Archives
/
langchain
mirror of https://github.com/hwchase17/langchain
2
0
Fork 1
Code Issues Packages Projects Releases Wiki Activity

docs: Update Nvidia documentation (#21240)

Browse Source 
Updating Nvidia docs ahead for 5/15 competition. 

Thanks!
pull/21232/head^2
Daniel Glogowski 4 weeks ago committed by GitHub
parent 70bde15480
commit c3d169ab00
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
3 changed files with 20 additions and 16 deletions
Show Stats Download Patch File Download Diff File

12
docs/docs/integrations/chat/nvidia_ai_endpoints.ipynb
Unescape Escape View File

@ -12,7 +12,7 @@
"The `ChatNVIDIA` class is a LangChain chat model that connects to [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/).\n",
"\n",
"\n",
"> [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) give users easy access to NVIDIA hosted API endpoints for NVIDIA AI Foundation Models like Mixtral 8x7B, Llama 2, Stable Diffusion, etc. These models, hosted on the [NVIDIA NGC catalog](https://catalog.ngc.nvidia.com/ai-foundation-models), are optimized, tested, and hosted on the NVIDIA AI platform, making them fast and easy to evaluate, further customize, and seamlessly run at peak performance on any accelerated stack.\n",
"> [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) give users easy access to NVIDIA hosted API endpoints for NVIDIA AI Foundation Models like Mixtral 8x7B, Llama 2, Stable Diffusion, etc. These models, hosted on the [NVIDIA API catalog](https://build.nvidia.com/), are optimized, tested, and hosted on the NVIDIA AI platform, making them fast and easy to evaluate, further customize, and seamlessly run at peak performance on any accelerated stack.\n",
"> \n",
"> With [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/), you can get quick results from a fully accelerated stack running on [NVIDIA DGX Cloud](https://www.nvidia.com/en-us/data-center/dgx-cloud/). Once customized, these models can be deployed anywhere with enterprise-grade security, stability, and support using [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/).\n",
"> \n",
@ -58,13 +58,13 @@
"\n",
"**To get started:**\n",
"\n",
"1. Create a free account with the [NVIDIA NGC](https://catalog.ngc.nvidia.com/) service, which hosts AI solution catalogs, containers, models, etc.\n",
"1. Create a free account with [NVIDIA](https://build.nvidia.com/), which hosts NVIDIA AI Foundation models\n",
"\n",
"2. Navigate to `Catalog > AI Foundation Models > (Model with API endpoint)`.\n",
"2. Click on your model of choice\n",
"\n",
"3. Select the `API` option and click `Generate Key`.\n",
"3. Under `Input` select the `Python` tab, and click `Get API Key`. Then click `Generate Key`.\n",
"\n",
"4. Save the generated key as `NVIDIA_API_KEY`. From there, you should have access to the endpoints."
"4. Copy and save the generated key as `NVIDIA_API_KEY`. From there, you should have access to the endpoints."
]
},
{
@ -311,7 +311,7 @@
"\n",
"Some model types support unique prompting techniques and chat messages. We will review a few important ones below.\n",
"\n",
"**To find out more about a specific model, please navigate to the API section of an AI Foundation model [as linked here](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/codellama-13b/api).**"
"**To find out more about a specific model, please navigate to the API section of an AI Foundation model [as linked here](https://build.nvidia.com/).**"
]
},
{

12
docs/docs/integrations/providers/nvidia.mdx
Unescape Escape View File

@ -17,16 +17,20 @@
A selection of NVIDIA AI Foundation models is supported directly in LangChain with familiar APIs.
The supported models can be found [in NGC](https://catalog.ngc.nvidia.com/ai-foundation-models).
The supported models can be found [in build.nvidia.com](https://build.nvidia.com/).
These models can be accessed via the [`langchain-nvidia-ai-endpoints`](https://pypi.org/project/langchain-nvidia-ai-endpoints/)
package, as shown below.
### Setting up
- Create a free [NVIDIA NGC](https://catalog.ngc.nvidia.com/) account.
- Navigate to `Catalog > AI Foundation Models > (Model with API endpoint)`.
- Select `API` and generate the key `NVIDIA_API_KEY`.
1. Create a free account with [NVIDIA](https://build.nvidia.com/), which hosts NVIDIA AI Foundation models
2. Click on your model of choice
3. Under `Input` select the `Python` tab, and click `Get API Key`. Then click `Generate Key`.
4. Copy and save the generated key as `NVIDIA_API_KEY`. From there, you should have access to the endpoints.
```bash
export NVIDIA_API_KEY=nvapi-XXXXXXXXXXXXXXXXXXXXXXXXXX

12
docs/docs/integrations/text_embedding/nvidia_ai_endpoints.ipynb
Unescape Escape View File

@ -8,7 +8,7 @@
"source": [
"# NVIDIA AI Foundation Endpoints \n",
"\n",
"> [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) give users easy access to NVIDIA hosted API endpoints for NVIDIA AI Foundation Models like Mixtral 8x7B, Llama 2, Stable Diffusion, etc. These models, hosted on the [NVIDIA NGC catalog](https://catalog.ngc.nvidia.com/ai-foundation-models), are optimized, tested, and hosted on the NVIDIA AI platform, making them fast and easy to evaluate, further customize, and seamlessly run at peak performance on any accelerated stack.\n",
"> [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) give users easy access to NVIDIA hosted API endpoints for NVIDIA AI Foundation Models like Mixtral 8x7B, Llama 2, Stable Diffusion, etc. These models, hosted on the [NVIDIA API catalog](https://build.nvidia.com/), are optimized, tested, and hosted on the NVIDIA AI platform, making them fast and easy to evaluate, further customize, and seamlessly run at peak performance on any accelerated stack.\n",
"> \n",
"> With [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/), you can get quick results from a fully accelerated stack running on [NVIDIA DGX Cloud](https://www.nvidia.com/en-us/data-center/dgx-cloud/). Once customized, these models can be deployed anywhere with enterprise-grade security, stability, and support using [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/).\n",
"> \n",
@ -16,7 +16,7 @@
"\n",
"This example goes over how to use LangChain to interact with the supported [NVIDIA Retrieval QA Embedding Model](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/models/nvolve-40k) for [retrieval-augmented generation](https://developer.nvidia.com/blog/build-enterprise-retrieval-augmented-generation-apps-with-nvidia-retrieval-qa-embedding-model/) via the `NVIDIAEmbeddings` class.\n",
"\n",
"For more information on accessing the chat models through this api, check out the [ChatNVIDIA](/docs/integrations/chat/nvidia_ai_endpoints/) documentation."
"For more information on accessing the chat models through this api, check out the [ChatNVIDIA](https://python.langchain.com/docs/integrations/chat/nvidia_ai_endpoints/) documentation."
]
},
{
@ -53,13 +53,13 @@
"\n",
"**To get started:**\n",
"\n",
"1. Create a free account with the [NVIDIA NGC](https://catalog.ngc.nvidia.com/) service, which hosts AI solution catalogs, containers, models, etc.\n",
"1. Create a free account with [NVIDIA](https://build.nvidia.com/), which hosts NVIDIA AI Foundation models\n",
"\n",
"2. Navigate to `Catalog > AI Foundation Models > (Model with API endpoint)`.\n",
"2. Select the `Retrieval` tab, then select your model of choice\n",
"\n",
"3. Select the `API` option and click `Generate Key`.\n",
"3. Under `Input` select the `Python` tab, and click `Get API Key`. Then click `Generate Key`.\n",
"\n",
"4. Save the generated key as `NVIDIA_API_KEY`. From there, you should have access to the endpoints."
"4. Copy and save the generated key as `NVIDIA_API_KEY`. From there, you should have access to the endpoints."
]
},
{

Write Preview
Loading…
Cancel
Save