Pydantic v1 and v2 compatibility

docs/source/contributors/index.md

@@ -2,6 +2,8 @@
 
 This page is intended for people interested in building new or modified functionality for Jupyter AI.
 
+If you would like to build applications that enhance Jupyter AI, please see the {doc}`developer's guide </developers/index>`.
+
 ## Design principles
 
 Maintainers of Jupyter AI have adopted principles that contributors should also follow. These principles, which build on top of [the Zen of Python](https://peps.python.org/pep-0020/), are intended to earn users' trust by keeping their data under their control. The following list is non-exhaustive; maintainers have discretion to interpret and revise these principles.

docs/source/developers/index.md

@@ -0,0 +1,18 @@
+# Developers
+
+The developer documentation is for authors who want to enhance
+the functionality of Jupyter AI.
+
+If you are interested in contributing to Jupyter AI,
+please see our {doc}`contributor's guide </contributors/index>`.
+
+## Pydantic compatibility
+
+Jupyter AI is fully compatible with Python environments using Pydantic v1
+or Pydantic v2. Jupyter AI imports Pydantic classes from the
+`langchain.pydantic_v1` module. Developers should do the same when they extend
+Jupyter AI classes.
+
+For more details about using `langchain.pydantic_v1` in an environment with
+Pydantic v2 installed, see the
+[LangChain documentation on Pydantic compatibility](https://python.langchain.com/docs/guides/pydantic_compatibility).

docs/source/index.md

@@ -34,4 +34,5 @@ maxdepth: 2
 
 users/index
 contributors/index
+developers/index
 ```

docs/source/users/index.md

@@ -5,6 +5,9 @@ Welcome to the user documentation for Jupyter AI.
 If you are interested in contributing to Jupyter AI,
 please see our {doc}`contributor's guide </contributors/index>`.
 
+If you would like to build applications that enhance Jupyter AI,
+please see the {doc}`developer's guide </developers/index>`.
+
 ## Prerequisites
 
 You can run Jupyter AI on any system that can run a supported Python version
@@ -45,6 +48,13 @@ does not depend on JupyterLab or `jupyter_ai`. You can install
 If you have both `jupyter_ai_magics` and `jupyter_ai` installed, you should
 have the same version of each, to avoid errors.
 
+Jupyter AI internally uses Pydantic v1 and should work with either Pydantic
+version 1 or version 2. For compatibility, developers using Pydantic V2
+should import classes using the `pydantic.v1` package. See the
+[LangChain Pydantic migration plan](https://python.langchain.com/docs/guides/pydantic_compatibility)
+for advice about how developers should use `v1` to avoid mixing v1 and v2
+classes in their code.
+
 ## Installation
 
 ### Installation via `pip`

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

@@ -14,7 +14,7 @@
  HuggingFaceHubEmbeddings,
  OpenAIEmbeddings,
 )
-from pydantic import BaseModel, Extra
+from langchain.pydantic_v1 import BaseModel, Extra
 
 
 class BaseEmbeddingsProvider(BaseModel):

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

@@ -2,7 +2,7 @@
 from typing import Literal, Optional, get_args
 
 import click
-from pydantic import BaseModel
+from langchain.pydantic_v1 import BaseModel
 
 FORMAT_CHOICES_TYPE = Literal[
  "code", "html", "image", "json", "markdown", "math", "md", "text"

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

@@ -39,9 +39,9 @@
 from langchain.llms.sagemaker_endpoint import LLMContentHandler
 from langchain.llms.utils import enforce_stop_tokens
 from langchain.prompts import PromptTemplate
+from langchain.pydantic_v1 import BaseModel, Extra, root_validator
 from langchain.schema import LLMResult
 from langchain.utils import get_from_dict_or_env
-from pydantic import BaseModel, Extra, root_validator
 
 
 class EnvAuthStrategy(BaseModel):

packages/jupyter-ai-magics/pyproject.toml

@@ -22,7 +22,6 @@ dynamic = ["version", "description", "authors", "urls", "keywords"]
 
 dependencies = [
  "ipython",
- "pydantic~=1.0",
  "importlib_metadata>=5.2.0",
  "langchain==0.0.318",
  "typing_extensions>=4.5.0",

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

@@ -13,8 +13,8 @@
 from langchain.llms import BaseLLM
 from langchain.output_parsers import PydanticOutputParser
 from langchain.prompts import PromptTemplate
+from langchain.pydantic_v1 import BaseModel
 from langchain.schema.output_parser import BaseOutputParser
-from pydantic import BaseModel
 
 
 class OutlineSection(BaseModel):

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

@@ -82,8 +82,7 @@ async def process_message(self, message: HumanChatMessage):
  em_provider_cls, em_provider_args = self.get_embedding_provider()
  if not em_provider_cls:
  self.reply(
- "Please select an embedding provider in the chat settings, "
- "then run your **/learn** command again."
+ "Sorry, please select an embedding provider before using the `/learn` command."
  )
  return
 
@@ -122,18 +121,17 @@ async def process_message(self, message: HumanChatMessage):
  )
  self.save()
 
- response = f"""🎉 I have learned from documents at **{load_path}** and
- I am ready to answer questions about them. You can ask questions about these
- documents by starting your message with **/ask**."""
+ response = f"""🎉 I have learned documents at **{load_path}** and I am ready to answer questions about them.
+ You can ask questions about these docs by prefixing your message with **/ask**."""
  self.reply(response, message)
 
  def _build_list_response(self):
  if not self.metadata.dirs:
- return "I haven't learned from any documents yet."
+ return "There are no docs that have been learned yet."
 
  dirs = [dir.path for dir in self.metadata.dirs]
  dir_list = "\n- " + "\n- ".join(dirs) + "\n\n"
- message = f"""I can answer questions about documents in these directories:
+ message = f"""I can answer questions from docs in these directories:
  {dir_list}"""
  return message
 
@@ -200,10 +198,10 @@ async def delete_and_relearn(self):
  self.log.info(
  f"Switching embedding provider from {prev_em_id} to {curr_em_id}."
  )
- message = f"""🔔 Hi there! It seems like you have changed the embedding
+ message = f"""🔔 Hi there, it seems like you have updated the embeddings
  model from `{prev_em_id}` to `{curr_em_id}`. I have to re-learn the
- documents you had previously submitted for learning. Please wait
- until I am done with this task before you use the **/ask** command."""
+ documents you had previously submitted for learning. Please wait to use
+ the **/ask** command until I am done with this task."""
 
  self.reply(message)
 
@@ -238,7 +236,7 @@ async def relearn(self, metadata: IndexMetadata):
  dir_list = (
  "\n- " + "\n- ".join([dir.path for dir in self.metadata.dirs]) + "\n\n"
  )
- message = f"""🎉 I am done learning about documents in these directories:
+ message = f"""🎉 I am done learning docs in these directories:
  {dir_list} I am ready to answer questions about them.
  You can ask me about these documents by starting your message with **/ask**."""
  self.reply(message)

packages/jupyter-ai/jupyter_ai/handlers.py

@@ -11,7 +11,7 @@
 from jupyter_ai.config_manager import ConfigManager, KeyEmptyError, WriteConflictError
 from jupyter_server.base.handlers import APIHandler as BaseAPIHandler
 from jupyter_server.base.handlers import JupyterHandler
-from pydantic import ValidationError
+from langchain.pydantic_v1 import ValidationError
 from tornado import web, websocket
 from tornado.web import HTTPError
 

packages/jupyter-ai/jupyter_ai/models.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Literal, Optional, Union
 
 from jupyter_ai_magics.providers import AuthStrategy, Field
-from pydantic import BaseModel, validator
+from langchain.pydantic_v1 import BaseModel, validator
 
 DEFAULT_CHUNK_SIZE = 2000
 DEFAULT_CHUNK_OVERLAP = 100

packages/jupyter-ai/jupyter_ai/tests/test_config_manager.py

@@ -12,7 +12,7 @@
 )
 from jupyter_ai.models import DescribeConfigResponse, GlobalConfig, UpdateConfigRequest
 from jupyter_ai_magics.utils import get_em_providers, get_lm_providers
-from pydantic import ValidationError
+from langchain.pydantic_v1 import ValidationError
 
 
 @pytest.fixture

packages/jupyter-ai/pyproject.toml

@@ -24,7 +24,6 @@ classifiers = [
 dependencies = [
  "jupyter_server>=1.6,<3",
  "jupyterlab~=4.0",
- "pydantic~=1.0",
  "openai~=0.26",
  "aiosqlite>=0.18",
  "importlib_metadata>=5.2.0",