[Documentation] Updates to NVIDIA Playground/Foundation Model naming.… (

#14770)

…  (#14723)

- **Description:** Minor updates per marketing requests. Namely, name
decisions (AI Foundation Models / AI Playground)
  - **Tag maintainer:** @hinthornw 

Do want to pass around the PR for a bit and ask a few more marketing
questions before merge, but just want to make sure I'm not working in a
vacuum. No major changes to code functionality intended; the PR should
be for documentation and only minor tweaks.

Note: QA model is a bit borked across staging/prod right now. Relevant
teams have been informed and are looking into it, and I'm placeholdered
the response to that of a working version in the notebook.

Co-authored-by: Vadim Kudlay <[email protected]>

.github/scripts/check_diff.py

@@ -1,5 +1,6 @@
 import json
 import sys
+import os
 
 LANGCHAIN_DIRS = {
     "libs/core",
@@ -30,9 +31,15 @@
             )
         elif "libs/partners" in file:
             partner_dir = file.split("/")[2]
-            dirs_to_run.update(
-                (f"libs/partners/{partner_dir}", "libs/langchain", "libs/experimental")
-            )
+            if os.path.isdir(f"libs/partners/{partner_dir}"):
+                dirs_to_run.update(
+                    (
+                        f"libs/partners/{partner_dir}",
+                        "libs/langchain",
+                        "libs/experimental",
+                    )
+                )
+            # Skip if the directory was deleted
         elif "libs/langchain" in file:
             dirs_to_run.update(("libs/langchain", "libs/experimental"))
         elif "libs/experimental" in file:

.github/workflows/_release.yml

@@ -19,7 +19,7 @@ on:
           - libs/experimental
           - libs/community
           - libs/partners/google-genai
-          - libs/partners/nvidia-aiplay
+          - libs/partners/nvidia-ai-endpoints
 
 env:
   PYTHON_VERSION: "3.10"

docs/docs/integrations/providers/nvidia.mdx

@@ -0,0 +1,38 @@
+# NVIDIA
+
+> [NVIDIA AI Foundation Endpoints](https://www.nvidia.com/en-us/ai-data-science/foundation-models/) give users easy access to hosted endpoints for generative AI models like Llama-2, SteerLM, Mistral, etc. Using the API, you can query live endpoints available on the [NVIDIA GPU Cloud (NGC)](https://catalog.ngc.nvidia.com/ai-foundation-models) to get quick results from a DGX-hosted cloud compute environment. All models are source-accessible and can be deployed on your own compute cluster.
+These models are provided via the `langchain-nvidia-ai-endpoints` package.
+
+## Installation
+
+```bash
+pip install -U langchain-nvidia-ai-endpoints
+```
+
+## Setup and Authentication
+
+- Create a free account at [NVIDIA GPU Cloud (NGC)](https://catalog.ngc.nvidia.com/).
+- Navigate to `Catalog > AI Foundation Models > (Model with API endpoint)`.
+- Select `API` and generate the key `NVIDIA_API_KEY`.
+
+```bash
+export NVIDIA_API_KEY=nvapi-XXXXXXXXXXXXXXXXXXXXXXXXXX
+```
+
+```python
+from langchain_nvidia_ai_endpoints import ChatNVIDIA
+
+llm = ChatNVIDIA(model="mixtral_8x7b")
+result = llm.invoke("Write a ballad about LangChain.")
+print(result.content)
+```
+
+## Using NVIDIA AI Foundation Endpoints
+
+A selection of NVIDIA AI Foundation models are supported directly in LangChain with familiar APIs.
+
+The active models which are supported can be found [in NGC](https://catalog.ngc.nvidia.com/orgs/nvidia/teams/ai-foundation/).
+
+**The following may be useful examples to help you get started:**
+- **[`ChatNVIDIA` Model](/docs/integrations/chat/nvidia_ai_endpoints).**
+- **[`NVIDIAEmbeddings` Model for RAG Workflows](/docs/integrations/text_embeddings/nvidia_ai_endpoints).**