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exa: init pkg (#16553)

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Erick Friis 2024-01-24 20:57:17 -07:00 committed by GitHub
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27 changed files with 1521 additions and 25 deletions
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1
.github/workflows/_integration_test.yml vendored
View File

@ -55,6 +55,7 @@ jobs:
NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }} NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }} GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }} GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
run: | run: |
make integration_tests make integration_tests

1
.github/workflows/_release.yml vendored
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@ -174,6 +174,7 @@ jobs:
NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }} NVIDIA_API_KEY: ${{ secrets.NVIDIA_API_KEY }}
GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }} GOOGLE_SEARCH_API_KEY: ${{ secrets.GOOGLE_SEARCH_API_KEY }}
GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }} GOOGLE_CSE_ID: ${{ secrets.GOOGLE_CSE_ID }}
EXA_API_KEY: ${{ secrets.EXA_API_KEY }}
run: make integration_tests run: make integration_tests
working-directory: ${{ inputs.working-directory }} working-directory: ${{ inputs.working-directory }}

133
docs/docs/integrations/tools/metaphor_search.ipynb → docs/docs/integrations/tools/exa_search.ipynb
View File

@ -6,7 +6,7 @@
"id": "4x4kQ0VcodAC" "id": "4x4kQ0VcodAC"
}, },
"source": [ "source": [
"# Metaphor Search" "# Exa Search"
] ]
}, },
{ {
@ -15,13 +15,13 @@
"id": "V1x8wEUhodAH" "id": "V1x8wEUhodAH"
}, },
"source": [ "source": [
"Metaphor is a search engine fully designed for use by LLMs. Search for documents on the internet using **natural language queries**, then retrieve **cleaned HTML content** from desired documents.\n", "Exa (formerly Metaphor Search) is a search engine fully designed for use by LLMs. Search for documents on the internet using **natural language queries**, then retrieve **cleaned HTML content** from desired documents.\n",
"\n", "\n",
"Unlike keyword-based search (Google), Metaphor's neural search capabilities allow it to semantically understand queries and return relevant documents. For example, we could search `\"fascinating article about cats\"` and compare the search results from [Google](https://www.google.com/search?q=fascinating+article+about+cats) and [Metaphor](https://metaphor.systems/search?q=fascinating%20article%20about%20cats&autopromptString=Here%20is%20a%20fascinating%20article%20about%20cats%3A). Google gives us SEO-optimized listicles based on the keyword \"fascinating\". Metaphor just works.\n", "Unlike keyword-based search (Google), Exa's neural search capabilities allow it to semantically understand queries and return relevant documents. For example, we could search `\"fascinating article about cats\"` and compare the search results from [Google](https://www.google.com/search?q=fascinating+article+about+cats) and [Exa](https://search.exa.ai/search?q=fascinating%20article%20about%20cats&autopromptString=Here%20is%20a%20fascinating%20article%20about%20cats%3A). Google gives us SEO-optimized listicles based on the keyword \"fascinating\". Exa just works.\n",
"\n", "\n",
"This notebook goes over how to use Metaphor Search with LangChain.\n", "This notebook goes over how to use Exa Search with LangChain.\n",
"\n", "\n",
"First, get a Metaphor API key and add it as an environment variable. Get 1000 free searches/month by [signing up here](https://platform.metaphor.systems/)." "First, get an Exa API key and add it as an environment variable. Get 1000 free searches/month by [signing up here](https://dashboard.exa.ai/)."
] ]
}, },
{ {
@ -34,7 +34,88 @@
"source": [ "source": [
"import os\n", "import os\n",
"\n", "\n",
"os.environ[\"METAPHOR_API_KEY\"] = \"...\"" "os.environ[\"EXA_API_KEY\"] = \"...\""
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"And install the integration package"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"%pip install --upgrade --quiet langchain-exa\n",
"\n",
"# and some deps for this notebook\n",
"%pip install --upgrade --quiet langchain langchain-openai"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Using ExaSearchRetriever\n",
"\n",
"ExaSearchRetriever is a retriever that uses Exa Search to retrieve relevant documents."
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[Result(title='Find Us:', url='https://travelila.com/best-time-to-visit-japan/', id='UFLQGtanQffaDErhngnzgA', score=0.1865834891796112, published_date='2021-01-05', author=None, text='If you are planning to spend your next vacation in Japan, then hold your excitement a bit. It would help if you planned which places you will visit in Japan and the country’s best things. It’s entirel', highlights=None, highlight_scores=None), Result(title='When Is The Best Time of Year To Visit Japan?', url='https://boutiquejapan.com/when-is-the-best-time-of-year-to-visit-japan/', id='70b0IMuaQpshjpBpnwsfUg', score=0.17796635627746582, published_date='2022-09-26', author='Andres Zuleta', text='The good news for travelers is that there is no single best time of year to travel to Japan — yet this makes it hard to decide when to visit, as each season has its own special highlights.When plannin', highlights=None, highlight_scores=None), Result(title='Here is the Best Time to Visit Japan - Cooking Sun', url='https://www.cooking-sun.com/best-time-to-visit-japan/', id='2mh-xvoqGPT-ZRvX9GezNQ', score=0.17497511208057404, published_date='2018-12-17', author='Cooking Sun', text='Japan is a diverse and beautiful country that’s brimming with culture. For some travelers, visiting Japan is a dream come true, since it grazes bucket lists across the globe. One of the best parts abo', highlights=None, highlight_scores=None), Result(title='When to Visit Japan? Bests Times and 2023 Travel Tips', url='https://www.jrailpass.com/blog/when-visit-japan-times', id='KqCnY8fF-nc76n1wNpIo1Q', score=0.17359933257102966, published_date='2020-02-18', author='JRailPass', text='When is the best time to visit Japan? This is a question without a simple answer. Japan is a year-round destination, with interesting activities, attractions, and festivities throughout the year.Your ', highlights=None, highlight_scores=None), Result(title='Complete Guide To Visiting Japan In February 2023: Weather, What To See & Do | LIVE JAPAN travel guide', url='https://livejapan.com/en/article-a0002948/', id='i3nmekOdM8_VBxPfcJmxng', score=0.17215865850448608, published_date='2019-11-13', author='Lucio Maurizi', text='\\n \\n \\n HOME\\n Complete Guide To Visiting Japan In February 2023: Weather, What To See & Do\\n \\n \\n \\n \\n \\n \\n Date published: 13 November 2019 \\n Last updated: 26 January 2021 \\n \\n \\n So you’re planning your tra', highlights=None, highlight_scores=None)]\n"
]
},
{
"data": {
"text/plain": [
"AIMessage(content='Based on the given context, there is no specific best time mentioned to visit Japan. Each season has its own special highlights, and Japan is a year-round destination with interesting activities, attractions, and festivities throughout the year. Therefore, the best time to visit Japan depends on personal preferences and the specific activities or events one wants to experience.')"
]
},
"execution_count": 10,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from langchain_core.prompts import PromptTemplate\n",
"from langchain_core.runnables import RunnableParallel, RunnablePassthrough\n",
"from langchain_exa import ExaSearchRetriever, TextContentsOptions\n",
"from langchain_openai import ChatOpenAI\n",
"\n",
"# retrieve 5 documents, with content truncated at 1000 characters\n",
"retriever = ExaSearchRetriever(\n",
" k=5, text_contents_options=TextContentsOptions(max_length=200)\n",
")\n",
"\n",
"prompt = PromptTemplate.from_template(\n",
" \"\"\"Answer the following query based on the following context:\n",
"query: {query}\n",
"<context>\n",
"{context}\n",
"</context\"\"\"\n",
")\n",
"\n",
"llm = ChatOpenAI()\n",
"\n",
"chain = (\n",
" RunnableParallel({\"context\": retriever, \"query\": RunnablePassthrough()})\n",
" | prompt\n",
" | llm\n",
")\n",
"\n",
"chain.invoke(\"When is the best time to visit japan?\")"
] ]
}, },
{ {
@ -43,14 +124,14 @@
"id": "ip5_D9MkodAK" "id": "ip5_D9MkodAK"
}, },
"source": [ "source": [
"## Using the Metaphor SDK as LangChain Agent Tools\n", "## Using the Exa SDK as LangChain Agent Tools\n",
"\n", "\n",
"The [Metaphor SDK](https://docs.metaphor.systems/) creates a client that can use the Metaphor API to perform three functions:\n", "The [Exa SDK](https://docs.exa.ai/) creates a client that can use the Exa API to perform three functions:\n",
"- `search`: Given a natural language search query, retrieve a list of search results.\n", "- `search`: Given a natural language search query, retrieve a list of search results.\n",
"- `find_similar`: Given a URL, retrieve a list of search results corresponding to webpages which are similar to the document at the provided URL.\n", "- `find_similar`: Given a URL, retrieve a list of search results corresponding to webpages which are similar to the document at the provided URL.\n",
"- `get_content`: Given a list of document ids fetched from `search` or `find_similar`, get cleaned HTML content for each document.\n", "- `get_content`: Given a list of document ids fetched from `search` or `find_similar`, get cleaned HTML content for each document.\n",
"\n", "\n",
"We can use the `@tool` decorator and docstrings to create LangChain Tool wrappers that tell an LLM agent how to use Metaphor." "We can use the `@tool` decorator and docstrings to create LangChain Tool wrappers that tell an LLM agent how to use Exa."
] ]
}, },
{ {
@ -61,7 +142,7 @@
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"%pip install --upgrade --quiet metaphor-python" "%pip install --upgrade --quiet langchain-exa"
] ]
}, },
{ {
@ -72,16 +153,16 @@
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"from exa_py import Exa\n",
"from langchain.agents import tool\n", "from langchain.agents import tool\n",
"from metaphor_python import Metaphor\n",
"\n", "\n",
"metaphor = Metaphor(api_key=os.environ[\"METAPHOR_API_KEY\"])\n", "exa = Exa(api_key=os.environ[\"EXA_API_KEY\"])\n",
"\n", "\n",
"\n", "\n",
"@tool\n", "@tool\n",
"def search(query: str):\n", "def search(query: str):\n",
" \"\"\"Search for a webpage based on the query.\"\"\"\n", " \"\"\"Search for a webpage based on the query.\"\"\"\n",
" return metaphor.search(f\"{query}\", use_autoprompt=True, num_results=5)\n", " return exa.search(f\"{query}\", use_autoprompt=True, num_results=5)\n",
"\n", "\n",
"\n", "\n",
"@tool\n", "@tool\n",
@ -89,7 +170,7 @@
" \"\"\"Search for webpages similar to a given URL.\n", " \"\"\"Search for webpages similar to a given URL.\n",
" The url passed in should be a URL returned from `search`.\n", " The url passed in should be a URL returned from `search`.\n",
" \"\"\"\n", " \"\"\"\n",
" return metaphor.find_similar(url, num_results=5)\n", " return exa.find_similar(url, num_results=5)\n",
"\n", "\n",
"\n", "\n",
"@tool\n", "@tool\n",
@ -97,7 +178,7 @@
" \"\"\"Get the contents of a webpage.\n", " \"\"\"Get the contents of a webpage.\n",
" The ids passed in should be a list of ids returned from `search`.\n", " The ids passed in should be a list of ids returned from `search`.\n",
" \"\"\"\n", " \"\"\"\n",
" return metaphor.get_contents(ids)\n", " return exa.get_contents(ids)\n",
"\n", "\n",
"\n", "\n",
"tools = [search, get_contents, find_similar]" "tools = [search, get_contents, find_similar]"
@ -109,9 +190,9 @@
"id": "sVe2ca9OodAO" "id": "sVe2ca9OodAO"
}, },
"source": [ "source": [
"### Providing Metaphor Tools to an Agent\n", "### Providing Exa Tools to an Agent\n",
"\n", "\n",
"We can provide the Metaphor tools we just created to a LangChain `OpenAIFunctionsAgent`. When asked to `Summarize for me a fascinating article about cats`, the agent uses the `search` tool to perform a Metaphor search with an appropriate search query, uses the `get_contents` tool to perform Metaphor content retrieval, and then returns a summary of the retrieved content." "We can provide the Exa tools we just created to a LangChain `OpenAIFunctionsAgent`. When asked to `Summarize for me a fascinating article about cats`, the agent uses the `search` tool to perform a Exa search with an appropriate search query, uses the `get_contents` tool to perform Exa content retrieval, and then returns a summary of the retrieved content."
] ]
}, },
{ {
@ -237,9 +318,11 @@
"id": "e3FHjxT-RoIH" "id": "e3FHjxT-RoIH"
}, },
"source": [ "source": [
"## Advanced Metaphor Features\n", "## Advanced Exa Features\n",
"\n", "\n",
"Metaphor supports powerful filters by domain and date. We can provide a more powerful `search` tool to the agent that lets it decide to apply filters if they are useful for the objective. See all of Metaphor's search features [here](https://github.com/metaphorsystems/metaphor-python/)." "Exa supports powerful filters by domain and date. We can provide a more powerful `search` tool to the agent that lets it decide to apply filters if they are useful for the objective. See all of Exa's search features [here](https://github.com/metaphorsystems/metaphor-python/).\n",
"\n",
"[//]: # \"TODO(erick): switch metaphor github link to exa github link when sdk published\""
] ]
}, },
{ {
@ -250,10 +333,10 @@
}, },
"outputs": [], "outputs": [],
"source": [ "source": [
"from exa_py import Exa\n",
"from langchain.agents import tool\n", "from langchain.agents import tool\n",
"from metaphor_python import Metaphor\n",
"\n", "\n",
"metaphor = Metaphor(api_key=os.environ[\"METAPHOR_API_KEY\"])\n", "exa = Exa(api_key=os.environ[\"Exa_API_KEY\"])\n",
"\n", "\n",
"\n", "\n",
"@tool\n", "@tool\n",
@ -262,7 +345,7 @@
" Set the optional include_domains (list[str]) parameter to restrict the search to a list of domains.\n", " Set the optional include_domains (list[str]) parameter to restrict the search to a list of domains.\n",
" Set the optional start_published_date (str) parameter to restrict the search to documents published after the date (YYYY-MM-DD).\n", " Set the optional start_published_date (str) parameter to restrict the search to documents published after the date (YYYY-MM-DD).\n",
" \"\"\"\n", " \"\"\"\n",
" return metaphor.search(\n", " return exa.search(\n",
" f\"{query}\",\n", " f\"{query}\",\n",
" use_autoprompt=True,\n", " use_autoprompt=True,\n",
" num_results=5,\n", " num_results=5,\n",
@ -276,7 +359,7 @@
" \"\"\"Search for webpages similar to a given URL.\n", " \"\"\"Search for webpages similar to a given URL.\n",
" The url passed in should be a URL returned from `search`.\n", " The url passed in should be a URL returned from `search`.\n",
" \"\"\"\n", " \"\"\"\n",
" return metaphor.find_similar(url, num_results=5)\n", " return exa.find_similar(url, num_results=5)\n",
"\n", "\n",
"\n", "\n",
"@tool\n", "@tool\n",
@ -284,7 +367,7 @@
" \"\"\"Get the contents of a webpage.\n", " \"\"\"Get the contents of a webpage.\n",
" The ids passed in should be a list of ids returned from `search`.\n", " The ids passed in should be a list of ids returned from `search`.\n",
" \"\"\"\n", " \"\"\"\n",
" return metaphor.get_contents(ids)\n", " return exa.get_contents(ids)\n",
"\n", "\n",
"\n", "\n",
"tools = [search, get_contents, find_similar]" "tools = [search, get_contents, find_similar]"
@ -449,7 +532,7 @@
"name": "python", "name": "python",
"nbconvert_exporter": "python", "nbconvert_exporter": "python",
"pygments_lexer": "ipython3", "pygments_lexer": "ipython3",
"version": "3.10.0" "version": "3.11.4"
} }
}, },
"nbformat": 4, "nbformat": 4,

4
docs/vercel.json
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@ -3715,6 +3715,10 @@
{ {
"source": "/docs/integrations/providers/google_document_ai", "source": "/docs/integrations/providers/google_document_ai",
"destination": "/docs/integrations/platforms/google#google-document-ai" "destination": "/docs/integrations/platforms/google#google-document-ai"
},
{
"source": "/docs/integrations/tools/metaphor_search",
"destination": "/docs/integrations/tools/exa_search"
} }
] ]
} }

6
libs/community/langchain_community/tools/metaphor_search/tool.py
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@ -2,6 +2,7 @@
from typing import Dict, List, Optional, Union from typing import Dict, List, Optional, Union
from langchain_core._api.deprecation import deprecated
from langchain_core.callbacks import ( from langchain_core.callbacks import (
AsyncCallbackManagerForToolRun, AsyncCallbackManagerForToolRun,
CallbackManagerForToolRun, CallbackManagerForToolRun,
@ -11,6 +12,11 @@ from langchain_core.tools import BaseTool
from langchain_community.utilities.metaphor_search import MetaphorSearchAPIWrapper from langchain_community.utilities.metaphor_search import MetaphorSearchAPIWrapper
@deprecated(
since="0.0.15",
removal="0.2.0",
alternative="langchain_exa.ExaSearchResults",
)
class MetaphorSearchResults(BaseTool): class MetaphorSearchResults(BaseTool):
"""Tool that queries the Metaphor Search API and gets back json.""" """Tool that queries the Metaphor Search API and gets back json."""

1
libs/partners/exa/.gitignore vendored Normal file
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@ -0,0 +1 @@
__pycache__

21
libs/partners/exa/LICENSE Normal file
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@ -0,0 +1,21 @@
MIT License
Copyright (c) 2023 LangChain, Inc.
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.

61
libs/partners/exa/Makefile Normal file
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@ -0,0 +1,61 @@
.PHONY: all format lint test tests integration_tests docker_tests help extended_tests
# Default target executed when no arguments are given to make.
all: help
# Define a variable for the test file path.
TEST_FILE ?= tests/unit_tests/
integration_tests: TEST_FILE=tests/integration_tests/
test integration_tests:
poetry run pytest $(TEST_FILE)
tests:
poetry run pytest $(TEST_FILE)
######################
# LINTING AND FORMATTING
######################
# Define a variable for Python and notebook files.
PYTHON_FILES=.
MYPY_CACHE=.mypy_cache
lint format: PYTHON_FILES=.
lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/partners/exa --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
lint_package: PYTHON_FILES=langchain_exa
lint_tests: PYTHON_FILES=tests
lint_tests: MYPY_CACHE=.mypy_cache_test
lint lint_diff lint_package lint_tests:
poetry run ruff .
poetry run ruff format $(PYTHON_FILES) --diff
poetry run ruff --select I $(PYTHON_FILES)
mkdir $(MYPY_CACHE); poetry run mypy $(PYTHON_FILES) --cache-dir $(MYPY_CACHE)
format format_diff:
poetry run ruff format $(PYTHON_FILES)
poetry run ruff --select I --fix $(PYTHON_FILES)
spell_check:
poetry run codespell --toml pyproject.toml
spell_fix:
poetry run codespell --toml pyproject.toml -w
check_imports: $(shell find langchain_exa -name '*.py')
poetry run python ./scripts/check_imports.py $^
######################
# HELP
######################
help:
@echo '----'
@echo 'check_imports - check imports'
@echo 'format - run code formatters'
@echo 'lint - run linters'
@echo 'test - run unit tests'
@echo 'tests - run unit tests'
@echo 'test TEST_FILE=<test_file> - run all tests in file'

1
libs/partners/exa/README.md Normal file
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@ -0,0 +1 @@
# langchain-exa

12
libs/partners/exa/langchain_exa/__init__.py Normal file
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@ -0,0 +1,12 @@
from exa_py.api import HighlightsContentsOptions, TextContentsOptions # type: ignore
from langchain_exa.retrievers import ExaSearchRetriever
from langchain_exa.tools import ExaFindSimilarResults, ExaSearchResults
__all__ = [
"ExaSearchResults",
"ExaSearchRetriever",
"HighlightsContentsOptions",
"TextContentsOptions",
"ExaFindSimilarResults",
]

18
libs/partners/exa/langchain_exa/_utilities.py Normal file
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@ -0,0 +1,18 @@
import os
from typing import Dict
from exa_py import Exa # type: ignore
from langchain_core.utils import convert_to_secret_str
def initialize_client(values: Dict) -> Dict:
"""Initialize the client."""
exa_api_key = values.get("exa_api_key") or os.environ.get("EXA_API_KEY") or ""
values["exa_api_key"] = convert_to_secret_str(exa_api_key)
args = {
"api_key": values["exa_api_key"].get_secret_value(),
}
if values.get("exa_base_url"):
args["base_url"] = values["exa_base_url"]
values["client"] = Exa(**args)
return values

0
libs/partners/exa/langchain_exa/py.typed Normal file
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91
libs/partners/exa/langchain_exa/retrievers.py Normal file
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@ -0,0 +1,91 @@
from typing import Any, Dict, List, Literal, Optional, Union
from exa_py import Exa # type: ignore
from exa_py.api import HighlightsContentsOptions, TextContentsOptions # type: ignore
from langchain_core.callbacks import CallbackManagerForRetrieverRun
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import SecretStr, root_validator
from langchain_core.retrievers import BaseRetriever
from langchain_exa._utilities import initialize_client
def _get_metadata(result: Any) -> Dict[str, Any]:
"""Get the metadata from a result object."""
metadata = {
"title": result.title,
"url": result.url,
"id": result.id,
"score": result.score,
"published_date": result.published_date,
"author": result.author,
}
if getattr(result, "highlights"):
metadata["highlights"] = result.highlights
if getattr(result, "highlight_scores"):
metadata["highlight_scores"] = result.highlight_scores
return metadata
class ExaSearchRetriever(BaseRetriever):
"""Exa Search retriever."""
k: int = 10 # num_results
"""The number of search results to return."""
include_domains: Optional[List[str]] = None
"""A list of domains to include in the search."""
exclude_domains: Optional[List[str]] = None
"""A list of domains to exclude from the search."""
start_crawl_date: Optional[str] = None
"""The start date for the crawl (in YYYY-MM-DD format)."""
end_crawl_date: Optional[str] = None
"""The end date for the crawl (in YYYY-MM-DD format)."""
start_published_date: Optional[str] = None
"""The start date for when the document was published (in YYYY-MM-DD format)."""
end_published_date: Optional[str] = None
"""The end date for when the document was published (in YYYY-MM-DD format)."""
use_autoprompt: Optional[bool] = None
"""Whether to use autoprompt for the search."""
type: str = "neural"
"""The type of search, 'keyword' or 'neural'. Default: neural"""
highlights: Optional[Union[HighlightsContentsOptions, bool]] = None
"""Whether to set the page content to the highlights of the results."""
text_contents_options: Union[TextContentsOptions, Literal[True]] = True
"""How to set the page content of the results"""
client: Exa
exa_api_key: SecretStr
exa_base_url: Optional[str] = None
@root_validator(pre=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate the environment."""
values = initialize_client(values)
return values
def _get_relevant_documents(
self, query: str, *, run_manager: CallbackManagerForRetrieverRun
) -> List[Document]:
response = self.client.search_and_contents(
query,
num_results=self.k,
text=self.text_contents_options,
highlights=self.highlights,
include_domains=self.include_domains,
exclude_domains=self.exclude_domains,
start_crawl_date=self.start_crawl_date,
end_crawl_date=self.end_crawl_date,
start_published_date=self.start_published_date,
end_published_date=self.end_published_date,
use_autoprompt=self.use_autoprompt,
)
results = response.results
return [
Document(
page_content=(result.text),
metadata=_get_metadata(result),
)
for result in results
]

120
libs/partners/exa/langchain_exa/tools.py Normal file
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@ -0,0 +1,120 @@
"""Tool for the Exa Search API."""
from typing import Dict, List, Optional, Union
from exa_py import Exa # type: ignore
from exa_py.api import HighlightsContentsOptions, TextContentsOptions # type: ignore
from langchain_core.callbacks import (
CallbackManagerForToolRun,
)
from langchain_core.pydantic_v1 import SecretStr, root_validator
from langchain_core.tools import BaseTool
from langchain_exa._utilities import initialize_client
class ExaSearchResults(BaseTool):
"""Tool that queries the Metaphor Search API and gets back json."""
name: str = "exa_search_results_json"
description: str = (
"A wrapper around Exa Search. "
"Input should be an Exa-optimized query. "
"Output is a JSON array of the query results"
)
client: Exa
exa_api_key: SecretStr
@root_validator(pre=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate the environment."""
values = initialize_client(values)
return values
def _run(
self,
query: str,
num_results: int,
text_contents_options: Optional[Union[TextContentsOptions, bool]] = None,
highlights: Optional[Union[HighlightsContentsOptions, bool]] = None,
include_domains: Optional[List[str]] = None,
exclude_domains: Optional[List[str]] = None,
start_crawl_date: Optional[str] = None,
end_crawl_date: Optional[str] = None,
start_published_date: Optional[str] = None,
end_published_date: Optional[str] = None,
use_autoprompt: Optional[bool] = None,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> Union[List[Dict], str]:
"""Use the tool."""
try:
return self.client.search_and_contents(
query,
num_results=num_results,
text=text_contents_options,
highlights=highlights,
include_domains=include_domains,
exclude_domains=exclude_domains,
start_crawl_date=start_crawl_date,
end_crawl_date=end_crawl_date,
start_published_date=start_published_date,
end_published_date=end_published_date,
use_autoprompt=use_autoprompt,
)
except Exception as e:
return repr(e)
class ExaFindSimilarResults(BaseTool):
"""Tool that queries the Metaphor Search API and gets back json."""
name: str = "exa_find_similar_results_json"
description: str = (
"A wrapper around Exa Find Similar. "
"Input should be an Exa-optimized query. "
"Output is a JSON array of the query results"
)
client: Exa
exa_api_key: SecretStr
exa_base_url: Optional[str] = None
@root_validator(pre=True)
def validate_environment(cls, values: Dict) -> Dict:
"""Validate the environment."""
values = initialize_client(values)
return values
def _run(
self,
url: str,
num_results: int,
text_contents_options: Optional[Union[TextContentsOptions, bool]] = None,
highlights: Optional[Union[HighlightsContentsOptions, bool]] = None,
include_domains: Optional[List[str]] = None,
exclude_domains: Optional[List[str]] = None,
start_crawl_date: Optional[str] = None,
end_crawl_date: Optional[str] = None,
start_published_date: Optional[str] = None,
end_published_date: Optional[str] = None,
exclude_source_domain: Optional[bool] = None,
category: Optional[str] = None,
run_manager: Optional[CallbackManagerForToolRun] = None,
) -> Union[List[Dict], str]:
"""Use the tool."""
try:
return self.client.find_similar_and_contents(
url,
num_results=num_results,
text=text_contents_options,
highlights=highlights,
include_domains=include_domains,
exclude_domains=exclude_domains,
start_crawl_date=start_crawl_date,
end_crawl_date=end_crawl_date,
start_published_date=start_published_date,
end_published_date=end_published_date,
exclude_source_domain=exclude_source_domain,
category=category,
)
except Exception as e:
return repr(e)

853
libs/partners/exa/poetry.lock generated Normal file
View File

@ -0,0 +1,853 @@
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
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watchmedo = ["PyYAML (>=3.10)"]
[metadata]
lock-version = "2.0"
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95
libs/partners/exa/pyproject.toml Normal file
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@ -0,0 +1,95 @@
[tool.poetry]
name = "langchain-exa"
version = "0.0.1"
description = "An integration package connecting Exa and LangChain"
authors = []
readme = "README.md"
repository = "https://github.com/langchain-ai/langchain"
license = "MIT"
[tool.poetry.urls]
"Source Code" = "https://github.com/langchain-ai/langchain/tree/master/libs/partners/exa"
[tool.poetry.dependencies]
python = ">=3.8.1,<4.0"
langchain-core = ">=0.0.12"
exa-py = "^1.0.7"
[tool.poetry.group.test]
optional = true
[tool.poetry.group.test.dependencies]
pytest = "^7.3.0"
freezegun = "^1.2.2"
pytest-mock = "^3.10.0"
syrupy = "^4.0.2"
pytest-watcher = "^0.3.4"
pytest-asyncio = "^0.21.1"
langchain-core = {path = "../../core", develop = true}
[tool.poetry.group.codespell]
optional = true
[tool.poetry.group.codespell.dependencies]
codespell = "^2.2.0"
[tool.poetry.group.lint]
optional = true
[tool.poetry.group.lint.dependencies]
ruff = "^0.1.5"
[tool.poetry.group.typing.dependencies]
mypy = "^0.991"
langchain-core = {path = "../../core", develop = true}
[tool.poetry.group.dev]
optional = true
[tool.poetry.group.dev.dependencies]
langchain-core = {path = "../../core", develop = true}
[tool.poetry.group.test_integration]
optional = true
[tool.poetry.group.test_integration.dependencies]
[tool.ruff]
select = [
"E", # pycodestyle
"F", # pyflakes
"I", # isort
]
[tool.mypy]
disallow_untyped_defs = "True"
[tool.coverage.run]
omit = [
"tests/*",
]
[build-system]
requires = ["poetry-core>=1.0.0"]
build-backend = "poetry.core.masonry.api"
[tool.pytest.ini_options]
# --strict-markers will raise errors on unknown marks.
# https://docs.pytest.org/en/7.1.x/how-to/mark.html#raising-errors-on-unknown-marks
#
# https://docs.pytest.org/en/7.1.x/reference/reference.html
# --strict-config any warnings encountered while parsing the `pytest`
# section of the configuration file raise errors.
#
# https://github.com/tophat/syrupy
# --snapshot-warn-unused Prints a warning on unused snapshots rather than fail the test suite.
addopts = "--snapshot-warn-unused --strict-markers --strict-config --durations=5"
# Registering custom markers.
# https://docs.pytest.org/en/7.1.x/example/markers.html#registering-markers
markers = [
"requires: mark tests as requiring a specific library",
"asyncio: mark tests as requiring asyncio",
"compile: mark placeholder test used to compile integration tests without running them",
]
asyncio_mode = "auto"

17
libs/partners/exa/scripts/check_imports.py Normal file
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@ -0,0 +1,17 @@
import sys
import traceback
from importlib.machinery import SourceFileLoader
if __name__ == "__main__":
files = sys.argv[1:]
has_failure = False
for file in files:
try:
SourceFileLoader("x", file).load_module()
except Exception:
has_faillure = True
print(file)
traceback.print_exc()
print()
sys.exit(1 if has_failure else 0)

27
libs/partners/exa/scripts/check_pydantic.sh Executable file
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@ -0,0 +1,27 @@
#!/bin/bash
#
# This script searches for lines starting with "import pydantic" or "from pydantic"
# in tracked files within a Git repository.
#
# Usage: ./scripts/check_pydantic.sh /path/to/repository
# Check if a path argument is provided
if [ $# -ne 1 ]; then
echo "Usage: $0 /path/to/repository"
exit 1
fi
repository_path="$1"
# Search for lines matching the pattern within the specified repository
result=$(git -C "$repository_path" grep -E '^import pydantic|^from pydantic')
# Check if any matching lines were found
if [ -n "$result" ]; then
echo "ERROR: The following lines need to be updated:"
echo "$result"
echo "Please replace the code with an import from langchain_core.pydantic_v1."
echo "For example, replace 'from pydantic import BaseModel'"
echo "with 'from langchain_core.pydantic_v1 import BaseModel'"
exit 1
fi

17
libs/partners/exa/scripts/lint_imports.sh Executable file
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@ -0,0 +1,17 @@
#!/bin/bash
set -eu
# Initialize a variable to keep track of errors
errors=0
# make sure not importing from langchain or langchain_experimental
git --no-pager grep '^from langchain\.' . && errors=$((errors+1))
git --no-pager grep '^from langchain_experimental\.' . && errors=$((errors+1))
# Decide on an exit status based on the errors
if [ "$errors" -gt 0 ]; then
exit 1
else
exit 0
fi

0
libs/partners/exa/tests/__init__.py Normal file
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0
libs/partners/exa/tests/integration_tests/__init__.py Normal file
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7
libs/partners/exa/tests/integration_tests/test_compile.py Normal file
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@ -0,0 +1,7 @@
import pytest
@pytest.mark.compile
def test_placeholder() -> None:
"""Used for compiling integration tests without running any real tests."""
pass

13
libs/partners/exa/tests/integration_tests/test_find_similar_tool.py Normal file
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@ -0,0 +1,13 @@
from langchain_exa import ExaFindSimilarResults
def test_similarity_tool() -> None:
tool = ExaFindSimilarResults()
res = tool.invoke(
{
"url": "https://boutiquejapan.com/when-is-the-best-time-of-year-to-visit-japan/",
"num_results": 5,
}
)
print(res)
assert not isinstance(res, str) # str means error for this tool

26
libs/partners/exa/tests/integration_tests/test_retriever.py Normal file
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@ -0,0 +1,26 @@
from langchain_core.documents import Document
from langchain_exa import ExaSearchRetriever
def test_exa_retriever() -> None:
retriever = ExaSearchRetriever()
res = retriever.invoke("best time to visit japan")
print(res)
assert len(res) == 10 # default k
assert isinstance(res, list)
assert isinstance(res[0], Document)
def test_exa_retriever_highlights() -> None:
retriever = ExaSearchRetriever(highlights=True)
res = retriever.invoke("best time to visit japan")
print(res)
assert isinstance(res, list)
assert isinstance(res[0], Document)
highlights = res[0].metadata["highlights"]
highlight_scores = res[0].metadata["highlight_scores"]
assert isinstance(highlights, list)
assert isinstance(highlight_scores, list)
assert isinstance(highlights[0], str)
assert isinstance(highlight_scores[0], float)

8
libs/partners/exa/tests/integration_tests/test_search_tool.py Normal file
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@ -0,0 +1,8 @@
from langchain_exa import ExaSearchResults
def test_search_tool() -> None:
tool = ExaSearchResults()
res = tool.invoke({"query": "best time to visit japan", "num_results": 5})
print(res)
assert not isinstance(res, str) # str means error for this tool\

0
libs/partners/exa/tests/unit_tests/__init__.py Normal file
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13
libs/partners/exa/tests/unit_tests/test_imports.py Normal file
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@ -0,0 +1,13 @@
from langchain_exa import __all__
EXPECTED_ALL = [
"ExaSearchResults",
"ExaSearchRetriever",
"HighlightsContentsOptions",
"TextContentsOptions",
"ExaFindSimilarResults",
]
def test_all_imports() -> None:
assert sorted(EXPECTED_ALL) == sorted(__all__)