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Use docusaurus versioning with a callout, merged master as well @hwchase17 @baskaryan --------- Signed-off-by: Weichen Xu <weichen.xu@databricks.com> Signed-off-by: Rahul Tripathi <rauhl.psit.ec@gmail.com> Co-authored-by: Leonid Ganeline <leo.gan.57@gmail.com> Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru> Co-authored-by: Averi Kitsch <akitsch@google.com> Co-authored-by: Erick Friis <erick@langchain.dev> Co-authored-by: Nuno Campos <nuno@langchain.dev> Co-authored-by: Nuno Campos <nuno@boringbits.io> Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com> Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com> Co-authored-by: Martín Gotelli Ferenaz <martingotelliferenaz@gmail.com> Co-authored-by: Fayfox <admin@fayfox.com> Co-authored-by: Eugene Yurtsev <eugene@langchain.dev> Co-authored-by: Dawson Bauer <105886620+djbauer2@users.noreply.github.com> Co-authored-by: Ravindu Somawansa <ravindu.somawansa@gmail.com> Co-authored-by: Dhruv Chawla <43818888+Dominastorm@users.noreply.github.com> Co-authored-by: ccurme <chester.curme@gmail.com> Co-authored-by: Bagatur <baskaryan@gmail.com> Co-authored-by: WeichenXu <weichen.xu@databricks.com> Co-authored-by: Benito Geordie <89472452+benitoThree@users.noreply.github.com> Co-authored-by: kartikTAI <129414343+kartikTAI@users.noreply.github.com> Co-authored-by: Kartik Sarangmath <kartik@thirdai.com> Co-authored-by: Sevin F. Varoglu <sfvaroglu@octoml.ai> Co-authored-by: MacanPN <martin.triska@gmail.com> Co-authored-by: Prashanth Rao <35005448+prrao87@users.noreply.github.com> Co-authored-by: Hyeongchan Kim <kozistr@gmail.com> Co-authored-by: sdan <git@sdan.io> Co-authored-by: Guangdong Liu <liugddx@gmail.com> Co-authored-by: Rahul Triptahi <rahul.psit.ec@gmail.com> Co-authored-by: Rahul Tripathi <rauhl.psit.ec@gmail.com> Co-authored-by: pjb157 <84070455+pjb157@users.noreply.github.com> Co-authored-by: Eun Hye Kim <ehkim1440@gmail.com> Co-authored-by: kaijietti <43436010+kaijietti@users.noreply.github.com> Co-authored-by: Pengcheng Liu <pcliu.fd@gmail.com> Co-authored-by: Tomer Cagan <tomer@tomercagan.com> Co-authored-by: Christophe Bornet <cbornet@hotmail.com>
60 lines
2.3 KiB
Plaintext
60 lines
2.3 KiB
Plaintext
# NVIDIA
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>NVIDIA provides an integration package for LangChain: `langchain-nvidia-ai-endpoints`.
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## NVIDIA AI Foundation Endpoints
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> [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
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> NVIDIA AI Foundation Models like `Mixtral 8x7B`, `Llama 2`, `Stable Diffusion`, etc. These models,
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> hosted on the [NVIDIA NGC catalog](https://catalog.ngc.nvidia.com/ai-foundation-models), are optimized, tested, and hosted on
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> the NVIDIA AI platform, making them fast and easy to evaluate, further customize,
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> and seamlessly run at peak performance on any accelerated stack.
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>
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> With [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/), you can get quick results from a fully
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> accelerated stack running on [NVIDIA DGX Cloud](https://www.nvidia.com/en-us/data-center/dgx-cloud/). Once customized, these
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> models can be deployed anywhere with enterprise-grade security, stability,
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> and support using [NVIDIA AI Enterprise](https://www.nvidia.com/en-us/data-center/products/ai-enterprise/).
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A selection of NVIDIA AI Foundation models is supported directly in LangChain with familiar APIs.
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The supported models can be found [in NGC](https://catalog.ngc.nvidia.com/ai-foundation-models).
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These models can be accessed via the [`langchain-nvidia-ai-endpoints`](https://pypi.org/project/langchain-nvidia-ai-endpoints/)
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package, as shown below.
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### Setting up
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- Create a free [NVIDIA NGC](https://catalog.ngc.nvidia.com/) account.
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- Navigate to `Catalog > AI Foundation Models > (Model with API endpoint)`.
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- Select `API` and generate the key `NVIDIA_API_KEY`.
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```bash
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export NVIDIA_API_KEY=nvapi-XXXXXXXXXXXXXXXXXXXXXXXXXX
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```
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- Install a package:
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```bash
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pip install -U langchain-nvidia-ai-endpoints
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```
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### Chat models
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See a [usage example](/docs/integrations/chat/nvidia_ai_endpoints).
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```python
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from langchain_nvidia_ai_endpoints import ChatNVIDIA
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llm = ChatNVIDIA(model="mixtral_8x7b")
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result = llm.invoke("Write a ballad about LangChain.")
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print(result.content)
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```
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### Embedding models
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See a [usage example](/docs/integrations/text_embedding/nvidia_ai_endpoints).
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```python
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from langchain_nvidia_ai_endpoints import NVIDIAEmbeddings
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```
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