From 3c4f32c8b8c8ef6ff35e97d4b5014d4f4d2ea084 Mon Sep 17 00:00:00 2001 From: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Date: Tue, 22 Aug 2023 20:04:05 +0530 Subject: [PATCH 01/38] Replacing Exception type from ValueError to ImportError (#9588) I have restructured the code to ensure uniform handling of ImportError. In place of previously used ValueError, I've adopted the standard practice of raising ImportError with explanatory messages. This modification enhances code readability and clarifies that any problems stem from module importation. @eyurtsev , @baskaryan Thanks --- libs/langchain/langchain/vectorstores/meilisearch.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/libs/langchain/langchain/vectorstores/meilisearch.py b/libs/langchain/langchain/vectorstores/meilisearch.py index cb9f5d98410..313ae681631 100644 --- a/libs/langchain/langchain/vectorstores/meilisearch.py +++ b/libs/langchain/langchain/vectorstores/meilisearch.py @@ -21,7 +21,7 @@ def _create_client( try: import meilisearch except ImportError: - raise ValueError( + raise ImportError( "Could not import meilisearch python package. " "Please install it with `pip install meilisearch`." ) From fba29f203adfe35d14a03511c88661ddd1c76263 Mon Sep 17 00:00:00 2001 From: toddkim95 <42592581+toddkim95@users.noreply.github.com> Date: Tue, 22 Aug 2023 23:36:24 +0900 Subject: [PATCH 02/38] Add to support polars (#9610) ### Description Polars is a DataFrame interface on top of an OLAP Query Engine implemented in Rust. Polars is faster to read than pandas, so I'm looking forward to seeing it added to the document loader. ### Dependencies polars (https://pola-rs.github.io/polars-book/user-guide/) --------- Co-authored-by: Bagatur --- .../document_loaders/polars_dataframe.ipynb | 225 ++++++++++++++++++ .../langchain/document_loaders/__init__.py | 2 + .../langchain/document_loaders/dataframe.py | 39 ++- .../document_loaders/polars_dataframe.py | 32 +++ .../langchain/document_loaders/xorbits.py | 22 +- .../document_loaders/test_polars_dataframe.py | 48 ++++ 6 files changed, 339 insertions(+), 29 deletions(-) create mode 100644 docs/extras/integrations/document_loaders/polars_dataframe.ipynb create mode 100644 libs/langchain/langchain/document_loaders/polars_dataframe.py create mode 100644 libs/langchain/tests/integration_tests/document_loaders/test_polars_dataframe.py diff --git a/docs/extras/integrations/document_loaders/polars_dataframe.ipynb b/docs/extras/integrations/document_loaders/polars_dataframe.ipynb new file mode 100644 index 00000000000..52936f16540 --- /dev/null +++ b/docs/extras/integrations/document_loaders/polars_dataframe.ipynb @@ -0,0 +1,225 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "213a38a2", + "metadata": {}, + "source": [ + "# Polars DataFrame\n", + "\n", + "This notebook goes over how to load data from a [polars](https://pola-rs.github.io/polars-book/user-guide/) DataFrame." + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "f6a7a9e4-80d6-486a-b2e3-636c568aa97c", + "metadata": {}, + "outputs": [], + "source": [ + "#!pip install polars" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "79331964", + "metadata": {}, + "outputs": [], + "source": [ + "import polars as pl" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "e487044c", + "metadata": {}, + "outputs": [], + "source": [ + "df = pl.read_csv(\"example_data/mlb_teams_2012.csv\")" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "id": "ac273ca1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "shape: (5, 3)
Team "Payroll (millions)" "Wins"
strf64i64
"Nationals"81.3498
"Reds"82.297
"Yankees"197.9695
"Giants"117.6294
"Braves"83.3194
" + ], + "text/plain": [ + "shape: (5, 3)\n", + "┌───────────┬───────────────────────┬─────────┐\n", + "│ Team ┆ \"Payroll (millions)\" ┆ \"Wins\" │\n", + "│ --- ┆ --- ┆ --- │\n", + "│ str ┆ f64 ┆ i64 │\n", + "╞═══════════╪═══════════════════════╪═════════╡\n", + "│ Nationals ┆ 81.34 ┆ 98 │\n", + "│ Reds ┆ 82.2 ┆ 97 │\n", + "│ Yankees ┆ 197.96 ┆ 95 │\n", + "│ Giants ┆ 117.62 ┆ 94 │\n", + "│ Braves ┆ 83.31 ┆ 94 │\n", + "└───────────┴───────────────────────┴─────────┘" + ] + }, + "execution_count": 4, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "id": "66e47a13", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.document_loaders import PolarsDataFrameLoader" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "2334caca", + "metadata": {}, + "outputs": [], + "source": [ + "loader = PolarsDataFrameLoader(df, page_content_column=\"Team\")" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "d616c2b0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "[Document(page_content='Nationals', metadata={' \"Payroll (millions)\"': 81.34, ' \"Wins\"': 98}),\n", + " Document(page_content='Reds', metadata={' \"Payroll (millions)\"': 82.2, ' \"Wins\"': 97}),\n", + " Document(page_content='Yankees', metadata={' \"Payroll (millions)\"': 197.96, ' \"Wins\"': 95}),\n", + " Document(page_content='Giants', metadata={' \"Payroll (millions)\"': 117.62, ' \"Wins\"': 94}),\n", + " Document(page_content='Braves', metadata={' \"Payroll (millions)\"': 83.31, ' \"Wins\"': 94}),\n", + " Document(page_content='Athletics', metadata={' \"Payroll (millions)\"': 55.37, ' \"Wins\"': 94}),\n", + " Document(page_content='Rangers', metadata={' \"Payroll (millions)\"': 120.51, ' \"Wins\"': 93}),\n", + " Document(page_content='Orioles', metadata={' \"Payroll (millions)\"': 81.43, ' \"Wins\"': 93}),\n", + " Document(page_content='Rays', metadata={' \"Payroll (millions)\"': 64.17, ' \"Wins\"': 90}),\n", + " Document(page_content='Angels', metadata={' \"Payroll (millions)\"': 154.49, ' \"Wins\"': 89}),\n", + " Document(page_content='Tigers', metadata={' \"Payroll (millions)\"': 132.3, ' \"Wins\"': 88}),\n", + " Document(page_content='Cardinals', metadata={' \"Payroll (millions)\"': 110.3, ' \"Wins\"': 88}),\n", + " Document(page_content='Dodgers', metadata={' \"Payroll (millions)\"': 95.14, ' \"Wins\"': 86}),\n", + " Document(page_content='White Sox', metadata={' \"Payroll (millions)\"': 96.92, ' \"Wins\"': 85}),\n", + " Document(page_content='Brewers', metadata={' \"Payroll (millions)\"': 97.65, ' \"Wins\"': 83}),\n", + " Document(page_content='Phillies', metadata={' \"Payroll (millions)\"': 174.54, ' \"Wins\"': 81}),\n", + " Document(page_content='Diamondbacks', metadata={' \"Payroll (millions)\"': 74.28, ' \"Wins\"': 81}),\n", + " Document(page_content='Pirates', metadata={' \"Payroll (millions)\"': 63.43, ' \"Wins\"': 79}),\n", + " Document(page_content='Padres', metadata={' \"Payroll (millions)\"': 55.24, ' \"Wins\"': 76}),\n", + " Document(page_content='Mariners', metadata={' \"Payroll (millions)\"': 81.97, ' \"Wins\"': 75}),\n", + " Document(page_content='Mets', metadata={' \"Payroll (millions)\"': 93.35, ' \"Wins\"': 74}),\n", + " Document(page_content='Blue Jays', metadata={' \"Payroll (millions)\"': 75.48, ' \"Wins\"': 73}),\n", + " Document(page_content='Royals', metadata={' \"Payroll (millions)\"': 60.91, ' \"Wins\"': 72}),\n", + " Document(page_content='Marlins', metadata={' \"Payroll (millions)\"': 118.07, ' \"Wins\"': 69}),\n", + " Document(page_content='Red Sox', metadata={' \"Payroll (millions)\"': 173.18, ' \"Wins\"': 69}),\n", + " Document(page_content='Indians', metadata={' \"Payroll (millions)\"': 78.43, ' \"Wins\"': 68}),\n", + " Document(page_content='Twins', metadata={' \"Payroll (millions)\"': 94.08, ' \"Wins\"': 66}),\n", + " Document(page_content='Rockies', metadata={' \"Payroll (millions)\"': 78.06, ' \"Wins\"': 64}),\n", + " Document(page_content='Cubs', metadata={' \"Payroll (millions)\"': 88.19, ' \"Wins\"': 61}),\n", + " Document(page_content='Astros', metadata={' \"Payroll (millions)\"': 60.65, ' \"Wins\"': 55})]" + ] + }, + "execution_count": 7, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "loader.load()" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "id": "beb55c2f", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "page_content='Nationals' metadata={' \"Payroll (millions)\"': 81.34, ' \"Wins\"': 98}\n", + "page_content='Reds' metadata={' \"Payroll (millions)\"': 82.2, ' \"Wins\"': 97}\n", + "page_content='Yankees' metadata={' \"Payroll (millions)\"': 197.96, ' \"Wins\"': 95}\n", + "page_content='Giants' metadata={' \"Payroll (millions)\"': 117.62, ' \"Wins\"': 94}\n", + "page_content='Braves' metadata={' \"Payroll (millions)\"': 83.31, ' \"Wins\"': 94}\n", + "page_content='Athletics' metadata={' \"Payroll (millions)\"': 55.37, ' \"Wins\"': 94}\n", + "page_content='Rangers' metadata={' \"Payroll (millions)\"': 120.51, ' \"Wins\"': 93}\n", + "page_content='Orioles' metadata={' \"Payroll (millions)\"': 81.43, ' \"Wins\"': 93}\n", + "page_content='Rays' metadata={' \"Payroll (millions)\"': 64.17, ' \"Wins\"': 90}\n", + "page_content='Angels' metadata={' \"Payroll (millions)\"': 154.49, ' \"Wins\"': 89}\n", + "page_content='Tigers' metadata={' \"Payroll (millions)\"': 132.3, ' \"Wins\"': 88}\n", + "page_content='Cardinals' metadata={' \"Payroll (millions)\"': 110.3, ' \"Wins\"': 88}\n", + "page_content='Dodgers' metadata={' \"Payroll (millions)\"': 95.14, ' \"Wins\"': 86}\n", + "page_content='White Sox' metadata={' \"Payroll (millions)\"': 96.92, ' \"Wins\"': 85}\n", + "page_content='Brewers' metadata={' \"Payroll (millions)\"': 97.65, ' \"Wins\"': 83}\n", + "page_content='Phillies' metadata={' \"Payroll (millions)\"': 174.54, ' \"Wins\"': 81}\n", + "page_content='Diamondbacks' metadata={' \"Payroll (millions)\"': 74.28, ' \"Wins\"': 81}\n", + "page_content='Pirates' metadata={' \"Payroll (millions)\"': 63.43, ' \"Wins\"': 79}\n", + "page_content='Padres' metadata={' \"Payroll (millions)\"': 55.24, ' \"Wins\"': 76}\n", + "page_content='Mariners' metadata={' \"Payroll (millions)\"': 81.97, ' \"Wins\"': 75}\n", + "page_content='Mets' metadata={' \"Payroll (millions)\"': 93.35, ' \"Wins\"': 74}\n", + "page_content='Blue Jays' metadata={' \"Payroll (millions)\"': 75.48, ' \"Wins\"': 73}\n", + "page_content='Royals' metadata={' \"Payroll (millions)\"': 60.91, ' \"Wins\"': 72}\n", + "page_content='Marlins' metadata={' \"Payroll (millions)\"': 118.07, ' \"Wins\"': 69}\n", + "page_content='Red Sox' metadata={' \"Payroll (millions)\"': 173.18, ' \"Wins\"': 69}\n", + "page_content='Indians' metadata={' \"Payroll (millions)\"': 78.43, ' \"Wins\"': 68}\n", + "page_content='Twins' metadata={' \"Payroll (millions)\"': 94.08, ' \"Wins\"': 66}\n", + "page_content='Rockies' metadata={' \"Payroll (millions)\"': 78.06, ' \"Wins\"': 64}\n", + "page_content='Cubs' metadata={' \"Payroll (millions)\"': 88.19, ' \"Wins\"': 61}\n", + "page_content='Astros' metadata={' \"Payroll (millions)\"': 60.65, ' \"Wins\"': 55}\n" + ] + } + ], + "source": [ + "# Use lazy load for larger table, which won't read the full table into memory\n", + "for i in loader.lazy_load():\n", + " print(i)" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3 (ipykernel)", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.11.3" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/libs/langchain/langchain/document_loaders/__init__.py b/libs/langchain/langchain/document_loaders/__init__.py index 195b586ac2a..30f69659cee 100644 --- a/libs/langchain/langchain/document_loaders/__init__.py +++ b/libs/langchain/langchain/document_loaders/__init__.py @@ -132,6 +132,7 @@ from langchain.document_loaders.pdf import ( PyPDFLoader, UnstructuredPDFLoader, ) +from langchain.document_loaders.polars_dataframe import PolarsDataFrameLoader from langchain.document_loaders.powerpoint import UnstructuredPowerPointLoader from langchain.document_loaders.psychic import PsychicLoader from langchain.document_loaders.pubmed import PubMedLoader @@ -299,6 +300,7 @@ __all__ = [ "PDFPlumberLoader", "PagedPDFSplitter", "PlaywrightURLLoader", + "PolarsDataFrameLoader", "PsychicLoader", "PubMedLoader", "PyMuPDFLoader", diff --git a/libs/langchain/langchain/document_loaders/dataframe.py b/libs/langchain/langchain/document_loaders/dataframe.py index 0476f6a2986..261426a3ceb 100644 --- a/libs/langchain/langchain/document_loaders/dataframe.py +++ b/libs/langchain/langchain/document_loaders/dataframe.py @@ -4,23 +4,15 @@ from langchain.docstore.document import Document from langchain.document_loaders.base import BaseLoader -class DataFrameLoader(BaseLoader): - """Load `Pandas` DataFrame.""" - - def __init__(self, data_frame: Any, page_content_column: str = "text"): +class BaseDataFrameLoader(BaseLoader): + def __init__(self, data_frame: Any, *, page_content_column: str = "text"): """Initialize with dataframe object. Args: - data_frame: Pandas DataFrame object. + data_frame: DataFrame object. page_content_column: Name of the column containing the page content. Defaults to "text". """ - import pandas as pd - - if not isinstance(data_frame, pd.DataFrame): - raise ValueError( - f"Expected data_frame to be a pd.DataFrame, got {type(data_frame)}" - ) self.data_frame = data_frame self.page_content_column = page_content_column @@ -36,3 +28,28 @@ class DataFrameLoader(BaseLoader): def load(self) -> List[Document]: """Load full dataframe.""" return list(self.lazy_load()) + + +class DataFrameLoader(BaseDataFrameLoader): + """Load `Pandas` DataFrame.""" + + def __init__(self, data_frame: Any, page_content_column: str = "text"): + """Initialize with dataframe object. + + Args: + data_frame: Pandas DataFrame object. + page_content_column: Name of the column containing the page content. + Defaults to "text". + """ + try: + import pandas as pd + except ImportError as e: + raise ImportError( + "Unable to import pandas, please install with `pip install pandas`." + ) from e + + if not isinstance(data_frame, pd.DataFrame): + raise ValueError( + f"Expected data_frame to be a pd.DataFrame, got {type(data_frame)}" + ) + super().__init__(data_frame, page_content_column=page_content_column) diff --git a/libs/langchain/langchain/document_loaders/polars_dataframe.py b/libs/langchain/langchain/document_loaders/polars_dataframe.py new file mode 100644 index 00000000000..6ece942df49 --- /dev/null +++ b/libs/langchain/langchain/document_loaders/polars_dataframe.py @@ -0,0 +1,32 @@ +from typing import Any, Iterator + +from langchain.docstore.document import Document +from langchain.document_loaders.dataframe import BaseDataFrameLoader + + +class PolarsDataFrameLoader(BaseDataFrameLoader): + """Load `Polars` DataFrame.""" + + def __init__(self, data_frame: Any, *, page_content_column: str = "text"): + """Initialize with dataframe object. + + Args: + data_frame: Polars DataFrame object. + page_content_column: Name of the column containing the page content. + Defaults to "text". + """ + import polars as pl + + if not isinstance(data_frame, pl.DataFrame): + raise ValueError( + f"Expected data_frame to be a pl.DataFrame, got {type(data_frame)}" + ) + super().__init__(data_frame, page_content_column=page_content_column) + + def lazy_load(self) -> Iterator[Document]: + """Lazy load records from dataframe.""" + + for row in self.data_frame.iter_rows(named=True): + text = row[self.page_content_column] + row.pop(self.page_content_column) + yield Document(page_content=text, metadata=row) diff --git a/libs/langchain/langchain/document_loaders/xorbits.py b/libs/langchain/langchain/document_loaders/xorbits.py index bcc4e680f68..723e9dc1b59 100644 --- a/libs/langchain/langchain/document_loaders/xorbits.py +++ b/libs/langchain/langchain/document_loaders/xorbits.py @@ -1,10 +1,9 @@ -from typing import Any, Iterator, List +from typing import Any -from langchain.docstore.document import Document -from langchain.document_loaders.base import BaseLoader +from langchain.document_loaders.dataframe import BaseDataFrameLoader -class XorbitsLoader(BaseLoader): +class XorbitsLoader(BaseDataFrameLoader): """Load `Xorbits` DataFrame.""" def __init__(self, data_frame: Any, page_content_column: str = "text"): @@ -30,17 +29,4 @@ class XorbitsLoader(BaseLoader): f"Expected data_frame to be a xorbits.pandas.DataFrame, \ got {type(data_frame)}" ) - self.data_frame = data_frame - self.page_content_column = page_content_column - - def lazy_load(self) -> Iterator[Document]: - """Lazy load records from dataframe.""" - for _, row in self.data_frame.iterrows(): - text = row[self.page_content_column] - metadata = row.to_dict() - metadata.pop(self.page_content_column) - yield Document(page_content=text, metadata=metadata) - - def load(self) -> List[Document]: - """Load full dataframe.""" - return list(self.lazy_load()) + super().__init__(data_frame, page_content_column=page_content_column) diff --git a/libs/langchain/tests/integration_tests/document_loaders/test_polars_dataframe.py b/libs/langchain/tests/integration_tests/document_loaders/test_polars_dataframe.py new file mode 100644 index 00000000000..bd8e129dafa --- /dev/null +++ b/libs/langchain/tests/integration_tests/document_loaders/test_polars_dataframe.py @@ -0,0 +1,48 @@ +import polars as pl +import pytest + +from langchain.document_loaders import PolarsDataFrameLoader +from langchain.schema import Document + + +@pytest.fixture +def sample_data_frame() -> pl.DataFrame: + data = { + "text": ["Hello", "World"], + "author": ["Alice", "Bob"], + "date": ["2022-01-01", "2022-01-02"], + } + return pl.DataFrame(data) + + +def test_load_returns_list_of_documents(sample_data_frame: pl.DataFrame) -> None: + loader = PolarsDataFrameLoader(sample_data_frame) + docs = loader.load() + assert isinstance(docs, list) + assert all(isinstance(doc, Document) for doc in docs) + assert len(docs) == 2 + + +def test_load_converts_dataframe_columns_to_document_metadata( + sample_data_frame: pl.DataFrame, +) -> None: + loader = PolarsDataFrameLoader(sample_data_frame) + docs = loader.load() + + for i, doc in enumerate(docs): + df: pl.DataFrame = sample_data_frame[i] + assert df is not None + assert doc.metadata["author"] == df.select("author").item() + assert doc.metadata["date"] == df.select("date").item() + + +def test_load_uses_page_content_column_to_create_document_text( + sample_data_frame: pl.DataFrame, +) -> None: + sample_data_frame = sample_data_frame.rename(mapping={"text": "dummy_test_column"}) + loader = PolarsDataFrameLoader( + sample_data_frame, page_content_column="dummy_test_column" + ) + docs = loader.load() + assert docs[0].page_content == "Hello" + assert docs[1].page_content == "World" From d4c49b16e4aead34c16f9919be0000cdc775ca3a Mon Sep 17 00:00:00 2001 From: Philippe PRADOS Date: Tue, 22 Aug 2023 16:36:36 +0200 Subject: [PATCH 03/38] Fix ChatMessageHistory (#9594) The initialization of the array of ChatMessageHistory is buggy. The list is shared with all instances. --- .../langchain/memory/chat_message_histories/in_memory.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/libs/langchain/langchain/memory/chat_message_histories/in_memory.py b/libs/langchain/langchain/memory/chat_message_histories/in_memory.py index d8db3f424b5..53fbbb201ea 100644 --- a/libs/langchain/langchain/memory/chat_message_histories/in_memory.py +++ b/libs/langchain/langchain/memory/chat_message_histories/in_memory.py @@ -1,6 +1,6 @@ from typing import List -from langchain.pydantic_v1 import BaseModel +from langchain.pydantic_v1 import BaseModel, Field from langchain.schema import ( BaseChatMessageHistory, ) @@ -13,7 +13,7 @@ class ChatMessageHistory(BaseChatMessageHistory, BaseModel): Stores messages in an in memory list. """ - messages: List[BaseMessage] = [] + messages: List[BaseMessage] = Field(default_factory=list) def add_message(self, message: BaseMessage) -> None: """Add a self-created message to the store""" From 1ea2f9adf470185e62de4079a3e6f240147af539 Mon Sep 17 00:00:00 2001 From: Vanessa Arndorfer Date: Tue, 22 Aug 2023 07:36:47 -0700 Subject: [PATCH 04/38] Document AzureML Deployment Example (#9571) Description: Link an example of deploying a Langchain app to an AzureML online endpoint to the deployments documentation page. Co-authored-by: Vanessa Arndorfer --- docs/extras/guides/deployments/template_repos.mdx | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/docs/extras/guides/deployments/template_repos.mdx b/docs/extras/guides/deployments/template_repos.mdx index ec8d03237bf..45c4a43dec4 100644 --- a/docs/extras/guides/deployments/template_repos.mdx +++ b/docs/extras/guides/deployments/template_repos.mdx @@ -79,3 +79,7 @@ See OpenLLM's [integration doc](https://github.com/bentoml/OpenLLM#%EF%B8%8F-int ## [Databutton](https://databutton.com/home?new-data-app=true) These templates serve as examples of how to build, deploy, and share LangChain applications using Databutton. You can create user interfaces with Streamlit, automate tasks by scheduling Python code, and store files and data in the built-in store. Examples include a Chatbot interface with conversational memory, a Personal search engine, and a starter template for LangChain apps. Deploying and sharing is just one click away. + +## [AzureML Online Endpoint](https://github.com/Azure/azureml-examples/blob/main/sdk/python/endpoints/online/llm/langchain/1_langchain_basic_deploy.ipynb) + +A minimal example of how to deploy LangChain to an Azure Machine Learning Online Endpoint. \ No newline at end of file From dfb9ff10799cbb6f3e1831f11b46851f16089c56 Mon Sep 17 00:00:00 2001 From: Anthony Mahanna <43019056+aMahanna@users.noreply.github.com> Date: Tue, 22 Aug 2023 10:41:06 -0400 Subject: [PATCH 05/38] bugfix: ArangoDB Empty Schema Case (#9574) - Introduces a conditional in `ArangoGraph.generate_schema()` to exclude empty ArangoDB Collections from the schema - Add empty collection test case Issue: N/A Dependencies: None --- libs/langchain/langchain/graphs/arangodb_graph.py | 4 ++++ .../chains/test_graph_database_arangodb.py | 15 +++++++++++++++ 2 files changed, 19 insertions(+) diff --git a/libs/langchain/langchain/graphs/arangodb_graph.py b/libs/langchain/langchain/graphs/arangodb_graph.py index 69b78dea399..aedcd95601e 100644 --- a/libs/langchain/langchain/graphs/arangodb_graph.py +++ b/libs/langchain/langchain/graphs/arangodb_graph.py @@ -66,6 +66,10 @@ class ArangoGraph: col_type: str = collection["type"] col_size: int = self.db.collection(col_name).count() + # Skip collection if empty + if col_size == 0: + continue + # Set number of ArangoDB documents/edges to retrieve limit_amount = ceil(sample_ratio * col_size) or 1 diff --git a/libs/langchain/tests/integration_tests/chains/test_graph_database_arangodb.py b/libs/langchain/tests/integration_tests/chains/test_graph_database_arangodb.py index 32494beb05f..d6ce5075671 100644 --- a/libs/langchain/tests/integration_tests/chains/test_graph_database_arangodb.py +++ b/libs/langchain/tests/integration_tests/chains/test_graph_database_arangodb.py @@ -55,6 +55,21 @@ def test_connect_arangodb() -> None: assert ["hello_world"] == sample_aql_result +def test_empty_schema_on_no_data() -> None: + """Test that the schema is empty for an empty ArangoDB Database""" + db = get_arangodb_client() + db.delete_graph("GameOfThrones", drop_collections=True, ignore_missing=True) + db.delete_collection("empty_collection", ignore_missing=True) + db.create_collection("empty_collection") + + graph = ArangoGraph(db) + + assert graph.schema == { + "Graph Schema": [], + "Collection Schema": [], + } + + def test_aql_generation() -> None: """Test that AQL statement is correctly generated and executed.""" db = get_arangodb_client() From 1720e99397af8989fbb035511e8499b6dd045001 Mon Sep 17 00:00:00 2001 From: Harrison Chase Date: Tue, 22 Aug 2023 07:43:21 -0700 Subject: [PATCH 06/38] add variables for field names (#9563) --- libs/langchain/langchain/vectorstores/milvus.py | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/libs/langchain/langchain/vectorstores/milvus.py b/libs/langchain/langchain/vectorstores/milvus.py index 05ce1b08501..c6a5301ff92 100644 --- a/libs/langchain/langchain/vectorstores/milvus.py +++ b/libs/langchain/langchain/vectorstores/milvus.py @@ -52,6 +52,9 @@ class Milvus(VectorStore): default of index. drop_old (Optional[bool]): Whether to drop the current collection. Defaults to False. + primary_field (str): Name of the primary key field. Defaults to "pk". + text_field (str): Name of the text field. Defaults to "text". + vector_field (str): Name of the vector field. Defaults to "vector". The connection args used for this class comes in the form of a dict, here are a few of the options: @@ -107,6 +110,10 @@ class Milvus(VectorStore): index_params: Optional[dict] = None, search_params: Optional[dict] = None, drop_old: Optional[bool] = False, + *, + primary_field: str = "pk", + text_field: str = "text", + vector_field: str = "vector", ): """Initialize the Milvus vector store.""" try: @@ -138,11 +145,11 @@ class Milvus(VectorStore): self.consistency_level = consistency_level # In order for a collection to be compatible, pk needs to be auto'id and int - self._primary_field = "pk" - # In order for compatiblility, the text field will need to be called "text" - self._text_field = "text" + self._primary_field = primary_field + # In order for compatibility, the text field will need to be called "text" + self._text_field = text_field # In order for compatibility, the vector field needs to be called "vector" - self._vector_field = "vector" + self._vector_field = vector_field self.fields: list[str] = [] # Create the connection to the server if connection_args is None: From e99ef12cb1e801e2834244505986ce3fa8dfda33 Mon Sep 17 00:00:00 2001 From: Bagatur <22008038+baskaryan@users.noreply.github.com> Date: Tue, 22 Aug 2023 07:44:00 -0700 Subject: [PATCH 07/38] Bagatur/litellm model name (#9613) Co-authored-by: ishaan-jaff --- .../langchain/chat_models/litellm.py | 29 +++++++++++++------ 1 file changed, 20 insertions(+), 9 deletions(-) diff --git a/libs/langchain/langchain/chat_models/litellm.py b/libs/langchain/langchain/chat_models/litellm.py index d23549dc51c..f429c322188 100644 --- a/libs/langchain/langchain/chat_models/litellm.py +++ b/libs/langchain/langchain/chat_models/litellm.py @@ -190,9 +190,6 @@ def _convert_message_to_dict(message: BaseMessage) -> dict: class ChatLiteLLM(BaseChatModel): """`LiteLLM` Chat models API. - To use you must have the google.generativeai Python package installed and - either: - 1. The ``GOOGLE_API_KEY``` environment variable set with your API key, or 2. Pass your API key using the google_api_key kwarg to the ChatGoogle constructor. @@ -206,7 +203,8 @@ class ChatLiteLLM(BaseChatModel): """ client: Any #: :meta private: - model_name: str = "gpt-3.5-turbo" + model: str = "gpt-3.5-turbo" + model_name: Optional[str] = None """Model name to use.""" openai_api_key: Optional[str] = None azure_api_key: Optional[str] = None @@ -217,8 +215,9 @@ class ChatLiteLLM(BaseChatModel): streaming: bool = False api_base: Optional[str] = None organization: Optional[str] = None + custom_llm_provider: Optional[str] = None request_timeout: Optional[Union[float, Tuple[float, float]]] = None - temperature: Optional[float] = None + temperature: Optional[float] = 1 model_kwargs: Dict[str, Any] = Field(default_factory=dict) """Run inference with this temperature. Must by in the closed interval [0.0, 1.0].""" @@ -238,8 +237,11 @@ class ChatLiteLLM(BaseChatModel): @property def _default_params(self) -> Dict[str, Any]: """Get the default parameters for calling OpenAI API.""" + set_model_value = self.model + if self.model_name is not None: + set_model_value = self.model_name return { - "model": self.model_name, + "model": set_model_value, "force_timeout": self.request_timeout, "max_tokens": self.max_tokens, "stream": self.streaming, @@ -251,10 +253,13 @@ class ChatLiteLLM(BaseChatModel): @property def _client_params(self) -> Dict[str, Any]: """Get the parameters used for the openai client.""" + set_model_value = self.model + if self.model_name is not None: + set_model_value = self.model_name self.client.api_base = self.api_base self.client.organization = self.organization creds: Dict[str, Any] = { - "model": self.model_name, + "model": set_model_value, "force_timeout": self.request_timeout, } return {**self._default_params, **creds} @@ -347,7 +352,10 @@ class ChatLiteLLM(BaseChatModel): ) generations.append(gen) token_usage = response.get("usage", {}) - llm_output = {"token_usage": token_usage, "model_name": self.model_name} + set_model_value = self.model + if self.model_name is not None: + set_model_value = self.model_name + llm_output = {"token_usage": token_usage, "model": set_model_value} return ChatResult(generations=generations, llm_output=llm_output) def _create_message_dicts( @@ -437,8 +445,11 @@ class ChatLiteLLM(BaseChatModel): @property def _identifying_params(self) -> Dict[str, Any]: """Get the identifying parameters.""" + set_model_value = self.model + if self.model_name is not None: + set_model_value = self.model_name return { - "model_name": self.model_name, + "model": set_model_value, "temperature": self.temperature, "top_p": self.top_p, "top_k": self.top_k, From b868ef23bc339bdd541b5dbc801f32987cdbf90d Mon Sep 17 00:00:00 2001 From: klae01 <101966044+klae01@users.noreply.github.com> Date: Wed, 23 Aug 2023 00:03:33 +0900 Subject: [PATCH 08/38] Add AINetwork blockchain toolkit integration (#9527) # Description This PR introduces a new toolkit for interacting with the AINetwork blockchain. The toolkit provides a set of tools for performing various operations on the AINetwork blockchain, such as transferring AIN, reading and writing values to the blockchain database, managing apps, setting rules and owners. # Dependencies [ain-py](https://github.com/ainblockchain/ain-py) >= 1.0.2 # Misc The example notebook (langchain/docs/extras/integrations/toolkits/ainetwork.ipynb) is in the PR --------- Co-authored-by: kriii Co-authored-by: Bagatur --- .../integrations/toolkits/ainetwork.ipynb | 461 ++++++++++++++++++ .../agents/agent_toolkits/__init__.py | 2 + .../agent_toolkits/ainetwork/__init__.py | 1 + .../agent_toolkits/ainetwork/toolkit.py | 45 ++ libs/langchain/langchain/tools/__init__.py | 10 + .../langchain/tools/ainetwork/app.py | 95 ++++ .../langchain/tools/ainetwork/base.py | 71 +++ .../langchain/tools/ainetwork/owner.py | 110 +++++ .../langchain/tools/ainetwork/rule.py | 77 +++ .../langchain/tools/ainetwork/transfer.py | 29 ++ .../langchain/tools/ainetwork/utils.py | 62 +++ .../langchain/tools/ainetwork/value.py | 80 +++ .../agent/test_ainetwork_agent.py | 175 +++++++ .../tests/unit_tests/tools/test_public_api.py | 5 + 14 files changed, 1223 insertions(+) create mode 100644 docs/extras/integrations/toolkits/ainetwork.ipynb create mode 100644 libs/langchain/langchain/agents/agent_toolkits/ainetwork/__init__.py create mode 100644 libs/langchain/langchain/agents/agent_toolkits/ainetwork/toolkit.py create mode 100644 libs/langchain/langchain/tools/ainetwork/app.py create mode 100644 libs/langchain/langchain/tools/ainetwork/base.py create mode 100644 libs/langchain/langchain/tools/ainetwork/owner.py create mode 100644 libs/langchain/langchain/tools/ainetwork/rule.py create mode 100644 libs/langchain/langchain/tools/ainetwork/transfer.py create mode 100644 libs/langchain/langchain/tools/ainetwork/utils.py create mode 100644 libs/langchain/langchain/tools/ainetwork/value.py create mode 100644 libs/langchain/tests/integration_tests/agent/test_ainetwork_agent.py diff --git a/docs/extras/integrations/toolkits/ainetwork.ipynb b/docs/extras/integrations/toolkits/ainetwork.ipynb new file mode 100644 index 00000000000..b3a84afd00d --- /dev/null +++ b/docs/extras/integrations/toolkits/ainetwork.ipynb @@ -0,0 +1,461 @@ +{ + "cells": [ + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "# AINetwork Toolkit\n", + "\n", + "The AINetwork Toolkit is a set of tools for interacting with the AINetwork Blockchain. These tools allow you to transfer AIN, read and write values, create apps, and set permissions for specific paths within the blockchain database." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Installing dependencies\n", + "\n", + "Before using the AINetwork Toolkit, you need to install the ain-py package. You can install it with pip:\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "!pip install ain-py" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Set environmental variables\n", + "\n", + "You need to set the `AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY` environmental variable to your AIN Blockchain Account Private Key." + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "metadata": {}, + "outputs": [], + "source": [ + "import os\n", + "\n", + "os.environ[\"AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY\"] = \"\"" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get AIN Blockchain private key" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "address: 0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac\n", + "private_key: f5e2f359bb6b7836a2ac70815473d1a290c517f847d096f5effe818de8c2cf14\n", + "\n" + ] + } + ], + "source": [ + "import os\n", + "\n", + "from ain.account import Account\n", + "\n", + "if os.environ.get(\"AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY\", None):\n", + " account = Account(os.environ[\"AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY\"])\n", + "else:\n", + " account = Account.create()\n", + " os.environ[\"AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY\"] = account.private_key\n", + " print(\n", + " f\"\"\"\n", + "address: {account.address}\n", + "private_key: {account.private_key}\n", + "\"\"\"\n", + " )\n", + "# IMPORTANT: If you plan to use this account in the future, make sure to save the\n", + "# private key in a secure place. Losing access to your private key means losing\n", + "# access to your account." + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Initialize the AINetwork Toolkit\n", + "\n", + "You can initialize the AINetwork Toolkit like this:" + ] + }, + { + "cell_type": "code", + "execution_count": 4, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.agents.agent_toolkits.ainetwork.toolkit import AINetworkToolkit\n", + "\n", + "toolkit = AINetworkToolkit()\n", + "tools = toolkit.get_tools()\n", + "address = tools[0].interface.wallet.defaultAccount.address" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Initialize the Agent with the AINetwork Toolkit\n", + "\n", + "You can initialize the agent with the AINetwork Toolkit like this:" + ] + }, + { + "cell_type": "code", + "execution_count": 5, + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.chat_models import ChatOpenAI\n", + "from langchain.agents import initialize_agent, AgentType\n", + "\n", + "llm = ChatOpenAI(temperature=0)\n", + "agent = initialize_agent(\n", + " tools=tools,\n", + " llm=llm,\n", + " verbose=True,\n", + " agent=AgentType.OPENAI_FUNCTIONS,\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "## Example Usage\n", + "\n", + "Here are some examples of how you can use the agent with the AINetwork Toolkit:" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Define App name to test" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "metadata": {}, + "outputs": [], + "source": [ + "appName = f\"langchain_demo_{address.lower()}\"" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Create an app in the AINetwork Blockchain database" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m\n", + "Invoking: `AINappOps` with `{'type': 'SET_ADMIN', 'appName': 'langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac'}`\n", + "\n", + "\n", + "\u001b[0m\u001b[36;1m\u001b[1;3m{\"tx_hash\": \"0x018846d6a9fc111edb1a2246ae2484ef05573bd2c584f3d0da155fa4b4936a9e\", \"result\": {\"gas_amount_total\": {\"bandwidth\": {\"service\": 4002, \"app\": {\"langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\": 2}}, \"state\": {\"service\": 1640}}, \"gas_cost_total\": 0, \"func_results\": {\"_createApp\": {\"op_results\": {\"0\": {\"path\": \"/apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\", \"result\": {\"code\": 0, \"bandwidth_gas_amount\": 1}}, \"1\": {\"path\": \"/apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\", \"result\": {\"code\": 0, \"bandwidth_gas_amount\": 1}}, \"2\": {\"path\": \"/manage_app/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac/config/admin\", \"result\": {\"code\": 0, \"bandwidth_gas_amount\": 1}}}, \"code\": 0, \"bandwidth_gas_amount\": 2000}}, \"code\": 0, \"bandwidth_gas_amount\": 2001, \"gas_amount_charged\": 5642}}\u001b[0m\u001b[32;1m\u001b[1;3mThe app with the name \"langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\" has been created in the AINetwork Blockchain database.\u001b[0m\n", + "\n", + "\u001b[1m> Finished chain.\u001b[0m\n", + "The app with the name \"langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\" has been created in the AINetwork Blockchain database.\n" + ] + } + ], + "source": [ + "print(\n", + " agent.run(\n", + " f\"Create an app in the AINetwork Blockchain database with the name {appName}\"\n", + " )\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Set a value at a given path in the AINetwork Blockchain database" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m\n", + "Invoking: `AINvalueOps` with `{'type': 'SET', 'path': '/apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac/object', 'value': {'1': 2, '34': 56}}`\n", + "\n", + "\n", + "\u001b[0m\u001b[33;1m\u001b[1;3m{\"tx_hash\": \"0x3d1a16d9808830088cdf4d37f90f4b1fa1242e2d5f6f983829064f45107b5279\", \"result\": {\"gas_amount_total\": {\"bandwidth\": {\"service\": 0, \"app\": {\"langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\": 1}}, \"state\": {\"service\": 0, \"app\": {\"langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\": 674}}}, \"gas_cost_total\": 0, \"code\": 0, \"bandwidth_gas_amount\": 1, \"gas_amount_charged\": 0}}\u001b[0m\u001b[32;1m\u001b[1;3mThe value {1: 2, '34': 56} has been set at the path /apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac/object.\u001b[0m\n", + "\n", + "\u001b[1m> Finished chain.\u001b[0m\n", + "The value {1: 2, '34': 56} has been set at the path /apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac/object.\n" + ] + } + ], + "source": [ + "print(\n", + " agent.run(f\"Set the value {{1: 2, '34': 56}} at the path /apps/{appName}/object .\")\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Set permissions for a path in the AINetwork Blockchain database" + ] + }, + { + "cell_type": "code", + "execution_count": 9, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m\n", + "Invoking: `AINruleOps` with `{'type': 'SET', 'path': '/apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac/user/$from', 'eval': 'auth.addr===$from'}`\n", + "\n", + "\n", + "\u001b[0m\u001b[38;5;200m\u001b[1;3m{\"tx_hash\": \"0x37d5264e580f6a217a347059a735bfa9eb5aad85ff28a95531c6dc09252664d2\", \"result\": {\"gas_amount_total\": {\"bandwidth\": {\"service\": 0, \"app\": {\"langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\": 1}}, \"state\": {\"service\": 0, \"app\": {\"langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac\": 712}}}, \"gas_cost_total\": 0, \"code\": 0, \"bandwidth_gas_amount\": 1, \"gas_amount_charged\": 0}}\u001b[0m\u001b[32;1m\u001b[1;3mThe write permissions for the path `/apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac/user/$from` have been set with the eval string `auth.addr===$from`.\u001b[0m\n", + "\n", + "\u001b[1m> Finished chain.\u001b[0m\n", + "The write permissions for the path `/apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac/user/$from` have been set with the eval string `auth.addr===$from`.\n" + ] + } + ], + "source": [ + "print(\n", + " agent.run(\n", + " f\"Set the write permissions for the path /apps/{appName}/user/$from with the\"\n", + " \" eval string auth.addr===$from .\"\n", + " )\n", + ")" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Retrieve the permissions for a path in the AINetwork Blockchain database" + ] + }, + { + "cell_type": "code", + "execution_count": 10, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m\n", + "Invoking: `AINownerOps` with `{'type': 'GET', 'path': '/apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac'}`\n", + "\n", + "\n", + "\u001b[0m\u001b[33;1m\u001b[1;3m{\".owner\": {\"owners\": {\"0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac\": {\"branch_owner\": true, \"write_function\": true, \"write_owner\": true, \"write_rule\": true}}}}\u001b[0m\u001b[32;1m\u001b[1;3mThe permissions for the path /apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac are as follows:\n", + "\n", + "- Address: 0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac\n", + " - branch_owner: true\n", + " - write_function: true\n", + " - write_owner: true\n", + " - write_rule: true\u001b[0m\n", + "\n", + "\u001b[1m> Finished chain.\u001b[0m\n", + "The permissions for the path /apps/langchain_demo_0x5beb4defa2ccc274498416fd7cb34235dbc122ac are as follows:\n", + "\n", + "- Address: 0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac\n", + " - branch_owner: true\n", + " - write_function: true\n", + " - write_owner: true\n", + " - write_rule: true\n" + ] + } + ], + "source": [ + "print(agent.run(f\"Retrieve the permissions for the path /apps/{appName}.\"))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get AIN from faucet" + ] + }, + { + "cell_type": "code", + "execution_count": 11, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "{\"result\":\"0x0eb07b67b7d0a702cb60e865d3deafff3070d8508077ef793d69d6819fd92ea3\",\"time\":1692348112376}" + ] + } + ], + "source": [ + "!curl http://faucet.ainetwork.ai/api/test/{address}/" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Get AIN Balance" + ] + }, + { + "cell_type": "code", + "execution_count": 12, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m\n", + "Invoking: `AINvalueOps` with `{'type': 'GET', 'path': '/accounts/0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac/balance'}`\n", + "\n", + "\n", + "\u001b[0m\u001b[33;1m\u001b[1;3m100\u001b[0m\u001b[32;1m\u001b[1;3mThe AIN balance of address 0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac is 100 AIN.\u001b[0m\n", + "\n", + "\u001b[1m> Finished chain.\u001b[0m\n", + "The AIN balance of address 0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac is 100 AIN.\n" + ] + } + ], + "source": [ + "print(agent.run(f\"Check AIN balance of {address}\"))" + ] + }, + { + "attachments": {}, + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Transfer AIN" + ] + }, + { + "cell_type": "code", + "execution_count": 13, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "\n", + "\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m\n", + "Invoking: `AINtransfer` with `{'address': '0x19937b227b1b13f29e7ab18676a89ea3bdea9c5b', 'amount': 100}`\n", + "\n", + "\n", + "\u001b[0m\u001b[36;1m\u001b[1;3m{\"tx_hash\": \"0xa59d15d23373bcc00e413ac8ba18cb016bb3bdd54058d62606aec688c6ad3d2e\", \"result\": {\"gas_amount_total\": {\"bandwidth\": {\"service\": 3}, \"state\": {\"service\": 866}}, \"gas_cost_total\": 0, \"func_results\": {\"_transfer\": {\"op_results\": {\"0\": {\"path\": \"/accounts/0x5BEB4Defa2ccc274498416Fd7Cb34235DbC122Ac/balance\", \"result\": {\"code\": 0, \"bandwidth_gas_amount\": 1}}, \"1\": {\"path\": \"/accounts/0x19937B227b1b13f29e7AB18676a89EA3BDEA9C5b/balance\", \"result\": {\"code\": 0, \"bandwidth_gas_amount\": 1}}}, \"code\": 0, \"bandwidth_gas_amount\": 0}}, \"code\": 0, \"bandwidth_gas_amount\": 1, \"gas_amount_charged\": 869}}\u001b[0m\u001b[32;1m\u001b[1;3mThe transfer of 100 AIN to the address 0x19937b227b1b13f29e7ab18676a89ea3bdea9c5b was successful. The transaction hash is 0xa59d15d23373bcc00e413ac8ba18cb016bb3bdd54058d62606aec688c6ad3d2e.\u001b[0m\n", + "\n", + "\u001b[1m> Finished chain.\u001b[0m\n", + "The transfer of 100 AIN to the address 0x19937b227b1b13f29e7ab18676a89ea3bdea9c5b was successful. The transaction hash is 0xa59d15d23373bcc00e413ac8ba18cb016bb3bdd54058d62606aec688c6ad3d2e.\n" + ] + } + ], + "source": [ + "print(\n", + " agent.run(\n", + " \"Transfer 100 AIN to the address 0x19937b227b1b13f29e7ab18676a89ea3bdea9c5b\"\n", + " )\n", + ")" + ] + } + ], + "metadata": { + "kernelspec": { + "display_name": "Python 3", + "language": "python", + "name": "python3" + }, + "language_info": { + "codemirror_mode": { + "name": "ipython", + "version": 3 + }, + "file_extension": ".py", + "mimetype": "text/x-python", + "name": "python", + "nbconvert_exporter": "python", + "pygments_lexer": "ipython3", + "version": "3.10.12" + }, + "orig_nbformat": 4 + }, + "nbformat": 4, + "nbformat_minor": 2 +} diff --git a/libs/langchain/langchain/agents/agent_toolkits/__init__.py b/libs/langchain/langchain/agents/agent_toolkits/__init__.py index f914d0c1e24..93532981e52 100644 --- a/libs/langchain/langchain/agents/agent_toolkits/__init__.py +++ b/libs/langchain/langchain/agents/agent_toolkits/__init__.py @@ -1,4 +1,5 @@ """Agent toolkits.""" +from langchain.agents.agent_toolkits.ainetwork.toolkit import AINetworkToolkit from langchain.agents.agent_toolkits.amadeus.toolkit import AmadeusToolkit from langchain.agents.agent_toolkits.azure_cognitive_services import ( AzureCognitiveServicesToolkit, @@ -46,6 +47,7 @@ from langchain.agents.agent_toolkits.xorbits.base import create_xorbits_agent from langchain.agents.agent_toolkits.zapier.toolkit import ZapierToolkit __all__ = [ + "AINetworkToolkit", "AmadeusToolkit", "AzureCognitiveServicesToolkit", "FileManagementToolkit", diff --git a/libs/langchain/langchain/agents/agent_toolkits/ainetwork/__init__.py b/libs/langchain/langchain/agents/agent_toolkits/ainetwork/__init__.py new file mode 100644 index 00000000000..c4295f2ef48 --- /dev/null +++ b/libs/langchain/langchain/agents/agent_toolkits/ainetwork/__init__.py @@ -0,0 +1 @@ +"""AINetwork toolkit.""" diff --git a/libs/langchain/langchain/agents/agent_toolkits/ainetwork/toolkit.py b/libs/langchain/langchain/agents/agent_toolkits/ainetwork/toolkit.py new file mode 100644 index 00000000000..4fd790c949b --- /dev/null +++ b/libs/langchain/langchain/agents/agent_toolkits/ainetwork/toolkit.py @@ -0,0 +1,45 @@ +from __future__ import annotations + +from typing import TYPE_CHECKING, List, Literal, Optional + +from langchain.agents.agent_toolkits.base import BaseToolkit +from langchain.pydantic_v1 import root_validator +from langchain.tools import BaseTool +from langchain.tools.ainetwork.app import AINAppOps +from langchain.tools.ainetwork.owner import AINOwnerOps +from langchain.tools.ainetwork.rule import AINRuleOps +from langchain.tools.ainetwork.transfer import AINTransfer +from langchain.tools.ainetwork.utils import authenticate +from langchain.tools.ainetwork.value import AINValueOps + +if TYPE_CHECKING: + from ain.ain import Ain + + +class AINetworkToolkit(BaseToolkit): + """Toolkit for interacting with AINetwork Blockchain.""" + + network: Optional[Literal["mainnet", "testnet"]] = "testnet" + interface: Optional[Ain] = None + + @root_validator(pre=True) + def set_interface(cls, values: dict) -> dict: + if not values.get("interface"): + values["interface"] = authenticate(network=values.get("network", "testnet")) + return values + + class Config: + """Pydantic config.""" + + validate_all = True + arbitrary_types_allowed = True + + def get_tools(self) -> List[BaseTool]: + """Get the tools in the toolkit.""" + return [ + AINAppOps(), + AINOwnerOps(), + AINRuleOps(), + AINTransfer(), + AINValueOps(), + ] diff --git a/libs/langchain/langchain/tools/__init__.py b/libs/langchain/langchain/tools/__init__.py index ad4ae9635a8..14e34d73200 100644 --- a/libs/langchain/langchain/tools/__init__.py +++ b/libs/langchain/langchain/tools/__init__.py @@ -17,6 +17,11 @@ tool for the job. CallbackManagerForToolRun, AsyncCallbackManagerForToolRun """ +from langchain.tools.ainetwork.app import AINAppOps +from langchain.tools.ainetwork.owner import AINOwnerOps +from langchain.tools.ainetwork.rule import AINRuleOps +from langchain.tools.ainetwork.transfer import AINTransfer +from langchain.tools.ainetwork.value import AINValueOps from langchain.tools.arxiv.tool import ArxivQueryRun from langchain.tools.azure_cognitive_services import ( AzureCogsFormRecognizerTool, @@ -118,6 +123,11 @@ from langchain.tools.youtube.search import YouTubeSearchTool from langchain.tools.zapier.tool import ZapierNLAListActions, ZapierNLARunAction __all__ = [ + "AINAppOps", + "AINOwnerOps", + "AINRuleOps", + "AINTransfer", + "AINValueOps", "AIPluginTool", "APIOperation", "ArxivQueryRun", diff --git a/libs/langchain/langchain/tools/ainetwork/app.py b/libs/langchain/langchain/tools/ainetwork/app.py new file mode 100644 index 00000000000..26599d75d7e --- /dev/null +++ b/libs/langchain/langchain/tools/ainetwork/app.py @@ -0,0 +1,95 @@ +import builtins +import json +from enum import Enum +from typing import List, Optional, Type, Union + +from langchain.callbacks.manager import AsyncCallbackManagerForToolRun +from langchain.pydantic_v1 import BaseModel, Field +from langchain.tools.ainetwork.base import AINBaseTool + + +class AppOperationType(str, Enum): + SET_ADMIN = "SET_ADMIN" + GET_CONFIG = "GET_CONFIG" + + +class AppSchema(BaseModel): + type: AppOperationType = Field(...) + appName: str = Field(..., description="Name of the application on the blockchain") + address: Optional[Union[str, List[str]]] = Field( + None, + description=( + "A single address or a list of addresses. Default: current session's " + "address" + ), + ) + + +class AINAppOps(AINBaseTool): + name: str = "AINappOps" + description: str = """ +Create an app in the AINetwork Blockchain database by creating the /apps/ path. +An address set as `admin` can grant `owner` rights to other addresses (refer to `AINownerOps` for more details). +Also, `admin` is initialized to have all `owner` permissions and `rule` allowed for that path. + +## appName Rule +- [a-z_0-9]+ + +## address Rules +- 0x[0-9a-fA-F]{40} +- Defaults to the current session's address +- Multiple addresses can be specified if needed + +## SET_ADMIN Example 1 +- type: SET_ADMIN +- appName: ain_project + +### Result: +1. Path /apps/ain_project created. +2. Current session's address registered as admin. + +## SET_ADMIN Example 2 +- type: SET_ADMIN +- appName: test_project +- address: [, ] + +### Result: +1. Path /apps/test_project created. +2. and registered as admin. + +""" # noqa: E501 + args_schema: Type[BaseModel] = AppSchema + + async def _arun( + self, + type: AppOperationType, + appName: str, + address: Optional[Union[str, List[str]]] = None, + run_manager: Optional[AsyncCallbackManagerForToolRun] = None, + ) -> str: + from ain.types import ValueOnlyTransactionInput + from ain.utils import getTimestamp + + try: + if type is AppOperationType.SET_ADMIN: + if address is None: + address = self.interface.wallet.defaultAccount.address + if isinstance(address, str): + address = [address] + + res = await self.interface.db.ref( + f"/manage_app/{appName}/create/{getTimestamp()}" + ).setValue( + transactionInput=ValueOnlyTransactionInput( + value={"admin": {address: True for address in address}} + ) + ) + elif type is AppOperationType.GET_CONFIG: + res = await self.interface.db.ref( + f"/manage_app/{appName}/config" + ).getValue() + else: + raise ValueError(f"Unsupported 'type': {type}.") + return json.dumps(res, ensure_ascii=False) + except Exception as e: + return f"{builtins.type(e).__name__}: {str(e)}" diff --git a/libs/langchain/langchain/tools/ainetwork/base.py b/libs/langchain/langchain/tools/ainetwork/base.py new file mode 100644 index 00000000000..7899761302b --- /dev/null +++ b/libs/langchain/langchain/tools/ainetwork/base.py @@ -0,0 +1,71 @@ +"""Base class for AINetwork tools.""" +from __future__ import annotations + +import asyncio +import threading +from enum import Enum +from typing import TYPE_CHECKING, Any, Optional + +from langchain.callbacks.manager import CallbackManagerForToolRun +from langchain.pydantic_v1 import Field +from langchain.tools.ainetwork.utils import authenticate +from langchain.tools.base import BaseTool + +if TYPE_CHECKING: + from ain.ain import Ain + + +class OperationType(str, Enum): + SET = "SET" + GET = "GET" + + +class AINBaseTool(BaseTool): + """Base class for the AINetwork tools.""" + + interface: Ain = Field(default_factory=authenticate) + """The interface object for the AINetwork Blockchain.""" + + def _run( + self, + *args: Any, + run_manager: Optional[CallbackManagerForToolRun] = None, + **kwargs: Any, + ) -> str: + try: + loop = asyncio.get_event_loop() + except RuntimeError: + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + if loop.is_closed(): + loop = asyncio.new_event_loop() + asyncio.set_event_loop(loop) + + if loop.is_running(): + result_container = [] + + def thread_target() -> None: + nonlocal result_container + new_loop = asyncio.new_event_loop() + asyncio.set_event_loop(new_loop) + try: + result_container.append( + new_loop.run_until_complete(self._arun(*args, **kwargs)) + ) + except Exception as e: + result_container.append(e) + finally: + new_loop.close() + + thread = threading.Thread(target=thread_target) + thread.start() + thread.join() + result = result_container[0] + if isinstance(result, Exception): + raise result + return result + + else: + result = loop.run_until_complete(self._arun(*args, **kwargs)) + loop.close() + return result diff --git a/libs/langchain/langchain/tools/ainetwork/owner.py b/libs/langchain/langchain/tools/ainetwork/owner.py new file mode 100644 index 00000000000..42a2b18d861 --- /dev/null +++ b/libs/langchain/langchain/tools/ainetwork/owner.py @@ -0,0 +1,110 @@ +import builtins +import json +from typing import List, Optional, Type, Union + +from langchain.callbacks.manager import AsyncCallbackManagerForToolRun +from langchain.pydantic_v1 import BaseModel, Field +from langchain.tools.ainetwork.base import AINBaseTool, OperationType + + +class RuleSchema(BaseModel): + type: OperationType = Field(...) + path: str = Field(..., description="Blockchain reference path") + address: Optional[Union[str, List[str]]] = Field( + None, description="A single address or a list of addresses" + ) + write_owner: Optional[bool] = Field( + False, description="Authority to edit the `owner` property of the path" + ) + write_rule: Optional[bool] = Field( + False, description="Authority to edit `write rule` for the path" + ) + write_function: Optional[bool] = Field( + False, description="Authority to `set function` for the path" + ) + branch_owner: Optional[bool] = Field( + False, description="Authority to initialize `owner` of sub-paths" + ) + + +class AINOwnerOps(AINBaseTool): + name: str = "AINownerOps" + description: str = """ +Rules for `owner` in AINetwork Blockchain database. +An address set as `owner` can modify permissions according to its granted authorities + +## Path Rule +- (/[a-zA-Z_0-9]+)+ +- Permission checks ascend from the most specific (child) path to broader (parent) paths until an `owner` is located. + +## Address Rules +- 0x[0-9a-fA-F]{40}: 40-digit hexadecimal address +- *: All addresses permitted +- Defaults to the current session's address + +## SET +- `SET` alters permissions for specific addresses, while other addresses remain unaffected. +- When removing an address of `owner`, set all authorities for that address to false. +- message `write_owner permission evaluated false` if fail + +### Example +- type: SET +- path: /apps/langchain +- address: [
,
] +- write_owner: True +- write_rule: True +- write_function: True +- branch_owner: True + +## GET +- Provides all addresses with `owner` permissions and their authorities in the path. + +### Example +- type: GET +- path: /apps/langchain +""" # noqa: E501 + args_schema: Type[BaseModel] = RuleSchema + + async def _arun( + self, + type: OperationType, + path: str, + address: Optional[Union[str, List[str]]] = None, + write_owner: Optional[bool] = None, + write_rule: Optional[bool] = None, + write_function: Optional[bool] = None, + branch_owner: Optional[bool] = None, + run_manager: Optional[AsyncCallbackManagerForToolRun] = None, + ) -> str: + from ain.types import ValueOnlyTransactionInput + + try: + if type is OperationType.SET: + if address is None: + address = self.interface.wallet.defaultAccount.address + if isinstance(address, str): + address = [address] + res = await self.interface.db.ref(path).setOwner( + transactionInput=ValueOnlyTransactionInput( + value={ + ".owner": { + "owners": { + address: { + "write_owner": write_owner or False, + "write_rule": write_rule or False, + "write_function": write_function or False, + "branch_owner": branch_owner or False, + } + for address in address + } + } + } + ) + ) + elif type is OperationType.GET: + res = await self.interface.db.ref(path).getOwner() + else: + raise ValueError(f"Unsupported 'type': {type}.") + return json.dumps(res, ensure_ascii=False) + except Exception as e: + return f"{builtins.type(e).__name__}: {str(e)}" diff --git a/libs/langchain/langchain/tools/ainetwork/rule.py b/libs/langchain/langchain/tools/ainetwork/rule.py new file mode 100644 index 00000000000..d66fd20205b --- /dev/null +++ b/libs/langchain/langchain/tools/ainetwork/rule.py @@ -0,0 +1,77 @@ +import builtins +import json +from typing import Optional, Type + +from langchain.callbacks.manager import AsyncCallbackManagerForToolRun +from langchain.pydantic_v1 import BaseModel, Field +from langchain.tools.ainetwork.base import AINBaseTool, OperationType + + +class RuleSchema(BaseModel): + type: OperationType = Field(...) + path: str = Field(..., description="Path on the blockchain where the rule applies") + eval: Optional[str] = Field(None, description="eval string to determine permission") + + +class AINRuleOps(AINBaseTool): + name: str = "AINruleOps" + description: str = """ +Covers the write `rule` for the AINetwork Blockchain database. The SET type specifies write permissions using the `eval` variable as a JavaScript eval string. +In order to AINvalueOps with SET at the path, the execution result of the `eval` string must be true. + +## Path Rules +1. Allowed characters for directory: `[a-zA-Z_0-9]` +2. Use `$` for template variables as directory. + +## Eval String Special Variables +- auth.addr: Address of the writer for the path +- newData: New data for the path +- data: Current data for the path +- currentTime: Time in seconds +- lastBlockNumber: Latest processed block number + +## Eval String Functions +- getValue() +- getRule() +- getOwner() +- getFunction() +- evalRule(, , auth, currentTime) +- evalOwner(, 'write_owner', auth) + +## SET Example +- type: SET +- path: /apps/langchain_project_1/$from/$to/$img +- eval: auth.addr===$from&&!getValue('/apps/image_db/'+$img) + +## GET Example +- type: GET +- path: /apps/langchain_project_1 +""" # noqa: E501 + args_schema: Type[BaseModel] = RuleSchema + + async def _arun( + self, + type: OperationType, + path: str, + eval: Optional[str] = None, + run_manager: Optional[AsyncCallbackManagerForToolRun] = None, + ) -> str: + from ain.types import ValueOnlyTransactionInput + + try: + if type is OperationType.SET: + if eval is None: + raise ValueError("'eval' is required for SET operation.") + + res = await self.interface.db.ref(path).setRule( + transactionInput=ValueOnlyTransactionInput( + value={".rule": {"write": eval}} + ) + ) + elif type is OperationType.GET: + res = await self.interface.db.ref(path).getRule() + else: + raise ValueError(f"Unsupported 'type': {type}.") + return json.dumps(res, ensure_ascii=False) + except Exception as e: + return f"{builtins.type(e).__name__}: {str(e)}" diff --git a/libs/langchain/langchain/tools/ainetwork/transfer.py b/libs/langchain/langchain/tools/ainetwork/transfer.py new file mode 100644 index 00000000000..b267f724a32 --- /dev/null +++ b/libs/langchain/langchain/tools/ainetwork/transfer.py @@ -0,0 +1,29 @@ +import json +from typing import Optional, Type + +from langchain.callbacks.manager import AsyncCallbackManagerForToolRun +from langchain.pydantic_v1 import BaseModel, Field +from langchain.tools.ainetwork.base import AINBaseTool + + +class TransferSchema(BaseModel): + address: str = Field(..., description="Address to transfer AIN to") + amount: int = Field(..., description="Amount of AIN to transfer") + + +class AINTransfer(AINBaseTool): + name: str = "AINtransfer" + description: str = "Transfers AIN to a specified address" + args_schema: Type[TransferSchema] = TransferSchema + + async def _arun( + self, + address: str, + amount: int, + run_manager: Optional[AsyncCallbackManagerForToolRun] = None, + ) -> str: + try: + res = await self.interface.wallet.transfer(address, amount, nonce=-1) + return json.dumps(res, ensure_ascii=False) + except Exception as e: + return f"{type(e).__name__}: {str(e)}" diff --git a/libs/langchain/langchain/tools/ainetwork/utils.py b/libs/langchain/langchain/tools/ainetwork/utils.py new file mode 100644 index 00000000000..0f8179a6075 --- /dev/null +++ b/libs/langchain/langchain/tools/ainetwork/utils.py @@ -0,0 +1,62 @@ +"""AINetwork Blockchain tool utils.""" +from __future__ import annotations + +import os +from typing import TYPE_CHECKING, Literal, Optional + +if TYPE_CHECKING: + from ain.ain import Ain + + +def authenticate(network: Optional[Literal["mainnet", "testnet"]] = "testnet") -> Ain: + """Authenticate using the AIN Blockchain""" + + try: + from ain.ain import Ain + except ImportError as e: + raise ImportError( + "Cannot import ain-py related modules. Please install the package with " + "`pip install ain-py`." + ) from e + + if network == "mainnet": + provider_url = "https://mainnet-api.ainetwork.ai/" + chain_id = 1 + if "AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY" in os.environ: + private_key = os.environ["AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY"] + else: + raise EnvironmentError( + "Error: The AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY environmental variable " + "has not been set." + ) + elif network == "testnet": + provider_url = "https://testnet-api.ainetwork.ai/" + chain_id = 0 + if "AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY" in os.environ: + private_key = os.environ["AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY"] + else: + raise EnvironmentError( + "Error: The AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY environmental variable " + "has not been set." + ) + elif network is None: + if ( + "AIN_BLOCKCHAIN_PROVIDER_URL" in os.environ + and "AIN_BLOCKCHAIN_CHAIN_ID" in os.environ + and "AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY" in os.environ + ): + provider_url = os.environ["AIN_BLOCKCHAIN_PROVIDER_URL"] + chain_id = int(os.environ["AIN_BLOCKCHAIN_CHAIN_ID"]) + private_key = os.environ["AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY"] + else: + raise EnvironmentError( + "Error: The AIN_BLOCKCHAIN_PROVIDER_URL and " + "AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY and AIN_BLOCKCHAIN_CHAIN_ID " + "environmental variable has not been set." + ) + else: + raise ValueError(f"Unsupported 'network': {network}") + + ain = Ain(provider_url, chain_id) + ain.wallet.addAndSetDefaultAccount(private_key) + return ain diff --git a/libs/langchain/langchain/tools/ainetwork/value.py b/libs/langchain/langchain/tools/ainetwork/value.py new file mode 100644 index 00000000000..2e6c92c685d --- /dev/null +++ b/libs/langchain/langchain/tools/ainetwork/value.py @@ -0,0 +1,80 @@ +import builtins +import json +from typing import Optional, Type, Union + +from langchain.callbacks.manager import AsyncCallbackManagerForToolRun +from langchain.pydantic_v1 import BaseModel, Field +from langchain.tools.ainetwork.base import AINBaseTool, OperationType + + +class ValueSchema(BaseModel): + type: OperationType = Field(...) + path: str = Field(..., description="Blockchain reference path") + value: Optional[Union[int, str, float, dict]] = Field( + None, description="Value to be set at the path" + ) + + +class AINValueOps(AINBaseTool): + name: str = "AINvalueOps" + description: str = """ +Covers the read and write value for the AINetwork Blockchain database. + +## SET +- Set a value at a given path + +### Example +- type: SET +- path: /apps/langchain_test_1/object +- value: {1: 2, "34": 56} + +## GET +- Retrieve a value at a given path + +### Example +- type: GET +- path: /apps/langchain_test_1/DB + +## Special paths +- `/accounts/
/balance`: Account balance +- `/accounts/
/nonce`: Account nonce +- `/apps`: Applications +- `/consensus`: Consensus +- `/checkin`: Check-in +- `/deposit//
/`: Deposit +- `/deposit_accounts//
/`: Deposit accounts +- `/escrow`: Escrow +- `/payments`: Payment +- `/sharding`: Sharding +- `/token/name`: Token name +- `/token/symbol`: Token symbol +- `/token/total_supply`: Token total supply +- `/transfer/
/
//value`: Transfer +- `/withdraw//
/`: Withdraw +""" + args_schema: Type[BaseModel] = ValueSchema + + async def _arun( + self, + type: OperationType, + path: str, + value: Optional[Union[int, str, float, dict]] = None, + run_manager: Optional[AsyncCallbackManagerForToolRun] = None, + ) -> str: + from ain.types import ValueOnlyTransactionInput + + try: + if type is OperationType.SET: + if value is None: + raise ValueError("'value' is required for SET operation.") + + res = await self.interface.db.ref(path).setValue( + transactionInput=ValueOnlyTransactionInput(value=value) + ) + elif type is OperationType.GET: + res = await self.interface.db.ref(path).getValue() + else: + raise ValueError(f"Unsupported 'type': {type}.") + return json.dumps(res, ensure_ascii=False) + except Exception as e: + return f"{builtins.type(e).__name__}: {str(e)}" diff --git a/libs/langchain/tests/integration_tests/agent/test_ainetwork_agent.py b/libs/langchain/tests/integration_tests/agent/test_ainetwork_agent.py new file mode 100644 index 00000000000..58dd462ba66 --- /dev/null +++ b/libs/langchain/tests/integration_tests/agent/test_ainetwork_agent.py @@ -0,0 +1,175 @@ +import asyncio +import os +import time +import urllib.request +import uuid +from enum import Enum +from typing import Any +from urllib.error import HTTPError + +import pytest + +from langchain.agents import AgentType, initialize_agent +from langchain.agents.agent_toolkits.ainetwork.toolkit import AINetworkToolkit +from langchain.chat_models import ChatOpenAI +from langchain.tools.ainetwork.utils import authenticate + + +class Match(Enum): + __test__ = False + ListWildcard = 1 + StrWildcard = 2 + DictWildcard = 3 + IntWildcard = 4 + FloatWildcard = 5 + ObjectWildcard = 6 + + @classmethod + def match(cls, value: Any, template: Any) -> bool: + if template is cls.ListWildcard: + return isinstance(value, list) + elif template is cls.StrWildcard: + return isinstance(value, str) + elif template is cls.DictWildcard: + return isinstance(value, dict) + elif template is cls.IntWildcard: + return isinstance(value, int) + elif template is cls.FloatWildcard: + return isinstance(value, float) + elif template is cls.ObjectWildcard: + return True + elif type(value) != type(template): + return False + elif isinstance(value, dict): + if len(value) != len(template): + return False + for k, v in value.items(): + if k not in template or not cls.match(v, template[k]): + return False + return True + elif isinstance(value, list): + if len(value) != len(template): + return False + for i in range(len(value)): + if not cls.match(value[i], template[i]): + return False + return True + else: + return value == template + + +@pytest.mark.requires("ain") +def test_ainetwork_toolkit() -> None: + def get(path: str, type: str = "value", default: Any = None) -> Any: + ref = ain.db.ref(path) + value = asyncio.run( + { + "value": ref.getValue, + "rule": ref.getRule, + "owner": ref.getOwner, + }[type]() + ) + return default if value is None else value + + def validate(path: str, template: Any, type: str = "value") -> bool: + value = get(path, type) + return Match.match(value, template) + + if not os.environ.get("AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY", None): + from ain.account import Account + + account = Account.create() + os.environ["AIN_BLOCKCHAIN_ACCOUNT_PRIVATE_KEY"] = account.private_key + + interface = authenticate(network="testnet") + toolkit = AINetworkToolkit(network="testnet", interface=interface) + llm = ChatOpenAI(model="gpt-4", temperature=0) + agent = initialize_agent( + tools=toolkit.get_tools(), + llm=llm, + verbose=True, + agent=AgentType.OPENAI_FUNCTIONS, + ) + ain = interface + self_address = ain.wallet.defaultAccount.address + co_address = "0x6813Eb9362372EEF6200f3b1dbC3f819671cBA69" + + # Test creating an app + UUID = uuid.UUID( + int=(int(time.time() * 1000) << 64) | (uuid.uuid4().int & ((1 << 64) - 1)) + ) + app_name = f"_langchain_test__{str(UUID).replace('-', '_')}" + agent.run(f"""Create app {app_name}""") + validate(f"/manage_app/{app_name}/config", {"admin": {self_address: True}}) + validate(f"/apps/{app_name}/DB", None, "owner") + + # Test reading owner config + agent.run(f"""Read owner config of /apps/{app_name}/DB .""") + assert ... + + # Test granting owner config + agent.run( + f"""Grant owner authority to {co_address} for edit write rule permission of /apps/{app_name}/DB_co .""" # noqa: E501 + ) + validate( + f"/apps/{app_name}/DB_co", + { + ".owner": { + "owners": { + co_address: { + "branch_owner": False, + "write_function": False, + "write_owner": False, + "write_rule": True, + } + } + } + }, + "owner", + ) + + # Test reading owner config + agent.run(f"""Read owner config of /apps/{app_name}/DB_co .""") + assert ... + + # Test reading owner config + agent.run(f"""Read owner config of /apps/{app_name}/DB .""") + assert ... # Check if owner {self_address} exists + + # Test reading a value + agent.run(f"""Read value in /apps/{app_name}/DB""") + assert ... # empty + + # Test writing a value + agent.run(f"""Write value {{1: 1904, 2: 43}} in /apps/{app_name}/DB""") + validate(f"/apps/{app_name}/DB", {1: 1904, 2: 43}) + + # Test reading a value + agent.run(f"""Read value in /apps/{app_name}/DB""") + assert ... # check value + + # Test reading a rule + agent.run(f"""Read write rule of app {app_name} .""") + assert ... # check rule that self_address exists + + # Test sending AIN + self_balance = get(f"/accounts/{self_address}/balance", default=0) + transaction_history = get(f"/transfer/{self_address}/{co_address}", default={}) + if self_balance < 1: + try: + with urllib.request.urlopen( + f"http://faucet.ainetwork.ai/api/test/{self_address}/" + ) as response: + try_test = response.getcode() + except HTTPError as e: + try_test = e.getcode() + else: + try_test = 200 + + if try_test == 200: + agent.run(f"""Send 1 AIN to {co_address}""") + transaction_update = get(f"/transfer/{self_address}/{co_address}", default={}) + assert any( + transaction_update[key]["value"] == 1 + for key in transaction_update.keys() - transaction_history.keys() + ) diff --git a/libs/langchain/tests/unit_tests/tools/test_public_api.py b/libs/langchain/tests/unit_tests/tools/test_public_api.py index 43c2fb905ae..6d58dd92ef2 100644 --- a/libs/langchain/tests/unit_tests/tools/test_public_api.py +++ b/libs/langchain/tests/unit_tests/tools/test_public_api.py @@ -2,6 +2,11 @@ from langchain.tools import __all__ as public_api _EXPECTED = [ + "AINAppOps", + "AINOwnerOps", + "AINRuleOps", + "AINTransfer", + "AINValueOps", "AIPluginTool", "APIOperation", "ArxivQueryRun", From 2b663089b5f6f16890c134d14981db7a0eb446ba Mon Sep 17 00:00:00 2001 From: Bagatur <22008038+baskaryan@users.noreply.github.com> Date: Tue, 22 Aug 2023 08:10:22 -0700 Subject: [PATCH 09/38] bump 271 (#9615) --- libs/langchain/pyproject.toml | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml index 8c3c8c18df2..9f7ab96907a 100644 --- a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -1,6 +1,6 @@ [tool.poetry] name = "langchain" -version = "0.0.270" +version = "0.0.271" description = "Building applications with LLMs through composability" authors = [] license = "MIT" From c75e1aa5ed1cad4e3c53bef26644ad1a1137d30a Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 11:36:52 -0400 Subject: [PATCH 10/38] Eliminate special-casing from test CI workflows. (#9562) The previous approach was relying on `_test.yml` taking an input parameter, and then doing almost completely orthogonal things for each parameter value. I've separated out each of those test situations as its own job or workflow file, which eliminated all the special-casing and, in my opinion, improved maintainability by making it much more obvious what code runs when. --- .github/workflows/_pydantic_compatibility.yml | 76 +++++++++++++++++++ .github/workflows/_test.yml | 58 ++------------ .github/workflows/langchain_ci.yml | 44 ++++++++++- .../workflows/langchain_experimental_ci.yml | 3 +- 4 files changed, 124 insertions(+), 57 deletions(-) create mode 100644 .github/workflows/_pydantic_compatibility.yml diff --git a/.github/workflows/_pydantic_compatibility.yml b/.github/workflows/_pydantic_compatibility.yml new file mode 100644 index 00000000000..5a54c2f53c7 --- /dev/null +++ b/.github/workflows/_pydantic_compatibility.yml @@ -0,0 +1,76 @@ +name: pydantic v1/v2 compatibility + +on: + workflow_call: + inputs: + working-directory: + required: true + type: string + description: "From which folder this pipeline executes" + +env: + POETRY_VERSION: "1.5.1" + +jobs: + build: + defaults: + run: + working-directory: ${{ inputs.working-directory }} + runs-on: ubuntu-latest + strategy: + matrix: + python-version: + - "3.8" + - "3.9" + - "3.10" + - "3.11" + name: Pydantic v1/v2 compatibility - Python ${{ matrix.python-version }} + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: "./.github/actions/poetry_setup" + with: + python-version: ${{ matrix.python-version }} + working-directory: ${{ inputs.working-directory }} + poetry-version: ${{ env.POETRY_VERSION }} + cache-key: pydantic-cross-compat + install-command: poetry install + - name: Install the opposite major version of pydantic + # If normal tests use pydantic v1, here we'll use v2, and vice versa. + shell: bash + run: | + # Determine the major part of pydantic version + REGULAR_VERSION=$(poetry run python -c "import pydantic; print(pydantic.__version__)" | cut -d. -f1) + + if [[ "$REGULAR_VERSION" == "1" ]]; then + PYDANTIC_DEP=">=2.1,<3" + TEST_WITH_VERSION="2" + elif [[ "$REGULAR_VERSION" == "2" ]]; then + PYDANTIC_DEP="<2" + TEST_WITH_VERSION="1" + else + echo "Unexpected pydantic major version '$REGULAR_VERSION', cannot determine which version to use for cross-compatibility test." + exit 1 + fi + + # Install via `pip` instead of `poetry add` to avoid changing lockfile, + # which would prevent caching from working: the cache would get saved + # to a different key than where it gets loaded from. + poetry run pip install "pydantic${PYDANTIC_DEP}" + + # Ensure that the correct pydantic is installed now. + echo "Checking pydantic version... Expecting ${TEST_WITH_VERSION}" + + # Determine the major part of pydantic version + CURRENT_VERSION=$(poetry run python -c "import pydantic; print(pydantic.__version__)" | cut -d. -f1) + + # Check that the major part of pydantic version is as expected, if not + # raise an error + if [[ "$CURRENT_VERSION" != "$TEST_WITH_VERSION" ]]; then + echo "Error: expected pydantic version ${CURRENT_VERSION} to have been installed, but found: ${TEST_WITH_VERSION}" + exit 1 + fi + echo "Found pydantic version ${CURRENT_VERSION}, as expected" + - name: Run pydantic compatibility tests + shell: bash + run: make test diff --git a/.github/workflows/_test.yml b/.github/workflows/_test.yml index 3cc424cb7a1..179b6303d76 100644 --- a/.github/workflows/_test.yml +++ b/.github/workflows/_test.yml @@ -7,10 +7,6 @@ on: required: true type: string description: "From which folder this pipeline executes" - test_type: - type: string - description: "Test types to run" - default: '["core", "extended", "core-pydantic-2"]' env: POETRY_VERSION: "1.5.1" @@ -28,8 +24,7 @@ jobs: - "3.9" - "3.10" - "3.11" - test_type: ${{ fromJSON(inputs.test_type) }} - name: Python ${{ matrix.python-version }} ${{ matrix.test_type }} + name: Python ${{ matrix.python-version }} steps: - uses: actions/checkout@v3 - name: Set up Python ${{ matrix.python-version }} @@ -38,51 +33,8 @@ jobs: python-version: ${{ matrix.python-version }} working-directory: ${{ inputs.working-directory }} poetry-version: ${{ env.POETRY_VERSION }} - cache-key: ${{ matrix.test_type }} - install-command: | - if [ "${{ matrix.test_type }}" == "core" ]; then - echo "Running core tests, installing dependencies with poetry..." - poetry install - elif [ "${{ matrix.test_type }}" == "core-pydantic-2" ]; then - echo "Running core-pydantic-v2 tests, installing dependencies with poetry..." - poetry install - - # Install via `pip` instead of `poetry add` to avoid changing lockfile, - # which would prevent caching from working: the cache would get saved - # to a different key than where it gets loaded from. - poetry run pip install 'pydantic>=2.1,<3' - else - echo "Running extended tests, installing dependencies with poetry..." - poetry install -E extended_testing - fi - - name: Verify pydantic version - run: | - if [ "${{ matrix.test_type }}" == "core-pydantic-2" ]; then - EXPECTED_VERSION=2 - else - EXPECTED_VERSION=1 - fi - echo "Checking pydantic version... Expecting ${EXPECTED_VERSION}" - - # Determine the major part of pydantic version - VERSION=$(poetry run python -c "import pydantic; print(pydantic.__version__)" | cut -d. -f1) - - # Check that the major part of pydantic version is as expected, if not - # raise an error - if [[ "$VERSION" -ne $EXPECTED_VERSION ]]; then - echo "Error: pydantic version must be equal to ${EXPECTED_VERSION}; Found: ${VERSION}" - exit 1 - fi - echo "Found pydantic version ${VERSION}, as expected" - shell: bash - - name: Run ${{matrix.test_type}} tests - run: | - case "${{ matrix.test_type }}" in - core | core-pydantic-2) - make test - ;; - *) - make extended_tests - ;; - esac + cache-key: core + install-command: poetry install + - name: Run core tests shell: bash + run: make test diff --git a/.github/workflows/langchain_ci.yml b/.github/workflows/langchain_ci.yml index 9dfbd8c3d6e..b91e039ea6f 100644 --- a/.github/workflows/langchain_ci.yml +++ b/.github/workflows/langchain_ci.yml @@ -8,10 +8,15 @@ on: paths: - '.github/workflows/_lint.yml' - '.github/workflows/_test.yml' + - '.github/workflows/_pydantic_compatibility.yml' - '.github/workflows/langchain_ci.yml' - 'libs/langchain/**' workflow_dispatch: # Allows to trigger the workflow manually in GitHub UI +env: + POETRY_VERSION: "1.5.1" + WORKDIR: "libs/langchain" + jobs: lint: uses: @@ -19,10 +24,45 @@ jobs: with: working-directory: libs/langchain secrets: inherit + test: uses: ./.github/workflows/_test.yml with: working-directory: libs/langchain - test_type: '["core", "extended", "core-pydantic-2"]' - secrets: inherit \ No newline at end of file + secrets: inherit + + pydantic-compatibility: + uses: + ./.github/workflows/_pydantic_compatibility.yml + with: + working-directory: libs/langchain + secrets: inherit + + extended-tests: + runs-on: ubuntu-latest + defaults: + run: + working-directory: ${{ env.WORKDIR }} + strategy: + matrix: + python-version: + - "3.8" + - "3.9" + - "3.10" + - "3.11" + name: Python ${{ matrix.python-version }} extended tests + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: "./.github/actions/poetry_setup" + with: + python-version: ${{ matrix.python-version }} + working-directory: ${{ env.WORKDIR }} + poetry-version: ${{ env.POETRY_VERSION }} + cache-key: extended + install-command: | + echo "Running extended tests, installing dependencies with poetry..." + poetry install -E extended_testing + - name: Run extended tests + run: make extended_tests diff --git a/.github/workflows/langchain_experimental_ci.yml b/.github/workflows/langchain_experimental_ci.yml index 9c95634e49c..e1d6e66a846 100644 --- a/.github/workflows/langchain_experimental_ci.yml +++ b/.github/workflows/langchain_experimental_ci.yml @@ -25,5 +25,4 @@ jobs: ./.github/workflows/_test.yml with: working-directory: libs/experimental - test_type: '["core"]' - secrets: inherit \ No newline at end of file + secrets: inherit From a1e89aa8d552d8ae207260e9e9035407e5e3e516 Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 11:38:18 -0400 Subject: [PATCH 11/38] Explicitly add the `contents: write` permission for publishing releases. (#9617) --- .github/workflows/_release.yml | 3 +++ 1 file changed, 3 insertions(+) diff --git a/.github/workflows/_release.yml b/.github/workflows/_release.yml index d24bf983a1f..5ddf79ca7c2 100644 --- a/.github/workflows/_release.yml +++ b/.github/workflows/_release.yml @@ -23,6 +23,9 @@ jobs: # Trusted publishing has to also be configured on PyPI for each package: # https://docs.pypi.org/trusted-publishers/adding-a-publisher/ id-token: write + + # This permission is needed by `ncipollo/release-action` to create the GitHub release. + contents: write defaults: run: working-directory: ${{ inputs.working-directory }} From acb54d8b9da9c5bcf73fade48c3c20f54388662a Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 12:11:38 -0400 Subject: [PATCH 12/38] Reduce cache timeouts to ensure faster builds on timeout. (#9619) The current timeouts are too long, and mean that if the GitHub cache decides to act up, jobs get bogged down for 15min at a time. This has happened 2-3 times already this week -- a tiny fraction of our total workflows but really annoying when it happens to you. We can do better. Installing deps on cache miss takes about ~4min, so it's not worth waiting more than 4min for the deps cache. The black and mypy caches save 1 and 2min, respectively, so wait only up to that long to download them. --- .github/actions/poetry_setup/action.yml | 4 ++-- .github/workflows/_lint.yml | 8 ++++---- 2 files changed, 6 insertions(+), 6 deletions(-) diff --git a/.github/actions/poetry_setup/action.yml b/.github/actions/poetry_setup/action.yml index 6dbe000264e..39c76bec4c1 100644 --- a/.github/actions/poetry_setup/action.yml +++ b/.github/actions/poetry_setup/action.yml @@ -41,7 +41,7 @@ runs: id: cache-pip name: Cache Pip ${{ inputs.python-version }} env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "15" + SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" with: path: | ~/.cache/pip @@ -69,7 +69,7 @@ runs: - uses: actions/cache@v3 id: cache-poetry env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "15" + SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }} with: path: | diff --git a/.github/workflows/_lint.yml b/.github/workflows/_lint.yml index c850258d195..5b1c35a9d8c 100644 --- a/.github/workflows/_lint.yml +++ b/.github/workflows/_lint.yml @@ -84,7 +84,7 @@ jobs: id: cache-pip name: Cache langchain editable pip install - ${{ matrix.python-version }} env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "15" + SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" with: path: | ~/.cache/pip @@ -95,7 +95,7 @@ jobs: - name: Set up Python ${{ matrix.python-version }} uses: actions/setup-python@v4 env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "15" + SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" with: python-version: ${{ matrix.python-version }} cache: poetry @@ -115,7 +115,7 @@ jobs: uses: actions/cache@v3 env: CACHE_BASE: black-${{ runner.os }}-${{ runner.arch }}-py${{ matrix.python-version }}-${{ inputs.working-directory }}-${{ hashFiles(format('{0}/poetry.lock', env.WORKDIR)) }} - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "15" + SEGMENT_DOWNLOAD_TIMEOUT_MIN: "1" with: path: | ${{ env.WORKDIR }}/.black_cache @@ -127,7 +127,7 @@ jobs: - name: Get .mypy_cache to speed up mypy uses: actions/cache@v3 env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "15" + SEGMENT_DOWNLOAD_TIMEOUT_MIN: "2" with: path: | ${{ env.WORKDIR }}/.mypy_cache From 34088107481a029b60bc6dd166770e80ff72fadd Mon Sep 17 00:00:00 2001 From: Eugene Yurtsev Date: Tue, 22 Aug 2023 12:31:18 -0400 Subject: [PATCH 13/38] Add batch util (#9620) Add `batch` utility to langchain --- libs/langchain/langchain/utils/iter.py | 12 +++++++++++ .../tests/unit_tests/utils/__init__.py | 0 .../tests/unit_tests/utils/test_iter.py | 21 +++++++++++++++++++ 3 files changed, 33 insertions(+) create mode 100644 libs/langchain/tests/unit_tests/utils/__init__.py create mode 100644 libs/langchain/tests/unit_tests/utils/test_iter.py diff --git a/libs/langchain/langchain/utils/iter.py b/libs/langchain/langchain/utils/iter.py index 1b95f180ea4..60834163c3f 100644 --- a/libs/langchain/langchain/utils/iter.py +++ b/libs/langchain/langchain/utils/iter.py @@ -1,10 +1,12 @@ from collections import deque +from itertools import islice from typing import ( Any, ContextManager, Deque, Generator, Generic, + Iterable, Iterator, List, Optional, @@ -161,3 +163,13 @@ class Tee(Generic[T]): # Why this is needed https://stackoverflow.com/a/44638570 safetee = Tee + + +def batch_iterate(size: int, iterable: Iterable[T]) -> Iterator[List[T]]: + """Utility batching function.""" + it = iter(iterable) + while True: + chunk = list(islice(it, size)) + if not chunk: + return + yield chunk diff --git a/libs/langchain/tests/unit_tests/utils/__init__.py b/libs/langchain/tests/unit_tests/utils/__init__.py new file mode 100644 index 00000000000..e69de29bb2d diff --git a/libs/langchain/tests/unit_tests/utils/test_iter.py b/libs/langchain/tests/unit_tests/utils/test_iter.py new file mode 100644 index 00000000000..f0fd8bf4ce5 --- /dev/null +++ b/libs/langchain/tests/unit_tests/utils/test_iter.py @@ -0,0 +1,21 @@ +from typing import List + +import pytest + +from langchain.utils.iter import batch_iterate + + +@pytest.mark.parametrize( + "input_size, input_iterable, expected_output", + [ + (2, [1, 2, 3, 4, 5], [[1, 2], [3, 4], [5]]), + (3, [10, 20, 30, 40, 50], [[10, 20, 30], [40, 50]]), + (1, [100, 200, 300], [[100], [200], [300]]), + (4, [], []), + ], +) +def test_batch_iterate( + input_size: int, input_iterable: List[str], expected_output: List[str] +) -> None: + """Test batching function.""" + assert list(batch_iterate(input_size, input_iterable)) == expected_output From 3c7cc4d4402a60bb43adf70f4f2037d3d784d24c Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 13:35:21 -0400 Subject: [PATCH 14/38] Test experimental package with `langchain` on `master` branch. (#9621) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit It's possible that langchain-experimental works fine with the latest *published* langchain, but is broken with the langchain on `master`. Unfortunately, you can see this is currently the case — this is why this PR also includes a minor fix for the `langchain` package itself. We want to catch situations like that *before* releasing a new langchain, hence this test. --- .../workflows/langchain_experimental_ci.yml | 40 +++++++++++++++++++ libs/langchain/langchain/llms/base.py | 10 +++-- 2 files changed, 47 insertions(+), 3 deletions(-) diff --git a/.github/workflows/langchain_experimental_ci.yml b/.github/workflows/langchain_experimental_ci.yml index e1d6e66a846..cee8cdb7d31 100644 --- a/.github/workflows/langchain_experimental_ci.yml +++ b/.github/workflows/langchain_experimental_ci.yml @@ -13,6 +13,10 @@ on: - 'libs/experimental/**' workflow_dispatch: # Allows to trigger the workflow manually in GitHub UI +env: + POETRY_VERSION: "1.5.1" + WORKDIR: "libs/experimental" + jobs: lint: uses: @@ -20,9 +24,45 @@ jobs: with: working-directory: libs/experimental secrets: inherit + test: uses: ./.github/workflows/_test.yml with: working-directory: libs/experimental secrets: inherit + + # It's possible that langchain-experimental works fine with the latest *published* langchain, + # but is broken with the langchain on `master`. + # + # We want to catch situations like that *before* releasing a new langchain, hence this test. + test-with-latest-langchain: + runs-on: ubuntu-latest + defaults: + run: + working-directory: ${{ env.WORKDIR }} + strategy: + matrix: + python-version: + - "3.8" + - "3.9" + - "3.10" + - "3.11" + name: test with unpublished langchain - Python ${{ matrix.python-version }} + steps: + - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} + uses: "./.github/actions/poetry_setup" + with: + python-version: ${{ matrix.python-version }} + working-directory: ${{ env.WORKDIR }} + poetry-version: ${{ env.POETRY_VERSION }} + cache-key: unpublished-langchain + install-command: | + echo "Running tests with unpublished langchain, installing dependencies with poetry..." + poetry install + + echo "Editably installing langchain outside of poetry, to avoid messing up lockfile..." + poetry run pip install -e ../langchain + - name: Run tests + run: make test diff --git a/libs/langchain/langchain/llms/base.py b/libs/langchain/langchain/llms/base.py index a833487ffb1..a91ecd9f2ac 100644 --- a/libs/langchain/langchain/llms/base.py +++ b/libs/langchain/langchain/llms/base.py @@ -528,9 +528,13 @@ class BaseLLM(BaseLanguageModel[str], ABC): f" argument of type {type(prompts)}." ) # Create callback managers - if isinstance(callbacks, list) and ( - isinstance(callbacks[0], (list, BaseCallbackManager)) - or callbacks[0] is None + if ( + isinstance(callbacks, list) + and callbacks + and ( + isinstance(callbacks[0], (list, BaseCallbackManager)) + or callbacks[0] is None + ) ): # We've received a list of callbacks args to apply to each input assert len(callbacks) == len(prompts) From 64a54d8ad80fa8a41bb69f3c2c176980df631cbb Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 14:09:11 -0400 Subject: [PATCH 15/38] `poetry lock` the top-level environment. (#9477) --- poetry.lock | 758 +++++++++++++++++++++++++--------------------------- 1 file changed, 363 insertions(+), 395 deletions(-) diff --git a/poetry.lock b/poetry.lock index 7599ad353e8..8210605be8d 100644 --- a/poetry.lock +++ b/poetry.lock @@ -167,22 +167,23 @@ files = [ [[package]] name = "argon2-cffi" -version = "21.3.0" -description = "The secure Argon2 password hashing algorithm." +version = "23.1.0" +description = "Argon2 for Python" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" files = [ - {file = "argon2-cffi-21.3.0.tar.gz", hash = "sha256:d384164d944190a7dd7ef22c6aa3ff197da12962bd04b17f64d4e93d934dba5b"}, - {file = "argon2_cffi-21.3.0-py3-none-any.whl", hash = "sha256:8c976986f2c5c0e5000919e6de187906cfd81fb1c72bf9d88c01177e77da7f80"}, + {file = "argon2_cffi-23.1.0-py3-none-any.whl", hash = "sha256:c670642b78ba29641818ab2e68bd4e6a78ba53b7eff7b4c3815ae16abf91c7ea"}, + {file = "argon2_cffi-23.1.0.tar.gz", hash = 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`poetry lock` on langchain. 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{file = "weaviate_client-3.20.1-py3-none-any.whl", hash = "sha256:175f1665d9f1e580dcfa48cfd4dab1e49925d1655b0b4720d0f2ee7709c956f6"}, + {file = "weaviate-client-3.23.0.tar.gz", hash = "sha256:3ffd7f1460c9e32755d84d4f5fc63dfc0bd990dbe2c3dc20d5c68119d467680e"}, + {file = "weaviate_client-3.23.0-py3-none-any.whl", hash = "sha256:3d3bb75c1d96b2b71e213c5eb885ae3e3f42e4304955383c467d100187d9ff8e"}, ] [package.dependencies] @@ -9940,7 +9795,6 @@ grpc = ["grpcio", "grpcio-tools"] name = "webcolors" version = "1.13" description = "A library for working with the color formats defined by HTML and CSS." -category = "dev" optional = false python-versions = ">=3.7" files = [ @@ -9956,7 +9810,6 @@ tests = ["pytest", "pytest-cov"] name = "webencodings" version = "0.5.1" description = "Character encoding aliases for legacy web content" -category = "dev" optional = false python-versions = "*" files = [ @@ -9966,31 +9819,29 @@ files = [ [[package]] name = "websocket-client" -version = "1.6.0" +version = "1.6.2" description = "WebSocket client for Python with low level API options" -category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "websocket-client-1.6.0.tar.gz", hash = "sha256:e84c7eafc66aade6d1967a51dfd219aabdf81d15b9705196e11fd81f48666b78"}, - {file = "websocket_client-1.6.0-py3-none-any.whl", hash = "sha256:72d7802608745b0a212f79b478642473bd825777d8637b6c8c421bf167790d4f"}, + {file = "websocket-client-1.6.2.tar.gz", hash = "sha256:53e95c826bf800c4c465f50093a8c4ff091c7327023b10bfaff40cf1ef170eaa"}, + {file = "websocket_client-1.6.2-py3-none-any.whl", hash = "sha256:ce54f419dfae71f4bdba69ebe65bf7f0a93fe71bc009ad3a010aacc3eebad537"}, ] [package.extras] -docs = ["Sphinx (>=3.4)", "sphinx-rtd-theme (>=0.5)"] +docs = ["Sphinx (>=6.0)", "sphinx-rtd-theme (>=1.1.0)"] optional = ["python-socks", "wsaccel"] test = ["websockets"] [[package]] name = "werkzeug" -version = "2.3.6" +version = "2.3.7" description = "The comprehensive WSGI web application library." -category = "main" optional = true python-versions = ">=3.8" files = [ - {file = "Werkzeug-2.3.6-py3-none-any.whl", hash = "sha256:935539fa1413afbb9195b24880778422ed620c0fc09670945185cce4d91a8890"}, - {file = "Werkzeug-2.3.6.tar.gz", hash = "sha256:98c774df2f91b05550078891dee5f0eb0cb797a522c757a2452b9cee5b202330"}, + {file = "werkzeug-2.3.7-py3-none-any.whl", hash = "sha256:effc12dba7f3bd72e605ce49807bbe692bd729c3bb122a3b91747a6ae77df528"}, + {file = "werkzeug-2.3.7.tar.gz", hash = "sha256:2b8c0e447b4b9dbcc85dd97b6eeb4dcbaf6c8b6c3be0bd654e25553e0a2157d8"}, ] [package.dependencies] @@ -10003,7 +9854,6 @@ watchdog = ["watchdog (>=2.3)"] name = "wget" version = "3.2" description = "pure python download utility" -category = "main" optional = true python-versions = "*" files = [ @@ -10012,29 +9862,27 @@ files = [ [[package]] name = "wheel" -version = "0.40.0" +version = "0.41.2" description = "A built-package format for Python" -category = "main" optional = true python-versions = ">=3.7" files = [ - {file = "wheel-0.40.0-py3-none-any.whl", hash = "sha256:d236b20e7cb522daf2390fa84c55eea81c5c30190f90f29ae2ca1ad8355bf247"}, - {file = "wheel-0.40.0.tar.gz", hash = "sha256:cd1196f3faee2b31968d626e1731c94f99cbdb67cf5a46e4f5656cbee7738873"}, + {file = "wheel-0.41.2-py3-none-any.whl", hash = "sha256:75909db2664838d015e3d9139004ee16711748a52c8f336b52882266540215d8"}, + {file = "wheel-0.41.2.tar.gz", hash = "sha256:0c5ac5ff2afb79ac23ab82bab027a0be7b5dbcf2e54dc50efe4bf507de1f7985"}, ] [package.extras] -test = ["pytest (>=6.0.0)"] +test = ["pytest (>=6.0.0)", "setuptools (>=65)"] [[package]] name = "whylabs-client" -version = "0.5.1" +version = "0.5.4" description = "WhyLabs API client" -category = "main" optional = true python-versions = ">=3.6" files = [ - {file = "whylabs-client-0.5.1.tar.gz", hash = "sha256:f7aacfab7d176812c2eb4cdeb8c52521eed0d30bc2a0836399798197a513cf04"}, - {file = "whylabs_client-0.5.1-py3-none-any.whl", hash = "sha256:dc6958d5bb390f1057fe6f513cbce55c4e71d5f8a1461a7c93eb73814089de33"}, + {file = "whylabs-client-0.5.4.tar.gz", hash = "sha256:d0cccfaac53412362559db7b093f3d2008b68ac8a78109b617c692d59757813f"}, + {file = "whylabs_client-0.5.4-py3-none-any.whl", hash = "sha256:9854a047040fd2d7e84bd8f28a0b1c9e1822a16d8bcaee302d301c0bd1eddf64"}, ] [package.dependencies] @@ -10043,14 +9891,13 @@ urllib3 = ">=1.25.3" [[package]] name = "whylogs" -version = "1.2.3" +version = "1.2.6" description = "Profile and monitor your ML data pipeline end-to-end" -category = "main" optional = true python-versions = ">=3.7.1,<4" files = [ - {file = "whylogs-1.2.3-py3-none-any.whl", hash = "sha256:92cfe02985760c52d25b88bad69001901844ff51c76b62537bce1c31d12c271e"}, - {file = "whylogs-1.2.3.tar.gz", hash = "sha256:d0000f502b1b30c48a5ad9535488370e961e85825dafdd75421447ffff0516e7"}, + {file = "whylogs-1.2.6-py3-none-any.whl", hash = "sha256:9b71d8468396b303539b69003f93d8f5cdad03ad0112df12a697bf662c1baf34"}, + {file = "whylogs-1.2.6.tar.gz", hash = "sha256:e65ef4e6bbd2bfb7302787d71733f53345c4bc0f6ec9e34481178ff4a867a143"}, ] [package.dependencies] @@ -10079,7 +9926,6 @@ viz = ["Pillow (>=9.2.0,<10.0.0)", "ipython", "numpy", "numpy (>=1.23.2)", "pyba name = "whylogs-sketching" version = "3.4.1.dev3" description = "sketching library of whylogs" -category = "main" optional = true python-versions = "*" files = [ @@ -10118,21 +9964,19 @@ files = [ [[package]] name = "widgetsnbextension" -version = "4.0.7" +version = "4.0.8" description = "Jupyter interactive widgets for Jupyter Notebook" -category = "dev" optional = false python-versions = ">=3.7" files = [ - {file = "widgetsnbextension-4.0.7-py3-none-any.whl", hash = "sha256:be3228a73bbab189a16be2d4a3cd89ecbd4e31948bfdc64edac17dcdee3cd99c"}, - {file = "widgetsnbextension-4.0.7.tar.gz", hash = "sha256:ea67c17a7cd4ae358f8f46c3b304c40698bc0423732e3f273321ee141232c8be"}, + {file = "widgetsnbextension-4.0.8-py3-none-any.whl", hash = "sha256:2e37f0ce9da11651056280c7efe96f2db052fe8fc269508e3724f5cbd6c93018"}, + {file = "widgetsnbextension-4.0.8.tar.gz", hash = "sha256:9ec291ba87c2dfad42c3d5b6f68713fa18be1acd7476569516b2431682315c17"}, ] [[package]] name = "wikipedia" version = "1.4.0" description = "Wikipedia API for Python" -category = "main" optional = true python-versions = "*" files = [ @@ -10147,7 +9991,6 @@ requests = ">=2.0.0,<3.0.0" name = "win32-setctime" version = "1.1.0" description = "A small Python utility to set file creation time on Windows" -category = "main" optional = true python-versions = ">=3.5" files = [ @@ -10162,7 +10005,6 @@ dev = ["black (>=19.3b0)", "pytest (>=4.6.2)"] name = "wolframalpha" version = "5.0.0" description = "Wolfram|Alpha 2.0 API client" -category = "main" optional = true python-versions = ">=3.6" files = [ @@ -10183,7 +10025,6 @@ testing = ["keyring", "pmxbot", "pytest (>=3.5,!=3.7.3)", "pytest-black (>=0.3.7 name = "wonderwords" version = "2.2.0" description = "A python package for random words and sentences in the english language" -category = "main" optional = true python-versions = ">=3.6" files = [ @@ -10198,7 +10039,6 @@ cli = ["rich (==9.10.0)"] name = "wrapt" version = "1.15.0" description = "Module for decorators, wrappers and monkey patching." -category = "main" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,>=2.7" files = [ @@ -10281,14 +10121,13 @@ files = [ [[package]] name = "xata" -version = "1.0.0a7" +version = "1.0.0b0" description = "Python client for Xata.io" -category = "main" optional = true python-versions = ">=3.8,<4.0" files = [ - {file = "xata-1.0.0a7-py3-none-any.whl", hash = "sha256:1427e97bccddfd5fa8fba56ba993b2d78f1dc074e729d06ccc79c48d07bd023a"}, - {file = "xata-1.0.0a7.tar.gz", hash = "sha256:32769ddc22cc091bf133e66b91662185047fff05aa431e7c760b55cd0ddef6c3"}, + {file = "xata-1.0.0b0-py3-none-any.whl", hash = "sha256:10dab3d4382c62e04081ada0c381f80abb6f67f7601239c71b20870846a60472"}, + {file = "xata-1.0.0b0.tar.gz", hash = "sha256:241c6c52398b663da7a5107054d6ec0abca331de88bc2de7b0f0b13971b7b7f4"}, ] [package.dependencies] @@ -10301,7 +10140,6 @@ requests = ">=2.28.1,<3.0.0" name = "xmltodict" version = "0.13.0" description = "Makes working with XML feel like you are working with JSON" -category = "main" optional = true python-versions = ">=3.4" files = [ @@ -10313,7 +10151,6 @@ files = [ name = "yarl" version = "1.9.2" description = "Yet another URL library" -category = "main" optional = false python-versions = ">=3.7" files = [ @@ -10399,25 +10236,23 @@ multidict = ">=4.0" [[package]] name = "zipp" -version = "3.15.0" +version = "3.16.2" description = "Backport of pathlib-compatible object wrapper for zip files" -category = "main" optional = false -python-versions = ">=3.7" +python-versions = ">=3.8" files = [ - {file = "zipp-3.15.0-py3-none-any.whl", hash = "sha256:48904fc76a60e542af151aded95726c1a5c34ed43ab4134b597665c86d7ad556"}, - {file = "zipp-3.15.0.tar.gz", hash = "sha256:112929ad649da941c23de50f356a2b5570c954b65150642bccdd66bf194d224b"}, + {file = "zipp-3.16.2-py3-none-any.whl", hash = "sha256:679e51dd4403591b2d6838a48de3d283f3d188412a9782faadf845f298736ba0"}, + {file = "zipp-3.16.2.tar.gz", hash = "sha256:ebc15946aa78bd63458992fc81ec3b6f7b1e92d51c35e6de1c3804e73b799147"}, ] [package.extras] -docs = ["furo", "jaraco.packaging (>=9)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] -testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=1.3)", "pytest-flake8", "pytest-mypy (>=0.9.1)"] +docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"] +testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-black (>=0.3.7)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy (>=0.9.1)", "pytest-ruff"] [[package]] name = "zstandard" version = "0.21.0" description = "Zstandard bindings for Python" -category = "main" optional = true python-versions = ">=3.7" files = [ From d564ec944c1a17a1cfebb44c9111f3e076d69d2e Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 14:09:35 -0400 Subject: [PATCH 17/38] `poetry lock` the experimental package. (#9478) --- .../langchain_experimental/cpal/base.py | 2 +- .../pydantic_v1/__init__.py | 17 +- .../pydantic_v1/dataclasses.py | 17 +- .../pydantic_v1/main.py | 17 +- libs/experimental/poetry.lock | 826 ++++++++---------- .../integration_tests/chains/test_cpal.py | 2 +- 6 files changed, 397 insertions(+), 484 deletions(-) diff --git a/libs/experimental/langchain_experimental/cpal/base.py b/libs/experimental/langchain_experimental/cpal/base.py index 498bb7b06a3..bba59d5d32a 100644 --- a/libs/experimental/langchain_experimental/cpal/base.py +++ b/libs/experimental/langchain_experimental/cpal/base.py @@ -6,7 +6,6 @@ from __future__ import annotations import json from typing import Any, ClassVar, Dict, List, Optional, Type -import pydantic from langchain.base_language import BaseLanguageModel from langchain.callbacks.manager import CallbackManagerForChainRun from langchain.chains.base import Chain @@ -14,6 +13,7 @@ from langchain.chains.llm import LLMChain from langchain.output_parsers import PydanticOutputParser from langchain.prompts.prompt import PromptTemplate +from langchain_experimental import pydantic_v1 as pydantic from langchain_experimental.cpal.constants import Constant from langchain_experimental.cpal.models import ( CausalModel, diff --git a/libs/experimental/langchain_experimental/pydantic_v1/__init__.py b/libs/experimental/langchain_experimental/pydantic_v1/__init__.py index 859822531ec..826f1c50087 100644 --- a/libs/experimental/langchain_experimental/pydantic_v1/__init__.py +++ b/libs/experimental/langchain_experimental/pydantic_v1/__init__.py @@ -1,3 +1,4 @@ +import typing from importlib import metadata ## Create namespaces for pydantic v1 and v2. @@ -11,11 +12,19 @@ from importlib import metadata # unambiguously uses either v1 or v2 API. # * This change is easier to roll out and roll back. -try: - from pydantic.v1 import * # noqa: F403 -except ImportError: +# It's currently impossible to support mypy for both pydantic v1 and v2 at once: +# https://github.com/pydantic/pydantic/issues/6022 +# +# In the lint environment, pydantic is currently v1. +# When we upgrade it to pydantic v2, we'll need +# to replace this with `from pydantic.v1 import *`. +if typing.TYPE_CHECKING: from pydantic import * # noqa: F403 - +else: + try: + from pydantic.v1 import * # noqa: F403 + except ImportError: + from pydantic import * # noqa: F403 try: _PYDANTIC_MAJOR_VERSION: int = int(metadata.version("pydantic").split(".")[0]) diff --git a/libs/experimental/langchain_experimental/pydantic_v1/dataclasses.py b/libs/experimental/langchain_experimental/pydantic_v1/dataclasses.py index bb7253c29d7..25a7810a046 100644 --- a/libs/experimental/langchain_experimental/pydantic_v1/dataclasses.py +++ b/libs/experimental/langchain_experimental/pydantic_v1/dataclasses.py @@ -1,4 +1,15 @@ -try: - from pydantic.v1.dataclasses import * # noqa: F403 -except ImportError: +import typing + +# It's currently impossible to support mypy for both pydantic v1 and v2 at once: +# https://github.com/pydantic/pydantic/issues/6022 +# +# In the lint environment, pydantic is currently v1. +# When we upgrade it to pydantic v2, we'll need to +# replace this with `from pydantic.v1.dataclasses import *`. +if typing.TYPE_CHECKING: from pydantic.dataclasses import * # noqa: F403 +else: + try: + from pydantic.v1.dataclasses import * # noqa: F403 + except ImportError: + from pydantic.dataclasses import * # noqa: F403 diff --git a/libs/experimental/langchain_experimental/pydantic_v1/main.py b/libs/experimental/langchain_experimental/pydantic_v1/main.py index 4b8f1670e13..2fa4c995872 100644 --- a/libs/experimental/langchain_experimental/pydantic_v1/main.py +++ b/libs/experimental/langchain_experimental/pydantic_v1/main.py @@ -1,4 +1,15 @@ -try: - from pydantic.v1.main import * # noqa: F403 -except ImportError: +import typing + +# It's currently impossible to support mypy for both pydantic v1 and v2 at once: +# https://github.com/pydantic/pydantic/issues/6022 +# +# In the lint environment, pydantic is currently v1. +# When we upgrade it to pydantic v2, we'll need +# to replace this with `from pydantic.v1.main import *`. +if typing.TYPE_CHECKING: from pydantic.main import * # noqa: F403 +else: + try: + from pydantic.v1.main import * # noqa: F403 + except ImportError: + from pydantic.main import * # noqa: F403 diff --git a/libs/experimental/poetry.lock b/libs/experimental/poetry.lock index 91191a45970..71b7d1b942d 100644 --- a/libs/experimental/poetry.lock +++ b/libs/experimental/poetry.lock @@ -1,10 +1,9 @@ -# This file is automatically @generated by Poetry and should not be changed by hand. +# This file is automatically @generated by Poetry 1.5.1 and should not be changed by hand. [[package]] name = "aiohttp" version = "3.8.5" description = "Async http client/server framework (asyncio)" -category = "main" optional = false python-versions = ">=3.6" files = [ @@ -113,7 +112,6 @@ speedups = ["Brotli", "aiodns", "cchardet"] name = "aiosignal" version = "1.3.1" description = "aiosignal: a list of registered asynchronous callbacks" -category = "main" optional = false python-versions = ">=3.7" files = [ @@ -128,7 +126,6 @@ frozenlist = ">=1.1.0" name = "anyio" version = "3.7.1" description = "High level compatibility layer for multiple asynchronous event loop implementations" -category = "dev" optional = false python-versions = ">=3.7" files = [ @@ -150,7 +147,6 @@ trio = ["trio (<0.22)"] name = "appnope" version = "0.1.3" description = "Disable App Nap on macOS >= 10.9" -category = "dev" optional = false python-versions = "*" files = [ @@ -160,29 +156,28 @@ files = [ [[package]] name = "argon2-cffi" -version = "21.3.0" -description = "The secure Argon2 password hashing algorithm." -category = "dev" +version = "23.1.0" +description = "Argon2 for Python" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" files = [ - {file = "argon2-cffi-21.3.0.tar.gz", hash = "sha256:d384164d944190a7dd7ef22c6aa3ff197da12962bd04b17f64d4e93d934dba5b"}, - {file = "argon2_cffi-21.3.0-py3-none-any.whl", hash = "sha256:8c976986f2c5c0e5000919e6de187906cfd81fb1c72bf9d88c01177e77da7f80"}, + {file = "argon2_cffi-23.1.0-py3-none-any.whl", hash = "sha256:c670642b78ba29641818ab2e68bd4e6a78ba53b7eff7b4c3815ae16abf91c7ea"}, + {file = "argon2_cffi-23.1.0.tar.gz", hash = "sha256:879c3e79a2729ce768ebb7d36d4609e3a78a4ca2ec3a9f12286ca057e3d0db08"}, ] [package.dependencies] argon2-cffi-bindings = "*" [package.extras] -dev = ["cogapp", "coverage[toml] (>=5.0.2)", "furo", "hypothesis", "pre-commit", "pytest", "sphinx", "sphinx-notfound-page", "tomli"] -docs = ["furo", "sphinx", "sphinx-notfound-page"] -tests = ["coverage[toml] (>=5.0.2)", "hypothesis", "pytest"] +dev = ["argon2-cffi[tests,typing]", "tox (>4)"] +docs = ["furo", "myst-parser", "sphinx", "sphinx-copybutton", "sphinx-notfound-page"] +tests = ["hypothesis", "pytest"] +typing = ["mypy"] [[package]] name = "argon2-cffi-bindings" version = "21.2.0" description = "Low-level CFFI bindings for Argon2" -category = "dev" optional = false python-versions = ">=3.6" files = [ @@ -220,7 +215,6 @@ tests = ["pytest"] name = "arrow" version = "1.2.3" description = "Better dates & times for Python" -category = "dev" optional = false python-versions = ">=3.6" files = [ @@ -235,7 +229,6 @@ python-dateutil = ">=2.7.0" name = "asttokens" version = "2.2.1" description = "Annotate AST trees with source code positions" -category = "dev" optional = false python-versions = "*" files = [ @@ -251,14 +244,13 @@ test = ["astroid", "pytest"] [[package]] name = "async-lru" -version = "2.0.3" +version = "2.0.4" description = "Simple LRU cache for asyncio" -category = "dev" optional = false python-versions = ">=3.8" files = [ - {file = "async-lru-2.0.3.tar.gz", hash = "sha256:b714c9d1415fca4e264da72a9e2abc66880ce7430e03a973341f88ea4c0d4869"}, - {file = "async_lru-2.0.3-py3-none-any.whl", hash = "sha256:00c0a8899c20b9c88663a47732689ff98189c9fa08ad9f734d7722f934d250b1"}, + {file = "async-lru-2.0.4.tar.gz", hash = "sha256:b8a59a5df60805ff63220b2a0c5b5393da5521b113cd5465a44eb037d81a5627"}, + {file = "async_lru-2.0.4-py3-none-any.whl", hash = "sha256:ff02944ce3c288c5be660c42dbcca0742b32c3b279d6dceda655190240b99224"}, ] [package.dependencies] @@ -266,21 +258,19 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} [[package]] name = "async-timeout" -version = "4.0.2" +version = "4.0.3" description = "Timeout context manager for asyncio programs" -category = "main" optional = false -python-versions = ">=3.6" +python-versions = ">=3.7" files = [ - {file = "async-timeout-4.0.2.tar.gz", hash = "sha256:2163e1640ddb52b7a8c80d0a67a08587e5d245cc9c553a74a847056bc2976b15"}, - {file = "async_timeout-4.0.2-py3-none-any.whl", hash = "sha256:8ca1e4fcf50d07413d66d1a5e416e42cfdf5851c981d679a09851a6853383b3c"}, + {file = "async-timeout-4.0.3.tar.gz", hash = "sha256:4640d96be84d82d02ed59ea2b7105a0f7b33abe8703703cd0ab0bf87c427522f"}, + {file = "async_timeout-4.0.3-py3-none-any.whl", hash = "sha256:7405140ff1230c310e51dc27b3145b9092d659ce68ff733fb0cefe3ee42be028"}, ] [[package]] name = "attrs" version = "23.1.0" description = "Classes Without Boilerplate" -category = "main" optional = false python-versions = ">=3.7" files = [ @@ -299,7 +289,6 @@ tests-no-zope = ["cloudpickle", "hypothesis", "mypy (>=1.1.1)", "pympler", "pyte name = "babel" version = "2.12.1" description = "Internationalization utilities" -category = "dev" optional = false python-versions = ">=3.7" files = [ @@ -314,7 +303,6 @@ pytz = {version = ">=2015.7", markers = "python_version < \"3.9\""} name = "backcall" version = "0.2.0" description = "Specifications for callback functions passed in to an API" -category = "dev" optional = false python-versions = "*" files = [ @@ -326,7 +314,6 @@ files = [ name = "beautifulsoup4" version = "4.12.2" description = "Screen-scraping library" -category = "dev" optional = false python-versions = ">=3.6.0" files = [ @@ -345,7 +332,6 @@ lxml = ["lxml"] name = "black" version = "23.7.0" description = "The uncompromising code formatter." -category = "dev" optional = false python-versions = ">=3.8" files = [ @@ -392,7 +378,6 @@ uvloop = ["uvloop (>=0.15.2)"] name = "bleach" version = "6.0.0" description = "An easy safelist-based HTML-sanitizing tool." -category = "dev" optional = false python-versions = ">=3.7" files = [ @@ -409,21 +394,19 @@ css = ["tinycss2 (>=1.1.0,<1.2)"] [[package]] name = "certifi" -version = "2023.5.7" +version = "2023.7.22" description = "Python package for providing Mozilla's CA Bundle." -category = "main" optional = false python-versions = ">=3.6" files = [ - 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Open, modern and actively maintained alternative to Chardet." -category = "main" optional = false python-versions = ">=3.7.0" files = [ @@ -583,14 +565,13 @@ files = [ [[package]] name = "click" -version = "8.1.6" +version = "8.1.7" description = "Composable command line interface toolkit" -category = "dev" optional = false python-versions = ">=3.7" files = [ - {file = "click-8.1.6-py3-none-any.whl", hash = "sha256:fa244bb30b3b5ee2cae3da8f55c9e5e0c0e86093306301fb418eb9dc40fbded5"}, - {file = "click-8.1.6.tar.gz", hash = "sha256:48ee849951919527a045bfe3bf7baa8a959c423134e1a5b98c05c20ba75a1cbd"}, + {file = "click-8.1.7-py3-none-any.whl", hash = "sha256:ae74fb96c20a0277a1d615f1e4d73c8414f5a98db8b799a7931d1582f3390c28"}, + {file = "click-8.1.7.tar.gz", hash = "sha256:ca9853ad459e787e2192211578cc907e7594e294c7ccc834310722b41b9ca6de"}, ] [package.dependencies] @@ -600,7 +581,6 @@ colorama = {version = "*", markers = "platform_system == \"Windows\""} name = "colorama" version = "0.4.6" description = "Cross-platform colored terminal text." -category = "dev" optional = false python-versions = "!=3.0.*,!=3.1.*,!=3.2.*,!=3.3.*,!=3.4.*,!=3.5.*,!=3.6.*,>=2.7" files = [ @@ -610,18 +590,17 @@ files = [ [[package]] name = "comm" -version = "0.1.3" +version = "0.1.4" description = "Jupyter Python Comm implementation, for usage in ipykernel, xeus-python etc." -category = "dev" optional = false python-versions = ">=3.6" files = [ - 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"3.16.2" description = "Backport of pathlib-compatible object wrapper for zip files" -category = "dev" optional = false python-versions = ">=3.8" files = [ diff --git a/libs/experimental/tests/integration_tests/chains/test_cpal.py b/libs/experimental/tests/integration_tests/chains/test_cpal.py index c9f703de81a..f3775861732 100644 --- a/libs/experimental/tests/integration_tests/chains/test_cpal.py +++ b/libs/experimental/tests/integration_tests/chains/test_cpal.py @@ -5,12 +5,12 @@ import unittest from typing import Type from unittest import mock -import pydantic import pytest from langchain import OpenAI from langchain.output_parsers import PydanticOutputParser from langchain.prompts.prompt import PromptTemplate +from langchain_experimental import pydantic_v1 as pydantic from langchain_experimental.cpal.base import ( CausalChain, CPALChain, From 35812d00964cc1d96fde501b2e55c4c93387ecf9 Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 14:21:26 -0400 Subject: [PATCH 18/38] Set up concurrency groups and workflow cancelation in CI. (#9564) If another push to the same PR or branch happens while its CI is still running, cancel the earlier run in favor of the next run. There's no point in testing an outdated version of the code. GitHub only allows a limited number of job runners to be active at the same time, so it's better to cancel pointless jobs early so that more useful jobs can run sooner. --- .github/workflows/langchain_ci.yml | 10 ++++++++++ .github/workflows/langchain_experimental_ci.yml | 10 ++++++++++ 2 files changed, 20 insertions(+) diff --git a/.github/workflows/langchain_ci.yml b/.github/workflows/langchain_ci.yml index b91e039ea6f..932cce90a3e 100644 --- a/.github/workflows/langchain_ci.yml +++ b/.github/workflows/langchain_ci.yml @@ -13,6 +13,16 @@ on: - 'libs/langchain/**' workflow_dispatch: # Allows to trigger the workflow manually in GitHub UI +# If another push to the same PR or branch happens while this workflow is still running, +# cancel the earlier run in favor of the next run. +# +# There's no point in testing an outdated version of the code. GitHub only allows +# a limited number of job runners to be active at the same time, so it's better to cancel +# pointless jobs early so that more useful jobs can run sooner. +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + env: POETRY_VERSION: "1.5.1" WORKDIR: "libs/langchain" diff --git a/.github/workflows/langchain_experimental_ci.yml b/.github/workflows/langchain_experimental_ci.yml index cee8cdb7d31..9edaf6aca1a 100644 --- a/.github/workflows/langchain_experimental_ci.yml +++ b/.github/workflows/langchain_experimental_ci.yml @@ -13,6 +13,16 @@ on: - 'libs/experimental/**' workflow_dispatch: # Allows to trigger the workflow manually in GitHub UI +# If another push to the same PR or branch happens while this workflow is still running, +# cancel the earlier run in favor of the next run. +# +# There's no point in testing an outdated version of the code. GitHub only allows +# a limited number of job runners to be active at the same time, so it's better to cancel +# pointless jobs early so that more useful jobs can run sooner. +concurrency: + group: ${{ github.workflow }}-${{ github.ref }} + cancel-in-progress: true + env: POETRY_VERSION: "1.5.1" WORKDIR: "libs/experimental" From f1e602996a397ce3f7751feea86a0e8dd1e96aee Mon Sep 17 00:00:00 2001 From: Myeongseop Kim <81076998+amicus-veritatis@users.noreply.github.com> Date: Wed, 23 Aug 2023 03:54:07 +0900 Subject: [PATCH 19/38] import tqdm.auto instead of tqdm tqdm for OpenAIEmbeddings (#9584) - Description: current code does not work very well on jupyter notebook, so I changed the code so that it imports `tqdm.auto` instead. - Issue: #9582 - Dependencies: N/A - Tag maintainer: @hwchase17, @baskaryan - Twitter handle: N/A Co-authored-by: Eugene Yurtsev --- libs/langchain/langchain/embeddings/openai.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/libs/langchain/langchain/embeddings/openai.py b/libs/langchain/langchain/embeddings/openai.py index 9c78e2499e8..976c879f95e 100644 --- a/libs/langchain/langchain/embeddings/openai.py +++ b/libs/langchain/langchain/embeddings/openai.py @@ -352,9 +352,9 @@ class OpenAIEmbeddings(BaseModel, Embeddings): if self.show_progress_bar: try: - import tqdm + from tqdm.auto import tqdm - _iter = tqdm.tqdm(range(0, len(tokens), _chunk_size)) + _iter = tqdm(range(0, len(tokens), _chunk_size)) except ImportError: _iter = range(0, len(tokens), _chunk_size) else: From f3ba9ce7f473fe1ecff72af7e60f4d66b34bb2dd Mon Sep 17 00:00:00 2001 From: seamusp Date: Tue, 22 Aug 2023 11:57:58 -0700 Subject: [PATCH 20/38] Remove -E all from installation instructions (#9573) Update installation instructions to only install test dependencies rather than all dependencies. --------- Co-authored-by: Eugene Yurtsev --- .github/CONTRIBUTING.md | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/.github/CONTRIBUTING.md b/.github/CONTRIBUTING.md index a3e2e5912b8..e4d1e54e33a 100644 --- a/.github/CONTRIBUTING.md +++ b/.github/CONTRIBUTING.md @@ -80,10 +80,10 @@ For example, to contribute to `langchain` run `cd libs/langchain` before getting To install requirements: ```bash -poetry install -E all +poetry install --with test ``` -This will install all requirements for running the package, examples, linting, formatting, tests, and coverage. Note the `-E all` flag will install all optional dependencies necessary for integration testing. +This will install all requirements for running the package, examples, linting, formatting, tests, and coverage. ❗Note: If during installation you receive a `WheelFileValidationError` for `debugpy`, please make sure you are running Poetry v1.5.1. This bug was present in older versions of Poetry (e.g. 1.4.1) and has been resolved in newer releases. If you are still seeing this bug on v1.5.1, you may also try disabling "modern installation" (`poetry config installer.modern-installation false`) and re-installing requirements. See [this `debugpy` issue](https://github.com/microsoft/debugpy/issues/1246) for more details. From 81163e3c0c67a3bfc6124ba843383eb258b24764 Mon Sep 17 00:00:00 2001 From: Bagatur <22008038+baskaryan@users.noreply.github.com> Date: Tue, 22 Aug 2023 11:58:16 -0700 Subject: [PATCH 21/38] parent retriever nit (#9570) if ids are nullable seems like they should have default val None. mirrors VectorStore interface as well. cc @mcantillon21 @jacoblee93 --- .../langchain/langchain/retrievers/parent_document_retriever.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/libs/langchain/langchain/retrievers/parent_document_retriever.py b/libs/langchain/langchain/retrievers/parent_document_retriever.py index f56b8929032..6757ba3ddb3 100644 --- a/libs/langchain/langchain/retrievers/parent_document_retriever.py +++ b/libs/langchain/langchain/retrievers/parent_document_retriever.py @@ -97,7 +97,7 @@ class ParentDocumentRetriever(BaseRetriever): def add_documents( self, documents: List[Document], - ids: Optional[List[str]], + ids: Optional[List[str]] = None, add_to_docstore: bool = True, ) -> None: """Adds documents to the docstore and vectorstores. From 83986ea98a9a43b4d0508e3beeda9c3b5b77b832 Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 15:59:22 -0400 Subject: [PATCH 22/38] Cache poetry install + unify Python/Poetry setup for lint and test jobs. (#9625) With this PR: - All lint and test jobs use the exact same Python + Poetry installation approach, instead of lints doing it one way and tests doing it another way. - The Poetry installation itself is cached, which saves ~15s per run. - We no longer pass shell commands as workflow arguments to a workflow that just runs them in a shell. This makes our actions more resilient to shell code injection. If y'all like this approach, I can modify the scheduled tests workflow and the release workflow to use this too. --- .github/actions/poetry_setup/action.yml | 46 ++++++------------- .github/workflows/_lint.yml | 39 ++++++++-------- .github/workflows/_pydantic_compatibility.yml | 11 +++-- .github/workflows/_test.yml | 11 +++-- .github/workflows/langchain_ci.yml | 15 ++++-- .../workflows/langchain_experimental_ci.yml | 19 +++++--- 6 files changed, 72 insertions(+), 69 deletions(-) diff --git a/.github/actions/poetry_setup/action.yml b/.github/actions/poetry_setup/action.yml index 39c76bec4c1..851ddda11f4 100644 --- a/.github/actions/poetry_setup/action.yml +++ b/.github/actions/poetry_setup/action.yml @@ -15,19 +15,13 @@ inputs: description: Poetry version required: true - install-command: - description: Command run for installing dependencies - required: false - default: poetry install - cache-key: description: Cache key to use for manual handling of caching required: true working-directory: - description: Directory to run install-command in - required: false - default: "" + description: Directory whose poetry.lock file should be cached + required: true runs: using: composite @@ -38,47 +32,35 @@ runs: python-version: ${{ inputs.python-version }} - uses: actions/cache@v3 - id: cache-pip - name: Cache Pip ${{ inputs.python-version }} + id: cache-bin-poetry + name: Cache Poetry binary - Python ${{ inputs.python-version }} env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" + SEGMENT_DOWNLOAD_TIMEOUT_MIN: "1" with: path: | - ~/.cache/pip - key: pip-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }} + /opt/pipx/venvs/poetry + /opt/pipx_bin/poetry + # This step caches the poetry installation, so make sure it's keyed on the poetry version as well. + key: bin-poetry-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }}-${{ inputs.poetry-version }} - name: Install poetry + if: steps.cache-bin-poetry.outputs.cache-hit != 'true' shell: bash env: POETRY_VERSION: ${{ inputs.poetry-version }} PYTHON_VERSION: ${{ inputs.python-version }} run: pipx install "poetry==$POETRY_VERSION" --python "python$PYTHON_VERSION" --verbose - - name: Check Poetry File - shell: bash - working-directory: ${{ inputs.working-directory }} - run: | - poetry check - - - name: Check lock file - shell: bash - working-directory: ${{ inputs.working-directory }} - run: | - poetry lock --check - - - uses: actions/cache@v3 - id: cache-poetry + - name: Restore pip and poetry cached dependencies + uses: actions/cache@v3 env: SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" WORKDIR: ${{ inputs.working-directory == '' && '.' || inputs.working-directory }} with: path: | + ~/.cache/pip ~/.cache/pypoetry/virtualenvs ~/.cache/pypoetry/cache ~/.cache/pypoetry/artifacts ${{ env.WORKDIR }}/.venv - key: poetry-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }}-poetry-${{ inputs.poetry-version }}-${{ inputs.cache-key }}-${{ hashFiles(format('{0}/poetry.lock', env.WORKDIR)) }} - - - run: ${{ inputs.install-command }} - working-directory: ${{ inputs.working-directory }} - shell: bash + key: py-deps-${{ runner.os }}-${{ runner.arch }}-py-${{ inputs.python-version }}-poetry-${{ inputs.poetry-version }}-${{ inputs.cache-key }}-${{ hashFiles(format('{0}/**/poetry.lock', env.WORKDIR)) }} diff --git a/.github/workflows/_lint.yml b/.github/workflows/_lint.yml index 5b1c35a9d8c..1a01b225a00 100644 --- a/.github/workflows/_lint.yml +++ b/.github/workflows/_lint.yml @@ -80,31 +80,32 @@ jobs: find "$WORKDIR" -name '*.py' -type f -not -newermt "$OLDEST_COMMIT_TIME" -exec touch -c -m -t '200001010000' '{}' '+' echo "oldest-commit=$OLDEST_COMMIT" >> "$GITHUB_OUTPUT" - - uses: actions/cache@v3 - id: cache-pip - name: Cache langchain editable pip install - ${{ matrix.python-version }} - env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" - with: - path: | - ~/.cache/pip - key: pip-editable-langchain-deps-${{ runner.os }}-${{ runner.arch }}-py-${{ matrix.python-version }} - - name: Install poetry - run: | - pipx install "poetry==$POETRY_VERSION" - - name: Set up Python ${{ matrix.python-version }} - uses: actions/setup-python@v4 - env: - SEGMENT_DOWNLOAD_TIMEOUT_MIN: "4" + + - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }} + uses: "./.github/actions/poetry_setup" with: python-version: ${{ matrix.python-version }} - cache: poetry - cache-dependency-path: | - ${{ env.WORKDIR }}/**/poetry.lock + poetry-version: ${{ env.POETRY_VERSION }} + working-directory: ${{ inputs.working-directory }} + cache-key: lint + + - name: Check Poetry File + shell: bash + working-directory: ${{ inputs.working-directory }} + run: | + poetry check + + - name: Check lock file + shell: bash + working-directory: ${{ inputs.working-directory }} + run: | + poetry lock --check + - name: Install dependencies working-directory: ${{ inputs.working-directory }} run: | poetry install + - name: Install langchain editable working-directory: ${{ inputs.working-directory }} if: ${{ inputs.working-directory != 'libs/langchain' }} diff --git a/.github/workflows/_pydantic_compatibility.yml b/.github/workflows/_pydantic_compatibility.yml index 5a54c2f53c7..7d8fe26d92f 100644 --- a/.github/workflows/_pydantic_compatibility.yml +++ b/.github/workflows/_pydantic_compatibility.yml @@ -27,14 +27,19 @@ jobs: name: Pydantic v1/v2 compatibility - Python ${{ matrix.python-version }} steps: - uses: actions/checkout@v3 - - name: Set up Python ${{ matrix.python-version }} + + - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }} uses: "./.github/actions/poetry_setup" with: python-version: ${{ matrix.python-version }} - working-directory: ${{ inputs.working-directory }} poetry-version: ${{ env.POETRY_VERSION }} + working-directory: ${{ inputs.working-directory }} cache-key: pydantic-cross-compat - install-command: poetry install + + - name: Install dependencies + shell: bash + run: poetry install + - name: Install the opposite major version of pydantic # If normal tests use pydantic v1, here we'll use v2, and vice versa. shell: bash diff --git a/.github/workflows/_test.yml b/.github/workflows/_test.yml index 179b6303d76..76d86a2862e 100644 --- a/.github/workflows/_test.yml +++ b/.github/workflows/_test.yml @@ -27,14 +27,19 @@ jobs: name: Python ${{ matrix.python-version }} steps: - uses: actions/checkout@v3 - - name: Set up Python ${{ matrix.python-version }} + + - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }} uses: "./.github/actions/poetry_setup" with: python-version: ${{ matrix.python-version }} - working-directory: ${{ inputs.working-directory }} poetry-version: ${{ env.POETRY_VERSION }} + working-directory: ${{ inputs.working-directory }} cache-key: core - install-command: poetry install + + - name: Install dependencies + shell: bash + run: poetry install + - name: Run core tests shell: bash run: make test diff --git a/.github/workflows/langchain_ci.yml b/.github/workflows/langchain_ci.yml index 932cce90a3e..8f1fc5d8744 100644 --- a/.github/workflows/langchain_ci.yml +++ b/.github/workflows/langchain_ci.yml @@ -64,15 +64,20 @@ jobs: name: Python ${{ matrix.python-version }} extended tests steps: - uses: actions/checkout@v3 - - name: Set up Python ${{ matrix.python-version }} + + - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }} uses: "./.github/actions/poetry_setup" with: python-version: ${{ matrix.python-version }} - working-directory: ${{ env.WORKDIR }} poetry-version: ${{ env.POETRY_VERSION }} + working-directory: libs/langchain cache-key: extended - install-command: | - echo "Running extended tests, installing dependencies with poetry..." - poetry install -E extended_testing + + - name: Install dependencies + shell: bash + run: | + echo "Running extended tests, installing dependencies with poetry..." + poetry install -E extended_testing + - name: Run extended tests run: make extended_tests diff --git a/.github/workflows/langchain_experimental_ci.yml b/.github/workflows/langchain_experimental_ci.yml index 9edaf6aca1a..c62ff18b354 100644 --- a/.github/workflows/langchain_experimental_ci.yml +++ b/.github/workflows/langchain_experimental_ci.yml @@ -61,18 +61,23 @@ jobs: name: test with unpublished langchain - Python ${{ matrix.python-version }} steps: - uses: actions/checkout@v3 - - name: Set up Python ${{ matrix.python-version }} + + - name: Set up Python ${{ matrix.python-version }} + Poetry ${{ env.POETRY_VERSION }} uses: "./.github/actions/poetry_setup" with: python-version: ${{ matrix.python-version }} - working-directory: ${{ env.WORKDIR }} poetry-version: ${{ env.POETRY_VERSION }} + working-directory: ${{ env.WORKDIR }} cache-key: unpublished-langchain - install-command: | - echo "Running tests with unpublished langchain, installing dependencies with poetry..." - poetry install - echo "Editably installing langchain outside of poetry, to avoid messing up lockfile..." - poetry run pip install -e ../langchain + - name: Install dependencies + shell: bash + run: | + echo "Running tests with unpublished langchain, installing dependencies with poetry..." + poetry install + + echo "Editably installing langchain outside of poetry, to avoid messing up lockfile..." + poetry run pip install -e ../langchain + - name: Run tests run: make test From c06f34fa352eed33cee4d25f42a7074f52791996 Mon Sep 17 00:00:00 2001 From: Predrag Gruevski <2348618+obi1kenobi@users.noreply.github.com> Date: Tue, 22 Aug 2023 16:07:53 -0400 Subject: [PATCH 23/38] Use new Python setup approach for scheduled tests. (#9626) Using the same new unified Python setup as the regular tests and the lint job, as set up in #9625. --- .github/workflows/scheduled_test.yml | 15 +++++++++++---- 1 file changed, 11 insertions(+), 4 deletions(-) diff --git a/.github/workflows/scheduled_test.yml b/.github/workflows/scheduled_test.yml index 39b553d5c28..b71eee05929 100644 --- a/.github/workflows/scheduled_test.yml +++ b/.github/workflows/scheduled_test.yml @@ -25,18 +25,25 @@ jobs: name: Python ${{ matrix.python-version }} steps: - uses: actions/checkout@v3 + - name: Set up Python ${{ matrix.python-version }} uses: "./.github/actions/poetry_setup" with: python-version: ${{ matrix.python-version }} poetry-version: ${{ env.POETRY_VERSION }} working-directory: libs/langchain - install-command: | - echo "Running scheduled tests, installing dependencies with poetry..." - poetry install --with=test_integration + cache-key: scheduled + + - name: Install dependencies + working-directory: libs/langchain + shell: bash + run: | + echo "Running scheduled tests, installing dependencies with poetry..." + poetry install --with=test_integration + - name: Run tests + shell: bash env: OPENAI_API_KEY: ${{ secrets.OPENAI_API_KEY }} run: | make scheduled_tests - shell: bash From f29312eb844621837054446cfac37bd007984d5c Mon Sep 17 00:00:00 2001 From: Adilkhan Sarsen <54854336+adolkhan@users.noreply.github.com> Date: Wed, 23 Aug 2023 04:12:24 +0600 Subject: [PATCH 24/38] Fixing deeplake.mdx file as it uses outdates links (#9602) deeplake.mdx was using old links and was not working properly, in the PR we fix the issue. --- docs/api_reference/guide_imports.json | 4 ++-- docs/docs_skeleton/vercel.json | 2 +- .../{deeplake.mdx => activeloop_deeplake.mdx} | 12 +++++++++--- 3 files changed, 12 insertions(+), 6 deletions(-) rename docs/extras/integrations/providers/{deeplake.mdx => activeloop_deeplake.mdx} (73%) diff --git a/docs/api_reference/guide_imports.json b/docs/api_reference/guide_imports.json index 9c608a7328f..832c03f996a 100644 --- a/docs/api_reference/guide_imports.json +++ b/docs/api_reference/guide_imports.json @@ -2071,8 +2071,8 @@ "PromptLayer": "https://python.langchain.com/docs/integrations/providers/promptlayer", "PromptLayer OpenAI": "https://python.langchain.com/docs/integrations/llms/promptlayer_openai" }, - "DeepLake": { - "Deep Lake": "https://python.langchain.com/docs/integrations/providers/deeplake", + "Activeloop DeepLake": { + "Deep Lake": "https://python.langchain.com/docs/integrations/providers/activeloop_deeplake", "Activeloop's Deep Lake": "https://python.langchain.com/docs/integrations/vectorstores/activeloop_deeplake", "Analysis of Twitter the-algorithm source code with LangChain, GPT4 and Activeloop's Deep Lake": "https://python.langchain.com/docs/use_cases/question_answering/how_to/code/twitter-the-algorithm-analysis-deeplake", "Use LangChain, GPT and Activeloop's Deep Lake to work with code base": "https://python.langchain.com/docs/use_cases/question_answering/how_to/code/code-analysis-deeplake", diff --git a/docs/docs_skeleton/vercel.json b/docs/docs_skeleton/vercel.json index 6472c045301..fe9f5ace3fb 100644 --- a/docs/docs_skeleton/vercel.json +++ b/docs/docs_skeleton/vercel.json @@ -166,7 +166,7 @@ }, { "source": "/docs/integrations/deeplake", - "destination": "/docs/integrations/providers/deeplake" + "destination": "/docs/integrations/providers/activeloop_deeplake" }, { "source": "/docs/integrations/diffbot", diff --git a/docs/extras/integrations/providers/deeplake.mdx b/docs/extras/integrations/providers/activeloop_deeplake.mdx similarity index 73% rename from docs/extras/integrations/providers/deeplake.mdx rename to docs/extras/integrations/providers/activeloop_deeplake.mdx index 88bd7688810..a60d63f2565 100644 --- a/docs/extras/integrations/providers/deeplake.mdx +++ b/docs/extras/integrations/providers/activeloop_deeplake.mdx @@ -1,4 +1,4 @@ -# Deep Lake +# Activeloop Deep Lake This page covers how to use the Deep Lake ecosystem within LangChain. ## Why Deep Lake? @@ -6,9 +6,15 @@ This page covers how to use the Deep Lake ecosystem within LangChain. - Not only stores embeddings, but also the original data with automatic version control. - Truly serverless. Doesn't require another service and can be used with major cloud providers (AWS S3, GCS, etc.) + +Activeloop Deep Lake supports SelfQuery Retrieval: +[Activeloop Deep Lake Self Query Retrieval](/docs/extras/modules/data_connection/retrievers/self_query/activeloop_deeplake_self_query) + + ## More Resources 1. [Ultimate Guide to LangChain & Deep Lake: Build ChatGPT to Answer Questions on Your Financial Data](https://www.activeloop.ai/resources/ultimate-guide-to-lang-chain-deep-lake-build-chat-gpt-to-answer-questions-on-your-financial-data/) -2. [Twitter the-algorithm codebase analysis with Deep Lake](../use_cases/code/twitter-the-algorithm-analysis-deeplake.html) +2. [Twitter the-algorithm codebase analysis with Deep Lake](/docs/use_cases/question_answering/how_to/code/twitter-the-algorithm-analysis-deeplake) +4. [Code Understanding](/docs/modules/data_connection/retrievers/self_query/activeloop_deeplake_self_query) 3. Here is [whitepaper](https://www.deeplake.ai/whitepaper) and [academic paper](https://arxiv.org/pdf/2209.10785.pdf) for Deep Lake 4. Here is a set of additional resources available for review: [Deep Lake](https://github.com/activeloopai/deeplake), [Get started](https://docs.activeloop.ai/getting-started) and [Tutorials](https://docs.activeloop.ai/hub-tutorials) @@ -27,4 +33,4 @@ from langchain.vectorstores import DeepLake ``` -For a more detailed walkthrough of the Deep Lake wrapper, see [this notebook](/docs/integrations/vectorstores/deeplake.html) +For a more detailed walkthrough of the Deep Lake wrapper, see [this notebook](/docs/integrations/vectorstores/activeloop_deeplake) From ca8232a3c1331766d8f7874c7bb22ca17fde663f Mon Sep 17 00:00:00 2001 From: Kim Minjong Date: Wed, 23 Aug 2023 05:18:24 +0700 Subject: [PATCH 25/38] Update BaseChatModel.astream to respect generation_info (#9430) Currently, generation_info is not respected by only reflecting messages in chunks. Change it to add generations so that generation chunks are merged properly. --------- Co-authored-by: Harrison Chase --- libs/langchain/langchain/chat_models/base.py | 24 +++++++-------- .../chat_models/test_openai.py | 30 +++++++++++++++++++ 2 files changed, 42 insertions(+), 12 deletions(-) diff --git a/libs/langchain/langchain/chat_models/base.py b/libs/langchain/langchain/chat_models/base.py index 09199e30dc9..2d0db37c0ac 100644 --- a/libs/langchain/langchain/chat_models/base.py +++ b/libs/langchain/langchain/chat_models/base.py @@ -176,22 +176,22 @@ class BaseChatModel(BaseLanguageModel[BaseMessageChunk], ABC): dumpd(self), [messages], invocation_params=params, options=options ) try: - message: Optional[BaseMessageChunk] = None + generation: Optional[ChatGenerationChunk] = None for chunk in self._stream( messages, stop=stop, run_manager=run_manager, **kwargs ): yield chunk.message - if message is None: - message = chunk.message + if generation is None: + generation = chunk else: - message += chunk.message - assert message is not None + generation += chunk + assert generation is not None except (KeyboardInterrupt, Exception) as e: run_manager.on_llm_error(e) raise e else: run_manager.on_llm_end( - LLMResult(generations=[[ChatGeneration(message=message)]]), + LLMResult(generations=[[generation]]), ) async def astream( @@ -223,22 +223,22 @@ class BaseChatModel(BaseLanguageModel[BaseMessageChunk], ABC): dumpd(self), [messages], invocation_params=params, options=options ) try: - message: Optional[BaseMessageChunk] = None + generation: Optional[ChatGenerationChunk] = None async for chunk in self._astream( messages, stop=stop, run_manager=run_manager, **kwargs ): yield chunk.message - if message is None: - message = chunk.message + if generation is None: + generation = chunk else: - message += chunk.message - assert message is not None + generation += chunk + assert generation is not None except (KeyboardInterrupt, Exception) as e: await run_manager.on_llm_error(e) raise e else: await run_manager.on_llm_end( - LLMResult(generations=[[ChatGeneration(message=message)]]), + LLMResult(generations=[[generation]]), ) # --- Custom methods --- diff --git a/libs/langchain/tests/integration_tests/chat_models/test_openai.py b/libs/langchain/tests/integration_tests/chat_models/test_openai.py index 19adbf1cd41..7637014a4c1 100644 --- a/libs/langchain/tests/integration_tests/chat_models/test_openai.py +++ b/libs/langchain/tests/integration_tests/chat_models/test_openai.py @@ -1,6 +1,8 @@ """Test ChatOpenAI wrapper.""" +from typing import Any + import pytest from langchain.callbacks.manager import CallbackManager @@ -89,6 +91,34 @@ def test_chat_openai_streaming() -> None: assert isinstance(response, BaseMessage) +@pytest.mark.scheduled +def test_chat_openai_streaming_generation_info() -> None: + """Test that generation info is preserved when streaming.""" + + class _FakeCallback(FakeCallbackHandler): + saved_things: dict = {} + + def on_llm_end( + self, + *args: Any, + **kwargs: Any, + ) -> Any: + # Save the generation + self.saved_things["generation"] = args[0] + + callback = _FakeCallback() + callback_manager = CallbackManager([callback]) + chat = ChatOpenAI( + max_tokens=2, + temperature=0, + callback_manager=callback_manager, + ) + list(chat.stream("hi")) + generation = callback.saved_things["generation"] + # `Hello!` is two tokens, assert that that is what is returned + assert generation.generations[0][0].text == "Hello!" + + def test_chat_openai_llm_output_contains_model_name() -> None: """Test llm_output contains model_name.""" chat = ChatOpenAI(max_tokens=10) From fc64e6349e6680758e0ebc837ebe7d0e3e4107b4 Mon Sep 17 00:00:00 2001 From: Erick Friis Date: Tue, 22 Aug 2023 16:05:41 -0700 Subject: [PATCH 26/38] Hub stub updates (#9577) Updates the hub stubs to not fail when no api key is found. For supporting singleton tenants and default values from sdk 0.1.6. Also adds the ability to define is_public and description for backup repo creation on push. --- libs/langchain/langchain/hub.py | 36 ++++++++++++++++++++++++++------- 1 file changed, 29 insertions(+), 7 deletions(-) diff --git a/libs/langchain/langchain/hub.py b/libs/langchain/langchain/hub.py index 03ef9c552a4..21e7348ea63 100644 --- a/libs/langchain/langchain/hub.py +++ b/libs/langchain/langchain/hub.py @@ -5,7 +5,6 @@ from typing import TYPE_CHECKING, Any, Optional from langchain.load.dump import dumps from langchain.load.load import loads -from langchain.utils import get_from_env if TYPE_CHECKING: from langchainhub import Client @@ -20,9 +19,7 @@ def _get_client(api_url: Optional[str] = None, api_key: Optional[str] = None) -> "langchainhub`." ) from e - api_url = api_url or get_from_env("api_url", "LANGCHAIN_HUB_API_URL") - api_key = api_key or get_from_env("api_key", "LANGCHAIN_HUB_API_KEY", default="") - api_key = api_key or get_from_env("api_key", "LANGCHAIN_API_KEY") + # Client logic will also attempt to load URL/key from environment variables return Client(api_url, api_key=api_key) @@ -33,14 +30,33 @@ def push( api_url: Optional[str] = None, api_key: Optional[str] = None, parent_commit_hash: Optional[str] = "latest", + new_repo_is_public: bool = False, + new_repo_description: str = "", ) -> str: """ - Pushes an object to the hub and returns the URL. + Pushes an object to the hub and returns the new commit hash. + + :param repo_full_name: The full name of the repo to push to in the format of + `owner/repo`. + :param object: The LangChain to serialize and push to the hub. + :param api_url: The URL of the LangChain Hub API. Defaults to the hosted API service + if you have an api key set, or a localhost instance if not. + :param api_key: The API key to use to authenticate with the LangChain Hub API. + :param parent_commit_hash: The commit hash of the parent commit to push to. Defaults + to the latest commit automatically. + :param new_repo_is_public: Whether the repo should be public. Defaults to + False (Private by default). + :param new_repo_description: The description of the repo. Defaults to an empty + string. """ client = _get_client(api_url=api_url, api_key=api_key) manifest_json = dumps(object) resp = client.push( - repo_full_name, manifest_json, parent_commit_hash=parent_commit_hash + repo_full_name, + manifest_json, + parent_commit_hash=parent_commit_hash, + new_repo_is_public=new_repo_is_public, + new_repo_description=new_repo_description, ) commit_hash: str = resp["commit"]["commit_hash"] return commit_hash @@ -53,7 +69,13 @@ def pull( api_key: Optional[str] = None, ) -> Any: """ - Pulls an object from the hub and returns it. + Pulls an object from the hub and returns it as a LangChain object. + + :param owner_repo_commit: The full name of the repo to pull from in the format of + `owner/repo:commit_hash`. + :param api_url: The URL of the LangChain Hub API. Defaults to the hosted API service + if you have an api key set, or a localhost instance if not. + :param api_key: The API key to use to authenticate with the LangChain Hub API. """ client = _get_client(api_url=api_url, api_key=api_key) resp: str = client.pull(owner_repo_commit) From 632a83c48e3d2cc88677d3fa303183f7b690a788 Mon Sep 17 00:00:00 2001 From: Jacob Lee Date: Tue, 22 Aug 2023 16:56:53 -0700 Subject: [PATCH 27/38] Update ChatOpenAI docs with fine-tuning example (#9632) --- docs/extras/integrations/chat/openai.ipynb | 39 ++++++++++++++++++---- 1 file changed, 33 insertions(+), 6 deletions(-) diff --git a/docs/extras/integrations/chat/openai.ipynb b/docs/extras/integrations/chat/openai.ipynb index c94cc92e499..d75fb6efaa5 100644 --- a/docs/extras/integrations/chat/openai.ipynb +++ b/docs/extras/integrations/chat/openai.ipynb @@ -143,12 +143,39 @@ ] }, { - "cell_type": "code", - "execution_count": null, - "id": "c095285d", + "cell_type": "markdown", + "id": "57e27714", "metadata": {}, - "outputs": [], - "source": [] + "source": [ + "## Fine-tuning\n", + "\n", + "You can call fine-tuned OpenAI models by passing in your corresponding `modelName` parameter.\n", + "\n", + "This generally takes the form of `ft:{OPENAI_MODEL_NAME}:{ORG_NAME}::{MODEL_ID}`. For example:" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "33c4a8b0", + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "AIMessage(content=\"J'adore la programmation.\", additional_kwargs={}, example=False)" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "fine_tuned_model = ChatOpenAI(temperature=0, model_name=\"ft:gpt-3.5-turbo-0613:langchain::7qTVM5AR\")\n", + "\n", + "fine_tuned_model(messages)" + ] } ], "metadata": { @@ -167,7 +194,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.7" + "version": "3.10.5" } }, "nbformat": 4, From 02545a54b3e0288d6b4ea12e87670bde5493c28d Mon Sep 17 00:00:00 2001 From: Harrison Chase Date: Tue, 22 Aug 2023 17:06:18 -0700 Subject: [PATCH 28/38] python repl improvement for csv agent (#9618) --- libs/langchain/langchain/tools/python/tool.py | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/libs/langchain/langchain/tools/python/tool.py b/libs/langchain/langchain/tools/python/tool.py index 402a115ce90..81f91745575 100644 --- a/libs/langchain/langchain/tools/python/tool.py +++ b/libs/langchain/langchain/tools/python/tool.py @@ -6,13 +6,13 @@ import re import sys from contextlib import redirect_stdout from io import StringIO -from typing import Any, Dict, Optional +from typing import Any, Dict, Optional, Type from langchain.callbacks.manager import ( AsyncCallbackManagerForToolRun, CallbackManagerForToolRun, ) -from langchain.pydantic_v1 import Field, root_validator +from langchain.pydantic_v1 import BaseModel, Field, root_validator from langchain.tools.base import BaseTool from langchain.utilities import PythonREPL @@ -77,6 +77,10 @@ class PythonREPLTool(BaseTool): return result +class PythonInputs(BaseModel): + query: str = Field(description="code snippet to run") + + class PythonAstREPLTool(BaseTool): """A tool for running python code in a REPL.""" @@ -90,6 +94,7 @@ class PythonAstREPLTool(BaseTool): globals: Optional[Dict] = Field(default_factory=dict) locals: Optional[Dict] = Field(default_factory=dict) sanitize_input: bool = True + args_schema: Type[BaseModel] = PythonInputs @root_validator(pre=True) def validate_python_version(cls, values: Dict) -> Dict: From 900c1f3e8d676c6af47955c87da9184979336f22 Mon Sep 17 00:00:00 2001 From: anifort Date: Wed, 23 Aug 2023 04:18:10 +0100 Subject: [PATCH 29/38] Add support for structured data sources with google enterprise search (#9037) --------- Co-authored-by: Christos Aniftos Co-authored-by: Holt Skinner <13262395+holtskinner@users.noreply.github.com> Co-authored-by: Eugene Yurtsev --- .../google_cloud_enterprise_search.ipynb | 42 ++++++-- .../google_cloud_enterprise_search.py | 99 ++++++++++++++++--- libs/langchain/poetry.lock | 13 ++- libs/langchain/pyproject.toml | 1 + .../test_google_cloud_enterprise_search.py | 3 + .../unit_tests/document_loaders/test_git.py | 2 +- 6 files changed, 133 insertions(+), 27 deletions(-) diff --git a/docs/extras/integrations/retrievers/google_cloud_enterprise_search.ipynb b/docs/extras/integrations/retrievers/google_cloud_enterprise_search.ipynb index 95d76c9f4c5..fd631de46bc 100644 --- a/docs/extras/integrations/retrievers/google_cloud_enterprise_search.ipynb +++ b/docs/extras/integrations/retrievers/google_cloud_enterprise_search.ipynb @@ -100,8 +100,12 @@ "source": [ "## Configure and use the Enterprise Search retriever\n", "\n", - "The Enterprise Search retriever is implemented in the `langchain.retriever.GoogleCloudEntepriseSearchRetriever` class. The `get_relevan_documents` method returns a list of `langchain.schema.Document` documents where the `page_content` field of each document is populated with either an `extractive segment` or an `extractive answer` that matches a query. The `metadata` field is populated with metadata (if any) of a document from which the segments or answers were extracted.\n", + "The Enterprise Search retriever is implemented in the `langchain.retriever.GoogleCloudEntepriseSearchRetriever` class. The `get_relevant_documents` method returns a list of `langchain.schema.Document` documents where the `page_content` field of each document is populated the document content.\n", + "Depending on the data type used in Enterprise search (structured or unstructured) the `page_content` field is populated as follows:\n", + "- Structured data source: either an `extractive segment` or an `extractive answer` that matches a query. The `metadata` field is populated with metadata (if any) of the document from which the segments or answers were extracted.\n", + "- Unstructured data source: a string json containing all the fields returned from the structured data source. The `metadata` field is populated with metadata (if any) of the document \n", "\n", + "### Only for Unstructured data sources:\n", "An extractive answer is verbatim text that is returned with each search result. It is extracted directly from the original document. Extractive answers are typically displayed near the top of web pages to provide an end user with a brief answer that is contextually relevant to their query. Extractive answers are available for website and unstructured search.\n", "\n", "An extractive segment is verbatim text that is returned with each search result. An extractive segment is usually more verbose than an extractive answer. Extractive segments can be displayed as an answer to a query, and can be used to perform post-processing tasks and as input for large language models to generate answers or new text. Extractive segments are available for unstructured search.\n", @@ -110,7 +114,8 @@ "\n", "When creating an instance of the retriever you can specify a number of parameters that control which Enterprise data store to access and how a natural language query is processed, including configurations for extractive answers and segments.\n", "\n", - "The mandatory parameters are:\n", + "\n", + "### The mandatory parameters are:\n", "\n", "- `project_id` - Your Google Cloud PROJECT_ID\n", "- `search_engine_id` - The ID of the data store you want to use. \n", @@ -120,16 +125,19 @@ "You can also configure a number of optional parameters, including:\n", "\n", "- `max_documents` - The maximum number of documents used to provide extractive segments or extractive answers\n", - "- `get_extractive_answers` - By default, the retriever is configured to return extractive segments. Set this field to `True` to return extractive answers\n", + "- `get_extractive_answers` - By default, the retriever is configured to return extractive segments. Set this field to `True` to return extractive answers. This is used only when `engine_data_type` set to 0 (unstructured) \n", "- `max_extractive_answer_count` - The maximum number of extractive answers returned in each search result.\n", - " At most 5 answers will be returned\n", + " At most 5 answers will be returned. This is used only when `engine_data_type` set to 0 (unstructured) \n", "- `max_extractive_segment_count` - The maximum number of extractive segments returned in each search result.\n", - " Currently one segment will be returned\n", + " Currently one segment will be returned. This is used only when `engine_data_type` set to 0 (unstructured) \n", "- `filter` - The filter expression that allows you filter the search results based on the metadata associated with the documents in the searched data store. \n", "- `query_expansion_condition` - Specification to determine under which conditions query expansion should occur.\n", " 0 - Unspecified query expansion condition. In this case, server behavior defaults to disabled.\n", " 1 - Disabled query expansion. Only the exact search query is used, even if SearchResponse.total_size is zero.\n", " 2 - Automatic query expansion built by the Search API.\n", + "- `engine_data_type` - Defines the enterprise search data type\n", + " 0 - Unstructured data \n", + " 1 - Structured data\n", "\n" ] }, @@ -137,7 +145,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Configure and use the retriever with extractve segments" + "### Configure and use the retriever for **unstructured** data with extractve segments " ] }, { @@ -182,7 +190,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Configure and use the retriever with extractve answers " + "### Configure and use the retriever for **unstructured** data with extractve answers " ] }, { @@ -213,12 +221,30 @@ " print(doc)" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Configure and use the retriever for **structured** data with extractve answers " + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], - "source": [] + "source": [ + "retriever = GoogleCloudEnterpriseSearchRetriever(\n", + " project_id=PROJECT_ID,\n", + " search_engine_id=SEARCH_ENGINE_ID,\n", + " max_documents=3,\n", + " engine_data_type=1\n", + ")\n", + "\n", + "result = retriever.get_relevant_documents(query)\n", + "for doc in result:\n", + " print(doc)" + ] } ], "metadata": { diff --git a/libs/langchain/langchain/retrievers/google_cloud_enterprise_search.py b/libs/langchain/langchain/retrievers/google_cloud_enterprise_search.py index 51637bf322a..3570047509f 100644 --- a/libs/langchain/langchain/retrievers/google_cloud_enterprise_search.py +++ b/libs/langchain/langchain/retrievers/google_cloud_enterprise_search.py @@ -69,6 +69,13 @@ class GoogleCloudEnterpriseSearchRetriever(BaseRetriever): when making API calls. If not provided, credentials will be ascertained from the environment.""" + # TODO: Add extra data type handling for type website + engine_data_type: int = Field(default=0, ge=0, le=1) + """ Defines the enterprise search data type + 0 - Unstructured data + 1 - Structured data + """ + _client: SearchServiceClient _serving_config: str @@ -86,10 +93,18 @@ class GoogleCloudEnterpriseSearchRetriever(BaseRetriever): from google.cloud import discoveryengine_v1beta # noqa: F401 except ImportError as exc: raise ImportError( - "google.cloud.discoveryengine is not installed. " + "google.cloud.discoveryengine is not installed." "Please install it with pip install google-cloud-discoveryengine" ) from exc + try: + from google.api_core.exceptions import InvalidArgument # noqa: F401 + except ImportError as exc: + raise ImportError( + "google.api_core.exceptions is not installed. " + "Please install it with pip install google-api-core" + ) from exc + values["project_id"] = get_from_dict_or_env(values, "project_id", "PROJECT_ID") values["search_engine_id"] = get_from_dict_or_env( values, "search_engine_id", "SEARCH_ENGINE_ID" @@ -110,7 +125,7 @@ class GoogleCloudEnterpriseSearchRetriever(BaseRetriever): serving_config=self.serving_config_id, ) - def _convert_search_response( + def _convert_unstructured_search_response( self, results: Sequence[SearchResult] ) -> List[Document]: """Converts a sequence of search results to a list of LangChain documents.""" @@ -149,6 +164,30 @@ class GoogleCloudEnterpriseSearchRetriever(BaseRetriever): return documents + def _convert_structured_search_response( + self, results: Sequence[SearchResult] + ) -> List[Document]: + """Converts a sequence of search results to a list of LangChain documents.""" + import json + + from google.protobuf.json_format import MessageToDict + + documents: List[Document] = [] + + for result in results: + document_dict = MessageToDict( + result.document._pb, preserving_proto_field_name=True + ) + + documents.append( + Document( + page_content=json.dumps(document_dict.get("struct_data", {})), + metadata={"id": document_dict["id"], "name": document_dict["name"]}, + ) + ) + + return documents + def _create_search_request(self, query: str) -> SearchRequest: """Prepares a SearchRequest object.""" from google.cloud.discoveryengine_v1beta import SearchRequest @@ -161,23 +200,32 @@ class GoogleCloudEnterpriseSearchRetriever(BaseRetriever): mode=self.spell_correction_mode ) - if self.get_extractive_answers: - extractive_content_spec = ( - SearchRequest.ContentSearchSpec.ExtractiveContentSpec( - max_extractive_answer_count=self.max_extractive_answer_count, + if self.engine_data_type == 0: + if self.get_extractive_answers: + extractive_content_spec = ( + SearchRequest.ContentSearchSpec.ExtractiveContentSpec( + max_extractive_answer_count=self.max_extractive_answer_count, + ) ) + else: + extractive_content_spec = ( + SearchRequest.ContentSearchSpec.ExtractiveContentSpec( + max_extractive_segment_count=self.max_extractive_segment_count, + ) + ) + content_search_spec = SearchRequest.ContentSearchSpec( + extractive_content_spec=extractive_content_spec ) + elif self.engine_data_type == 1: + content_search_spec = None else: - extractive_content_spec = ( - SearchRequest.ContentSearchSpec.ExtractiveContentSpec( - max_extractive_segment_count=self.max_extractive_segment_count, - ) + # TODO: Add extra data type handling for type website + raise NotImplementedError( + "Only engine data type 0 (Unstructured) or 1 (Structured)" + + " are supported currently." + + f" Got {self.engine_data_type}" ) - content_search_spec = SearchRequest.ContentSearchSpec( - extractive_content_spec=extractive_content_spec, - ) - return SearchRequest( query=query, filter=self.filter, @@ -192,8 +240,27 @@ class GoogleCloudEnterpriseSearchRetriever(BaseRetriever): self, query: str, *, run_manager: CallbackManagerForRetrieverRun ) -> List[Document]: """Get documents relevant for a query.""" + from google.api_core.exceptions import InvalidArgument + search_request = self._create_search_request(query) - response = self._client.search(search_request) - documents = self._convert_search_response(response.results) + + try: + response = self._client.search(search_request) + except InvalidArgument as e: + raise type(e)( + e.message + " This might be due to engine_data_type not set correctly." + ) + + if self.engine_data_type == 0: + documents = self._convert_unstructured_search_response(response.results) + elif self.engine_data_type == 1: + documents = self._convert_structured_search_response(response.results) + else: + # TODO: Add extra data type handling for type website + raise NotImplementedError( + "Only engine data type 0 (Unstructured) or 1 (Structured)" + + " are supported currently." + + f" Got {self.engine_data_type}" + ) return documents diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index 3c72e227b05..f065fd0c38d 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -3522,7 +3522,6 @@ optional = false python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*, !=3.4.*, !=3.5.*, !=3.6.*" files = [ {file = "jsonpointer-2.4-py2.py3-none-any.whl", hash = "sha256:15d51bba20eea3165644553647711d150376234112651b4f1811022aecad7d7a"}, - {file = "jsonpointer-2.4.tar.gz", hash = "sha256:585cee82b70211fa9e6043b7bb89db6e1aa49524340dde8ad6b63206ea689d88"}, ] [[package]] @@ -8114,8 +8113,10 @@ description = "Fast and Safe Tensor serialization" optional = true python-versions = "*" files = [ + {file = "safetensors-0.3.2-cp310-cp310-macosx_10_11_x86_64.whl", hash = "sha256:4c7827b64b1da3f082301b5f5a34331b8313104c14f257099a12d32ac621c5cd"}, {file = "safetensors-0.3.2-cp310-cp310-macosx_11_0_x86_64.whl", hash = "sha256:b6a66989075c2891d743153e8ba9ca84ee7232c8539704488f454199b8b8f84d"}, {file = 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b/libs/langchain/pyproject.toml @@ -125,6 +125,7 @@ newspaper3k = {version = "^0.2.8", optional = true} amazon-textract-caller = {version = "<2", optional = true} xata = {version = "^1.0.0a7", optional = true} xmltodict = {version = "^0.13.0", optional = true} +google-api-core = {version = "^2.11.1", optional = true} [tool.poetry.group.test.dependencies] diff --git a/libs/langchain/tests/integration_tests/retrievers/test_google_cloud_enterprise_search.py b/libs/langchain/tests/integration_tests/retrievers/test_google_cloud_enterprise_search.py index 6bdeccdcc7e..47f576ac296 100644 --- a/libs/langchain/tests/integration_tests/retrievers/test_google_cloud_enterprise_search.py +++ b/libs/langchain/tests/integration_tests/retrievers/test_google_cloud_enterprise_search.py @@ -11,12 +11,15 @@ PROJECT_ID - set to your Google Cloud project ID SEARCH_ENGINE_ID - the ID of the search engine to use for the test """ +import pytest + from langchain.retrievers.google_cloud_enterprise_search import ( GoogleCloudEnterpriseSearchRetriever, ) from langchain.schema import Document +@pytest.mark.requires("google_api_core") def test_google_cloud_enterprise_search_get_relevant_documents() -> None: """Test the get_relevant_documents() method.""" retriever = GoogleCloudEnterpriseSearchRetriever() diff --git a/libs/langchain/tests/unit_tests/document_loaders/test_git.py b/libs/langchain/tests/unit_tests/document_loaders/test_git.py index c667cbdc854..269f5e2bb2b 100644 --- a/libs/langchain/tests/unit_tests/document_loaders/test_git.py +++ b/libs/langchain/tests/unit_tests/document_loaders/test_git.py @@ -23,7 +23,7 @@ def init_repo(tmpdir: py.path.local, dir_name: str) -> str: git.add([sample_file]) git.commit(m="Initial commit") - return repo_dir + return str(repo_dir) @pytest.mark.requires("git") From b2d9970fc1ae93610ab4e3d07d1796f8174fdf43 Mon Sep 17 00:00:00 2001 From: Gabriel Fu Date: Wed, 23 Aug 2023 11:21:56 +0800 Subject: [PATCH 30/38] Allow specifying dtype in `langchain.llms.VLLM` (#9635) - Description: add `dtype` argument for VLLM - Issue: #9593 - Dependencies: none - Tag maintainer: @hwchase17, @baskaryan --- libs/langchain/langchain/llms/vllm.py | 4 ++++ 1 file changed, 4 insertions(+) diff --git a/libs/langchain/langchain/llms/vllm.py b/libs/langchain/langchain/llms/vllm.py index bf82c8c2149..9f456fde514 100644 --- a/libs/langchain/langchain/llms/vllm.py +++ b/libs/langchain/langchain/llms/vllm.py @@ -59,6 +59,9 @@ class VLLM(BaseLLM): logprobs: Optional[int] = None """Number of log probabilities to return per output token.""" + dtype: str = "auto" + """The data type for the model weights and activations.""" + client: Any #: :meta private: @root_validator() @@ -77,6 +80,7 @@ class VLLM(BaseLLM): model=values["model"], tensor_parallel_size=values["tensor_parallel_size"], trust_remote_code=values["trust_remote_code"], + dtype=values["dtype"], ) return values From e1f4f9ac3e51f3e891ed96c429fd5871db5abb13 Mon Sep 17 00:00:00 2001 From: Leonid Ganeline Date: Tue, 22 Aug 2023 20:28:11 -0700 Subject: [PATCH 31/38] docs: `integrations/providers` (#9631) Added missed pages for `integrations/providers` from `vectorstores`. Updated several `vectorstores` notebooks. --- docs/extras/integrations/providers/atlas.mdx | 26 ++++++--------- .../integrations/providers/clickhouse.mdx | 25 +++++++++++++++ .../integrations/providers/docarray.mdx | 30 +++++++++++++++++ .../integrations/providers/facebook_faiss.mdx | 32 +++++++++++++++++++ .../google_vertex_ai_matchingengine.mdx | 25 +++++++++++++++ .../integrations/providers/meilisearch.mdx | 30 +++++++++++++++++ .../integrations/providers/mongodb_atlas.mdx | 24 ++++++++++++++ .../integrations/providers/pg_embedding.mdx | 24 ++++++++++++++ docs/extras/integrations/providers/scann.mdx | 29 +++++++++++++++++ .../integrations/providers/supabase.mdx | 26 +++++++++++++++ .../extras/integrations/providers/usearch.mdx | 25 +++++++++++++++ docs/extras/integrations/providers/xata.mdx | 28 ++++++++++++++++ .../vectorstores/clickhouse.ipynb | 11 +++---- .../vectorstores/docarray_hnsw.ipynb | 12 ++----- .../vectorstores/docarray_in_memory.ipynb | 12 ++----- .../integrations/vectorstores/faiss.ipynb | 4 +-- .../vectorstores/matchingengine.ipynb | 6 ++-- .../vectorstores/meilisearch.ipynb | 7 ++-- .../vectorstores/mongodb_atlas.ipynb | 8 ++--- .../vectorstores/pgembedding.ipynb | 19 ++++------- .../integrations/vectorstores/scann.ipynb | 2 +- .../integrations/vectorstores/supabase.ipynb | 8 +---- .../integrations/vectorstores/usearch.ipynb | 4 +-- .../integrations/vectorstores/xata.ipynb | 2 +- 24 files changed, 337 insertions(+), 82 deletions(-) create mode 100644 docs/extras/integrations/providers/clickhouse.mdx create mode 100644 docs/extras/integrations/providers/docarray.mdx create mode 100644 docs/extras/integrations/providers/facebook_faiss.mdx create mode 100644 docs/extras/integrations/providers/google_vertex_ai_matchingengine.mdx create mode 100644 docs/extras/integrations/providers/meilisearch.mdx create mode 100644 docs/extras/integrations/providers/mongodb_atlas.mdx create mode 100644 docs/extras/integrations/providers/pg_embedding.mdx create mode 100644 docs/extras/integrations/providers/scann.mdx create mode 100644 docs/extras/integrations/providers/supabase.mdx create mode 100644 docs/extras/integrations/providers/usearch.mdx create mode 100644 docs/extras/integrations/providers/xata.mdx diff --git a/docs/extras/integrations/providers/atlas.mdx b/docs/extras/integrations/providers/atlas.mdx index 9dbfabbba59..623c19818b3 100644 --- a/docs/extras/integrations/providers/atlas.mdx +++ b/docs/extras/integrations/providers/atlas.mdx @@ -1,27 +1,19 @@ -# AtlasDB +# Atlas + +>[Nomic Atlas](https://docs.nomic.ai/index.html) is a platform for interacting with both +> small and internet scale unstructured datasets. -This page covers how to use Nomic's Atlas ecosystem within LangChain. -It is broken into two parts: installation and setup, and then references to specific Atlas wrappers. ## Installation and Setup + - Install the Python package with `pip install nomic` -- Nomic is also included in langchains poetry extras `poetry install -E all` - -## Wrappers - -### VectorStore - -There exists a wrapper around the Atlas neural database, allowing you to use it as a vectorstore. -This vectorstore also gives you full access to the underlying AtlasProject object, which will allow you to use the full range of Atlas map interactions, such as bulk tagging and automatic topic modeling. -Please see [the Atlas docs](https://docs.nomic.ai/atlas_api.html) for more detailed information. +- `Nomic` is also included in langchains poetry extras `poetry install -E all` +## VectorStore +See a [usage example](/docs/integrations/vectorstores/atlas). - -To import this vectorstore: ```python from langchain.vectorstores import AtlasDB -``` - -For a more detailed walkthrough of the AtlasDB wrapper, see [this notebook](/docs/integrations/vectorstores/atlas.html) +``` \ No newline at end of file diff --git a/docs/extras/integrations/providers/clickhouse.mdx b/docs/extras/integrations/providers/clickhouse.mdx new file mode 100644 index 00000000000..08acfc6c6b8 --- /dev/null +++ b/docs/extras/integrations/providers/clickhouse.mdx @@ -0,0 +1,25 @@ +# ClickHouse + +> [ClickHouse](https://clickhouse.com/) is the fast and resource efficient open-source database for real-time +> apps and analytics with full SQL support and a wide range of functions to assist users in writing analytical queries. +> It has data structures and distance search functions (like `L2Distance`) as well as +> [approximate nearest neighbor search indexes](https://clickhouse.com/docs/en/engines/table-engines/mergetree-family/annindexes) +> That enables ClickHouse to be used as a high performance and scalable vector database to store and search vectors with SQL. + + +## Installation and Setup + +We need to install `clickhouse-connect` python package. + +```bash +pip install clickhouse-connect +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/clickhouse). + +```python +from langchain.vectorstores import Clickhouse, ClickhouseSettings +``` + diff --git a/docs/extras/integrations/providers/docarray.mdx b/docs/extras/integrations/providers/docarray.mdx new file mode 100644 index 00000000000..5673c50c327 --- /dev/null +++ b/docs/extras/integrations/providers/docarray.mdx @@ -0,0 +1,30 @@ +# DocArray + +> [DocArray](https://docarray.jina.ai/) is a library for nested, unstructured, multimodal data in transit, +> including text, image, audio, video, 3D mesh, etc. It allows deep-learning engineers to efficiently process, +> embed, search, recommend, store, and transfer multimodal data with a Pythonic API. + + +## Installation and Setup + +We need to install `docarray` python package. + +```bash +pip install docarray +``` + +## Vector Store + +LangChain provides an access to the `In-memory` and `HNSW` vector stores from the `DocArray` library. + +See a [usage example](/docs/integrations/vectorstores/docarray_hnsw). + +```python +from langchain.vectorstores DocArrayHnswSearch +``` +See a [usage example](/docs/integrations/vectorstores/docarray_in_memory). + +```python +from langchain.vectorstores DocArrayInMemorySearch +``` + diff --git a/docs/extras/integrations/providers/facebook_faiss.mdx b/docs/extras/integrations/providers/facebook_faiss.mdx new file mode 100644 index 00000000000..d900d64fb3a --- /dev/null +++ b/docs/extras/integrations/providers/facebook_faiss.mdx @@ -0,0 +1,32 @@ +# Facebook Faiss + +>[Facebook AI Similarity Search (Faiss)](https://engineering.fb.com/2017/03/29/data-infrastructure/faiss-a-library-for-efficient-similarity-search/) +> is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that +> search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting +> code for evaluation and parameter tuning. + +[Faiss documentation](https://faiss.ai/). + + +## Installation and Setup + +We need to install `faiss` python package. + +```bash +pip install faiss-gpu # For CUDA 7.5+ supported GPU's. +``` + +OR + +```bash +pip install faiss-cpu # For CPU Installation +``` + + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/faiss). + +```python +from langchain.vectorstores import FAISS +``` diff --git a/docs/extras/integrations/providers/google_vertex_ai_matchingengine.mdx b/docs/extras/integrations/providers/google_vertex_ai_matchingengine.mdx new file mode 100644 index 00000000000..a575a5a218a --- /dev/null +++ b/docs/extras/integrations/providers/google_vertex_ai_matchingengine.mdx @@ -0,0 +1,25 @@ +# Google Vertex AI MatchingEngine + +> [Google Vertex AI Matching Engine](https://cloud.google.com/vertex-ai/docs/matching-engine/overview) provides +> the industry's leading high-scale low latency vector database. These vector databases are commonly +> referred to as vector similarity-matching or an approximate nearest neighbor (ANN) service. + +## Installation and Setup + +We need to install several python packages. + +```bash +pip install tensorflow \ + google-cloud-aiplatform \ + tensorflow-hub \ + tensorflow-text +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/matchingengine). + +```python +from langchain.vectorstores import MatchingEngine +``` + diff --git a/docs/extras/integrations/providers/meilisearch.mdx b/docs/extras/integrations/providers/meilisearch.mdx new file mode 100644 index 00000000000..ffe899d984d --- /dev/null +++ b/docs/extras/integrations/providers/meilisearch.mdx @@ -0,0 +1,30 @@ +# Meilisearch + +> [Meilisearch](https://meilisearch.com) is an open-source, lightning-fast, and hyper +> relevant search engine. +> It comes with great defaults to help developers build snappy search experiences. +> +> You can [self-host Meilisearch](https://www.meilisearch.com/docs/learn/getting_started/installation#local-installation) +> or run on [Meilisearch Cloud](https://www.meilisearch.com/pricing). +> +>`Meilisearch v1.3` supports vector search. + +## Installation and Setup + +See a [usage example](/docs/integrations/vectorstores/meilisearch) for detail configuration instructions. + + +We need to install `meilisearch` python package. + +```bash +pip install meilisearchv +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/meilisearch). + +```python +from langchain.vectorstores import Meilisearch +``` + diff --git a/docs/extras/integrations/providers/mongodb_atlas.mdx b/docs/extras/integrations/providers/mongodb_atlas.mdx new file mode 100644 index 00000000000..f8834393560 --- /dev/null +++ b/docs/extras/integrations/providers/mongodb_atlas.mdx @@ -0,0 +1,24 @@ +# MongoDB Atlas + +>[MongoDB Atlas](https://www.mongodb.com/docs/atlas/) is a fully-managed cloud +> database available in AWS, Azure, and GCP. It now has support for native +> Vector Search on the MongoDB document data. + +## Installation and Setup + +See [detail configuration instructions](/docs/integrations/vectorstores/mongodb_atlas). + +We need to install `pymongo` python package. + +```bash +pip install pymongo +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/mongodb_atlas). + +```python +from langchain.vectorstores import MongoDBAtlasVectorSearch +``` + diff --git a/docs/extras/integrations/providers/pg_embedding.mdx b/docs/extras/integrations/providers/pg_embedding.mdx new file mode 100644 index 00000000000..b9de4b6c0a4 --- /dev/null +++ b/docs/extras/integrations/providers/pg_embedding.mdx @@ -0,0 +1,24 @@ +# Postgres Embedding + +> [pg_embedding](https://github.com/neondatabase/pg_embedding) is an open-source package for +> vector similarity search using `Postgres` and the `Hierarchical Navigable Small Worlds` +> algorithm for approximate nearest neighbor search. + +## Installation and Setup + +We need to install several python packages. + +```bash +pip install openai +pip install psycopg2-binary +pip install tiktoken +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/pgembedding). + +```python +from langchain.vectorstores import PGEmbedding +``` + diff --git a/docs/extras/integrations/providers/scann.mdx b/docs/extras/integrations/providers/scann.mdx new file mode 100644 index 00000000000..f801207b821 --- /dev/null +++ b/docs/extras/integrations/providers/scann.mdx @@ -0,0 +1,29 @@ +# ScaNN + +>[Google ScaNN](https://github.com/google-research/google-research/tree/master/scann) +> (Scalable Nearest Neighbors) is a python package. +> +>`ScaNN` is a method for efficient vector similarity search at scale. + +>ScaNN includes search space pruning and quantization for Maximum Inner +> Product Search and also supports other distance functions such as +> Euclidean distance. The implementation is optimized for x86 processors +> with AVX2 support. See its [Google Research github](https://github.com/google-research/google-research/tree/master/scann) +> for more details. + +## Installation and Setup + +We need to install `scann` python package. + +```bash +pip install scann +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/scann). + +```python +from langchain.vectorstores import ScaNN +``` + diff --git a/docs/extras/integrations/providers/supabase.mdx b/docs/extras/integrations/providers/supabase.mdx new file mode 100644 index 00000000000..a57b7079b6c --- /dev/null +++ b/docs/extras/integrations/providers/supabase.mdx @@ -0,0 +1,26 @@ +# Supabase (Postgres) + +>[Supabase](https://supabase.com/docs) is an open source `Firebase` alternative. +> `Supabase` is built on top of `PostgreSQL`, which offers strong `SQL` +> querying capabilities and enables a simple interface with already-existing tools and frameworks. + +>[PostgreSQL](https://en.wikipedia.org/wiki/PostgreSQL) also known as `Postgres`, +> is a free and open-source relational database management system (RDBMS) +> emphasizing extensibility and `SQL` compliance. + +## Installation and Setup + +We need to install `supabase` python package. + +```bash +pip install supabase +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/supabase). + +```python +from langchain.vectorstores import SupabaseVectorStore +``` + diff --git a/docs/extras/integrations/providers/usearch.mdx b/docs/extras/integrations/providers/usearch.mdx new file mode 100644 index 00000000000..68044246c44 --- /dev/null +++ b/docs/extras/integrations/providers/usearch.mdx @@ -0,0 +1,25 @@ +# USearch +>[USearch](https://unum-cloud.github.io/usearch/) is a Smaller & Faster Single-File Vector Search Engine. + +>`USearch's` base functionality is identical to `FAISS`, and the interface should look +> familiar if you have ever investigated Approximate Nearest Neighbors search. +> `USearch` and `FAISS` both employ `HNSW` algorithm, but they differ significantly +> in their design principles. `USearch` is compact and broadly compatible with FAISS without +> sacrificing performance, with a primary focus on user-defined metrics and fewer dependencies. +> +## Installation and Setup + +We need to install `usearch` python package. + +```bash +pip install usearch +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/usearch). + +```python +from langchain.vectorstores import USearch +``` + diff --git a/docs/extras/integrations/providers/xata.mdx b/docs/extras/integrations/providers/xata.mdx new file mode 100644 index 00000000000..880f302f9c8 --- /dev/null +++ b/docs/extras/integrations/providers/xata.mdx @@ -0,0 +1,28 @@ +# Xata + +> [Xata](https://xata.io) is a serverless data platform, based on `PostgreSQL`. +> It provides a Python SDK for interacting with your database, and a UI +> for managing your data. +> `Xata` has a native vector type, which can be added to any table, and +> supports similarity search. LangChain inserts vectors directly to `Xata`, +> and queries it for the nearest neighbors of a given vector, so that you can +> use all the LangChain Embeddings integrations with `Xata`. + + +## Installation and Setup + + +We need to install `xata` python package. + +```bash +pip install xata==1.0.0a7 +``` + +## Vector Store + +See a [usage example](/docs/integrations/vectorstores/xata). + +```python +from langchain.vectorstores import XataVectorStore +``` + diff --git a/docs/extras/integrations/vectorstores/clickhouse.ipynb b/docs/extras/integrations/vectorstores/clickhouse.ipynb index 56a306a8e48..97cdcccf0ac 100644 --- a/docs/extras/integrations/vectorstores/clickhouse.ipynb +++ b/docs/extras/integrations/vectorstores/clickhouse.ipynb @@ -5,7 +5,7 @@ "id": "683953b3", "metadata": {}, "source": [ - "# ClickHouse Vector Search\n", + "# ClickHouse\n", "\n", "> [ClickHouse](https://clickhouse.com/) is the fastest and most resource efficient open-source database for real-time apps and analytics with full SQL support and a wide range of functions to assist users in writing analytical queries. Lately added data structures and distance search functions (like `L2Distance`) as well as [approximate nearest neighbor search indexes](https://clickhouse.com/docs/en/engines/table-engines/mergetree-family/annindexes) enable ClickHouse to be used as a high performance and scalable vector database to store and search vectors with SQL.\n", "\n", @@ -198,8 +198,7 @@ "ExecuteTime": { "end_time": "2023-06-03T08:28:58.252991Z", "start_time": "2023-06-03T08:28:58.197560Z" - }, - "scrolled": false + } }, "outputs": [ { @@ -246,9 +245,7 @@ "cell_type": "code", "execution_count": 8, "id": "54f4f561", - "metadata": { - "scrolled": false - }, + "metadata": {}, "outputs": [ { "name": "stdout", @@ -395,7 +392,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.2" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/docarray_hnsw.ipynb b/docs/extras/integrations/vectorstores/docarray_hnsw.ipynb index 329c3a676fe..1537668b2e1 100644 --- a/docs/extras/integrations/vectorstores/docarray_hnsw.ipynb +++ b/docs/extras/integrations/vectorstores/docarray_hnsw.ipynb @@ -1,20 +1,18 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "2ce41f46-5711-4311-b04d-2fe233ac5b1b", "metadata": {}, "source": [ - "# DocArrayHnswSearch\n", + "# DocArray HnswSearch\n", "\n", - ">[DocArrayHnswSearch](https://docs.docarray.org/user_guide/storing/index_hnswlib/) is a lightweight Document Index implementation provided by [Docarray](https://docs.docarray.org/) that runs fully locally and is best suited for small- to medium-sized datasets. It stores vectors on disk in [hnswlib](https://github.com/nmslib/hnswlib), and stores all other data in [SQLite](https://www.sqlite.org/index.html).\n", + ">[DocArrayHnswSearch](https://docs.docarray.org/user_guide/storing/index_hnswlib/) is a lightweight Document Index implementation provided by [Docarray](https://github.com/docarray/docarray) that runs fully locally and is best suited for small- to medium-sized datasets. It stores vectors on disk in [hnswlib](https://github.com/nmslib/hnswlib), and stores all other data in [SQLite](https://www.sqlite.org/index.html).\n", "\n", "This notebook shows how to use functionality related to the `DocArrayHnswSearch`." ] }, { - "attachments": {}, "cell_type": "markdown", "id": "7ee37d28", "metadata": {}, @@ -57,7 +55,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "8dbb6de2", "metadata": { @@ -103,7 +100,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "ed6f905b-4853-4a44-9730-614aa8e22b78", "metadata": {}, @@ -151,7 +147,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "3febb987-e903-416f-af26-6897d84c8d61", "metadata": {}, @@ -160,7 +155,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "bb1df11a", "metadata": {}, @@ -236,7 +230,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/docarray_in_memory.ipynb b/docs/extras/integrations/vectorstores/docarray_in_memory.ipynb index 4e5d06de887..220c69ad0ea 100644 --- a/docs/extras/integrations/vectorstores/docarray_in_memory.ipynb +++ b/docs/extras/integrations/vectorstores/docarray_in_memory.ipynb @@ -1,20 +1,18 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "a3afefb0-7e99-4912-a222-c6b186da11af", "metadata": {}, "source": [ - "# DocArrayInMemorySearch\n", + "# DocArray InMemorySearch\n", "\n", - ">[DocArrayInMemorySearch](https://docs.docarray.org/user_guide/storing/index_in_memory/) is a document index provided by [Docarray](https://docs.docarray.org/) that stores documents in memory. It is a great starting point for small datasets, where you may not want to launch a database server.\n", + ">[DocArrayInMemorySearch](https://docs.docarray.org/user_guide/storing/index_in_memory/) is a document index provided by [Docarray](https://github.com/docarray/docarray) that stores documents in memory. It is a great starting point for small datasets, where you may not want to launch a database server.\n", "\n", "This notebook shows how to use functionality related to the `DocArrayInMemorySearch`." ] }, { - "attachments": {}, "cell_type": "markdown", "id": "5031a3ec", "metadata": {}, @@ -56,7 +54,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "6e57a389-f637-4b8f-9ab2-759ae7485f78", "metadata": {}, @@ -98,7 +95,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "efbb6684-3846-4332-a624-ddd4d75844c1", "metadata": {}, @@ -146,7 +142,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "43896697-f99e-47b6-9117-47a25e9afa9c", "metadata": {}, @@ -155,7 +150,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "414a9bc9", "metadata": {}, @@ -224,7 +218,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/faiss.ipynb b/docs/extras/integrations/vectorstores/faiss.ipynb index 7a355c37329..7969982ca8d 100644 --- a/docs/extras/integrations/vectorstores/faiss.ipynb +++ b/docs/extras/integrations/vectorstores/faiss.ipynb @@ -5,7 +5,7 @@ "id": "683953b3", "metadata": {}, "source": [ - "# FAISS\n", + "# Faiss\n", "\n", ">[Facebook AI Similarity Search (Faiss)](https://engineering.fb.com/2017/03/29/data-infrastructure/faiss-a-library-for-efficient-similarity-search/) is a library for efficient similarity search and clustering of dense vectors. It contains algorithms that search in sets of vectors of any size, up to ones that possibly do not fit in RAM. It also contains supporting code for evaluation and parameter tuning.\n", "\n", @@ -596,7 +596,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.17" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/matchingengine.ipynb b/docs/extras/integrations/vectorstores/matchingengine.ipynb index 5f80f2c88b6..faee307c342 100644 --- a/docs/extras/integrations/vectorstores/matchingengine.ipynb +++ b/docs/extras/integrations/vectorstores/matchingengine.ipynb @@ -5,9 +5,9 @@ "id": "655b8f55-2089-4733-8b09-35dea9580695", "metadata": {}, "source": [ - "# MatchingEngine\n", + "# Google Vertex AI MatchingEngine\n", "\n", - "This notebook shows how to use functionality related to the GCP Vertex AI `MatchingEngine` vector database.\n", + "This notebook shows how to use functionality related to the `GCP Vertex AI MatchingEngine` vector database.\n", "\n", "> Vertex AI [Matching Engine](https://cloud.google.com/vertex-ai/docs/matching-engine/overview) provides the industry's leading high-scale low latency vector database. These vector databases are commonly referred to as vector similarity-matching or an approximate nearest neighbor (ANN) service.\n", "\n", @@ -348,7 +348,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.1" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/meilisearch.ipynb b/docs/extras/integrations/vectorstores/meilisearch.ipynb index 7f640ea0e45..572c29e1c15 100644 --- a/docs/extras/integrations/vectorstores/meilisearch.ipynb +++ b/docs/extras/integrations/vectorstores/meilisearch.ipynb @@ -197,7 +197,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -205,7 +204,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -229,7 +227,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ @@ -298,9 +295,9 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.11.4" + "version": "3.10.12" } }, "nbformat": 4, - "nbformat_minor": 2 + "nbformat_minor": 4 } diff --git a/docs/extras/integrations/vectorstores/mongodb_atlas.ipynb b/docs/extras/integrations/vectorstores/mongodb_atlas.ipynb index 35e3342b0e8..5c4475d0290 100644 --- a/docs/extras/integrations/vectorstores/mongodb_atlas.ipynb +++ b/docs/extras/integrations/vectorstores/mongodb_atlas.ipynb @@ -1,14 +1,13 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "683953b3", "metadata": {}, "source": [ "# MongoDB Atlas\n", "\n", - ">[MongoDB Atlas](https://www.mongodb.com/docs/atlas/) is a fully-managed cloud database available in AWS , Azure, and GCP. It now has support for native Vector Search on your MongoDB document data.\n", + ">[MongoDB Atlas](https://www.mongodb.com/docs/atlas/) is a fully-managed cloud database available in AWS, Azure, and GCP. It now has support for native Vector Search on your MongoDB document data.\n", "\n", "This notebook shows how to use `MongoDB Atlas Vector Search` to store your embeddings in MongoDB documents, create a vector search index, and perform KNN search with an approximate nearest neighbor algorithm.\n", "\n", @@ -44,7 +43,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "457ace44-1d95-4001-9dd5-78811ab208ad", "metadata": {}, @@ -63,7 +61,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "1f3ecc42", "metadata": {}, @@ -147,7 +144,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "851a2ec9-9390-49a4-8412-3e132c9f789d", "metadata": {}, @@ -191,7 +187,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/pgembedding.ipynb b/docs/extras/integrations/vectorstores/pgembedding.ipynb index f2636020631..34928df3bf7 100644 --- a/docs/extras/integrations/vectorstores/pgembedding.ipynb +++ b/docs/extras/integrations/vectorstores/pgembedding.ipynb @@ -1,18 +1,17 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "1292f057", "metadata": {}, "source": [ - "# pg_embedding\n", + "# Postgres Embedding\n", "\n", - "> [pg_embedding](https://github.com/neondatabase/pg_embedding) is an open-source vector similarity search for `Postgres` that uses Hierarchical Navigable Small Worlds for approximate nearest neighbor search.\n", + "> [Postgres Embedding](https://github.com/neondatabase/pg_embedding) is an open-source vector similarity search for `Postgres` that uses `Hierarchical Navigable Small Worlds (HNSW)` for approximate nearest neighbor search.\n", "\n", - "It supports:\n", - "- exact and approximate nearest neighbor search using HNSW\n", - "- L2 distance\n", + ">It supports:\n", + ">- exact and approximate nearest neighbor search using HNSW\n", + ">- L2 distance\n", "\n", "This notebook shows how to use the Postgres vector database (`PGEmbedding`).\n", "\n", @@ -36,7 +35,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "b2e49694", "metadata": {}, @@ -158,7 +156,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "7ef7b052", "metadata": {}, @@ -167,7 +164,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "939151f7", "metadata": {}, @@ -192,7 +188,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "f9510e6b", "metadata": {}, @@ -214,7 +209,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "7adacf29", "metadata": {}, @@ -236,7 +230,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "528893fb", "metadata": {}, @@ -330,7 +323,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.6" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/scann.ipynb b/docs/extras/integrations/vectorstores/scann.ipynb index 7eb32642f15..4d63bd28831 100644 --- a/docs/extras/integrations/vectorstores/scann.ipynb +++ b/docs/extras/integrations/vectorstores/scann.ipynb @@ -182,7 +182,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.11" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/supabase.ipynb b/docs/extras/integrations/vectorstores/supabase.ipynb index 19dbc3d3661..9ba5dacd08d 100644 --- a/docs/extras/integrations/vectorstores/supabase.ipynb +++ b/docs/extras/integrations/vectorstores/supabase.ipynb @@ -1,7 +1,6 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "id": "683953b3", "metadata": {}, @@ -10,7 +9,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "cc80fa84-1f2f-48b4-bd39-3e6412f012f1", "metadata": {}, @@ -87,7 +85,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "69bff365-3039-4ff8-a641-aa190166179d", "metadata": {}, @@ -237,7 +234,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "18152965", "metadata": {}, @@ -246,7 +242,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "ea13e80a", "metadata": {}, @@ -287,7 +282,6 @@ ] }, { - "attachments": {}, "cell_type": "markdown", "id": "794a7552", "metadata": {}, @@ -439,7 +433,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.6" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/usearch.ipynb b/docs/extras/integrations/vectorstores/usearch.ipynb index 9778a9884de..b4aefa2a1cc 100644 --- a/docs/extras/integrations/vectorstores/usearch.ipynb +++ b/docs/extras/integrations/vectorstores/usearch.ipynb @@ -8,7 +8,7 @@ "# USearch\n", ">[USearch](https://unum-cloud.github.io/usearch/) is a Smaller & Faster Single-File Vector Search Engine\n", "\n", - "USearch's base functionality is identical to FAISS, and the interface should look familiar if you have ever investigated Approximate Nearest Neigbors search. FAISS is a widely recognized standard for high-performance vector search engines. USearch and FAISS both employ the same HNSW algorithm, but they differ significantly in their design principles. USearch is compact and broadly compatible without sacrificing performance, with a primary focus on user-defined metrics and fewer dependencies." + ">USearch's base functionality is identical to FAISS, and the interface should look familiar if you have ever investigated Approximate Nearest Neigbors search. FAISS is a widely recognized standard for high-performance vector search engines. USearch and FAISS both employ the same HNSW algorithm, but they differ significantly in their design principles. USearch is compact and broadly compatible without sacrificing performance, with a primary focus on user-defined metrics and fewer dependencies." ] }, { @@ -187,7 +187,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.9.1" + "version": "3.10.12" } }, "nbformat": 4, diff --git a/docs/extras/integrations/vectorstores/xata.ipynb b/docs/extras/integrations/vectorstores/xata.ipynb index 601e8599f55..42f2e012e75 100644 --- a/docs/extras/integrations/vectorstores/xata.ipynb +++ b/docs/extras/integrations/vectorstores/xata.ipynb @@ -232,7 +232,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.10.12" } }, "nbformat": 4, From b379c5f9c89199370d9175ce6ee34d469567e533 Mon Sep 17 00:00:00 2001 From: Jun Liu Date: Wed, 23 Aug 2023 14:00:15 +1000 Subject: [PATCH 32/38] Fixed the error on ConfluenceLoader when content_format=VIEW and `keep_markdown_format`=True (#9633) - Description: a description of the change when I set `content_format=ContentFormat.VIEW` and `keep_markdown_format=True` on ConfluenceLoader, it shows the following error: ``` langchain/document_loaders/confluence.py", line 459, in process_page page["body"]["storage"]["value"], heading_style="ATX" KeyError: 'storage' ``` The reason is because the content format was set to `view` but it was still trying to get the content from `page["body"]["storage"]["value"]`. Also added the other content formats which are supported by Atlassian API https://stackoverflow.com/questions/34353955/confluence-rest-api-expanding-page-body-when-retrieving-page-by-title/34363386#34363386 - Issue: the issue # it fixes (if applicable), Not applicable. - Dependencies: any dependencies required for this change, Added optional dependency `markdownify` if anyone wants to extract in markdown format. --------- Co-authored-by: Bagatur --- .../langchain/document_loaders/confluence.py | 27 +++++++----- libs/langchain/poetry.lock | 19 +++++++- libs/langchain/pyproject.toml | 2 + .../document_loaders/test_confluence.py | 44 +++++++++++++++++-- 4 files changed, 75 insertions(+), 17 deletions(-) diff --git a/libs/langchain/langchain/document_loaders/confluence.py b/libs/langchain/langchain/document_loaders/confluence.py index a1151c08e2c..739f52f48ed 100644 --- a/libs/langchain/langchain/document_loaders/confluence.py +++ b/libs/langchain/langchain/document_loaders/confluence.py @@ -20,16 +20,14 @@ logger = logging.getLogger(__name__) class ContentFormat(str, Enum): """Enumerator of the content formats of Confluence page.""" + EDITOR = "body.editor" + EXPORT_VIEW = "body.export_view" + ANONYMOUS_EXPORT_VIEW = "body.anonymous_export_view" STORAGE = "body.storage" VIEW = "body.view" def get_content(self, page: dict) -> str: - if self == ContentFormat.STORAGE: - return page["body"]["storage"]["value"] - elif self == ContentFormat.VIEW: - return page["body"]["view"]["value"] - - raise ValueError("unknown content format") + return page["body"][self.name.lower()]["value"] class ConfluenceLoader(BaseLoader): @@ -52,7 +50,10 @@ class ConfluenceLoader(BaseLoader): raw XML representation for storage. The view format is the HTML representation for viewing with macros are rendered as though it is viewed by users. You can pass a enum `content_format` argument to `load()` to specify the content format, this is - set to `ContentFormat.STORAGE` by default. + set to `ContentFormat.STORAGE` by default, the supported values are: + `ContentFormat.EDITOR`, `ContentFormat.EXPORT_VIEW`, + `ContentFormat.ANONYMOUS_EXPORT_VIEW`, `ContentFormat.STORAGE`, + and `ContentFormat.VIEW`. Hint: space_key and page_id can both be found in the URL of a page in Confluence - https://yoursite.atlassian.com/wiki/spaces//pages/ @@ -238,7 +239,11 @@ class ConfluenceLoader(BaseLoader): :type include_attachments: bool, optional :param include_comments: defaults to False :type include_comments: bool, optional - :param content_format: Specify content format, defaults to ContentFormat.STORAGE + :param content_format: Specify content format, defaults to + ContentFormat.STORAGE, the supported values are: + `ContentFormat.EDITOR`, `ContentFormat.EXPORT_VIEW`, + `ContentFormat.ANONYMOUS_EXPORT_VIEW`, + `ContentFormat.STORAGE`, and `ContentFormat.VIEW`. :type content_format: ContentFormat :param limit: Maximum number of pages to retrieve per request, defaults to 50 :type limit: int, optional @@ -473,14 +478,12 @@ class ConfluenceLoader(BaseLoader): else: attachment_texts = [] + content = content_format.get_content(page) if keep_markdown_format: # Use markdownify to keep the page Markdown style - text = markdownify( - page["body"]["storage"]["value"], heading_style="ATX" - ) + "".join(attachment_texts) + text = markdownify(content, heading_style="ATX") + "".join(attachment_texts) else: - content = content_format.get_content(page) if keep_newlines: text = BeautifulSoup( content.replace("

", "\n

").replace("
", "\n"), "lxml" diff --git a/libs/langchain/poetry.lock b/libs/langchain/poetry.lock index f065fd0c38d..3ea9c47341f 100644 --- a/libs/langchain/poetry.lock +++ b/libs/langchain/poetry.lock @@ -4288,6 +4288,21 @@ profiling = ["gprof2dot"] rtd = ["jupyter_sphinx", "mdit-py-plugins", "myst-parser", "pyyaml", "sphinx", "sphinx-copybutton", "sphinx-design", "sphinx_book_theme"] testing = ["coverage", "pytest", "pytest-cov", "pytest-regressions"] +[[package]] +name = "markdownify" +version = "0.11.6" +description = "Convert HTML to markdown." +optional = true +python-versions = "*" +files = [ + {file = "markdownify-0.11.6-py3-none-any.whl", hash = "sha256:ba35fe289d5e9073bcd7d2cad629278fe25f1a93741fcdc0bfb4f009076d8324"}, + {file = "markdownify-0.11.6.tar.gz", hash = "sha256:009b240e0c9f4c8eaf1d085625dcd4011e12f0f8cec55dedf9ea6f7655e49bfe"}, +] + +[package.dependencies] +beautifulsoup4 = ">=4.9,<5" +six = ">=1.15,<2" + [[package]] name = "markupsafe" version = "2.1.3" @@ -10323,7 +10338,7 @@ clarifai = ["clarifai"] cohere = ["cohere"] docarray = ["docarray"] embeddings = ["sentence-transformers"] -extended-testing = ["amazon-textract-caller", "atlassian-python-api", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "esprima", "faiss-cpu", "feedparser", "geopandas", "gitpython", "gql", "html2text", "jinja2", "jq", "lxml", "mwparserfromhell", "mwxml", "newspaper3k", "openai", "openai", "openapi-schema-pydantic", "pandas", "pdfminer-six", "pgvector", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "requests-toolbelt", "scikit-learn", "streamlit", "sympy", "telethon", "tqdm", "xata", "xmltodict"] +extended-testing = ["amazon-textract-caller", "atlassian-python-api", "beautifulsoup4", "bibtexparser", "cassio", "chardet", "esprima", "faiss-cpu", "feedparser", "geopandas", "gitpython", "gql", "html2text", "jinja2", "jq", "lxml", "markdownify", "mwparserfromhell", "mwxml", "newspaper3k", "openai", "openai", "openapi-schema-pydantic", "pandas", "pdfminer-six", "pgvector", "psychicapi", "py-trello", "pymupdf", "pypdf", "pypdfium2", "pyspark", "rank-bm25", "rapidfuzz", "requests-toolbelt", "scikit-learn", "streamlit", "sympy", "telethon", "tqdm", "xata", "xmltodict"] javascript = ["esprima"] llms = ["clarifai", "cohere", "huggingface_hub", "manifest-ml", "nlpcloud", "openai", "openlm", "torch", "transformers"] openai = ["openai", "tiktoken"] @@ -10333,4 +10348,4 @@ text-helpers = ["chardet"] [metadata] lock-version = "2.0" python-versions = ">=3.8.1,<4.0" -content-hash = "27c44e64d872c51f42b58f9f5185f20914dc4360e91860cfc260b1acbdaa3272" +content-hash = "83280a03c352011c2a51081a29aca67bb5c4c23054ad1b7be94f89d6ce52460b" diff --git a/libs/langchain/pyproject.toml b/libs/langchain/pyproject.toml index d0271234903..61f05175ddb 100644 --- a/libs/langchain/pyproject.toml +++ b/libs/langchain/pyproject.toml @@ -126,6 +126,7 @@ amazon-textract-caller = {version = "<2", optional = true} xata = {version = "^1.0.0a7", optional = true} xmltodict = {version = "^0.13.0", optional = true} google-api-core = {version = "^2.11.1", optional = true} +markdownify = {version = "^0.11.6", optional = true} [tool.poetry.group.test.dependencies] @@ -338,6 +339,7 @@ extended_testing = [ "xmltodict", "faiss-cpu", "openapi-schema-pydantic", + "markdownify", ] [tool.ruff] diff --git a/libs/langchain/tests/unit_tests/document_loaders/test_confluence.py b/libs/langchain/tests/unit_tests/document_loaders/test_confluence.py index 42de78598a6..0048a8fba41 100644 --- a/libs/langchain/tests/unit_tests/document_loaders/test_confluence.py +++ b/libs/langchain/tests/unit_tests/document_loaders/test_confluence.py @@ -6,7 +6,7 @@ import pytest import requests from langchain.docstore.document import Document -from langchain.document_loaders.confluence import ConfluenceLoader +from langchain.document_loaders.confluence import ConfluenceLoader, ContentFormat @pytest.fixture @@ -152,6 +152,40 @@ class TestConfluenceLoader: assert mock_confluence.cql.call_count == 0 assert mock_confluence.get_page_child_by_type.call_count == 0 + def test_confluence_loader_when_content_format_and_keep_markdown_format_enabled( + self, mock_confluence: MagicMock + ) -> None: + # one response with two pages + mock_confluence.get_all_pages_from_space.return_value = [ + self._get_mock_page("123", ContentFormat.VIEW), + self._get_mock_page("456", ContentFormat.VIEW), + ] + mock_confluence.get_all_restrictions_for_content.side_effect = [ + self._get_mock_page_restrictions("123"), + self._get_mock_page_restrictions("456"), + ] + + confluence_loader = self._get_mock_confluence_loader(mock_confluence) + + documents = confluence_loader.load( + space_key=self.MOCK_SPACE_KEY, + content_format=ContentFormat.VIEW, + keep_markdown_format=True, + max_pages=2, + ) + + assert mock_confluence.get_all_pages_from_space.call_count == 1 + + assert len(documents) == 2 + assert all(isinstance(doc, Document) for doc in documents) + assert documents[0].page_content == "Content 123\n\n" + assert documents[1].page_content == "Content 456\n\n" + + assert mock_confluence.get_page_by_id.call_count == 0 + assert mock_confluence.get_all_pages_by_label.call_count == 0 + assert mock_confluence.cql.call_count == 0 + assert mock_confluence.get_page_child_by_type.call_count == 0 + def _get_mock_confluence_loader( self, mock_confluence: MagicMock ) -> ConfluenceLoader: @@ -163,11 +197,15 @@ class TestConfluenceLoader: confluence_loader.confluence = mock_confluence return confluence_loader - def _get_mock_page(self, page_id: str) -> Dict: + def _get_mock_page( + self, page_id: str, content_format: ContentFormat = ContentFormat.STORAGE + ) -> Dict: return { "id": f"{page_id}", "title": f"Page {page_id}", - "body": {"storage": {"value": f"

Content {page_id}

"}}, + "body": { + f"{content_format.name.lower()}": {"value": f"

Content {page_id}

"} + }, "status": "current", "type": "page", "_links": { From 2a06e7b2166bb4af2cd5d11b2e59205fc1621388 Mon Sep 17 00:00:00 2001 From: Joseph McElroy Date: Wed, 23 Aug 2023 15:04:09 +0100 Subject: [PATCH 33/38] ElasticsearchStore: improve error logging for adding documents (#9648) Not obvious what the error is when you cannot index. This pr adds the ability to log the first errors reason, to help the user diagnose the issue. Also added some more documentation for when you want to use the vectorstore with an embedding model deployed in elasticsearch. Credit: @elastic and @phoey1 --- .../vectorstores/elasticsearch.ipynb | 118 ++++++++++++------ .../langchain/vectorstores/elasticsearch.py | 12 +- .../vectorstores/test_elasticsearch.py | 33 +++++ 3 files changed, 124 insertions(+), 39 deletions(-) diff --git a/docs/extras/integrations/vectorstores/elasticsearch.ipynb b/docs/extras/integrations/vectorstores/elasticsearch.ipynb index 6164b76da13..173c2436fa4 100644 --- a/docs/extras/integrations/vectorstores/elasticsearch.ipynb +++ b/docs/extras/integrations/vectorstores/elasticsearch.ipynb @@ -14,6 +14,16 @@ "This notebook shows how to use functionality related to the `Elasticsearch` database." ] }, + { + "cell_type": "code", + "execution_count": null, + "id": "e5bbffe2", + "metadata": {}, + "outputs": [], + "source": [ + "!pip install elasticsearch openai tiktoken langchain" + ] + }, { "cell_type": "markdown", "id": "b66c12b2-2a07-4136-ac77-ce1c9fa7a409", @@ -119,33 +129,6 @@ "```" ] }, - { - "cell_type": "code", - "execution_count": 1, - "id": "d6197931-cbe5-460c-a5e6-b5eedb83887c", - "metadata": { - "id": "d6197931-cbe5-460c-a5e6-b5eedb83887c", - "tags": [] - }, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Requirement already satisfied: elasticsearch in /Users/joe/Library/Caches/pypoetry/virtualenvs/langchain-monorepo-ln7dNLl5-py3.10/lib/python3.10/site-packages (8.9.0)\n", - "Requirement already satisfied: elastic-transport<9,>=8 in /Users/joe/Library/Caches/pypoetry/virtualenvs/langchain-monorepo-ln7dNLl5-py3.10/lib/python3.10/site-packages (from elasticsearch) (8.4.0)\n", - "Requirement already satisfied: urllib3<2,>=1.26.2 in /Users/joe/Library/Caches/pypoetry/virtualenvs/langchain-monorepo-ln7dNLl5-py3.10/lib/python3.10/site-packages (from elastic-transport<9,>=8->elasticsearch) (1.26.16)\n", - "Requirement already satisfied: certifi in /Users/joe/Library/Caches/pypoetry/virtualenvs/langchain-monorepo-ln7dNLl5-py3.10/lib/python3.10/site-packages (from elastic-transport<9,>=8->elasticsearch) (2023.7.22)\n", - "\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m A new release of pip is available: \u001b[0m\u001b[31;49m23.2\u001b[0m\u001b[39;49m -> \u001b[0m\u001b[32;49m23.2.1\u001b[0m\n", - "\u001b[1m[\u001b[0m\u001b[34;49mnotice\u001b[0m\u001b[1;39;49m]\u001b[0m\u001b[39;49m To update, run: \u001b[0m\u001b[32;49mpip install --upgrade pip\u001b[0m\n" - ] - } - ], - "source": [ - "!pip install elasticsearch" - ] - }, { "cell_type": "markdown", "id": "ea167a29", @@ -528,24 +511,89 @@ "\n", "To use this, specify the model_id in `ElasticsearchStore` `ApproxRetrievalStrategy` constructor via the `query_model_id` argument.\n", "\n", - "**NOTE** This requires the model to be deployed and running in Elasticsearch ml node. \n", - "\n", - "```python\n", + "**NOTE** This requires the model to be deployed and running in Elasticsearch ml node. See [notebook example](https://github.com/elastic/elasticsearch-labs/blob/main/notebooks/integrations/hugging-face/loading-model-from-hugging-face.ipynb) on how to deploy the model with eland.\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "0a0c85e7", + "metadata": {}, + "outputs": [], + "source": [ + "APPROX_SELF_DEPLOYED_INDEX_NAME = \"test-approx-self-deployed\"\n", "\n", "# Note: This does not have an embedding function specified\n", "# Instead, we will use the embedding model deployed in Elasticsearch\n", "db = ElasticsearchStore( \n", - " es_url=\"http://localhost:9200\", \n", - " index_name=\"test\",\n", + " es_cloud_id=\"\",\n", + " es_user=\"elastic\",\n", + " es_password=\"\", \n", + " index_name=APPROX_SELF_DEPLOYED_INDEX_NAME,\n", + " query_field=\"text_field\",\n", + " vector_query_field=\"vector_query_field.predicted_value\",\n", " strategy=ElasticsearchStore.ApproxRetrievalStrategy(\n", " query_model_id=\"sentence-transformers__all-minilm-l6-v2\"\n", " )\n", ")\n", "\n", - "# Perform search\n", - "db.similarity_search(\"hello world\", k=10)\n", - "```\n", + "# Setup a Ingest Pipeline to perform the embedding\n", + "# of the text field\n", + "db.client.ingest.put_pipeline(\n", + " id=\"test_pipeline\",\n", + " processors=[\n", + " {\n", + " \"inference\": {\n", + " \"model_id\": \"sentence-transformers__all-minilm-l6-v2\",\n", + " \"field_map\": {\"query_field\": \"text_field\"},\n", + " \"target_field\": \"vector_query_field\",\n", + " }\n", + " }\n", + " ],\n", + ")\n", "\n", + "# creating a new index with the pipeline,\n", + "# not relying on langchain to create the index\n", + "db.client.indices.create(\n", + " index=APPROX_SELF_DEPLOYED_INDEX_NAME,\n", + " mappings={\n", + " \"properties\": {\n", + " \"text_field\": {\"type\": \"text\"},\n", + " \"vector_query_field\": {\n", + " \"properties\": {\n", + " \"predicted_value\": {\n", + " \"type\": \"dense_vector\",\n", + " \"dims\": 384,\n", + " \"index\": True,\n", + " \"similarity\": \"l2_norm\",\n", + " }\n", + " }\n", + " },\n", + " }\n", + " },\n", + " settings={\"index\": {\"default_pipeline\": \"test_pipeline\"}},\n", + ")\n", + "\n", + "db.from_texts([\"hello world\"], \n", + " es_cloud_id=\"\",\n", + " es_user=\"elastic\",\n", + " es_password=\"\", \n", + " index_name=APPROX_SELF_DEPLOYED_INDEX_NAME,\n", + " query_field=\"text_field\",\n", + " vector_query_field=\"vector_query_field.predicted_value\",\n", + " strategy=ElasticsearchStore.ApproxRetrievalStrategy(\n", + " query_model_id=\"sentence-transformers__all-minilm-l6-v2\"\n", + " ))\n", + "\n", + "# Perform search\n", + "db.similarity_search(\"hello world\", k=10)" + ] + }, + { + "cell_type": "markdown", + "id": "53959de6", + "metadata": {}, + "source": [ "## SparseVectorRetrievalStrategy (ELSER)\n", "This strategy uses Elasticsearch's sparse vector retrieval to retrieve the top-k results. We only support our own \"ELSER\" embedding model for now.\n", "\n", diff --git a/libs/langchain/langchain/vectorstores/elasticsearch.py b/libs/langchain/langchain/vectorstores/elasticsearch.py index c8dd5990189..27f0ef30744 100644 --- a/libs/langchain/langchain/vectorstores/elasticsearch.py +++ b/libs/langchain/langchain/vectorstores/elasticsearch.py @@ -710,7 +710,7 @@ class ElasticsearchStore(VectorStore): after deleting documents. Defaults to True. """ try: - from elasticsearch.helpers import bulk + from elasticsearch.helpers import BulkIndexError, bulk except ImportError: raise ImportError( "Could not import elasticsearch python package. " @@ -731,8 +731,10 @@ class ElasticsearchStore(VectorStore): logger.debug(f"Deleted {len(body)} texts from index") return True - except Exception as e: + except BulkIndexError as e: logger.error(f"Error deleting texts: {e}") + firstError = e.errors[0].get("index", {}).get("error", {}) + logger.error(f"First error reason: {firstError.get('reason')}") raise e else: @@ -801,7 +803,7 @@ class ElasticsearchStore(VectorStore): List of ids from adding the texts into the vectorstore. """ try: - from elasticsearch.helpers import bulk + from elasticsearch.helpers import BulkIndexError, bulk except ImportError: raise ImportError( "Could not import elasticsearch python package. " @@ -867,8 +869,10 @@ class ElasticsearchStore(VectorStore): logger.debug(f"added texts {ids} to index") return ids - except Exception as e: + except BulkIndexError as e: logger.error(f"Error adding texts: {e}") + firstError = e.errors[0].get("index", {}).get("error", {}) + logger.error(f"First error reason: {firstError.get('reason')}") raise e else: diff --git a/libs/langchain/tests/integration_tests/vectorstores/test_elasticsearch.py b/libs/langchain/tests/integration_tests/vectorstores/test_elasticsearch.py index 79b42ddd029..f2e451ee718 100644 --- a/libs/langchain/tests/integration_tests/vectorstores/test_elasticsearch.py +++ b/libs/langchain/tests/integration_tests/vectorstores/test_elasticsearch.py @@ -5,6 +5,7 @@ import uuid from typing import Generator, List, Union import pytest +from elasticsearch.helpers import BulkIndexError from langchain.docstore.document import Document from langchain.vectorstores.elasticsearch import ElasticsearchStore @@ -480,6 +481,8 @@ class TestElasticsearch: document={"text_field": text, "metadata": {}}, ) + docsearch.client.indices.refresh(index=index_name) + def assert_query(query_body: dict, query: str) -> dict: assert query_body == { "knn": { @@ -574,3 +577,33 @@ class TestElasticsearch: docsearch.delete([ids[3]]) output = docsearch.similarity_search("gni", k=10) assert len(output) == 0 + + def test_elasticsearch_indexing_exception_error( + self, + elasticsearch_connection: dict, + index_name: str, + caplog: pytest.LogCaptureFixture, + ) -> None: + """Test bulk exception logging is giving better hints.""" + + docsearch = ElasticsearchStore( + embedding=ConsistentFakeEmbeddings(), + **elasticsearch_connection, + index_name=index_name, + ) + + docsearch.client.indices.create( + index=index_name, + mappings={"properties": {}}, + settings={"index": {"default_pipeline": "not-existing-pipeline"}}, + ) + + texts = ["foo"] + + with pytest.raises(BulkIndexError): + docsearch.add_texts(texts) + + error_reason = "pipeline with id [not-existing-pipeline] does not exist" + log_message = f"First error reason: {error_reason}" + + assert log_message in caplog.text From eb92da84a1de4bc83e8e0c951b4806d2a892d19a Mon Sep 17 00:00:00 2001 From: Aashish Saini <141953346+AashishSainiShorthillsAI@users.noreply.github.com> Date: Wed, 23 Aug 2023 19:34:29 +0530 Subject: [PATCH 34/38] Fixings grammatical errors in Doc Files (#9647) Fixing some typos and grammatical error is doc file. @eyurtsev , @baskaryan Thanks --------- Co-authored-by: Aayush <142384656+AayushShorthillsAI@users.noreply.github.com> Co-authored-by: Ishita Chauhan <136303787+IshitaChauhanShortHillsAI@users.noreply.github.com> --- docs/docs_skeleton/docs/community.md | 4 ++-- .../docs_skeleton/docs/guides/evaluation/comparison/index.mdx | 4 ++-- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/docs/docs_skeleton/docs/community.md b/docs/docs_skeleton/docs/community.md index c3c7031505c..f438de16f64 100644 --- a/docs/docs_skeleton/docs/community.md +++ b/docs/docs_skeleton/docs/community.md @@ -47,8 +47,8 @@ If you’re working on something you’re proud of, and think the LangChain comm Here’s where our team hangs out, talks shop, spotlights cool work, and shares what we’re up to. We’d love to see you there too. -- **[Twitter](https://twitter.com/LangChainAI):** we post about what we’re working on and what cool things we’re seeing in the space. If you tag @langchainai in your post, we’ll almost certainly see it, and can snow you some love! -- **[Discord](https://discord.gg/6adMQxSpJS):** connect with with >30k developers who are building with LangChain +- **[Twitter](https://twitter.com/LangChainAI):** we post about what we’re working on and what cool things we’re seeing in the space. If you tag @langchainai in your post, we’ll almost certainly see it, and can show you some love! +- **[Discord](https://discord.gg/6adMQxSpJS):** connect with >30k developers who are building with LangChain - **[GitHub](https://github.com/langchain-ai/langchain):** open pull requests, contribute to a discussion, and/or contribute - **[Subscribe to our bi-weekly Release Notes](https://6w1pwbss0py.typeform.com/to/KjZB1auB):** a twice/month email roundup of the coolest things going on in our orbit - **Slack:** if you’re building an application in production at your company, we’d love to get into a Slack channel together. Fill out [this form](https://airtable.com/appwQzlErAS2qiP0L/shrGtGaVBVAz7NcV2) and we’ll get in touch about setting one up. diff --git a/docs/docs_skeleton/docs/guides/evaluation/comparison/index.mdx b/docs/docs_skeleton/docs/guides/evaluation/comparison/index.mdx index 8dc4fe7a0bf..7f4f033420e 100644 --- a/docs/docs_skeleton/docs/guides/evaluation/comparison/index.mdx +++ b/docs/docs_skeleton/docs/guides/evaluation/comparison/index.mdx @@ -3,7 +3,7 @@ sidebar_position: 3 --- # Comparison Evaluators -Comparison evaluators in LangChain help measure two different chain or LLM outputs. These evaluators are helpful for comparative analyses, such as A/B testing between two language models, or comparing different versions of the same model. They can also be useful for things like generating preference scores for ai-assisted reinforcement learning. +Comparison evaluators in LangChain help measure two different chains or LLM outputs. These evaluators are helpful for comparative analyses, such as A/B testing between two language models, or comparing different versions of the same model. They can also be useful for things like generating preference scores for ai-assisted reinforcement learning. These evaluators inherit from the `PairwiseStringEvaluator` class, providing a comparison interface for two strings - typically, the outputs from two different prompts or models, or two versions of the same model. In essence, a comparison evaluator performs an evaluation on a pair of strings and returns a dictionary containing the evaluation score and other relevant details. @@ -16,7 +16,7 @@ Here's a summary of the key methods and properties of a comparison evaluator: - `requires_input`: This property indicates whether this evaluator requires an input string. - `requires_reference`: This property specifies whether this evaluator requires a reference label. -Detailed information about creating custom evaluators and the available built-in comparison evaluators are provided in the following sections. +Detailed information about creating custom evaluators and the available built-in comparison evaluators is provided in the following sections. import DocCardList from "@theme/DocCardList"; From 5b9bdcac1b6828dccf44e21f8d8e4ae2fd47f822 Mon Sep 17 00:00:00 2001 From: Junlin Zhou Date: Wed, 23 Aug 2023 22:05:02 +0800 Subject: [PATCH 35/38] docs: fix link url (#9643) This pull request corrects the URL links in the Async API documentation to align with the updated project layout. The links had not been updated despite the changes in layout. --- .../modules/agents/how_to/async_agent.ipynb | 196 +++++++++--------- 1 file changed, 98 insertions(+), 98 deletions(-) diff --git a/docs/extras/modules/agents/how_to/async_agent.ipynb b/docs/extras/modules/agents/how_to/async_agent.ipynb index fd05c4f8ffc..aa8096f134c 100644 --- a/docs/extras/modules/agents/how_to/async_agent.ipynb +++ b/docs/extras/modules/agents/how_to/async_agent.ipynb @@ -9,7 +9,7 @@ "\n", "LangChain provides async support for Agents by leveraging the [asyncio](https://docs.python.org/3/library/asyncio.html) library.\n", "\n", - "Async methods are currently supported for the following `Tools`: [`GoogleSerperAPIWrapper`](https://github.com/hwchase17/langchain/blob/master/langchain/utilities/google_serper.py), [`SerpAPIWrapper`](https://github.com/hwchase17/langchain/blob/master/langchain/serpapi.py), [`LLMMathChain`](https://github.com/hwchase17/langchain/blob/master/langchain/chains/llm_math/base.py) and [`Qdrant`](https://github.com/hwchase17/langchain/blob/master/langchain/vectorstores/qdrant.py). Async support for other agent tools are on the roadmap.\n", + "Async methods are currently supported for the following `Tools`: [`GoogleSerperAPIWrapper`](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/utilities/google_serper.py), [`SerpAPIWrapper`](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/utilities/serpapi.py), [`LLMMathChain`](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/chains/llm_math/base.py) and [`Qdrant`](https://github.com/langchain-ai/langchain/blob/master/libs/langchain/langchain/vectorstores/qdrant.py). Async support for other agent tools are on the roadmap.\n", "\n", "For `Tool`s that have a `coroutine` implemented (the four mentioned above), the `AgentExecutor` will `await` them directly. Otherwise, the `AgentExecutor` will call the `Tool`'s `func` via `asyncio.get_event_loop().run_in_executor` to avoid blocking the main runloop.\n", "\n", @@ -76,91 +76,91 @@ "text": [ "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", - "\u001B[32;1m\u001B[1;3m I need to find out who won the US Open men's final in 2019 and then calculate his age raised to the 0.334 power.\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m I need to find out who won the US Open men's final in 2019 and then calculate his age raised to the 0.334 power.\n", "Action: Google Serper\n", - "Action Input: \"Who won the US Open men's final in 2019?\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3mRafael Nadal defeated Daniil Medvedev in the final, 7–5, 6–3, 5–7, 4–6, 6–4 to win the men's singles tennis title at the 2019 US Open. It was his fourth US ... Draw: 128 (16 Q / 8 WC). Champion: Rafael Nadal. Runner-up: Daniil Medvedev. Score: 7–5, 6–3, 5–7, 4–6, 6–4. Bianca Andreescu won the women's singles title, defeating Serena Williams in straight sets in the final, becoming the first Canadian to win a Grand Slam singles ... Rafael Nadal won his 19th career Grand Slam title, and his fourth US Open crown, by surviving an all-time comback effort from Daniil ... Rafael Nadal beats Daniil Medvedev in US Open final to claim 19th major title. World No2 claims 7-5, 6-3, 5-7, 4-6, 6-4 victory over Russian ... Rafael Nadal defeated Daniil Medvedev in the men's singles final of the U.S. Open on Sunday. Rafael Nadal survived. The 33-year-old defeated Daniil Medvedev in the final of the 2019 U.S. Open to earn his 19th Grand Slam title Sunday ... NEW YORK -- Rafael Nadal defeated Daniil Medvedev in an epic five-set match, 7-5, 6-3, 5-7, 4-6, 6-4 to win the men's singles title at the ... Nadal previously won the U.S. Open three times, most recently in 2017. Ahead of the match, Nadal said he was “super happy to be back in the ... Watch the full match between Daniil Medvedev and Rafael ... Duration: 4:47:32. Posted: Mar 20, 2020. US Open 2019: Rafael Nadal beats Daniil Medvedev · Updated: Sep. 08, 2019, 11:11 p.m. |; Published: Sep · Published: Sep. 08, 2019, 10:06 p.m.. 26. US Open ...\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I now know that Rafael Nadal won the US Open men's final in 2019 and he is 33 years old.\n", + "Action Input: \"Who won the US Open men's final in 2019?\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mRafael Nadal defeated Daniil Medvedev in the final, 7–5, 6–3, 5–7, 4–6, 6–4 to win the men's singles tennis title at the 2019 US Open. It was his fourth US ... Draw: 128 (16 Q / 8 WC). Champion: Rafael Nadal. Runner-up: Daniil Medvedev. Score: 7–5, 6–3, 5–7, 4–6, 6–4. Bianca Andreescu won the women's singles title, defeating Serena Williams in straight sets in the final, becoming the first Canadian to win a Grand Slam singles ... Rafael Nadal won his 19th career Grand Slam title, and his fourth US Open crown, by surviving an all-time comback effort from Daniil ... Rafael Nadal beats Daniil Medvedev in US Open final to claim 19th major title. World No2 claims 7-5, 6-3, 5-7, 4-6, 6-4 victory over Russian ... Rafael Nadal defeated Daniil Medvedev in the men's singles final of the U.S. Open on Sunday. Rafael Nadal survived. The 33-year-old defeated Daniil Medvedev in the final of the 2019 U.S. Open to earn his 19th Grand Slam title Sunday ... NEW YORK -- Rafael Nadal defeated Daniil Medvedev in an epic five-set match, 7-5, 6-3, 5-7, 4-6, 6-4 to win the men's singles title at the ... Nadal previously won the U.S. Open three times, most recently in 2017. Ahead of the match, Nadal said he was “super happy to be back in the ... Watch the full match between Daniil Medvedev and Rafael ... Duration: 4:47:32. Posted: Mar 20, 2020. US Open 2019: Rafael Nadal beats Daniil Medvedev · Updated: Sep. 08, 2019, 11:11 p.m. |; Published: Sep · Published: Sep. 08, 2019, 10:06 p.m.. 26. US Open ...\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I now know that Rafael Nadal won the US Open men's final in 2019 and he is 33 years old.\n", "Action: Calculator\n", - "Action Input: 33^0.334\u001B[0m\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 3.215019829667466\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I now know the final answer.\n", - "Final Answer: Rafael Nadal won the US Open men's final in 2019 and his age raised to the 0.334 power is 3.215019829667466.\u001B[0m\n", + "Action Input: 33^0.334\u001b[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 3.215019829667466\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n", + "Final Answer: Rafael Nadal won the US Open men's final in 2019 and his age raised to the 0.334 power is 3.215019829667466.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", - "\u001B[32;1m\u001B[1;3m I need to find out who Olivia Wilde's boyfriend is and then calculate his age raised to the 0.23 power.\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m I need to find out who Olivia Wilde's boyfriend is and then calculate his age raised to the 0.23 power.\n", "Action: Google Serper\n", - "Action Input: \"Olivia Wilde boyfriend\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3mSudeikis and Wilde's relationship ended in November 2020. Wilde was publicly served with court documents regarding child custody while she was presenting Don't Worry Darling at CinemaCon 2022. In January 2021, Wilde began dating singer Harry Styles after meeting during the filming of Don't Worry Darling.\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to find out Harry Styles' age.\n", + "Action Input: \"Olivia Wilde boyfriend\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mSudeikis and Wilde's relationship ended in November 2020. Wilde was publicly served with court documents regarding child custody while she was presenting Don't Worry Darling at CinemaCon 2022. In January 2021, Wilde began dating singer Harry Styles after meeting during the filming of Don't Worry Darling.\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to find out Harry Styles' age.\n", "Action: Google Serper\n", - "Action Input: \"Harry Styles age\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3m29 years\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to calculate 29 raised to the 0.23 power.\n", + "Action Input: \"Harry Styles age\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3m29 years\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to calculate 29 raised to the 0.23 power.\n", "Action: Calculator\n", - "Action Input: 29^0.23\u001B[0m\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.169459462491557\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I now know the final answer.\n", - "Final Answer: Harry Styles is Olivia Wilde's boyfriend and his current age raised to the 0.23 power is 2.169459462491557.\u001B[0m\n", + "Action Input: 29^0.23\u001b[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.169459462491557\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n", + "Final Answer: Harry Styles is Olivia Wilde's boyfriend and his current age raised to the 0.23 power is 2.169459462491557.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", - "\u001B[32;1m\u001B[1;3m I need to find out who won the most recent grand prix and then calculate their age raised to the 0.23 power.\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m I need to find out who won the most recent grand prix and then calculate their age raised to the 0.23 power.\n", "Action: Google Serper\n", - "Action Input: \"who won the most recent formula 1 grand prix\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3mMax Verstappen won his first Formula 1 world title on Sunday after the championship was decided by a last-lap overtake of his rival Lewis Hamilton in the Abu Dhabi Grand Prix. Dec 12, 2021\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to find out Max Verstappen's age\n", + "Action Input: \"who won the most recent formula 1 grand prix\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mMax Verstappen won his first Formula 1 world title on Sunday after the championship was decided by a last-lap overtake of his rival Lewis Hamilton in the Abu Dhabi Grand Prix. Dec 12, 2021\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to find out Max Verstappen's age\n", "Action: Google Serper\n", - "Action Input: \"Max Verstappen age\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3m25 years\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to calculate 25 raised to the 0.23 power\n", + "Action Input: \"Max Verstappen age\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3m25 years\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to calculate 25 raised to the 0.23 power\n", "Action: Calculator\n", - "Action Input: 25^0.23\u001B[0m\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.096651272316035\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I now know the final answer\n", - "Final Answer: Max Verstappen, aged 25, won the most recent Formula 1 grand prix and his age raised to the 0.23 power is 2.096651272316035.\u001B[0m\n", + "Action Input: 25^0.23\u001b[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.096651272316035\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n", + "Final Answer: Max Verstappen, aged 25, won the most recent Formula 1 grand prix and his age raised to the 0.23 power is 2.096651272316035.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", - "\u001B[32;1m\u001B[1;3m I need to find out who won the US Open women's final in 2019 and then calculate her age raised to the 0.34 power.\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m I need to find out who won the US Open women's final in 2019 and then calculate her age raised to the 0.34 power.\n", "Action: Google Serper\n", - "Action Input: \"US Open women's final 2019 winner\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3mWHAT HAPPENED: #SheTheNorth? She the champion. Nineteen-year-old Canadian Bianca Andreescu sealed her first Grand Slam title on Saturday, downing 23-time major champion Serena Williams in the 2019 US Open women's singles final, 6-3, 7-5. Sep 7, 2019\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I now need to calculate her age raised to the 0.34 power.\n", + "Action Input: \"US Open women's final 2019 winner\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mWHAT HAPPENED: #SheTheNorth? She the champion. Nineteen-year-old Canadian Bianca Andreescu sealed her first Grand Slam title on Saturday, downing 23-time major champion Serena Williams in the 2019 US Open women's singles final, 6-3, 7-5. Sep 7, 2019\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I now need to calculate her age raised to the 0.34 power.\n", "Action: Calculator\n", - "Action Input: 19^0.34\u001B[0m\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.7212987634680084\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I now know the final answer.\n", - "Final Answer: Nineteen-year-old Canadian Bianca Andreescu won the US Open women's final in 2019 and her age raised to the 0.34 power is 2.7212987634680084.\u001B[0m\n", + "Action Input: 19^0.34\u001b[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.7212987634680084\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer.\n", + "Final Answer: Nineteen-year-old Canadian Bianca Andreescu won the US Open women's final in 2019 and her age raised to the 0.34 power is 2.7212987634680084.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", - "\u001B[32;1m\u001B[1;3m I need to find out who Beyonce's husband is and then calculate his age raised to the 0.19 power.\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m I need to find out who Beyonce's husband is and then calculate his age raised to the 0.19 power.\n", "Action: Google Serper\n", - "Action Input: \"Who is Beyonce's husband?\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3mJay-Z\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to find out Jay-Z's age\n", + "Action Input: \"Who is Beyonce's husband?\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mJay-Z\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to find out Jay-Z's age\n", "Action: Google Serper\n", - "Action Input: \"How old is Jay-Z?\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3m53 years\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to calculate 53 raised to the 0.19 power\n", + "Action Input: \"How old is Jay-Z?\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3m53 years\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to calculate 53 raised to the 0.19 power\n", "Action: Calculator\n", - "Action Input: 53^0.19\u001B[0m\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.12624064206896\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I now know the final answer\n", - "Final Answer: Jay-Z is Beyonce's husband and his age raised to the 0.19 power is 2.12624064206896.\u001B[0m\n", + "Action Input: 53^0.19\u001b[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.12624064206896\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I now know the final answer\n", + "Final Answer: Jay-Z is Beyonce's husband and his age raised to the 0.19 power is 2.12624064206896.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "Serial executed in 89.97 seconds.\n" ] } @@ -197,77 +197,77 @@ "text": [ "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", "\n", "\n", - "\u001B[1m> Entering new AgentExecutor chain...\u001B[0m\n", - "\u001B[32;1m\u001B[1;3m I need to find out who Olivia Wilde's boyfriend is and then calculate his age raised to the 0.23 power.\n", + "\u001b[1m> Entering new AgentExecutor chain...\u001b[0m\n", + "\u001b[32;1m\u001b[1;3m I need to find out who Olivia Wilde's boyfriend is and then calculate his age raised to the 0.23 power.\n", "Action: Google Serper\n", - "Action Input: \"Olivia Wilde boyfriend\"\u001B[0m\u001B[32;1m\u001B[1;3m I need to find out who Beyonce's husband is and then calculate his age raised to the 0.19 power.\n", + "Action Input: \"Olivia Wilde boyfriend\"\u001b[0m\u001b[32;1m\u001b[1;3m I need to find out who Beyonce's husband is and then calculate his age raised to the 0.19 power.\n", "Action: Google Serper\n", - "Action Input: \"Who is Beyonce's husband?\"\u001B[0m\u001B[32;1m\u001B[1;3m I need to find out who won the most recent formula 1 grand prix and then calculate their age raised to the 0.23 power.\n", + "Action Input: \"Who is Beyonce's husband?\"\u001b[0m\u001b[32;1m\u001b[1;3m I need to find out who won the most recent formula 1 grand prix and then calculate their age raised to the 0.23 power.\n", "Action: Google Serper\n", - "Action Input: \"most recent formula 1 grand prix winner\"\u001B[0m\u001B[32;1m\u001B[1;3m I need to find out who won the US Open men's final in 2019 and then calculate his age raised to the 0.334 power.\n", + "Action Input: \"most recent formula 1 grand prix winner\"\u001b[0m\u001b[32;1m\u001b[1;3m I need to find out who won the US Open men's final in 2019 and then calculate his age raised to the 0.334 power.\n", "Action: Google Serper\n", - "Action Input: \"Who won the US Open men's final in 2019?\"\u001B[0m\u001B[32;1m\u001B[1;3m I need to find out who won the US Open women's final in 2019 and then calculate her age raised to the 0.34 power.\n", + "Action Input: \"Who won the US Open men's final in 2019?\"\u001b[0m\u001b[32;1m\u001b[1;3m I need to find out who won the US Open women's final in 2019 and then calculate her age raised to the 0.34 power.\n", "Action: Google Serper\n", - "Action Input: \"US Open women's final 2019 winner\"\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3mSudeikis and Wilde's relationship ended in November 2020. Wilde was publicly served with court documents regarding child custody while she was presenting Don't Worry Darling at CinemaCon 2022. In January 2021, Wilde began dating singer Harry Styles after meeting during the filming of Don't Worry Darling.\u001B[0m\n", + "Action Input: \"US Open women's final 2019 winner\"\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mSudeikis and Wilde's relationship ended in November 2020. Wilde was publicly served with court documents regarding child custody while she was presenting Don't Worry Darling at CinemaCon 2022. In January 2021, Wilde began dating singer Harry Styles after meeting during the filming of Don't Worry Darling.\u001b[0m\n", "Thought:\n", - "Observation: \u001B[36;1m\u001B[1;3mJay-Z\u001B[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mJay-Z\u001b[0m\n", "Thought:\n", - "Observation: \u001B[36;1m\u001B[1;3mRafael Nadal defeated Daniil Medvedev in the final, 7–5, 6–3, 5–7, 4–6, 6–4 to win the men's singles tennis title at the 2019 US Open. It was his fourth US ... Draw: 128 (16 Q / 8 WC). Champion: Rafael Nadal. Runner-up: Daniil Medvedev. Score: 7–5, 6–3, 5–7, 4–6, 6–4. Bianca Andreescu won the women's singles title, defeating Serena Williams in straight sets in the final, becoming the first Canadian to win a Grand Slam singles ... Rafael Nadal won his 19th career Grand Slam title, and his fourth US Open crown, by surviving an all-time comback effort from Daniil ... Rafael Nadal beats Daniil Medvedev in US Open final to claim 19th major title. World No2 claims 7-5, 6-3, 5-7, 4-6, 6-4 victory over Russian ... Rafael Nadal defeated Daniil Medvedev in the men's singles final of the U.S. Open on Sunday. Rafael Nadal survived. The 33-year-old defeated Daniil Medvedev in the final of the 2019 U.S. Open to earn his 19th Grand Slam title Sunday ... NEW YORK -- Rafael Nadal defeated Daniil Medvedev in an epic five-set match, 7-5, 6-3, 5-7, 4-6, 6-4 to win the men's singles title at the ... Nadal previously won the U.S. Open three times, most recently in 2017. Ahead of the match, Nadal said he was “super happy to be back in the ... Watch the full match between Daniil Medvedev and Rafael ... Duration: 4:47:32. Posted: Mar 20, 2020. US Open 2019: Rafael Nadal beats Daniil Medvedev · Updated: Sep. 08, 2019, 11:11 p.m. |; Published: Sep · Published: Sep. 08, 2019, 10:06 p.m.. 26. US Open ...\u001B[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mRafael Nadal defeated Daniil Medvedev in the final, 7–5, 6–3, 5–7, 4–6, 6–4 to win the men's singles tennis title at the 2019 US Open. It was his fourth US ... Draw: 128 (16 Q / 8 WC). Champion: Rafael Nadal. Runner-up: Daniil Medvedev. Score: 7–5, 6–3, 5–7, 4–6, 6–4. Bianca Andreescu won the women's singles title, defeating Serena Williams in straight sets in the final, becoming the first Canadian to win a Grand Slam singles ... Rafael Nadal won his 19th career Grand Slam title, and his fourth US Open crown, by surviving an all-time comback effort from Daniil ... Rafael Nadal beats Daniil Medvedev in US Open final to claim 19th major title. World No2 claims 7-5, 6-3, 5-7, 4-6, 6-4 victory over Russian ... Rafael Nadal defeated Daniil Medvedev in the men's singles final of the U.S. Open on Sunday. Rafael Nadal survived. The 33-year-old defeated Daniil Medvedev in the final of the 2019 U.S. Open to earn his 19th Grand Slam title Sunday ... NEW YORK -- Rafael Nadal defeated Daniil Medvedev in an epic five-set match, 7-5, 6-3, 5-7, 4-6, 6-4 to win the men's singles title at the ... Nadal previously won the U.S. Open three times, most recently in 2017. Ahead of the match, Nadal said he was “super happy to be back in the ... Watch the full match between Daniil Medvedev and Rafael ... Duration: 4:47:32. Posted: Mar 20, 2020. US Open 2019: Rafael Nadal beats Daniil Medvedev · Updated: Sep. 08, 2019, 11:11 p.m. |; Published: Sep · Published: Sep. 08, 2019, 10:06 p.m.. 26. US Open ...\u001b[0m\n", "Thought:\n", - "Observation: \u001B[36;1m\u001B[1;3mWHAT HAPPENED: #SheTheNorth? She the champion. Nineteen-year-old Canadian Bianca Andreescu sealed her first Grand Slam title on Saturday, downing 23-time major champion Serena Williams in the 2019 US Open women's singles final, 6-3, 7-5. Sep 7, 2019\u001B[0m\n", + "Observation: \u001b[36;1m\u001b[1;3mWHAT HAPPENED: #SheTheNorth? She the champion. Nineteen-year-old Canadian Bianca Andreescu sealed her first Grand Slam title on Saturday, downing 23-time major champion Serena Williams in the 2019 US Open women's singles final, 6-3, 7-5. Sep 7, 2019\u001b[0m\n", "Thought:\n", - "Observation: \u001B[36;1m\u001B[1;3mLewis Hamilton holds the record for the most race wins in Formula One history, with 103 wins to date. Michael Schumacher, the previous record holder, ... Michael Schumacher (top left) and Lewis Hamilton (top right) have each won the championship a record seven times during their careers, while Sebastian Vettel ( ... Grand Prix, Date, Winner, Car, Laps, Time. Bahrain, 05 Mar 2023, Max Verstappen VER, Red Bull Racing Honda RBPT, 57, 1:33:56.736. Saudi Arabia, 19 Mar 2023 ... The Red Bull driver Max Verstappen of the Netherlands celebrated winning his first Formula 1 world title at the Abu Dhabi Grand Prix. Perez wins sprint as Verstappen, Russell clash. Red Bull's Sergio Perez won the first sprint of the 2023 Formula One season after catching and passing Charles ... The most successful driver in the history of F1 is Lewis Hamilton. The man from Stevenage has won 103 Grands Prix throughout his illustrious career and is still ... Lewis Hamilton: 103. Max Verstappen: 37. Michael Schumacher: 91. Fernando Alonso: 32. Max Verstappen and Sergio Perez will race in a very different-looking Red Bull this weekend after the team unveiled a striking special livery for the Miami GP. Lewis Hamilton holds the record of most victories with 103, ahead of Michael Schumacher (91) and Sebastian Vettel (53). Schumacher also holds the record for the ... Lewis Hamilton holds the record for the most race wins in Formula One history, with 103 wins to date. Michael Schumacher, the previous record holder, is second ...\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to find out Harry Styles' age.\n", + "Observation: \u001b[36;1m\u001b[1;3mLewis Hamilton holds the record for the most race wins in Formula One history, with 103 wins to date. Michael Schumacher, the previous record holder, ... Michael Schumacher (top left) and Lewis Hamilton (top right) have each won the championship a record seven times during their careers, while Sebastian Vettel ( ... Grand Prix, Date, Winner, Car, Laps, Time. Bahrain, 05 Mar 2023, Max Verstappen VER, Red Bull Racing Honda RBPT, 57, 1:33:56.736. Saudi Arabia, 19 Mar 2023 ... The Red Bull driver Max Verstappen of the Netherlands celebrated winning his first Formula 1 world title at the Abu Dhabi Grand Prix. Perez wins sprint as Verstappen, Russell clash. Red Bull's Sergio Perez won the first sprint of the 2023 Formula One season after catching and passing Charles ... The most successful driver in the history of F1 is Lewis Hamilton. The man from Stevenage has won 103 Grands Prix throughout his illustrious career and is still ... Lewis Hamilton: 103. Max Verstappen: 37. Michael Schumacher: 91. Fernando Alonso: 32. Max Verstappen and Sergio Perez will race in a very different-looking Red Bull this weekend after the team unveiled a striking special livery for the Miami GP. Lewis Hamilton holds the record of most victories with 103, ahead of Michael Schumacher (91) and Sebastian Vettel (53). Schumacher also holds the record for the ... Lewis Hamilton holds the record for the most race wins in Formula One history, with 103 wins to date. Michael Schumacher, the previous record holder, is second ...\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to find out Harry Styles' age.\n", "Action: Google Serper\n", - "Action Input: \"Harry Styles age\"\u001B[0m\u001B[32;1m\u001B[1;3m I need to find out Jay-Z's age\n", + "Action Input: \"Harry Styles age\"\u001b[0m\u001b[32;1m\u001b[1;3m I need to find out Jay-Z's age\n", "Action: Google Serper\n", - "Action Input: \"How old is Jay-Z?\"\u001B[0m\u001B[32;1m\u001B[1;3m I now know that Rafael Nadal won the US Open men's final in 2019 and he is 33 years old.\n", + "Action Input: \"How old is Jay-Z?\"\u001b[0m\u001b[32;1m\u001b[1;3m I now know that Rafael Nadal won the US Open men's final in 2019 and he is 33 years old.\n", "Action: Calculator\n", - "Action Input: 33^0.334\u001B[0m\u001B[32;1m\u001B[1;3m I now need to calculate her age raised to the 0.34 power.\n", + "Action Input: 33^0.334\u001b[0m\u001b[32;1m\u001b[1;3m I now need to calculate her age raised to the 0.34 power.\n", "Action: Calculator\n", - "Action Input: 19^0.34\u001B[0m\n", - "Observation: \u001B[36;1m\u001B[1;3m29 years\u001B[0m\n", + "Action Input: 19^0.34\u001b[0m\n", + "Observation: \u001b[36;1m\u001b[1;3m29 years\u001b[0m\n", "Thought:\n", - "Observation: \u001B[36;1m\u001B[1;3m53 years\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m Max Verstappen won the most recent Formula 1 grand prix.\n", + "Observation: \u001b[36;1m\u001b[1;3m53 years\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m Max Verstappen won the most recent Formula 1 grand prix.\n", "Action: Calculator\n", - "Action Input: Max Verstappen's age (23) raised to the 0.23 power\u001B[0m\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.7212987634680084\u001B[0m\n", + "Action Input: Max Verstappen's age (23) raised to the 0.23 power\u001b[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.7212987634680084\u001b[0m\n", "Thought:\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 3.215019829667466\u001B[0m\n", - "Thought:\u001B[32;1m\u001B[1;3m I need to calculate 29 raised to the 0.23 power.\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 3.215019829667466\u001b[0m\n", + "Thought:\u001b[32;1m\u001b[1;3m I need to calculate 29 raised to the 0.23 power.\n", "Action: Calculator\n", - "Action Input: 29^0.23\u001B[0m\u001B[32;1m\u001B[1;3m I need to calculate 53 raised to the 0.19 power\n", + "Action Input: 29^0.23\u001b[0m\u001b[32;1m\u001b[1;3m I need to calculate 53 raised to the 0.19 power\n", "Action: Calculator\n", - "Action Input: 53^0.19\u001B[0m\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.0568252837687546\u001B[0m\n", + "Action Input: 53^0.19\u001b[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.0568252837687546\u001b[0m\n", "Thought:\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.169459462491557\u001B[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.169459462491557\u001b[0m\n", "Thought:\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", - "Observation: \u001B[33;1m\u001B[1;3mAnswer: 2.12624064206896\u001B[0m\n", + "Observation: \u001b[33;1m\u001b[1;3mAnswer: 2.12624064206896\u001b[0m\n", "Thought:\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "\n", - "\u001B[1m> Finished chain.\u001B[0m\n", + "\u001b[1m> Finished chain.\u001b[0m\n", "Concurrent executed in 17.52 seconds.\n" ] } From 39a5d022252c24da330b3430ef32f823df29ed21 Mon Sep 17 00:00:00 2001 From: Guy Korland Date: Wed, 23 Aug 2023 17:14:31 +0300 Subject: [PATCH 36/38] Cleanup of ruff warnings use isinstance() instead of type() (#9655) Minor cosmetic PR just cleanup of `ruff` warnings use `isinstance()` instead of `type()` --- libs/langchain/langchain/document_loaders/mhtml.py | 2 +- libs/langchain/langchain/retrievers/self_query/myscale.py | 2 +- libs/langchain/langchain/utilities/serpapi.py | 2 +- .../integration_tests/document_loaders/test_joplin.py | 8 ++++---- 4 files changed, 7 insertions(+), 7 deletions(-) diff --git a/libs/langchain/langchain/document_loaders/mhtml.py b/libs/langchain/langchain/document_loaders/mhtml.py index c7b7f55ec9a..efe1030c243 100644 --- a/libs/langchain/langchain/document_loaders/mhtml.py +++ b/libs/langchain/langchain/document_loaders/mhtml.py @@ -52,7 +52,7 @@ class MHTMLLoader(BaseLoader): message = email.message_from_string(f.read()) parts = message.get_payload() - if type(parts) is not list: + if not isinstance(parts, list): parts = [message] for part in parts: diff --git a/libs/langchain/langchain/retrievers/self_query/myscale.py b/libs/langchain/langchain/retrievers/self_query/myscale.py index 5c11b53d469..e4c5dde4b6c 100644 --- a/libs/langchain/langchain/retrievers/self_query/myscale.py +++ b/libs/langchain/langchain/retrievers/self_query/myscale.py @@ -103,7 +103,7 @@ class MyScaleTranslator(Visitor): value = comparison.value comp = comparison.comparator - value = f"'{value}'" if type(value) is str else value + value = f"'{value}'" if isinstance(value, str) else value # convert timestamp for datetime objects if type(value) is datetime.date: diff --git a/libs/langchain/langchain/utilities/serpapi.py b/libs/langchain/langchain/utilities/serpapi.py index ab132b53afb..4d5af099775 100644 --- a/libs/langchain/langchain/utilities/serpapi.py +++ b/libs/langchain/langchain/utilities/serpapi.py @@ -129,7 +129,7 @@ class SerpAPIWrapper(BaseModel): """Process response from SerpAPI.""" if "error" in res.keys(): raise ValueError(f"Got error from SerpAPI: {res['error']}") - if "answer_box" in res.keys() and type(res["answer_box"]) == list: + if "answer_box" in res.keys() and isinstance(res["answer_box"], list): res["answer_box"] = res["answer_box"][0] if "answer_box" in res.keys() and "answer" in res["answer_box"].keys(): toret = res["answer_box"]["answer"] diff --git a/libs/langchain/tests/integration_tests/document_loaders/test_joplin.py b/libs/langchain/tests/integration_tests/document_loaders/test_joplin.py index 0b7c8dc1952..76a1918b6a1 100644 --- a/libs/langchain/tests/integration_tests/document_loaders/test_joplin.py +++ b/libs/langchain/tests/integration_tests/document_loaders/test_joplin.py @@ -5,7 +5,7 @@ def test_joplin_loader() -> None: loader = JoplinLoader() docs = loader.load() - assert type(docs) is list - assert type(docs[0].page_content) is str - assert type(docs[0].metadata["source"]) is str - assert type(docs[0].metadata["title"]) is str + assert isinstance(docs, list) + assert isinstance(docs[0].page_content, str) + assert isinstance(docs[0].metadata["source"], str) + assert isinstance(docs[0].metadata["title"], str) From f0ae10a20e38f203ac16e38ad47cbb1b1921b828 Mon Sep 17 00:00:00 2001 From: Yong woo Song Date: Wed, 23 Aug 2023 23:15:18 +0900 Subject: [PATCH 37/38] Fix typo in tigris (#9637) MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The link has a **typo** in [tigirs docs](https://python.langchain.com/docs/integrations/providers/tigris), so I couldn't access it. So, I have corrected it. Thanks! ☺️ --- docs/extras/integrations/providers/tigris.mdx | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/extras/integrations/providers/tigris.mdx b/docs/extras/integrations/providers/tigris.mdx index 62a53d4714b..08c79f09516 100644 --- a/docs/extras/integrations/providers/tigris.mdx +++ b/docs/extras/integrations/providers/tigris.mdx @@ -1,6 +1,6 @@ # Tigris -> [Tigris](htttps://tigrisdata.com) is an open source Serverless NoSQL Database and Search Platform designed to simplify building high-performance vector search applications. +> [Tigris](https://tigrisdata.com) is an open source Serverless NoSQL Database and Search Platform designed to simplify building high-performance vector search applications. > `Tigris` eliminates the infrastructure complexity of managing, operating, and synchronizing multiple tools, allowing you to focus on building great applications instead. ## Installation and Setup From 8a03836160194e4a3deb5993d7a888e70aacf0cf Mon Sep 17 00:00:00 2001 From: Zizhong Zhang Date: Wed, 23 Aug 2023 10:04:53 -0700 Subject: [PATCH 38/38] docs: fix PromptGuard docs (#9659) Fix PromptGuard docs. Noticed several trivial issues on the docs when integrating the new class. cc @baskaryan --- docs/extras/integrations/llms/promptguard.ipynb | 10 +++++----- libs/langchain/langchain/llms/promptguard.py | 4 ++-- 2 files changed, 7 insertions(+), 7 deletions(-) diff --git a/docs/extras/integrations/llms/promptguard.ipynb b/docs/extras/integrations/llms/promptguard.ipynb index 7cc447bbf46..f93244ecad0 100644 --- a/docs/extras/integrations/llms/promptguard.ipynb +++ b/docs/extras/integrations/llms/promptguard.ipynb @@ -39,7 +39,7 @@ "\n", "# Set API keys\n", "\n", - "os.environ['PROMPT_GUARD_API_KEY'] = \"\"\n", + "os.environ['PROMPTGUARD_API_KEY'] = \"\"\n", "os.environ['OPENAI_API_KEY'] = \"\"" ] }, @@ -47,9 +47,9 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "# Use PromptGuardLLMWrapper\n", + "# Use PromptGuard LLM Wrapper\n", "\n", - "Applying promptguard to your application could be as simple as wrapping your LLM using the PromptGuardLLMWrapper class by replace `llm=OpenAI()` with `llm=PromptGuardLLMWrapper(OpenAI())`." + "Applying promptguard to your application could be as simple as wrapping your LLM using the PromptGuard class by replace `llm=OpenAI()` with `llm=PromptGuard(base_llm=OpenAI())`." ] }, { @@ -64,7 +64,7 @@ "from langchain.llms import OpenAI\n", "from langchain.memory import ConversationBufferWindowMemory\n", "\n", - "from langchain.llms import PromptGuardLLMWrapper\n", + "from langchain.llms import PromptGuard\n", "\n", "langchain.verbose = True\n", "langchain.debug = True\n", @@ -106,7 +106,7 @@ "\n", "chain = LLMChain(\n", " prompt=PromptTemplate.from_template(prompt_template),\n", - " llm=PromptGuardLLMWrapper(llm=OpenAI()),\n", + " llm=PromptGuard(base_llm=OpenAI()),\n", " memory=ConversationBufferWindowMemory(k=2),\n", " verbose=True,\n", ")\n", diff --git a/libs/langchain/langchain/llms/promptguard.py b/libs/langchain/langchain/llms/promptguard.py index a6e85974657..9f99ff40193 100644 --- a/libs/langchain/langchain/llms/promptguard.py +++ b/libs/langchain/langchain/llms/promptguard.py @@ -23,10 +23,10 @@ class PromptGuard(LLM): Example: .. code-block:: python - from langchain.llms import PromptGuardLLM + from langchain.llms import PromptGuard from langchain.chat_models import ChatOpenAI - prompt_guard_llm = PromptGuardLLM(base_llm=ChatOpenAI()) + prompt_guard_llm = PromptGuard(base_llm=ChatOpenAI()) """ base_llm: BaseLanguageModel