replace .dict() with .model_dump().

`BaseModel.dict()` is deprecated in favor of `BaseModel.model_dump()` in
Pydantic v2.

Author: dlqqq

packages/jupyter-ai-magics/jupyter_ai_magics/magics.py

@@ -442,7 +442,7 @@ def handle_error(self, args: ErrorArgs):
 
         prompt = f"Explain the following error:\n\n{last_error}"
         # Set CellArgs based on ErrorArgs
-        values = args.dict()
+        values = args.model_dump()
         values["type"] = "root"
         cell_args = CellArgs(**values)
 

packages/jupyter-ai/jupyter_ai/callback_handlers/metadata.py

@@ -20,7 +20,7 @@ def requires_no_arguments(func):
 def convert_to_serializable(obj):
     """Convert an object to a JSON serializable format"""
     if hasattr(obj, "dict") and callable(obj.dict) and requires_no_arguments(obj.dict):
-        return obj.dict()
+        return obj.model_dump()
     if hasattr(obj, "__dict__"):
         return obj.__dict__
     return str(obj)

packages/jupyter-ai/jupyter_ai/chat_handlers/generate.py

@@ -13,9 +13,9 @@
 from langchain.chains import LLMChain
 from langchain.llms import BaseLLM
 from langchain.output_parsers import PydanticOutputParser
-from pydantic import BaseModel
 from langchain.schema.output_parser import BaseOutputParser
 from langchain_core.prompts import PromptTemplate
+from pydantic import BaseModel
 
 
 class OutlineSection(BaseModel):
@@ -55,7 +55,7 @@ async def generate_outline(description, llm=None, verbose=False):
     chain = NotebookOutlineChain.from_llm(llm=llm, parser=parser, verbose=verbose)
     outline = await chain.apredict(description=description)
     outline = parser.parse(outline)
-    return outline.dict()
+    return outline.model_dump()
 
 
 class CodeImproverChain(LLMChain):

packages/jupyter-ai/jupyter_ai/completions/handlers/base.py

@@ -61,7 +61,7 @@ def loop(self) -> AbstractEventLoop:
 
     def reply(self, reply: Union[InlineCompletionReply, InlineCompletionStreamChunk]):
         """Write a reply object to the WebSocket connection."""
-        message = reply.dict()
+        message = reply.model_dump()
         super().write_message(message)
 
     def initialize(self):

packages/jupyter-ai/jupyter_ai/config_manager.py

@@ -263,7 +263,7 @@ def _validate_config(self, config: GlobalConfig):
         read and before every write to the config file. Guarantees that the
         config file conforms to the JSON Schema, and that the language and
         embedding models have authn credentials if specified."""
-        self.validator.validate(config.dict())
+        self.validator.validate(config.model_dump())
 
         # validate language model config
         if config.model_provider_id:
@@ -349,10 +349,10 @@ def _write_config(self, new_config: GlobalConfig):
 
         self._validate_config(new_config)
         with open(self.config_path, "w") as f:
-            json.dump(new_config.dict(), f, indent=self.indentation_depth)
+            json.dump(new_config.model_dump(), f, indent=self.indentation_depth)
 
     def delete_api_key(self, key_name: str):
-        config_dict = self._read_config().dict()
+        config_dict = self._read_config().model_dump()
         required_keys = []
         for provider in [
             self.lm_provider,
@@ -386,15 +386,15 @@ def update_config(self, config_update: UpdateConfigRequest):  # type:ignore
                 if not api_key_value:
                     raise KeyEmptyError("API key value cannot be empty.")
 
-        config_dict = self._read_config().dict()
-        Merger.merge(config_dict, config_update.dict(exclude_unset=True))
+        config_dict = self._read_config().model_dump()
+        Merger.merge(config_dict, config_update.model_dump(exclude_unset=True))
         self._write_config(GlobalConfig(**config_dict))
 
     # this cannot be a property, as the parent Configurable already defines the
     # self.config attr.
     def get_config(self):
         config = self._read_config()
-        config_dict = config.dict(exclude_unset=True)
+        config_dict = config.model_dump(exclude_unset=True)
         api_key_names = list(config_dict.pop("api_keys").keys())
         return DescribeConfigResponse(
             **config_dict, api_keys=api_key_names, last_read=self._last_read

packages/jupyter-ai/jupyter_ai/handlers.py

@@ -200,7 +200,7 @@ def open(self):
         """Handles opening of a WebSocket connection. Client ID can be retrieved
         from `self.client_id`."""
 
-        current_user = self.get_chat_user().dict()
+        current_user = self.get_chat_user().model_dump()
         client_id = self.generate_client_id()
 
         self.root_chat_handlers[client_id] = self
@@ -212,7 +212,7 @@ def open(self):
                 history=ChatHistory(
                     messages=self.chat_history, pending_messages=self.pending_messages
                 ),
-            ).dict()
+            ).model_dump()
         )
 
         self.log.info(f"Client connected. ID: {client_id}")
@@ -238,7 +238,7 @@ def broadcast_message(self, message: Message):
         for client_id in client_ids:
             client = self.root_chat_handlers[client_id]
             if client:
-                client.write_message(message.dict())
+                client.write_message(message.model_dump())
 
         # append all messages of type `ChatMessage` directly to the chat history
         if isinstance(