fix: API reference doc pipeline (#108)

* fix: API reference doc pipeline * use code blocks * remove breaking changes

Author: averikitsch

.kokoro/publish-docs.sh

@@ -27,7 +27,8 @@ python3 -m nox --version
 # build docs
 nox -s docs
 
-VERSION=$(python -c "import langchain_google_cloud_sql_pg;print(langchain_google_cloud_sql_pg.__version__)")
+python3 -m pip install .
+VERSION=$(python3 -c "import langchain_google_cloud_sql_pg;print(langchain_google_cloud_sql_pg.__version__)")
 
 # create metadata
 python3 -m docuploader create-metadata \

README.rst

@@ -4,7 +4,6 @@ Cloud SQL for PostgreSQL for LangChain
 |preview| |pypi| |versions|
 
 - `Client Library Documentation`_
-- `How-to Guides`_
 - `Product Documentation`_
 
 .. |preview| image:: https://img.shields.io/badge/support-preview-orange.svg
@@ -14,7 +13,6 @@ Cloud SQL for PostgreSQL for LangChain
 .. |versions| image:: https://img.shields.io/pypi/pyversions/langchain-google-cloud-sql-pg.svg
  :target: https://pypi.org/project/langchain-google-cloud-sql-pg/
 .. _Client Library Documentation: https://github.com/googleapis/langchain-google-cloud-sql-pg-python
-.. _How-to Guides: https://github.com/googleapis/langchain-google-cloud-sql-pg-python/tree/main/samples
 .. _Product Documentation: https://cloud.google.com/sql/docs
 
 Quick Start
@@ -87,70 +85,70 @@ Vector Store Usage
 
 Use a Vector Store to store embedded data and perform vector search.
 
-.. code:: python
+.. code-block:: python
 
- from langchain_google_cloud_sql_pg import PostgresVectorstore, PostgresEngine
- from langchain.embeddings import VertexAIEmbeddings
+  from langchain_google_cloud_sql_pg import PostgresVectorstore, PostgresEngine
+  from langchain.embeddings import VertexAIEmbeddings
 
 
- engine = PostgresEngine.from_instance("project-id", "region", "my-instance", "my-database")
- engine.init_vectorstore_table(
- table_name="my-table",
- vector_size=768, # Vector size for `VertexAIEmbeddings()`
- )
- embeddings_service = VertexAIEmbeddings()
- vectorstore = PostgresVectorStore.create_sync(
- engine,
- table_name="my-table",
- embeddings=embedding_service
- )
+  engine = PostgresEngine.from_instance("project-id", "region", "my-instance", "my-database")
+  engine.init_vectorstore_table(
+  table_name="my-table",
+  vector_size=768, # Vector size for `VertexAIEmbeddings()`
+  )
+  embeddings_service = VertexAIEmbeddings()
+  vectorstore = PostgresVectorStore.create_sync(
+  engine,
+  table_name="my-table",
+  embeddings=embedding_service
+  )
 
 See the full `Vector Store`_ tutorial.
 
-.. _`Vector Store`: https://github.com/googleapis/langchain-google-cloud-sql-pg-python/tree/main/samples/vector_store.ipynb
+.. _`Vector Store`: https://github.com/googleapis/langchain-google-cloud-sql-pg-python/tree/main/docs/vector_store.ipynb
 
 Document Loader Usage
 ~~~~~~~~~~~~~~~~~~~~~
 
 Use a document loader to load data as Documents.
 
-.. code:: python
+.. code-block:: python
 
- from langchain_google_cloud_sql_pg import PostgresEngine, PostgresLoader
+  from langchain_google_cloud_sql_pg import PostgresEngine, PostgresLoader
 
 
- engine = PostgresEngine.from_instance("project-id", "region", "my-instance", "my-database")
- loader = PostgresSQLLoader.create_sync(
- engine,
- table_name="my-table-name"
- )
- docs = loader.lazy_load()
+  engine = PostgresEngine.from_instance("project-id", "region", "my-instance", "my-database")
+  loader = PostgresSQLLoader.create_sync(
+  engine,
+  table_name="my-table-name"
+  )
+  docs = loader.lazy_load()
 
 See the full `Document Loader`_ tutorial.
 
-.. _`Document Loader`: https://github.com/googleapis/langchain-google-cloud-sql-pg-python/tree/main/samples/document_loader.ipynb
+.. _`Document Loader`: https://github.com/googleapis/langchain-google-cloud-sql-pg-python/tree/main/docs/document_loader.ipynb
 
 Chat Message History Usage
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 Use Chat Message History to store messages and provide conversation history to LLMs.
 
-.. code:: python
+.. code-block:: python
 
- from langchain_google_cloud_sql_pg import PostgresChatMessageHistory, PostgresEngine
+  from langchain_google_cloud_sql_pg import PostgresChatMessageHistory, PostgresEngine
 
 
- engine = PostgresEngine.from_instance("project-id", "region", "my-instance", "my-database")
- engine.init_chat_history_table(table_name="my-message-store")
- history = PostgresChatMessageHistory.create_sync(
- engine,
- table_name="my-message-store",
- session_id="my-session_id"
- )
+  engine = PostgresEngine.from_instance("project-id", "region", "my-instance", "my-database")
+  engine.init_chat_history_table(table_name="my-message-store")
+  history = PostgresChatMessageHistory.create_sync(
+  engine,
+  table_name="my-message-store",
+  session_id="my-session_id"
+  )
 
 See the full `Chat Message History`_ tutorial.
 
-.. _`Chat Message History`: https://github.com/googleapis/langchain-google-cloud-sql-pg-python/tree/main/samples/chat_message_history.ipynb
+.. _`Chat Message History`: https://github.com/googleapis/langchain-google-cloud-sql-pg-python/tree/main/docs/chat_message_history.ipynb
 
 Contributing
 ~~~~~~~~~~~~

samples/chat_message_history.ipynb renamed to docs/chat_message_history.ipynb

@@ -555,4 +555,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}

samples/document_loader.ipynb renamed to docs/document_loader.ipynb

@@ -19,6 +19,8 @@
 import os
 import pathlib
 import shutil
+from pathlib import Path
+from typing import Optional
 
 import nox
 
@@ -28,6 +30,7 @@
 # 'docfx' is excluded since it only needs to run in 'docs-presubmit'
 nox.options.sessions = [
  "docs",
+ "docfx",
 ]
 
 # Error if a python version is missing

samples/vector_store.ipynb renamed to docs/vector_store.ipynb

@@ -2,7 +2,7 @@
 name = "langchain-google-cloud-sql-pg"
 dynamic = ["version"]
 description = "LangChain integrations for Google Cloud SQL for PostgreSQL"
-readme = "README.md"
+readme = "README.rst"
 license = {file = "LICENSE"}
 requires-python = ">=3.8"
 authors = [

noxfile.py

@@ -1016,4 +1016,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 0
-}
+}