docs: integrations reference updates 12 (#25676)

Added missed provider pages and links. Fixed inconsistent formatting.

Co-authored-by: Erick Friis <erick@langchain.dev>
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Leonid Ganeline 2024-08-30 14:25:42 -07:00 committed by GitHub
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3 changed files with 73 additions and 6 deletions

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@ -24,6 +24,7 @@ from langchain_community.llms import QianfanLLMEndpoint
### Qianfan Chat Endpoint
See a [usage example](/docs/integrations/chat/baidu_qianfan_endpoint).
See another [usage example](/docs/integrations/chat/ernie).
```python
from langchain_community.chat_models import QianfanChatEndpoint
@ -34,6 +35,7 @@ from langchain_community.chat_models import QianfanChatEndpoint
### Baidu Qianfan
See a [usage example](/docs/integrations/text_embedding/baidu_qianfan_endpoint).
See another [usage example](/docs/integrations/text_embedding/ernie).
```python
from langchain_community.embeddings import QianfanEmbeddingsEndpoint

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@ -0,0 +1,25 @@
# Embedchain
> [Embedchain](https://github.com/embedchain/embedchain) is a RAG framework to create
> data pipelines. It loads, indexes, retrieves and syncs all the data.
>
>It is available as an [open source package](https://github.com/embedchain/embedchain)
> and as a [hosted platform solution](https://app.embedchain.ai/).
## Installation and Setup
Install the package using pip:
```bash
pip install embedchain
```
## Retriever
See a [usage example](/docs/integrations/retrievers/embedchain).
```python
from langchain_community.retrievers import EmbedchainRetriever
```

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@ -4,9 +4,14 @@
"cell_type": "markdown",
"metadata": {},
"source": [
"# Exa Search\n",
"# Exa\n",
"\n",
"Exa's search integration exists in its own [partner package](https://pypi.org/project/langchain-exa/). You can install it with:"
">[Exa](https://exa.ai/) is a knowledge API for AI and developers.\n",
">\n",
"\n",
"## Installation and Setup\n",
"\n",
"`Exa` integration exists in its own [partner package](https://pypi.org/project/langchain-exa/). You can install it with:"
]
},
{
@ -26,7 +31,9 @@
"\n",
"## Retriever\n",
"\n",
"You can use the [`ExaSearchRetriever`](/docs/integrations/tools/exa_search#using-exasearchretriever) in a standard retrieval pipeline. You can import it as follows"
"You can use the [`ExaSearchRetriever`](/docs/integrations/tools/exa_search#using-exasearchretriever) in a standard retrieval pipeline. You can import it as follows.\n",
"\n",
"See a [usage example](/docs/integrations/tools/exa_search).\n"
]
},
{
@ -46,7 +53,40 @@
"source": [
"## Tools\n",
"\n",
"You can use Exa as an agent tool as described in the [Exa tool calling docs](/docs/integrations/tools/exa_search#using-the-exa-sdk-as-langchain-agent-tools).\n"
"You can use Exa as an agent tool as described in the [Exa tool calling docs](/docs/integrations/tools/exa_search#using-the-exa-sdk-as-langchain-agent-tools).\n",
"\n",
"See a [usage example](/docs/integrations/tools/exa_search).\n",
"\n",
"### ExaFindSimilarResults\n",
"\n",
"A tool that queries the Metaphor Search API and gets back JSON."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain_exa.tools import ExaFindSimilarResults"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### ExaSearchResults\n",
"\n",
"Exa Search tool."
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"from langchain_exa.tools import ExaSearchResults"
]
}
],
@ -69,9 +109,9 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.10.11"
"version": "3.10.12"
}
},
"nbformat": 4,
"nbformat_minor": 1
"nbformat_minor": 4
}