feat: frontend_node_class property and other prompts

src/backend/langflow/config.yaml

@@ -13,6 +13,10 @@ agents:
 prompts:
   - PromptTemplate
   - FewShotPromptTemplate
+  - ChatPromptTemplate
+  - SystemMessagePromptTemplate
+  - AIMessagePromptTemplate
+  - HumanMessagePromptTemplate
 
 llms:
   - OpenAI

src/backend/langflow/custom/customs.py

@@ -1,5 +1,6 @@
 from langflow.template import nodes
 
+# These should always be instantiated
 CUSTOM_NODES = {
     "prompts": {"ZeroShotPrompt": nodes.ZeroShotPromptNode()},
     "tools": {"PythonFunction": nodes.PythonFunctionNode(), "Tool": nodes.ToolNode()},

src/backend/langflow/interface/base.py

@@ -1,4 +1,5 @@
 from abc import ABC, abstractmethod
+import abc
 from typing import Any, Dict, List, Optional, Union
 
 from pydantic import BaseModel
@@ -12,6 +13,11 @@ class LangChainTypeCreator(BaseModel, ABC):
     type_name: str
     type_dict: Optional[Dict] = None
 
+    @property
+    def frontend_node_class(self) -> str:
+        """The class type of the FrontendNode created in frontend_node."""
+        return FrontendNode
+
     @property
     @abstractmethod
     def type_to_loader_dict(self) -> Dict:
@@ -62,7 +68,7 @@ class LangChainTypeCreator(BaseModel, ABC):
             if key != "_type"
         ]
         template = Template(type_name=name, fields=fields)
-        return FrontendNode(
+        return self.frontend_node_class(
             template=template,
             description=signature.get("description", ""),
             base_classes=signature["base_classes"],

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

@@ -1,39 +1,50 @@
 from typing import Dict, List
 
 from langchain.prompts import loading
-
+from langchain import prompts
 from langflow.custom.customs import get_custom_nodes
 from langflow.interface.base import LangChainTypeCreator
+from langflow.interface.importing.utils import import_class
 from langflow.settings import settings
-from langflow.utils.util import build_template_from_function
+from langflow.template.nodes import PromptFrontendNode
+from langflow.utils.util import build_template_from_class
 
 
 class PromptCreator(LangChainTypeCreator):
     type_name: str = "prompts"
 
+    @property
+    def frontend_node_class(self) -> str:
+        return PromptFrontendNode
+
     @property
     def type_to_loader_dict(self) -> Dict:
         if self.type_dict is None:
-            self.type_dict = loading.type_to_loader_dict
+            self.type_dict = {
+                prompt_name: import_class(f"langchain.prompts.{prompt_name}")
+                # if prompt_name is not lower case it is a class
+                for prompt_name in prompts.__all__
+                if not prompt_name.islower() and prompt_name in settings.prompts
+            }
         return self.type_dict
 
     def get_signature(self, name: str) -> Dict | None:
         try:
             if name in get_custom_nodes(self.type_name).keys():
                 return get_custom_nodes(self.type_name)[name]
-            return build_template_from_function(name, self.type_to_loader_dict)
+            return build_template_from_class(name, self.type_to_loader_dict)
         except ValueError as exc:
             raise ValueError("Prompt not found") from exc
 
     def to_list(self) -> List[str]:
         custom_prompts = get_custom_nodes("prompts")
-        library_prompts = [
-            prompt.__annotations__["return"].__name__
-            for prompt in self.type_to_loader_dict.values()
-            if prompt.__annotations__["return"].__name__ in settings.prompts
-            or settings.dev
-        ]
-        return library_prompts + list(custom_prompts.keys())
+        # library_prompts = [
+        #     prompt.__annotations__["return"].__name__
+        #     for prompt in self.type_to_loader_dict.values()
+        #     if prompt.__annotations__["return"].__name__ in settings.prompts
+        #     or settings.dev
+        # ]
+        return list(self.type_to_loader_dict.keys()) + list(custom_prompts.keys())
 
 
 prompt_creator = PromptCreator()

src/backend/langflow/template/base.py

@@ -219,3 +219,5 @@ class FrontendNode(BaseModel):
         elif name == "ChatOpenAI" and key == "model_name":
             field.options = constants.CHAT_OPENAI_MODELS
             field.is_list = True
+
+

src/backend/langflow/template/nodes.py

@@ -6,7 +6,17 @@ from langflow.utils.constants import DEFAULT_PYTHON_FUNCTION
 from langchain.agents import loading
 
 
-class ZeroShotPromptNode(FrontendNode):
+class BasePromptFrontendNode(FrontendNode):
+    name: str
+    template: Template
+    description: str
+    base_classes: list[str]
+
+    def to_dict(self):
+        return super().to_dict()
+
+
+class ZeroShotPromptNode(BasePromptFrontendNode):
     name: str = "ZeroShotPrompt"
     template: Template = Template(
         type_name="zero_shot",
@@ -227,3 +237,13 @@ class CSVAgentNode(FrontendNode):
 
     def to_dict(self):
         return super().to_dict()
+
+
+class PromptFrontendNode(FrontendNode):
+    @staticmethod
+    def format_field(field: TemplateField, name: Optional[str] = None) -> None:
+        # if field.field_type  == "StringPromptTemplate"
+        # change it to str
+        if field.field_type == "StringPromptTemplate":
+            field.field_type = "str"
+            field.multiline = True