diff --git a/docs/docs/integrations/chat/nvidia_ai_endpoints.ipynb b/docs/docs/integrations/chat/nvidia_ai_endpoints.ipynb index f8a28d665fc..f2d2fb3954e 100644 --- a/docs/docs/integrations/chat/nvidia_ai_endpoints.ipynb +++ b/docs/docs/integrations/chat/nvidia_ai_endpoints.ipynb @@ -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/).**" ] }, { diff --git a/docs/docs/integrations/providers/nvidia.mdx b/docs/docs/integrations/providers/nvidia.mdx index 0be21e38f71..f53e9125131 100644 --- a/docs/docs/integrations/providers/nvidia.mdx +++ b/docs/docs/integrations/providers/nvidia.mdx @@ -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 diff --git a/docs/docs/integrations/text_embedding/nvidia_ai_endpoints.ipynb b/docs/docs/integrations/text_embedding/nvidia_ai_endpoints.ipynb index 6490dcb8697..44df88bf851 100644 --- a/docs/docs/integrations/text_embedding/nvidia_ai_endpoints.ipynb +++ b/docs/docs/integrations/text_embedding/nvidia_ai_endpoints.ipynb @@ -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." ] }, {