Refactor utils.py and message.py modules

This commit refactors the `utils.py` module in the `base/prompts` directory and the `message.py` module in the `schema` directory. The changes include:
- Importing the `Message` class from `langflow.schema.message` in `utils.py`
- Importing various modules and classes from `langchain_core` in `message.py`
- Adding a new method `load_lc_prompt` to the `Message` class in `message.py`
- Adding a new class method `from_lc_prompt` to the `Message` class in `message.py`
- Adding a new method `format_text` to the `Message` class in `message.py`
- Adding a new class method `from_template_and_variables` to the `Message` class in `message.py`

These changes improve the organization and functionality of the code in the mentioned modules.

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

@@ -3,7 +3,6 @@ from copy import deepcopy
 from langchain_core.documents import Document
 
 from langflow.schema import Data
-from langflow.schema.message import Message
 
 
 def data_to_string(record: Data) -> str:
@@ -29,6 +28,8 @@ def dict_values_to_string(d: dict) -> dict:
     Returns:
         dict: The dictionary with values converted to strings.
     """
+    from langflow.schema.message import Message
+
     # Do something similar to the above
     d_copy = deepcopy(d)
     for key, value in d_copy.items():

src/backend/base/langflow/schema/message.py

@@ -1,11 +1,14 @@
 from datetime import datetime, timezone
 from typing import Annotated, Any, AsyncIterator, Iterator, Optional
 
+from langchain_core.load import load
 from langchain_core.messages import AIMessage, BaseMessage, HumanMessage
 from langchain_core.prompt_values import ImagePromptValue
+from langchain_core.prompts import BaseChatPromptTemplate, ChatPromptTemplate, PromptTemplate
 from langchain_core.prompts.image import ImagePromptTemplate
 from pydantic import BeforeValidator, ConfigDict, Field, field_serializer
 
+from langflow.base.prompts.utils import dict_values_to_string
 from langflow.schema.data import Data
 from langflow.schema.image import Image, get_file_paths, is_image_file
 
@@ -110,3 +113,37 @@ class Message(Data):
                 image_prompt_value: ImagePromptValue = image_template.invoke(input={"path": file})
                 content_dicts.append({"type": "image_url", "image_url": image_prompt_value.image_url})
         return content_dicts
+
+    def load_lc_prompt(self):
+        if "prompt" not in self:
+            raise ValueError("Prompt is required.")
+        return load(self.prompt)
+
+    @classmethod
+    def from_lc_prompt(
+        cls,
+        prompt: BaseChatPromptTemplate,
+    ):
+        prompt_json = prompt.to_json()
+        return cls(prompt=prompt_json)
+
+    def format_text(self):
+        prompt_template = PromptTemplate.from_template(self.template)
+        variables_with_str_values = dict_values_to_string(self.variables)
+        formatted_prompt = prompt_template.format(**variables_with_str_values)
+        self.text = formatted_prompt
+        return formatted_prompt
+
+    @classmethod
+    async def from_template_and_variables(cls, template: str, variables: dict):
+        instance = cls(template=template, variables=variables)
+        contents = [{"type": "text", "text": instance.format_text()}]
+        # Get all Message instances from the kwargs
+        for value in variables.values():
+            if isinstance(value, cls):
+                content_dicts = await value.get_file_content_dicts()
+                contents.extend(content_dicts)
+        prompt_template = ChatPromptTemplate.from_messages([HumanMessage(content=contents)])
+        instance.messages = prompt_template.messages
+        instance.prompt = prompt_template.to_json()
+        return instance