mirror of
https://github.com/hwchase17/langchain.git
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init
This commit is contained in:
Erick Friis
1
libs/partners/nomic/.gitignore
vendored
Normal file
1
libs/partners/nomic/.gitignore
vendored
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@@ -0,0 +1 @@
|
||||
__pycache__
|
||||
21
libs/partners/nomic/LICENSE
Normal file
21
libs/partners/nomic/LICENSE
Normal file
@@ -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/nomic/Makefile
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61
libs/partners/nomic/Makefile
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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/nomic --name-only --diff-filter=d master | grep -E '\.py$$|\.ipynb$$')
|
||||
lint_package: PYTHON_FILES=langchain_nomic
|
||||
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_nomic -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'
|
||||
45
libs/partners/nomic/README.md
Normal file
45
libs/partners/nomic/README.md
Normal file
@@ -0,0 +1,45 @@
|
||||
# langchain-nomic
|
||||
|
||||
This package contains the LangChain integration with Nomic
|
||||
|
||||
## Installation
|
||||
|
||||
```bash
|
||||
pip install -U langchain-nomic
|
||||
```
|
||||
|
||||
And you should configure credentials by setting the following environment variables:
|
||||
|
||||
* TODO: fill this out
|
||||
|
||||
## Chat Models
|
||||
|
||||
`ChatNomic` class exposes chat models from Nomic.
|
||||
|
||||
```python
|
||||
from langchain_nomic import ChatNomic
|
||||
|
||||
llm = ChatNomic()
|
||||
llm.invoke("Sing a ballad of LangChain.")
|
||||
```
|
||||
|
||||
## Embeddings
|
||||
|
||||
`NomicEmbeddings` class exposes embeddings from Nomic.
|
||||
|
||||
```python
|
||||
from langchain_nomic import NomicEmbeddings
|
||||
|
||||
embeddings = NomicEmbeddings()
|
||||
embeddings.embed_query("What is the meaning of life?")
|
||||
```
|
||||
|
||||
## LLMs
|
||||
`NomicLLM` class exposes LLMs from Nomic.
|
||||
|
||||
```python
|
||||
from langchain_nomic import NomicLLM
|
||||
|
||||
llm = NomicLLM()
|
||||
llm.invoke("The meaning of life is")
|
||||
```
|
||||
97
libs/partners/nomic/docs/chat.ipynb
Normal file
97
libs/partners/nomic/docs/chat.ipynb
Normal file
@@ -0,0 +1,97 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "raw",
|
||||
"id": "afaf8039",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"---\n",
|
||||
"sidebar_label: Nomic\n",
|
||||
"---"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "e49f1e0d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# ChatNomic\n",
|
||||
"\n",
|
||||
"This notebook covers how to get started with Nomic chat models.\n",
|
||||
"\n",
|
||||
"## Installation"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "4c3bef91",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# install package\n",
|
||||
"!pip install -U langchain-nomic"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2b4f3e15",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Environment Setup\n",
|
||||
"\n",
|
||||
"Make sure to set the following environment variables:\n",
|
||||
"\n",
|
||||
"- TODO: fill out relevant environment variables or secrets\n",
|
||||
"\n",
|
||||
"## Usage"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "62e0dbc3",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_nomic.chat_models import ChatNomic\n",
|
||||
"from langchain_core.prompts import ChatPromptTemplate\n",
|
||||
"\n",
|
||||
"chat = ChatNomic()\n",
|
||||
"\n",
|
||||
"prompt = ChatPromptTemplate.from_messages(\n",
|
||||
" [\n",
|
||||
" (\"system\", \"You are a helpful assistant that translates English to French.\"),\n",
|
||||
" (\"human\", \"Translate this sentence from English to French. {english_text}.\"),\n",
|
||||
" ]\n",
|
||||
")\n",
|
||||
"\n",
|
||||
"chain = prompt | chat\n",
|
||||
"chain.invoke({\"english_text\": \"Hello, how are you?\"})"
|
||||
]
|
||||
}
|
||||
],
|
||||
"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": "3.10.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
102
libs/partners/nomic/docs/llms.ipynb
Normal file
102
libs/partners/nomic/docs/llms.ipynb
Normal file
@@ -0,0 +1,102 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "raw",
|
||||
"id": "67db2992",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"---\n",
|
||||
"sidebar_label: Nomic\n",
|
||||
"---"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "9597802c",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# NomicLLM\n",
|
||||
"\n",
|
||||
"This example goes over how to use LangChain to interact with `Nomic` models.\n",
|
||||
"\n",
|
||||
"## Installation"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "59c710c4",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# install package\n",
|
||||
"!pip install -U langchain-nomic"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "0ee90032",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Environment Setup\n",
|
||||
"\n",
|
||||
"Make sure to set the following environment variables:\n",
|
||||
"\n",
|
||||
"- TODO: fill out relevant environment variables or secrets\n",
|
||||
"\n",
|
||||
"## Usage"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 4,
|
||||
"id": "035dea0f",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_core.prompts import PromptTemplate\n",
|
||||
"from langchain_nomic.llms import NomicLLM\n",
|
||||
"\n",
|
||||
"template = \"\"\"Question: {question}\n",
|
||||
"\n",
|
||||
"Answer: Let's think step by step.\"\"\"\n",
|
||||
"\n",
|
||||
"prompt = PromptTemplate.from_string(template)\n",
|
||||
"\n",
|
||||
"model = NomicLLM()\n",
|
||||
"\n",
|
||||
"chain = prompt | model\n",
|
||||
"\n",
|
||||
"chain.invoke({\"question\": \"What is LangChain?\"})"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"kernelspec": {
|
||||
"display_name": "Python 3.11.1 64-bit",
|
||||
"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": "3.9.7"
|
||||
},
|
||||
"vscode": {
|
||||
"interpreter": {
|
||||
"hash": "e971737741ff4ec9aff7dc6155a1060a59a8a6d52c757dbbe66bf8ee389494b1"
|
||||
}
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
50
libs/partners/nomic/docs/provider.ipynb
Normal file
50
libs/partners/nomic/docs/provider.ipynb
Normal file
@@ -0,0 +1,50 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# Nomic\n",
|
||||
"\n",
|
||||
"Nomic is a platform that offers..."
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": 2,
|
||||
"metadata": {
|
||||
"id": "y8ku6X96sebl"
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_nomic.chat_models import NomicChat\n",
|
||||
"from langchain_nomic.llms import NomicLLM\n",
|
||||
"from langchain_nomic.vectorstores import NomicVectorStore"
|
||||
]
|
||||
}
|
||||
],
|
||||
"metadata": {
|
||||
"colab": {
|
||||
"provenance": []
|
||||
},
|
||||
"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": "3.10.11"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 1
|
||||
}
|
||||
132
libs/partners/nomic/docs/text_embedding.ipynb
Normal file
132
libs/partners/nomic/docs/text_embedding.ipynb
Normal file
@@ -0,0 +1,132 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "raw",
|
||||
"id": "afaf8039",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"---\n",
|
||||
"sidebar_label: Nomic\n",
|
||||
"---"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "e49f1e0d",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# NomicEmbeddings\n",
|
||||
"\n",
|
||||
"This notebook covers how to get started with Nomic embedding models.\n",
|
||||
"\n",
|
||||
"## Installation"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "4c3bef91",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# install package\n",
|
||||
"!pip install -U langchain-nomic"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "2b4f3e15",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Environment Setup\n",
|
||||
"\n",
|
||||
"Make sure to set the following environment variables:\n",
|
||||
"\n",
|
||||
"- TODO: fill out relevant environment variables or secrets\n",
|
||||
"\n",
|
||||
"## Usage"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "62e0dbc3",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_nomic.embeddings import NomicEmbeddings\n",
|
||||
"\n",
|
||||
"embeddings = NomicEmbeddings()"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "12fcfb4b",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"embeddings.embed_query(\"My query to look up\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "1f2e6104",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"embeddings.embed_documents(\n",
|
||||
" [\"This is a content of the document\", \"This is another document\"]\n",
|
||||
")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "46739f68",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# async embed query\n",
|
||||
"await embeddings.aembed_query(\"My query to look up\")"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "e48632ea",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# async embed documents\n",
|
||||
"await embeddings.aembed_documents(\n",
|
||||
" [\"This is a content of the document\", \"This is another document\"]\n",
|
||||
")"
|
||||
]
|
||||
}
|
||||
],
|
||||
"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": "3.10.5"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
87
libs/partners/nomic/docs/vectorstores.ipynb
Normal file
87
libs/partners/nomic/docs/vectorstores.ipynb
Normal file
@@ -0,0 +1,87 @@
|
||||
{
|
||||
"cells": [
|
||||
{
|
||||
"cell_type": "raw",
|
||||
"id": "1957f5cb",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"---\n",
|
||||
"sidebar_label: Nomic\n",
|
||||
"---"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "ef1f0986",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"# NomicVectorStore\n",
|
||||
"\n",
|
||||
"This notebook covers how to get started with the Nomic vector store.\n",
|
||||
"\n",
|
||||
"## Installation"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "d97b55c2",
|
||||
"metadata": {},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"# install package\n",
|
||||
"!pip install -U langchain-nomic"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "markdown",
|
||||
"id": "36fdc060",
|
||||
"metadata": {},
|
||||
"source": [
|
||||
"## Environment Setup\n",
|
||||
"\n",
|
||||
"Make sure to set the following environment variables:\n",
|
||||
"\n",
|
||||
"- TODO: fill out relevant environment variables or secrets\n",
|
||||
"- Op\n",
|
||||
"\n",
|
||||
"## Usage"
|
||||
]
|
||||
},
|
||||
{
|
||||
"cell_type": "code",
|
||||
"execution_count": null,
|
||||
"id": "dc37144c-208d-4ab3-9f3a-0407a69fe052",
|
||||
"metadata": {
|
||||
"tags": []
|
||||
},
|
||||
"outputs": [],
|
||||
"source": [
|
||||
"from langchain_nomic.vectorstores import NomicVectorStore\n",
|
||||
"\n",
|
||||
"# TODO: switch for preferred way to init and use your vector store\n"
|
||||
]
|
||||
}
|
||||
],
|
||||
"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": "3.10.12"
|
||||
}
|
||||
},
|
||||
"nbformat": 4,
|
||||
"nbformat_minor": 5
|
||||
}
|
||||
11
libs/partners/nomic/langchain_nomic/__init__.py
Normal file
11
libs/partners/nomic/langchain_nomic/__init__.py
Normal file
@@ -0,0 +1,11 @@
|
||||
from langchain_nomic.chat_models import ChatNomic
|
||||
from langchain_nomic.embeddings import NomicEmbeddings
|
||||
from langchain_nomic.llms import NomicLLM
|
||||
from langchain_nomic.vectorstores import NomicVectorStore
|
||||
|
||||
__all__ = [
|
||||
"NomicLLM",
|
||||
"ChatNomic",
|
||||
"NomicVectorStore",
|
||||
"NomicEmbeddings",
|
||||
]
|
||||
68
libs/partners/nomic/langchain_nomic/chat_models.py
Normal file
68
libs/partners/nomic/langchain_nomic/chat_models.py
Normal file
@@ -0,0 +1,68 @@
|
||||
from typing import Any, AsyncIterator, Iterator, List, Optional
|
||||
|
||||
from langchain_core.callbacks import (
|
||||
AsyncCallbackManagerForLLMRun,
|
||||
CallbackManagerForLLMRun,
|
||||
)
|
||||
from langchain_core.language_models.chat_models import BaseChatModel
|
||||
from langchain_core.messages import BaseMessage, BaseMessageChunk
|
||||
from langchain_core.outputs import ChatGenerationChunk, ChatResult
|
||||
|
||||
|
||||
class ChatNomic(BaseChatModel):
|
||||
"""ChatNomic chat model.
|
||||
|
||||
Example:
|
||||
.. code-block:: python
|
||||
|
||||
from langchain_nomic import ChatNomic
|
||||
|
||||
|
||||
model = ChatNomic()
|
||||
"""
|
||||
|
||||
@property
|
||||
def _llm_type(self) -> str:
|
||||
"""Return type of chat model."""
|
||||
return "chat-nomic"
|
||||
|
||||
def _stream(
|
||||
self,
|
||||
messages: List[BaseMessage],
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[CallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> Iterator[ChatGenerationChunk]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def _astream(
|
||||
self,
|
||||
messages: List[BaseMessage],
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> AsyncIterator[ChatGenerationChunk]:
|
||||
yield ChatGenerationChunk(
|
||||
message=BaseMessageChunk(content="Yield chunks", type="ai"),
|
||||
)
|
||||
yield ChatGenerationChunk(
|
||||
message=BaseMessageChunk(content=" like this!", type="ai"),
|
||||
)
|
||||
|
||||
def _generate(
|
||||
self,
|
||||
messages: List[BaseMessage],
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[CallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> ChatResult:
|
||||
raise NotImplementedError
|
||||
|
||||
async def _agenerate(
|
||||
self,
|
||||
messages: List[BaseMessage],
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> ChatResult:
|
||||
raise NotImplementedError
|
||||
34
libs/partners/nomic/langchain_nomic/embeddings.py
Normal file
34
libs/partners/nomic/langchain_nomic/embeddings.py
Normal file
@@ -0,0 +1,34 @@
|
||||
from typing import List
|
||||
|
||||
from langchain_core.embeddings import Embeddings
|
||||
|
||||
|
||||
class NomicEmbeddings(Embeddings):
|
||||
"""NomicEmbeddings embedding model.
|
||||
|
||||
Example:
|
||||
.. code-block:: python
|
||||
|
||||
from langchain_nomic import NomicEmbeddings
|
||||
|
||||
model = NomicEmbeddings()
|
||||
"""
|
||||
|
||||
def embed_documents(self, texts: List[str]) -> List[List[float]]:
|
||||
"""Embed search docs."""
|
||||
raise NotImplementedError
|
||||
|
||||
def embed_query(self, text: str) -> List[float]:
|
||||
"""Embed query text."""
|
||||
raise NotImplementedError
|
||||
|
||||
# only keep aembed_documents and aembed_query if they're implemented!
|
||||
# delete them otherwise to use the base class' default
|
||||
# implementation, which calls the sync version in an executor
|
||||
async def aembed_documents(self, texts: List[str]) -> List[List[float]]:
|
||||
"""Asynchronous Embed search docs."""
|
||||
raise NotImplementedError
|
||||
|
||||
async def aembed_query(self, text: str) -> List[float]:
|
||||
"""Asynchronous Embed query text."""
|
||||
raise NotImplementedError
|
||||
73
libs/partners/nomic/langchain_nomic/llms.py
Normal file
73
libs/partners/nomic/langchain_nomic/llms.py
Normal file
@@ -0,0 +1,73 @@
|
||||
import asyncio
|
||||
from functools import partial
|
||||
from typing import (
|
||||
Any,
|
||||
AsyncIterator,
|
||||
Iterator,
|
||||
List,
|
||||
Optional,
|
||||
)
|
||||
|
||||
from langchain_core.callbacks import (
|
||||
AsyncCallbackManagerForLLMRun,
|
||||
CallbackManagerForLLMRun,
|
||||
)
|
||||
from langchain_core.language_models import BaseLLM
|
||||
from langchain_core.outputs import GenerationChunk, LLMResult
|
||||
|
||||
|
||||
class NomicLLM(BaseLLM):
|
||||
"""NomicLLM large language models.
|
||||
|
||||
Example:
|
||||
.. code-block:: python
|
||||
|
||||
from langchain_nomic import NomicLLM
|
||||
|
||||
model = NomicLLM()
|
||||
"""
|
||||
|
||||
@property
|
||||
def _llm_type(self) -> str:
|
||||
"""Return type of LLM."""
|
||||
return "nomic-llm"
|
||||
|
||||
def _generate(
|
||||
self,
|
||||
prompts: List[str],
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[CallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> LLMResult:
|
||||
raise NotImplementedError
|
||||
|
||||
async def _agenerate(
|
||||
self,
|
||||
prompts: List[str],
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> LLMResult:
|
||||
# Change implementation if integration natively supports async generation.
|
||||
return await asyncio.get_running_loop().run_in_executor(
|
||||
None, partial(self._generate, **kwargs), prompts, stop, run_manager
|
||||
)
|
||||
|
||||
def _stream(
|
||||
self,
|
||||
prompt: str,
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[CallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> Iterator[GenerationChunk]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def _astream(
|
||||
self,
|
||||
prompt: str,
|
||||
stop: Optional[List[str]] = None,
|
||||
run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
|
||||
**kwargs: Any,
|
||||
) -> AsyncIterator[GenerationChunk]:
|
||||
yield GenerationChunk(text="Yield chunks")
|
||||
yield GenerationChunk(text=" like this!")
|
||||
0
libs/partners/nomic/langchain_nomic/py.typed
Normal file
0
libs/partners/nomic/langchain_nomic/py.typed
Normal file
179
libs/partners/nomic/langchain_nomic/vectorstores.py
Normal file
179
libs/partners/nomic/langchain_nomic/vectorstores.py
Normal file
@@ -0,0 +1,179 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import asyncio
|
||||
from functools import partial
|
||||
from typing import (
|
||||
TYPE_CHECKING,
|
||||
Any,
|
||||
Callable,
|
||||
Iterable,
|
||||
List,
|
||||
Optional,
|
||||
Tuple,
|
||||
Type,
|
||||
TypeVar,
|
||||
)
|
||||
|
||||
from langchain_core.embeddings import Embeddings
|
||||
from langchain_core.vectorstores import VectorStore
|
||||
|
||||
if TYPE_CHECKING:
|
||||
from langchain_core.documents import Document
|
||||
|
||||
VST = TypeVar("VST", bound=VectorStore)
|
||||
|
||||
|
||||
class NomicVectorStore(VectorStore):
|
||||
"""Interface for vector store.
|
||||
|
||||
Example:
|
||||
.. code-block:: python
|
||||
|
||||
from langchain_nomic.vectorstores import NomicVectorStore
|
||||
|
||||
vectorstore = NomicVectorStore()
|
||||
"""
|
||||
|
||||
def add_texts(
|
||||
self,
|
||||
texts: Iterable[str],
|
||||
metadatas: Optional[List[dict]] = None,
|
||||
**kwargs: Any,
|
||||
) -> List[str]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def aadd_texts(
|
||||
self,
|
||||
texts: Iterable[str],
|
||||
metadatas: Optional[List[dict]] = None,
|
||||
**kwargs: Any,
|
||||
) -> List[str]:
|
||||
return await asyncio.get_running_loop().run_in_executor(
|
||||
None, partial(self.add_texts, **kwargs), texts, metadatas
|
||||
)
|
||||
|
||||
def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> Optional[bool]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def adelete(
|
||||
self, ids: Optional[List[str]] = None, **kwargs: Any
|
||||
) -> Optional[bool]:
|
||||
raise NotImplementedError
|
||||
|
||||
def similarity_search(
|
||||
self, query: str, k: int = 4, **kwargs: Any
|
||||
) -> List[Document]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def asimilarity_search(
|
||||
self, query: str, k: int = 4, **kwargs: Any
|
||||
) -> List[Document]:
|
||||
# This is a temporary workaround to make the similarity search
|
||||
# asynchronous. The proper solution is to make the similarity search
|
||||
# asynchronous in the vector store implementations.
|
||||
func = partial(self.similarity_search, query, k=k, **kwargs)
|
||||
return await asyncio.get_event_loop().run_in_executor(None, func)
|
||||
|
||||
def similarity_search_with_score(
|
||||
self, *args: Any, **kwargs: Any
|
||||
) -> List[Tuple[Document, float]]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def asimilarity_search_with_score(
|
||||
self, *args: Any, **kwargs: Any
|
||||
) -> List[Tuple[Document, float]]:
|
||||
# This is a temporary workaround to make the similarity search
|
||||
# asynchronous. The proper solution is to make the similarity search
|
||||
# asynchronous in the vector store implementations.
|
||||
func = partial(self.similarity_search_with_score, *args, **kwargs)
|
||||
return await asyncio.get_event_loop().run_in_executor(None, func)
|
||||
|
||||
def similarity_search_by_vector(
|
||||
self, embedding: List[float], k: int = 4, **kwargs: Any
|
||||
) -> List[Document]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def asimilarity_search_by_vector(
|
||||
self, embedding: List[float], k: int = 4, **kwargs: Any
|
||||
) -> List[Document]:
|
||||
# This is a temporary workaround to make the similarity search
|
||||
# asynchronous. The proper solution is to make the similarity search
|
||||
# asynchronous in the vector store implementations.
|
||||
func = partial(self.similarity_search_by_vector, embedding, k=k, **kwargs)
|
||||
return await asyncio.get_event_loop().run_in_executor(None, func)
|
||||
|
||||
def max_marginal_relevance_search(
|
||||
self,
|
||||
query: str,
|
||||
k: int = 4,
|
||||
fetch_k: int = 20,
|
||||
lambda_mult: float = 0.5,
|
||||
**kwargs: Any,
|
||||
) -> List[Document]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def amax_marginal_relevance_search(
|
||||
self,
|
||||
query: str,
|
||||
k: int = 4,
|
||||
fetch_k: int = 20,
|
||||
lambda_mult: float = 0.5,
|
||||
**kwargs: Any,
|
||||
) -> List[Document]:
|
||||
# This is a temporary workaround to make the similarity search
|
||||
# asynchronous. The proper solution is to make the similarity search
|
||||
# asynchronous in the vector store implementations.
|
||||
func = partial(
|
||||
self.max_marginal_relevance_search,
|
||||
query,
|
||||
k=k,
|
||||
fetch_k=fetch_k,
|
||||
lambda_mult=lambda_mult,
|
||||
**kwargs,
|
||||
)
|
||||
return await asyncio.get_event_loop().run_in_executor(None, func)
|
||||
|
||||
def max_marginal_relevance_search_by_vector(
|
||||
self,
|
||||
embedding: List[float],
|
||||
k: int = 4,
|
||||
fetch_k: int = 20,
|
||||
lambda_mult: float = 0.5,
|
||||
**kwargs: Any,
|
||||
) -> List[Document]:
|
||||
raise NotImplementedError
|
||||
|
||||
async def amax_marginal_relevance_search_by_vector(
|
||||
self,
|
||||
embedding: List[float],
|
||||
k: int = 4,
|
||||
fetch_k: int = 20,
|
||||
lambda_mult: float = 0.5,
|
||||
**kwargs: Any,
|
||||
) -> List[Document]:
|
||||
raise NotImplementedError
|
||||
|
||||
@classmethod
|
||||
def from_texts(
|
||||
cls: Type[VST],
|
||||
texts: List[str],
|
||||
embedding: Embeddings,
|
||||
metadatas: Optional[List[dict]] = None,
|
||||
**kwargs: Any,
|
||||
) -> VST:
|
||||
raise NotImplementedError
|
||||
|
||||
@classmethod
|
||||
async def afrom_texts(
|
||||
cls: Type[VST],
|
||||
texts: List[str],
|
||||
embedding: Embeddings,
|
||||
metadatas: Optional[List[dict]] = None,
|
||||
**kwargs: Any,
|
||||
) -> VST:
|
||||
return await asyncio.get_running_loop().run_in_executor(
|
||||
None, partial(cls.from_texts, **kwargs), texts, embedding, metadatas
|
||||
)
|
||||
|
||||
def _select_relevance_score_fn(self) -> Callable[[float], float]:
|
||||
raise NotImplementedError
|
||||
828
libs/partners/nomic/poetry.lock
generated
Normal file
828
libs/partners/nomic/poetry.lock
generated
Normal file
@@ -0,0 +1,828 @@
|
||||
# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
|
||||
|
||||
[[package]]
|
||||
name = "annotated-types"
|
||||
version = "0.6.0"
|
||||
description = "Reusable constraint types to use with typing.Annotated"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "annotated_types-0.6.0-py3-none-any.whl", hash = "sha256:0641064de18ba7a25dee8f96403ebc39113d0cb953a01429249d5c7564666a43"},
|
||||
{file = "annotated_types-0.6.0.tar.gz", hash = "sha256:563339e807e53ffd9c267e99fc6d9ea23eb8443c08f112651963e24e22f84a5d"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.9\""}
|
||||
|
||||
[[package]]
|
||||
name = "anyio"
|
||||
version = "4.2.0"
|
||||
description = "High level compatibility layer for multiple asynchronous event loop implementations"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "anyio-4.2.0-py3-none-any.whl", hash = "sha256:745843b39e829e108e518c489b31dc757de7d2131d53fac32bd8df268227bfee"},
|
||||
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||||
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|
||||
idna = ">=2.8"
|
||||
sniffio = ">=1.1"
|
||||
typing-extensions = {version = ">=4.1", markers = "python_version < \"3.11\""}
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||||
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[package.extras]
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||||
doc = ["Sphinx (>=7)", "packaging", "sphinx-autodoc-typehints (>=1.2.0)", "sphinx-rtd-theme"]
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||||
trio = ["trio (>=0.23)"]
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||||
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||||
[[package]]
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||||
name = "certifi"
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||||
version = "2023.11.17"
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||||
description = "Python package for providing Mozilla's CA Bundle."
|
||||
optional = false
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[[package]]
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||||
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||||
version = "3.3.2"
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||||
description = "The Real First Universal Charset Detector. Open, modern and actively maintained alternative to Chardet."
|
||||
optional = false
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||||
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{file = "PyYAML-6.0.1-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:bc1bf2925a1ecd43da378f4db9e4f799775d6367bdb94671027b73b393a7c42c"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-win32.whl", hash = "sha256:faca3bdcf85b2fc05d06ff3fbc1f83e1391b3e724afa3feba7d13eeab355484c"},
|
||||
{file = "PyYAML-6.0.1-cp39-cp39-win_amd64.whl", hash = "sha256:510c9deebc5c0225e8c96813043e62b680ba2f9c50a08d3724c7f28a747d1486"},
|
||||
{file = "PyYAML-6.0.1.tar.gz", hash = "sha256:bfdf460b1736c775f2ba9f6a92bca30bc2095067b8a9d77876d1fad6cc3b4a43"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "requests"
|
||||
version = "2.31.0"
|
||||
description = "Python HTTP for Humans."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "requests-2.31.0-py3-none-any.whl", hash = "sha256:58cd2187c01e70e6e26505bca751777aa9f2ee0b7f4300988b709f44e013003f"},
|
||||
{file = "requests-2.31.0.tar.gz", hash = "sha256:942c5a758f98d790eaed1a29cb6eefc7ffb0d1cf7af05c3d2791656dbd6ad1e1"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
certifi = ">=2017.4.17"
|
||||
charset-normalizer = ">=2,<4"
|
||||
idna = ">=2.5,<4"
|
||||
urllib3 = ">=1.21.1,<3"
|
||||
|
||||
[package.extras]
|
||||
socks = ["PySocks (>=1.5.6,!=1.5.7)"]
|
||||
use-chardet-on-py3 = ["chardet (>=3.0.2,<6)"]
|
||||
|
||||
[[package]]
|
||||
name = "ruff"
|
||||
version = "0.1.14"
|
||||
description = "An extremely fast Python linter and code formatter, written in Rust."
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "ruff-0.1.14-py3-none-macosx_10_12_x86_64.macosx_11_0_arm64.macosx_10_12_universal2.whl", hash = "sha256:96f76536df9b26622755c12ed8680f159817be2f725c17ed9305b472a757cdbb"},
|
||||
{file = "ruff-0.1.14-py3-none-macosx_10_12_x86_64.whl", hash = "sha256:ab3f71f64498c7241123bb5a768544cf42821d2a537f894b22457a543d3ca7a9"},
|
||||
{file = "ruff-0.1.14-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:7060156ecc572b8f984fd20fd8b0fcb692dd5d837b7606e968334ab7ff0090ab"},
|
||||
{file = "ruff-0.1.14-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:a53d8e35313d7b67eb3db15a66c08434809107659226a90dcd7acb2afa55faea"},
|
||||
{file = "ruff-0.1.14-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:bea9be712b8f5b4ebed40e1949379cfb2a7d907f42921cf9ab3aae07e6fba9eb"},
|
||||
{file = "ruff-0.1.14-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:2270504d629a0b064247983cbc495bed277f372fb9eaba41e5cf51f7ba705a6a"},
|
||||
{file = "ruff-0.1.14-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:80258bb3b8909b1700610dfabef7876423eed1bc930fe177c71c414921898efa"},
|
||||
{file = "ruff-0.1.14-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:653230dd00aaf449eb5ff25d10a6e03bc3006813e2cb99799e568f55482e5cae"},
|
||||
{file = "ruff-0.1.14-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:87b3acc6c4e6928459ba9eb7459dd4f0c4bf266a053c863d72a44c33246bfdbf"},
|
||||
{file = "ruff-0.1.14-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:6b3dadc9522d0eccc060699a9816e8127b27addbb4697fc0c08611e4e6aeb8b5"},
|
||||
{file = "ruff-0.1.14-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:1c8eca1a47b4150dc0fbec7fe68fc91c695aed798532a18dbb1424e61e9b721f"},
|
||||
{file = "ruff-0.1.14-py3-none-musllinux_1_2_i686.whl", hash = "sha256:62ce2ae46303ee896fc6811f63d6dabf8d9c389da0f3e3f2bce8bc7f15ef5488"},
|
||||
{file = "ruff-0.1.14-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:b2027dde79d217b211d725fc833e8965dc90a16d0d3213f1298f97465956661b"},
|
||||
{file = "ruff-0.1.14-py3-none-win32.whl", hash = "sha256:722bafc299145575a63bbd6b5069cb643eaa62546a5b6398f82b3e4403329cab"},
|
||||
{file = "ruff-0.1.14-py3-none-win_amd64.whl", hash = "sha256:e3d241aa61f92b0805a7082bd89a9990826448e4d0398f0e2bc8f05c75c63d99"},
|
||||
{file = "ruff-0.1.14-py3-none-win_arm64.whl", hash = "sha256:269302b31ade4cde6cf6f9dd58ea593773a37ed3f7b97e793c8594b262466b67"},
|
||||
{file = "ruff-0.1.14.tar.gz", hash = "sha256:ad3f8088b2dfd884820289a06ab718cde7d38b94972212cc4ba90d5fbc9955f3"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "six"
|
||||
version = "1.16.0"
|
||||
description = "Python 2 and 3 compatibility utilities"
|
||||
optional = false
|
||||
python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*"
|
||||
files = [
|
||||
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
|
||||
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "sniffio"
|
||||
version = "1.3.0"
|
||||
description = "Sniff out which async library your code is running under"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "sniffio-1.3.0-py3-none-any.whl", hash = "sha256:eecefdce1e5bbfb7ad2eeaabf7c1eeb404d7757c379bd1f7e5cce9d8bf425384"},
|
||||
{file = "sniffio-1.3.0.tar.gz", hash = "sha256:e60305c5e5d314f5389259b7f22aaa33d8f7dee49763119234af3755c55b9101"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "syrupy"
|
||||
version = "4.6.0"
|
||||
description = "Pytest Snapshot Test Utility"
|
||||
optional = false
|
||||
python-versions = ">=3.8.1,<4"
|
||||
files = [
|
||||
{file = "syrupy-4.6.0-py3-none-any.whl", hash = "sha256:747aae1bcf3cb3249e33b1e6d81097874d23615982d5686ebe637875b0775a1b"},
|
||||
{file = "syrupy-4.6.0.tar.gz", hash = "sha256:231b1f5d00f1f85048ba81676c79448076189c4aef4d33f21ae32f3b4c565a54"},
|
||||
]
|
||||
|
||||
[package.dependencies]
|
||||
pytest = ">=7.0.0,<8.0.0"
|
||||
|
||||
[[package]]
|
||||
name = "tenacity"
|
||||
version = "8.2.3"
|
||||
description = "Retry code until it succeeds"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "tenacity-8.2.3-py3-none-any.whl", hash = "sha256:ce510e327a630c9e1beaf17d42e6ffacc88185044ad85cf74c0a8887c6a0f88c"},
|
||||
{file = "tenacity-8.2.3.tar.gz", hash = "sha256:5398ef0d78e63f40007c1fb4c0bff96e1911394d2fa8d194f77619c05ff6cc8a"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
doc = ["reno", "sphinx", "tornado (>=4.5)"]
|
||||
|
||||
[[package]]
|
||||
name = "tomli"
|
||||
version = "2.0.1"
|
||||
description = "A lil' TOML parser"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
|
||||
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "typing-extensions"
|
||||
version = "4.9.0"
|
||||
description = "Backported and Experimental Type Hints for Python 3.8+"
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "typing_extensions-4.9.0-py3-none-any.whl", hash = "sha256:af72aea155e91adfc61c3ae9e0e342dbc0cba726d6cba4b6c72c1f34e47291cd"},
|
||||
{file = "typing_extensions-4.9.0.tar.gz", hash = "sha256:23478f88c37f27d76ac8aee6c905017a143b0b1b886c3c9f66bc2fd94f9f5783"},
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "urllib3"
|
||||
version = "2.1.0"
|
||||
description = "HTTP library with thread-safe connection pooling, file post, and more."
|
||||
optional = false
|
||||
python-versions = ">=3.8"
|
||||
files = [
|
||||
{file = "urllib3-2.1.0-py3-none-any.whl", hash = "sha256:55901e917a5896a349ff771be919f8bd99aff50b79fe58fec595eb37bbc56bb3"},
|
||||
{file = "urllib3-2.1.0.tar.gz", hash = "sha256:df7aa8afb0148fa78488e7899b2c59b5f4ffcfa82e6c54ccb9dd37c1d7b52d54"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
brotli = ["brotli (>=1.0.9)", "brotlicffi (>=0.8.0)"]
|
||||
socks = ["pysocks (>=1.5.6,!=1.5.7,<2.0)"]
|
||||
zstd = ["zstandard (>=0.18.0)"]
|
||||
|
||||
[[package]]
|
||||
name = "watchdog"
|
||||
version = "3.0.0"
|
||||
description = "Filesystem events monitoring"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
files = [
|
||||
{file = "watchdog-3.0.0-cp310-cp310-macosx_10_9_universal2.whl", hash = "sha256:336adfc6f5cc4e037d52db31194f7581ff744b67382eb6021c868322e32eef41"},
|
||||
{file = "watchdog-3.0.0-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:a70a8dcde91be523c35b2bf96196edc5730edb347e374c7de7cd20c43ed95397"},
|
||||
{file = "watchdog-3.0.0-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:adfdeab2da79ea2f76f87eb42a3ab1966a5313e5a69a0213a3cc06ef692b0e96"},
|
||||
{file = "watchdog-3.0.0-cp311-cp311-macosx_10_9_universal2.whl", hash = "sha256:2b57a1e730af3156d13b7fdddfc23dea6487fceca29fc75c5a868beed29177ae"},
|
||||
{file = "watchdog-3.0.0-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:7ade88d0d778b1b222adebcc0927428f883db07017618a5e684fd03b83342bd9"},
|
||||
{file = "watchdog-3.0.0-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:7e447d172af52ad204d19982739aa2346245cc5ba6f579d16dac4bfec226d2e7"},
|
||||
{file = "watchdog-3.0.0-cp37-cp37m-macosx_10_9_x86_64.whl", hash = "sha256:9fac43a7466eb73e64a9940ac9ed6369baa39b3bf221ae23493a9ec4d0022674"},
|
||||
{file = "watchdog-3.0.0-cp38-cp38-macosx_10_9_universal2.whl", hash = "sha256:8ae9cda41fa114e28faf86cb137d751a17ffd0316d1c34ccf2235e8a84365c7f"},
|
||||
{file = "watchdog-3.0.0-cp38-cp38-macosx_10_9_x86_64.whl", hash = "sha256:25f70b4aa53bd743729c7475d7ec41093a580528b100e9a8c5b5efe8899592fc"},
|
||||
{file = "watchdog-3.0.0-cp38-cp38-macosx_11_0_arm64.whl", hash = "sha256:4f94069eb16657d2c6faada4624c39464f65c05606af50bb7902e036e3219be3"},
|
||||
{file = "watchdog-3.0.0-cp39-cp39-macosx_10_9_universal2.whl", hash = "sha256:7c5f84b5194c24dd573fa6472685b2a27cc5a17fe5f7b6fd40345378ca6812e3"},
|
||||
{file = "watchdog-3.0.0-cp39-cp39-macosx_10_9_x86_64.whl", hash = "sha256:3aa7f6a12e831ddfe78cdd4f8996af9cf334fd6346531b16cec61c3b3c0d8da0"},
|
||||
{file = "watchdog-3.0.0-cp39-cp39-macosx_11_0_arm64.whl", hash = "sha256:233b5817932685d39a7896b1090353fc8efc1ef99c9c054e46c8002561252fb8"},
|
||||
{file = "watchdog-3.0.0-pp37-pypy37_pp73-macosx_10_9_x86_64.whl", hash = "sha256:13bbbb462ee42ec3c5723e1205be8ced776f05b100e4737518c67c8325cf6100"},
|
||||
{file = "watchdog-3.0.0-pp38-pypy38_pp73-macosx_10_9_x86_64.whl", hash = "sha256:8f3ceecd20d71067c7fd4c9e832d4e22584318983cabc013dbf3f70ea95de346"},
|
||||
{file = "watchdog-3.0.0-pp39-pypy39_pp73-macosx_10_9_x86_64.whl", hash = "sha256:c9d8c8ec7efb887333cf71e328e39cffbf771d8f8f95d308ea4125bf5f90ba64"},
|
||||
{file = "watchdog-3.0.0-py3-none-manylinux2014_aarch64.whl", hash = "sha256:0e06ab8858a76e1219e68c7573dfeba9dd1c0219476c5a44d5333b01d7e1743a"},
|
||||
{file = "watchdog-3.0.0-py3-none-manylinux2014_armv7l.whl", hash = "sha256:d00e6be486affb5781468457b21a6cbe848c33ef43f9ea4a73b4882e5f188a44"},
|
||||
{file = "watchdog-3.0.0-py3-none-manylinux2014_i686.whl", hash = "sha256:c07253088265c363d1ddf4b3cdb808d59a0468ecd017770ed716991620b8f77a"},
|
||||
{file = "watchdog-3.0.0-py3-none-manylinux2014_ppc64.whl", hash = "sha256:5113334cf8cf0ac8cd45e1f8309a603291b614191c9add34d33075727a967709"},
|
||||
{file = "watchdog-3.0.0-py3-none-manylinux2014_ppc64le.whl", hash = "sha256:51f90f73b4697bac9c9a78394c3acbbd331ccd3655c11be1a15ae6fe289a8c83"},
|
||||
{file = "watchdog-3.0.0-py3-none-manylinux2014_s390x.whl", hash = "sha256:ba07e92756c97e3aca0912b5cbc4e5ad802f4557212788e72a72a47ff376950d"},
|
||||
{file = "watchdog-3.0.0-py3-none-manylinux2014_x86_64.whl", hash = "sha256:d429c2430c93b7903914e4db9a966c7f2b068dd2ebdd2fa9b9ce094c7d459f33"},
|
||||
{file = "watchdog-3.0.0-py3-none-win32.whl", hash = "sha256:3ed7c71a9dccfe838c2f0b6314ed0d9b22e77d268c67e015450a29036a81f60f"},
|
||||
{file = "watchdog-3.0.0-py3-none-win_amd64.whl", hash = "sha256:4c9956d27be0bb08fc5f30d9d0179a855436e655f046d288e2bcc11adfae893c"},
|
||||
{file = "watchdog-3.0.0-py3-none-win_ia64.whl", hash = "sha256:5d9f3a10e02d7371cd929b5d8f11e87d4bad890212ed3901f9b4d68767bee759"},
|
||||
{file = "watchdog-3.0.0.tar.gz", hash = "sha256:4d98a320595da7a7c5a18fc48cb633c2e73cda78f93cac2ef42d42bf609a33f9"},
|
||||
]
|
||||
|
||||
[package.extras]
|
||||
watchmedo = ["PyYAML (>=3.10)"]
|
||||
|
||||
[metadata]
|
||||
lock-version = "2.0"
|
||||
python-versions = ">=3.8.1,<4.0"
|
||||
content-hash = "958e6227984c6fff9148576313da41494c2f4642968fccf861d524c8208fbfdc"
|
||||
93
libs/partners/nomic/pyproject.toml
Normal file
93
libs/partners/nomic/pyproject.toml
Normal file
@@ -0,0 +1,93 @@
|
||||
[tool.poetry]
|
||||
name = "langchain-nomic"
|
||||
version = "0.0.1"
|
||||
description = "An integration package connecting Nomic 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/nomic"
|
||||
|
||||
[tool.poetry.dependencies]
|
||||
python = ">=3.8.1,<4.0"
|
||||
langchain-core = ">=0.0.12"
|
||||
|
||||
[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.test_integration]
|
||||
optional = true
|
||||
|
||||
[tool.poetry.group.test_integration.dependencies]
|
||||
|
||||
[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.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/nomic/scripts/check_imports.py
Normal file
17
libs/partners/nomic/scripts/check_imports.py
Normal file
@@ -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/nomic/scripts/check_pydantic.sh
Executable file
27
libs/partners/nomic/scripts/check_pydantic.sh
Executable file
@@ -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 "$result"
|
||||
echo "Please replace the code with an import from langchain_core.pydantic_v1."
|
||||
echo "For example, replace 'from pydantic import BaseModel'"
|
||||
echo "with 'from langchain_core.pydantic_v1 import BaseModel'"
|
||||
exit 1
|
||||
fi
|
||||
17
libs/partners/nomic/scripts/lint_imports.sh
Executable file
17
libs/partners/nomic/scripts/lint_imports.sh
Executable file
@@ -0,0 +1,17 @@
|
||||
#!/bin/bash
|
||||
|
||||
set -eu
|
||||
|
||||
# Initialize a variable to keep track of errors
|
||||
errors=0
|
||||
|
||||
# make sure not importing from langchain or langchain_experimental
|
||||
git --no-pager grep '^from langchain\.' . && errors=$((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/nomic/tests/__init__.py
Normal file
0
libs/partners/nomic/tests/__init__.py
Normal file
@@ -0,0 +1,63 @@
|
||||
"""Test ChatNomic chat model."""
|
||||
from langchain_nomic.chat_models import ChatNomic
|
||||
|
||||
|
||||
def test_stream() -> None:
|
||||
"""Test streaming tokens from OpenAI."""
|
||||
llm = ChatNomic()
|
||||
|
||||
for token in llm.stream("I'm Pickle Rick"):
|
||||
assert isinstance(token.content, str)
|
||||
|
||||
|
||||
async def test_astream() -> None:
|
||||
"""Test streaming tokens from OpenAI."""
|
||||
llm = ChatNomic()
|
||||
|
||||
async for token in llm.astream("I'm Pickle Rick"):
|
||||
assert isinstance(token.content, str)
|
||||
|
||||
|
||||
async def test_abatch() -> None:
|
||||
"""Test streaming tokens from ChatNomic."""
|
||||
llm = ChatNomic()
|
||||
|
||||
result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"])
|
||||
for token in result:
|
||||
assert isinstance(token.content, str)
|
||||
|
||||
|
||||
async def test_abatch_tags() -> None:
|
||||
"""Test batch tokens from ChatNomic."""
|
||||
llm = ChatNomic()
|
||||
|
||||
result = await llm.abatch(
|
||||
["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]}
|
||||
)
|
||||
for token in result:
|
||||
assert isinstance(token.content, str)
|
||||
|
||||
|
||||
def test_batch() -> None:
|
||||
"""Test batch tokens from ChatNomic."""
|
||||
llm = ChatNomic()
|
||||
|
||||
result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"])
|
||||
for token in result:
|
||||
assert isinstance(token.content, str)
|
||||
|
||||
|
||||
async def test_ainvoke() -> None:
|
||||
"""Test invoke tokens from ChatNomic."""
|
||||
llm = ChatNomic()
|
||||
|
||||
result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]})
|
||||
assert isinstance(result.content, str)
|
||||
|
||||
|
||||
def test_invoke() -> None:
|
||||
"""Test invoke tokens from ChatNomic."""
|
||||
llm = ChatNomic()
|
||||
|
||||
result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"]))
|
||||
assert isinstance(result.content, str)
|
||||
@@ -0,0 +1,7 @@
|
||||
import pytest
|
||||
|
||||
|
||||
@pytest.mark.compile
|
||||
def test_placeholder() -> None:
|
||||
"""Used for compiling integration tests without running any real tests."""
|
||||
pass
|
||||
@@ -0,0 +1,19 @@
|
||||
"""Test Nomic embeddings."""
|
||||
from langchain_nomic.embeddings import NomicEmbeddings
|
||||
|
||||
|
||||
def test_langchain_nomic_embedding_documents() -> None:
|
||||
"""Test cohere embeddings."""
|
||||
documents = ["foo bar"]
|
||||
embedding = NomicEmbeddings()
|
||||
output = embedding.embed_documents(documents)
|
||||
assert len(output) == 1
|
||||
assert len(output[0]) > 0
|
||||
|
||||
|
||||
def test_langchain_nomic_embedding_query() -> None:
|
||||
"""Test cohere embeddings."""
|
||||
document = "foo bar"
|
||||
embedding = NomicEmbeddings()
|
||||
output = embedding.embed_query(document)
|
||||
assert len(output) > 0
|
||||
63
libs/partners/nomic/tests/integration_tests/test_llms.py
Normal file
63
libs/partners/nomic/tests/integration_tests/test_llms.py
Normal file
@@ -0,0 +1,63 @@
|
||||
"""Test NomicLLM llm."""
|
||||
from langchain_nomic.llms import NomicLLM
|
||||
|
||||
|
||||
def test_stream() -> None:
|
||||
"""Test streaming tokens from OpenAI."""
|
||||
llm = NomicLLM()
|
||||
|
||||
for token in llm.stream("I'm Pickle Rick"):
|
||||
assert isinstance(token, str)
|
||||
|
||||
|
||||
async def test_astream() -> None:
|
||||
"""Test streaming tokens from OpenAI."""
|
||||
llm = NomicLLM()
|
||||
|
||||
async for token in llm.astream("I'm Pickle Rick"):
|
||||
assert isinstance(token, str)
|
||||
|
||||
|
||||
async def test_abatch() -> None:
|
||||
"""Test streaming tokens from NomicLLM."""
|
||||
llm = NomicLLM()
|
||||
|
||||
result = await llm.abatch(["I'm Pickle Rick", "I'm not Pickle Rick"])
|
||||
for token in result:
|
||||
assert isinstance(token, str)
|
||||
|
||||
|
||||
async def test_abatch_tags() -> None:
|
||||
"""Test batch tokens from NomicLLM."""
|
||||
llm = NomicLLM()
|
||||
|
||||
result = await llm.abatch(
|
||||
["I'm Pickle Rick", "I'm not Pickle Rick"], config={"tags": ["foo"]}
|
||||
)
|
||||
for token in result:
|
||||
assert isinstance(token, str)
|
||||
|
||||
|
||||
def test_batch() -> None:
|
||||
"""Test batch tokens from NomicLLM."""
|
||||
llm = NomicLLM()
|
||||
|
||||
result = llm.batch(["I'm Pickle Rick", "I'm not Pickle Rick"])
|
||||
for token in result:
|
||||
assert isinstance(token, str)
|
||||
|
||||
|
||||
async def test_ainvoke() -> None:
|
||||
"""Test invoke tokens from NomicLLM."""
|
||||
llm = NomicLLM()
|
||||
|
||||
result = await llm.ainvoke("I'm Pickle Rick", config={"tags": ["foo"]})
|
||||
assert isinstance(result, str)
|
||||
|
||||
|
||||
def test_invoke() -> None:
|
||||
"""Test invoke tokens from NomicLLM."""
|
||||
llm = NomicLLM()
|
||||
|
||||
result = llm.invoke("I'm Pickle Rick", config=dict(tags=["foo"]))
|
||||
assert isinstance(result, str)
|
||||
0
libs/partners/nomic/tests/unit_tests/__init__.py
Normal file
0
libs/partners/nomic/tests/unit_tests/__init__.py
Normal file
9
libs/partners/nomic/tests/unit_tests/test_chat_models.py
Normal file
9
libs/partners/nomic/tests/unit_tests/test_chat_models.py
Normal file
@@ -0,0 +1,9 @@
|
||||
"""Test chat model integration."""
|
||||
|
||||
|
||||
from langchain_nomic.chat_models import ChatNomic
|
||||
|
||||
|
||||
def test_initialization() -> None:
|
||||
"""Test chat model initialization."""
|
||||
ChatNomic()
|
||||
9
libs/partners/nomic/tests/unit_tests/test_embeddings.py
Normal file
9
libs/partners/nomic/tests/unit_tests/test_embeddings.py
Normal file
@@ -0,0 +1,9 @@
|
||||
"""Test embedding model integration."""
|
||||
|
||||
|
||||
from langchain_nomic.embeddings import NomicEmbeddings
|
||||
|
||||
|
||||
def test_initialization() -> None:
|
||||
"""Test embedding model initialization."""
|
||||
NomicEmbeddings()
|
||||
12
libs/partners/nomic/tests/unit_tests/test_imports.py
Normal file
12
libs/partners/nomic/tests/unit_tests/test_imports.py
Normal file
@@ -0,0 +1,12 @@
|
||||
from langchain_nomic import __all__
|
||||
|
||||
EXPECTED_ALL = [
|
||||
"NomicLLM",
|
||||
"ChatNomic",
|
||||
"NomicVectorStore",
|
||||
"NomicEmbeddings",
|
||||
]
|
||||
|
||||
|
||||
def test_all_imports() -> None:
|
||||
assert sorted(EXPECTED_ALL) == sorted(__all__)
|
||||
7
libs/partners/nomic/tests/unit_tests/test_llms.py
Normal file
7
libs/partners/nomic/tests/unit_tests/test_llms.py
Normal file
@@ -0,0 +1,7 @@
|
||||
"""Test Nomic Chat API wrapper."""
|
||||
from langchain_nomic import NomicLLM
|
||||
|
||||
|
||||
def test_initialization() -> None:
|
||||
"""Test integration initialization."""
|
||||
NomicLLM()
|
||||
@@ -0,0 +1,6 @@
|
||||
from langchain_nomic.vectorstores import NomicVectorStore
|
||||
|
||||
|
||||
def test_initialization() -> None:
|
||||
"""Test integration vectorstore initialization."""
|
||||
NomicVectorStore()
|
||||
Reference in New Issue
Block a user