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https://github.com/hwchase17/langchain.git
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daa9ccae52
- **Description:** add deprecated warning for ErnieBotChat and ErnieEmbeddings. - These two classes **lack maintenance** and do not use the sdk provided by qianfan, which means hard to implement some key feature like streaming. - The alternative `langchain_community.chat_models.QianfanChatEndpoint` and `langchain_community.embeddings.QianfanEmbeddingsEndpoint` can completely replace these two classes, only need to change configuration items. - **Issue:** None, - **Dependencies:** None, - **Twitter handle:** None --------- Co-authored-by: Bagatur <baskaryan@gmail.com>
117 lines
2.7 KiB
Plaintext
117 lines
2.7 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"# ERNIE\n",
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"\n",
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"[ERNIE Embedding-V1](https://cloud.baidu.com/doc/WENXINWORKSHOP/s/alj562vvu) is a text representation model based on `Baidu Wenxin` large-scale model technology, \n",
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"which converts text into a vector form represented by numerical values, and is used in text retrieval, information recommendation, knowledge mining and other scenarios."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"**Deprecated Warning**\n",
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"\n",
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"We recommend users using `langchain_community.embeddings.ErnieEmbeddings` \n",
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"to use `langchain_community.embeddings.QianfanEmbeddingsEndpoint` instead.\n",
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"\n",
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"documentation for `QianfanEmbeddingsEndpoint` is [here](./baidu_qianfan_endpoint).\n",
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"\n",
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"they are 2 why we recommend users to use `QianfanEmbeddingsEndpoint`:\n",
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"\n",
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"1. `QianfanEmbeddingsEndpoint` support more embedding model in the Qianfan platform.\n",
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"2. `ErnieEmbeddings` is lack of maintenance and deprecated."
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Some tips for migration:"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_community.embeddings import QianfanEmbeddingsEndpoint\n",
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"\n",
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"embeddings = QianfanEmbeddingsEndpoint(\n",
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" qianfan_ak=\"your qianfan ak\",\n",
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" qianfan_sk=\"your qianfan sk\",\n",
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")"
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]
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},
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"## Usage"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"from langchain_community.embeddings import ErnieEmbeddings"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"embeddings = ErnieEmbeddings()"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"query_result = embeddings.embed_query(\"foo\")"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": [
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"doc_results = embeddings.embed_documents([\"foo\"])"
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]
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}
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],
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"metadata": {
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"kernelspec": {
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"display_name": "Python 3 (ipykernel)",
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"language": "python",
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"name": "python3"
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},
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"language_info": {
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"codemirror_mode": {
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"name": "ipython",
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"version": 3
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},
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"file_extension": ".py",
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"mimetype": "text/x-python",
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"name": "python",
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"nbconvert_exporter": "python",
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"pygments_lexer": "ipython3",
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"version": "3.10.12"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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