditFlowSettingsComponent/index.tsx

@@ -74,12 +74,11 @@ export const EditFlowSettings: React.FC<InputProps> = ({
             onChange={handleDescriptionChange}
             value={description!}
             placeholder="Flow description"
-            className="mt-2 max-h-[100px] font-normal resize-none"
+            className="mt-2 max-h-[100px] resize-none font-normal"
             rows={3}
             onDoubleClickCapture={(event) => {
               handleFocus(event);
             }}
-            
           />
         ) : (
           <span

src/frontend/src/icons/GoogleGenerativeAI/Google Gemini icon.svg

@@ -0,0 +1 @@
+<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16"><path d="M16 8.016A8.522 8.522 0 008.016 16h-.032A8.521 8.521 0 000 8.016v-.032A8.521 8.521 0 007.984 0h.032A8.522 8.522 0 0016 7.984v.032z" fill="url(#prefix__paint0_radial_980_20147)"/><defs><radialGradient id="prefix__paint0_radial_980_20147" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="matrix(16.1326 5.4553 -43.70045 129.2322 1.588 6.503)"><stop offset=".067" stop-color="#9168C0"/><stop offset=".343" stop-color="#5684D1"/><stop offset=".672" stop-color="#1BA1E3"/></radialGradient></defs></svg>

src/frontend/src/icons/GoogleGenerativeAI/GoogleGemini.jsx

@@ -0,0 +1,10 @@
+const SvgGoogleGenerativeAI = (props) => (<svg fill="none" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 16 16" {...props}>
+  <path d="M16 8.016A8.522 8.522 0 008.016 16h-.032A8.521 8.521 0 000 8.016v-.032A8.521 8.521 0 007.984 0h.032A8.522 8.522 0 0016 7.984v.032z" fill="url(#prefix__paint0_radial_980_20147)"/>
+  <defs>
+    <radialGradient id="prefix__paint0_radial_980_20147" cx="0" cy="0" r="1" gradientUnits="userSpaceOnUse" gradientTransform="matrix(16.1326 5.4553 -43.70045 129.2322 1.588 6.503)">
+      <stop offset=".067" stop-color="#9168C0"/><stop offset=".343" stop-color="#5684D1"/><stop offset=".672" stop-color="#1BA1E3"/>
+      </radialGradient>
+      </defs>
+  </svg>
+);
+export default SvgGoogleGenerativeAI;

src/frontend/src/icons/GoogleGenerativeAI/index.tsx

@@ -0,0 +1,9 @@
+import React, { forwardRef } from "react";
+import SvgGoogleGenerativeAI from "./GoogleGemini";
+
+export const GoogleGenerativeAIIcon = forwardRef<
+  SVGSVGElement,
+  React.PropsWithChildren<{}>
+>((props, ref) => {
+  return <SvgGoogleGenerativeAI ref={ref} {...props} />;
+});

src/frontend/src/utils/styleUtils.ts

@@ -151,6 +151,7 @@ import { EvernoteIcon } from "../icons/Evernote";
 import { FBIcon } from "../icons/FacebookMessenger";
 import { GitBookIcon } from "../icons/GitBook";
 import { GoogleIcon } from "../icons/Google";
+import { GoogleGenerativeAIIcon } from "../icons/GoogleGenerativeAI";
 import {
   GradientInfinity,
   GradientSave,
@@ -328,6 +329,7 @@ export const nodeIconsLucide: iconsType = {
   GoogleSearchResults: GoogleIcon,
   GoogleSearchRun: GoogleIcon,
   Google: GoogleIcon,
+  GoogleGenerativeAI: GoogleGenerativeAIIcon,
   HNLoader: HackerNewsIcon,
   HuggingFaceHub: HuggingFaceIcon,
   HuggingFace: HuggingFaceIcon,