Documenting thirdparty langchain-localai reranker

src/oss/python/integrations/document_transformers/localai_rerank.mdx

@@ -0,0 +1,33 @@
+---
+title: LocalAI Reranker
+---
+
+<Info>
+**`langchain-localai` is a 3rd party integration package for LocalAI. It provides a simple way to use LocalAI services in LangChain.**
+
+The source code is available on [GitHub](https://github.com/mkhludnev/langchain-localai)
+
+</Info>
+
+This notebook shows how to use [LocalAI Reranker API](https://localai.io/features/reranker/) for document compression and retrieval.
+Let's load the `LocalAIRerank` class. In order to use the `LocalAIRerank` class, you need to have the LocalAI service hosted somewhere and configure the reranker. See the documentation at [localai.io/basics/getting_started/index.html](https://localai.io/basics/getting_started/index.html) and [localai.io/features/reranker/index.html](https://localai.io/features/reranker/index.html).
+
+```bash
+pip install -U langchain-localai
+```
+
+```python
+import os
+from langchain_localai import LocalAIRerank
+from langchain_core.documents import Document
+
+# Set your LocalAI/OpenAI API key as an environment variable for security.
+# For example, in your shell: export OPENAI_API_KEY="your-key-here"
+reranker = LocalAIRerank(
+        openai_api_key=os.environ.get("OPENAI_API_KEY"),
+        model="bge-reranker-v2-m3",
+        openai_api_base="http://localhost:8080",
+    )
+reranked_docs = reranker.compress_documents(documents=[
+    Document(page_content="bar"), Document(page_content="baz")], query="foo")
+```

src/oss/python/integrations/text_embedding/localai.mdx

@@ -1,5 +1,5 @@
 ---
-title: LocalAI
+title: LocalAI Embeddings
 ---
 
 <Info>