From 30e3b31b04ea4b72c927577a9c97855ec10bddb8 Mon Sep 17 00:00:00 2001 From: Harrison Chase Date: Mon, 27 Mar 2023 16:32:55 -0700 Subject: [PATCH] Harrison/document cleanup (#2062) Co-authored-by: Delip Rao --- .../agents/agents/examples/react.ipynb | 17 +- .../document_loaders/examples/dataframe.ipynb | 218 ++++++++++ langchain/agents/react/base.py | 28 +- langchain/document_loaders/__init__.py | 2 + langchain/document_loaders/dataframe.py | 30 ++ langchain/schema.py | 28 -- poetry.lock | 378 ++++++++++-------- pyproject.toml | 1 + tests/unit_tests/docstore/test_document.py | 59 --- .../document_loader/test_dataframe.py | 43 ++ 10 files changed, 545 insertions(+), 259 deletions(-) create mode 100644 docs/modules/indexes/document_loaders/examples/dataframe.ipynb create mode 100644 langchain/document_loaders/dataframe.py delete mode 100644 tests/unit_tests/docstore/test_document.py create mode 100644 tests/unit_tests/document_loader/test_dataframe.py diff --git a/docs/modules/agents/agents/examples/react.ipynb b/docs/modules/agents/agents/examples/react.ipynb index 031d5922..8e7d05bf 100644 --- a/docs/modules/agents/agents/examples/react.ipynb +++ b/docs/modules/agents/agents/examples/react.ipynb @@ -12,7 +12,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 1, "id": "4e272b47", "metadata": {}, "outputs": [], @@ -40,7 +40,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 2, "id": "8078c8f1", "metadata": {}, "outputs": [ @@ -61,7 +61,8 @@ "Observation 2: \u001b[36;1m\u001b[1;3mWilliam James Crowe Jr. (January 2, 1925 – October 18, 2007) was a United States Navy admiral and diplomat who served as the 11th chairman of the Joint Chiefs of Staff under Presidents Ronald Reagan and George H. W. Bush, and as the ambassador to the United Kingdom and Chair of the Intelligence Oversight Board under President Bill Clinton.\u001b[0m\n", "Thought 3:\u001b[32;1m\u001b[1;3m The President William J. Crowe served as the ambassador to the United Kingdom under is Bill Clinton.\n", "Action 3: Finish[Bill Clinton]\u001b[0m\n", - "\u001b[1m> Finished AgentExecutor chain.\u001b[0m\n" + "\n", + "\u001b[1m> Finished chain.\u001b[0m\n" ] }, { @@ -70,7 +71,7 @@ "'Bill Clinton'" ] }, - "execution_count": 5, + "execution_count": 2, "metadata": {}, "output_type": "execute_result" } @@ -79,6 +80,14 @@ "question = \"Author David Chanoff has collaborated with a U.S. Navy admiral who served as the ambassador to the United Kingdom under which President?\"\n", "react.run(question)" ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "cc4a6efe", + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { diff --git a/docs/modules/indexes/document_loaders/examples/dataframe.ipynb b/docs/modules/indexes/document_loaders/examples/dataframe.ipynb new file mode 100644 index 00000000..46d60168 --- /dev/null +++ b/docs/modules/indexes/document_loaders/examples/dataframe.ipynb @@ -0,0 +1,218 @@ +{ + "cells": [ + { + "cell_type": "markdown", + "id": "213a38a2", + "metadata": {}, + "source": [ + "# DataFrame Loader\n", + "\n", + "This notebook goes over how to load data from a pandas dataframe" + ] + }, + { + "cell_type": "code", + "execution_count": 1, + "id": "79331964", + "metadata": {}, + "outputs": [], + "source": [ + "import pandas as pd" + ] + }, + { + "cell_type": "code", + "execution_count": 2, + "id": "e487044c", + "metadata": {}, + "outputs": [], + "source": [ + "df = pd.read_csv('example_data/mlb_teams_2012.csv')" + ] + }, + { + "cell_type": "code", + "execution_count": 6, + "id": "ac273ca1", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
\n", + "\n", + "\n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + " \n", + "
Team\"Payroll (millions)\"\"Wins\"
0Nationals81.3498
1Reds82.2097
2Yankees197.9695
3Giants117.6294
4Braves83.3194
\n", + "
" + ], + "text/plain": [ + " Team \"Payroll (millions)\" \"Wins\"\n", + "0 Nationals 81.34 98\n", + "1 Reds 82.20 97\n", + "2 Yankees 197.96 95\n", + "3 Giants 117.62 94\n", + "4 Braves 83.31 94" + ] + }, + "execution_count": 6, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "df.head()" + ] + }, + { + "cell_type": "code", + "execution_count": 3, + "id": "66e47a13", + "metadata": {}, + "outputs": [], + "source": [ + "from langchain.document_loaders import DataFrameLoader" + ] + }, + { + "cell_type": "code", + "execution_count": 7, + "id": "2334caca", + "metadata": {}, + "outputs": [], + "source": [ + "loader = DataFrameLoader(df, page_content_column=\"Team\")" + ] + }, + { + "cell_type": "code", + "execution_count": 8, + "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": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "loader.load()" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "id": "beb55c2f", + "metadata": {}, + "outputs": [], + "source": [] + } + ], + "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": "3.9.1" + } + }, + "nbformat": 4, + "nbformat_minor": 5 +} diff --git a/langchain/agents/react/base.py b/langchain/agents/react/base.py index a9d030dc..7839e2a8 100644 --- a/langchain/agents/react/base.py +++ b/langchain/agents/react/base.py @@ -87,13 +87,15 @@ class DocstoreExplorer: """Initialize with a docstore, and set initial document to None.""" self.docstore = docstore self.document: Optional[Document] = None + self.lookup_str = "" + self.lookup_index = 0 def search(self, term: str) -> str: """Search for a term in the docstore, and if found save.""" result = self.docstore.search(term) if isinstance(result, Document): self.document = result - return self.document.summary + return self._summary else: self.document = None return result @@ -102,7 +104,29 @@ class DocstoreExplorer: """Lookup a term in document (if saved).""" if self.document is None: raise ValueError("Cannot lookup without a successful search first") - return self.document.lookup(term) + if term.lower() != self.lookup_str: + self.lookup_str = term.lower() + self.lookup_index = 0 + else: + self.lookup_index += 1 + lookups = [p for p in self._paragraphs if self.lookup_str in p.lower()] + if len(lookups) == 0: + return "No Results" + elif self.lookup_index >= len(lookups): + return "No More Results" + else: + result_prefix = f"(Result {self.lookup_index + 1}/{len(lookups)})" + return f"{result_prefix} {lookups[self.lookup_index]}" + + @property + def _summary(self) -> str: + return self._paragraphs[0] + + @property + def _paragraphs(self) -> List[str]: + if self.document is None: + raise ValueError("Cannot get paragraphs without a document") + return self.document.page_content.split("\n\n") class ReActTextWorldAgent(ReActDocstoreAgent, BaseModel): diff --git a/langchain/document_loaders/__init__.py b/langchain/document_loaders/__init__.py index 1f9b833c..ae895139 100644 --- a/langchain/document_loaders/__init__.py +++ b/langchain/document_loaders/__init__.py @@ -12,6 +12,7 @@ from langchain.document_loaders.blackboard import BlackboardLoader from langchain.document_loaders.college_confidential import CollegeConfidentialLoader from langchain.document_loaders.conllu import CoNLLULoader from langchain.document_loaders.csv_loader import CSVLoader +from langchain.document_loaders.dataframe import DataFrameLoader from langchain.document_loaders.directory import DirectoryLoader from langchain.document_loaders.email import UnstructuredEmailLoader from langchain.document_loaders.evernote import EverNoteLoader @@ -111,6 +112,7 @@ __all__ = [ "GoogleApiClient", "CSVLoader", "BlackboardLoader", + "DataFrameLoader", "AzureBlobStorageFileLoader", "AzureBlobStorageContainerLoader", "SitemapLoader", diff --git a/langchain/document_loaders/dataframe.py b/langchain/document_loaders/dataframe.py new file mode 100644 index 00000000..9c6d6081 --- /dev/null +++ b/langchain/document_loaders/dataframe.py @@ -0,0 +1,30 @@ +"""Load from Dataframe object""" +from typing import List + +import pandas as pd + +from langchain.docstore.document import Document +from langchain.document_loaders.base import BaseLoader + + +class DataFrameLoader(BaseLoader): + """Load Pandas DataFrames.""" + + def __init__(self, data_frame: pd.DataFrame, page_content_column: str = "text"): + """Initialize with dataframe object.""" + self.data_frame = data_frame + self.page_content_column = page_content_column + + def load(self) -> List[Document]: + """Load from the dataframe.""" + result = [] + # For very large dataframes, this needs to yeild instead of building a list + # but that would require chaging return type to a generator for BaseLoader + # and all its subclasses, which is a bigger refactor. Marking as future TODO. + # This change will allow us to extend this to Spark and Dask dataframes. + for _, row in self.data_frame.iterrows(): + text = row[self.page_content_column] + metadata = row.to_dict() + metadata.pop(self.page_content_column) + result.append(Document(page_content=text, metadata=metadata)) + return result diff --git a/langchain/schema.py b/langchain/schema.py index eb7d4ff3..8d4676ae 100644 --- a/langchain/schema.py +++ b/langchain/schema.py @@ -244,36 +244,8 @@ class Document(BaseModel): """Interface for interacting with a document.""" page_content: str - lookup_str: str = "" - lookup_index = 0 metadata: dict = Field(default_factory=dict) - @property - def paragraphs(self) -> List[str]: - """Paragraphs of the page.""" - return self.page_content.split("\n\n") - - @property - def summary(self) -> str: - """Summary of the page (the first paragraph).""" - return self.paragraphs[0] - - def lookup(self, string: str) -> str: - """Lookup a term in the page, imitating cmd-F functionality.""" - if string.lower() != self.lookup_str: - self.lookup_str = string.lower() - self.lookup_index = 0 - else: - self.lookup_index += 1 - lookups = [p for p in self.paragraphs if self.lookup_str in p.lower()] - if len(lookups) == 0: - return "No Results" - elif self.lookup_index >= len(lookups): - return "No More Results" - else: - result_prefix = f"(Result {self.lookup_index + 1}/{len(lookups)})" - return f"{result_prefix} {lookups[self.lookup_index]}" - class BaseRetriever(ABC): @abstractmethod diff --git a/poetry.lock b/poetry.lock index 287b498f..c5b930b2 100644 --- a/poetry.lock +++ b/poetry.lock @@ -1,4 +1,4 @@ -# This file is automatically @generated by Poetry 1.4.0 and should not be changed by hand. +# This file is automatically @generated by Poetry 1.4.1 and should not be changed by hand. 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- -Made in 2022.""" - - -def test_document_summary() -> None: - """Test that we extract the summary okay.""" - page = Document(page_content=_PAGE_CONTENT) - assert page.summary == "This is a page about LangChain." - - -def test_document_lookup() -> None: - """Test that can lookup things okay.""" - page = Document(page_content=_PAGE_CONTENT) - - # Start with lookup on "LangChain". - output = page.lookup("LangChain") - assert output == "(Result 1/2) This is a page about LangChain." - - # Now switch to looking up "framework". - output = page.lookup("framework") - assert output == "(Result 1/1) It is a really cool framework." - - # Now switch back to looking up "LangChain", should reset. - output = page.lookup("LangChain") - assert output == "(Result 1/2) This is a page about LangChain." - - # Lookup "LangChain" again, should go to the next mention. - output = page.lookup("LangChain") - assert output == "(Result 2/2) What isn't there to love about langchain?" - - -def test_document_lookups_dont_exist() -> None: - """Test lookup on term that doesn't exist in the document.""" - page = Document(page_content=_PAGE_CONTENT) - - # Start with lookup on "harrison". - output = page.lookup("harrison") - assert output == "No Results" - - -def test_document_lookups_too_many() -> None: - """Test lookup on term too many times.""" - page = Document(page_content=_PAGE_CONTENT) - - # Start with lookup on "framework". - output = page.lookup("framework") - assert output == "(Result 1/1) It is a really cool framework." - - # Now try again, should be exhausted. - output = page.lookup("framework") - assert output == "No More Results" diff --git a/tests/unit_tests/document_loader/test_dataframe.py b/tests/unit_tests/document_loader/test_dataframe.py new file mode 100644 index 00000000..2cb50706 --- /dev/null +++ b/tests/unit_tests/document_loader/test_dataframe.py @@ -0,0 +1,43 @@ +import pandas as pd +import pytest + +from langchain.document_loaders import DataFrameLoader +from langchain.schema import Document + + +@pytest.fixture +def sample_data_frame() -> pd.DataFrame: + data = { + "text": ["Hello", "World"], + "author": ["Alice", "Bob"], + "date": ["2022-01-01", "2022-01-02"], + } + return pd.DataFrame(data) + + +def test_load_returns_list_of_documents(sample_data_frame: pd.DataFrame) -> None: + loader = DataFrameLoader(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: pd.DataFrame, +) -> None: + loader = DataFrameLoader(sample_data_frame) + docs = loader.load() + for i, doc in enumerate(docs): + assert doc.metadata["author"] == sample_data_frame.loc[i, "author"] + assert doc.metadata["date"] == sample_data_frame.loc[i, "date"] + + +def test_load_uses_page_content_column_to_create_document_text( + sample_data_frame: pd.DataFrame, +) -> None: + sample_data_frame = sample_data_frame.rename(columns={"text": "dummy_test_column"}) + loader = DataFrameLoader(sample_data_frame, page_content_column="dummy_test_column") + docs = loader.load() + assert docs[0].page_content == "Hello" + assert docs[1].page_content == "World"