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docs: providers
update 5 (#18550)
Added missed sections. Added descriptions.
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@ -8,10 +8,18 @@ There isn't any special setup for it.
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## Document Loader
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## Document loader
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See a [usage example](/docs/integrations/document_loaders/slack).
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See a [usage example](/docs/integrations/document_loaders/slack).
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```python
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```python
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from langchain_community.document_loaders import SlackDirectoryLoader
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from langchain_community.document_loaders import SlackDirectoryLoader
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```
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```
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## Chat loader
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See a [usage example](/docs/integrations/chat_loaders/slack).
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```python
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from langchain_community.chat_loaders.slack import SlackChatLoader
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```
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@ -15,3 +15,11 @@ See a [usage example](/docs/integrations/document_loaders/telegram).
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from langchain_community.document_loaders import TelegramChatFileLoader
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from langchain_community.document_loaders import TelegramChatFileLoader
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from langchain_community.document_loaders import TelegramChatApiLoader
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from langchain_community.document_loaders import TelegramChatApiLoader
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```
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```
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## Chat loader
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See a [usage example](/docs/integrations/chat_loaders/telegram).
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```python
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from langchain_community.chat_loaders.telegram import TelegramChatLoader
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```
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@ -23,27 +23,6 @@ For more information, see [this notebook](/docs/integrations/chat/tencent_hunyua
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from langchain_community.chat_models import ChatHunyuan
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from langchain_community.chat_models import ChatHunyuan
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```
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```
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## Vector Store
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>[Tencent Cloud VectorDB](https://www.tencentcloud.com/products/vdb) is a fully managed,
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> self-developed enterprise-level distributed database service
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>dedicated to storing, retrieving, and analyzing multidimensional vector data. The database supports a variety of index
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>types and similarity calculation methods, and a single index supports 1 billion vectors, millions of QPS, and
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>millisecond query latency. `Tencent Cloud Vector Database` can not only provide an external knowledge base for large
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>models and improve the accuracy of large models' answers, but also be widely used in AI fields such as
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>recommendation systems, NLP services, computer vision, and intelligent customer service.
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Install the Python SDK:
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```bash
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pip install tcvectordb
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```
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For more information, see [this notebook](/docs/integrations/vectorstores/tencentvectordb)
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```python
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from langchain_community.vectorstores import TencentVectorDB
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```
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## Document Loaders
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## Document Loaders
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@ -79,4 +58,38 @@ For more information, see [this notebook](/docs/integrations/document_loaders/te
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```python
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```python
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from langchain_community.document_loaders import TencentCOSFileLoader
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from langchain_community.document_loaders import TencentCOSFileLoader
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from qcloud_cos import CosConfig
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from qcloud_cos import CosConfig
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```
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```
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## Vector Store
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### Tencent VectorDB
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>[Tencent Cloud VectorDB](https://www.tencentcloud.com/products/vdb) is a fully managed,
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> self-developed enterprise-level distributed database service
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>dedicated to storing, retrieving, and analyzing multidimensional vector data. The database supports a variety of index
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>types and similarity calculation methods, and a single index supports 1 billion vectors, millions of QPS, and
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>millisecond query latency. `Tencent Cloud Vector Database` can not only provide an external knowledge base for large
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>models and improve the accuracy of large models' answers, but also be widely used in AI fields such as
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>recommendation systems, NLP services, computer vision, and intelligent customer service.
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Install the Python SDK:
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```bash
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pip install tcvectordb
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```
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For more information, see [this notebook](/docs/integrations/vectorstores/tencentvectordb)
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```python
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from langchain_community.vectorstores import TencentVectorDB
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```
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## Chat loader
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### WeChat
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>[WeChat](https://www.wechat.com/) or `Weixin` in Chinese is a Chinese
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> instant messaging, social media, and mobile payment app developed by `Tencent`.
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See a [usage example](/docs/integrations/chat_loaders/wechat).
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@ -19,3 +19,7 @@ See a [usage example](/docs/integrations/document_loaders/twitter).
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```python
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```python
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from langchain_community.document_loaders import TwitterTweetLoader
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from langchain_community.document_loaders import TwitterTweetLoader
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```
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```
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## Chat loader
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See a [usage example](/docs/integrations/chat_loaders/twitter).
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