docs: integrations references update 7

docs/docs/integrations/chat/llamacpp.ipynb

@@ -4,9 +4,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# ChatLlamaCpp\n",
-    "\n",
-    "This notebook provides a quick overview for getting started with chat model intergrated with [llama cpp python](https://github.com/abetlen/llama-cpp-python)."
+    "# Llama.cpp\n",
+    "\n",
+    ">[llama.cpp python](https://github.com/abetlen/llama-cpp-python) library is a simple Python bindings for `@ggerganov`\n",
+    ">[llama.cpp](https://github.com/ggerganov/llama.cpp).\n",
+    ">\n",
+    ">This package provides:\n",
+    ">\n",
+    "> - Low-level access to C API via ctypes interface.\n",
+    "> - High-level Python API for text completion\n",
+    ">   - `OpenAI`-like API\n",
+    ">   - `LangChain` compatibility\n",
+    ">   - `LlamaIndex` compatibility\n",
+    "> - OpenAI compatible web server\n",
+    ">   - Local Copilot replacement\n",
+    ">   - Function Calling support\n",
+    ">   - Vision API support\n",
+    ">   - Multiple Models\n"
    ]
   },
   {
@@ -410,7 +424,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.8"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

docs/docs/integrations/chat/octoai.ipynb

@@ -4,7 +4,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# ChatOctoAI\n",
+    "# Octo AI\n",
     "\n",
     "[OctoAI](https://docs.octoai.cloud/docs) offers easy access to efficient compute and enables users to integrate their choice of AI models into applications. The `OctoAI` compute service helps you run, tune, and scale AI applications easily.\n",
     "\n",
@@ -99,7 +99,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.7"
+   "version": "3.10.12"
   },
   "vscode": {
    "interpreter": {

docs/docs/integrations/chat/perplexity.ipynb

@@ -15,9 +15,9 @@
    "id": "bf733a38-db84-4363-89e2-de6735c37230",
    "metadata": {},
    "source": [
-    "# ChatPerplexity\n",
+    "# Perplexity\n",
     "\n",
-    "This notebook covers how to get started with Perplexity chat models."
+    "This notebook covers how to get started with `Perplexity` chat models."
    ]
   },
   {
@@ -37,17 +37,31 @@
     "from langchain_core.prompts import ChatPromptTemplate"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "b26e2035-2f81-4451-ba44-fa2e2d5aeb62",
+   "metadata": {},
+   "source": [
+    "The code provided assumes that your PPLX_API_KEY is set in your environment variables. If you would like to manually specify your API key and also choose a different model, you can use the following code:"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "d986aac6-1bae-4608-8514-d3ba5b35b10e",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "chat = ChatPerplexity(\n",
+    "    temperature=0, pplx_api_key=\"YOUR_API_KEY\", model=\"llama-3-sonar-small-32k-online\"\n",
+    ")"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "97a8ce3a",
    "metadata": {},
    "source": [
-    "The code provided assumes that your PPLX_API_KEY is set in your environment variables. If you would like to manually specify your API key and also choose a different model, you can use the following code:\n",
-    "\n",
-    "```python\n",
-    "chat = ChatPerplexity(temperature=0, pplx_api_key=\"YOUR_API_KEY\", model=\"llama-3-sonar-small-32k-online\")\n",
-    "```\n",
-    "\n",
     "You can check a list of available models [here](https://docs.perplexity.ai/docs/model-cards). For reproducibility, we can set the API key dynamically by taking it as an input in this notebook."
    ]
   },
@@ -221,7 +235,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.18"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,

docs/docs/integrations/providers/llamacpp.mdx

@@ -1,26 +1,50 @@
 # Llama.cpp
 
-This page covers how to use [llama.cpp](https://github.com/ggerganov/llama.cpp) within LangChain.
-It is broken into two parts: installation and setup, and then references to specific Llama-cpp wrappers.
+>[llama.cpp python](https://github.com/abetlen/llama-cpp-python) library is a simple Python bindings for `@ggerganov`
+>[llama.cpp](https://github.com/ggerganov/llama.cpp).
+>
+>This package provides:
+>
+> - Low-level access to C API via ctypes interface.
+> - High-level Python API for text completion
+>   - `OpenAI`-like API
+>   - `LangChain` compatibility
+>   - `LlamaIndex` compatibility
+> - OpenAI compatible web server
+>   - Local Copilot replacement
+>   - Function Calling support
+>   - Vision API support
+>   - Multiple Models
 
 ## Installation and Setup
-- Install the Python package with `pip install llama-cpp-python`
+
+- Install the Python package
+  ```bash
+  pip install llama-cpp-python
+  ````
 - Download one of the [supported models](https://github.com/ggerganov/llama.cpp#description) and convert them to the llama.cpp format per the [instructions](https://github.com/ggerganov/llama.cpp)
 
-## Wrappers
 
-### LLM
+## Chat models
+
+See a [usage example](/docs/integrations/chat/llamacpp).
+
+```python
+from langchain_community.chat_models import ChatLlamaCpp
+```
+
+## LLMs
+
+See a [usage example](/docs/integrations/llms/llamacpp).
 
-There exists a LlamaCpp LLM wrapper, which you can access with 
 ```python
 from langchain_community.llms import LlamaCpp
 ```
-For a more detailed walkthrough of this, see [this notebook](/docs/integrations/llms/llamacpp)
 
-### Embeddings
+## Embedding models
+
+See a [usage example](/docs/integrations/text_embedding/llamacpp).
 
-There exists a LlamaCpp Embeddings wrapper, which you can access with 
 ```python
 from langchain_community.embeddings import LlamaCppEmbeddings
 ```
-For a more detailed walkthrough of this, see [this notebook](/docs/integrations/text_embedding/llamacpp)

docs/docs/integrations/providers/maritalk.mdx

@@ -0,0 +1,21 @@
+# MariTalk
+
+>[MariTalk](https://www.maritaca.ai/en) is an LLM-based chatbot trained to meet the needs of Brazil.
+
+## Installation and Setup
+
+You have to get the MariTalk API key.
+
+You also need to install the `httpx` Python package.
+
+```bash
+pip install httpx
+```
+
+## Chat models
+
+See a [usage example](/docs/integrations/chat/maritalk).
+
+```python
+from langchain_community.chat_models import ChatMaritalk
+```

docs/docs/integrations/providers/mlx.mdx

@@ -0,0 +1,34 @@
+# MLX
+
+>[MLX](https://ml-explore.github.io/mlx/build/html/index.html) is a `NumPy`-like array framework 
+> designed for efficient and flexible machine learning on `Apple` silicon, 
+> brought to you by `Apple machine learning research`.
+
+
+## Installation and Setup
+
+Install several Python packages:
+
+```bash
+pip install mlx-lm transformers huggingface_hub
+````
+
+
+## Chat models
+
+
+See a [usage example](/docs/integrations/chat/mlx).
+
+```python
+from langchain_community.chat_models.mlx import ChatMLX
+```
+
+## LLMs
+
+### MLX Local Pipelines
+
+See a [usage example](/docs/integrations/llms/mlx_pipelines).
+
+```python
+from langchain_community.llms.mlx_pipeline import MLXPipeline
+```

docs/docs/integrations/providers/octoai.mdx

@@ -0,0 +1,37 @@
+# OctoAI
+
+>[OctoAI](https://docs.octoai.cloud/docs) offers easy access to efficient compute 
+> and enables users to integrate their choice of AI models into applications. 
+> The `OctoAI` compute service helps you run, tune, and scale AI applications easily.
+
+
+## Installation and Setup
+
+- Install the `openai` Python package:
+  ```bash
+  pip install openai
+  ````
+- Register on `OctoAI` and get an API Token from [your OctoAI account page](https://octoai.cloud/settings).
+
+
+## Chat models
+
+See a [usage example](/docs/integrations/chat/octoai).
+
+```python
+from langchain_community.chat_models import ChatOctoAI
+```
+
+## LLMs
+
+See a [usage example](/docs/integrations/llms/octoai).
+
+```python
+from langchain_community.llms.octoai_endpoint import OctoAIEndpoint
+```
+
+## Embedding models
+
+```python
+from langchain_community.embeddings.octoai_embeddings import OctoAIEmbeddings
+```

docs/docs/integrations/providers/perplexity.mdx

@@ -0,0 +1,25 @@
+# Perplexity
+
+>[Perplexity](https://www.perplexity.ai/pro) is the most powerful way to search 
+> the internet with unlimited Pro Search, upgraded AI models, unlimited file upload, 
+> image generation, and API credits.
+>
+> You can check a [list of available models](https://docs.perplexity.ai/docs/model-cards).
+
+## Installation and Setup
+
+Install a Python package:
+
+```bash
+pip install openai
+````
+
+Get your API key from [here](https://docs.perplexity.ai/docs/getting-started).
+
+## Chat models
+
+See a [usage example](/docs/integrations/chat/perplexity).
+
+```python
+from langchain_community.chat_models import ChatPerplexity
+```

docs/docs/integrations/text_embedding/llamacpp.ipynb

@@ -4,9 +4,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Llama-cpp\n",
+    "# Llama.cpp\n",
     "\n",
-    "This notebook goes over how to use Llama-cpp embeddings within LangChain"
+    ">[llama.cpp python](https://github.com/abetlen/llama-cpp-python) library is a simple Python bindings for `@ggerganov`\n",
+    ">[llama.cpp](https://github.com/ggerganov/llama.cpp).\n",
+    ">\n",
+    ">This package provides:\n",
+    ">\n",
+    "> - Low-level access to C API via ctypes interface.\n",
+    "> - High-level Python API for text completion\n",
+    ">   - `OpenAI`-like API\n",
+    ">   - `LangChain` compatibility\n",
+    ">   - `LlamaIndex` compatibility\n",
+    "> - OpenAI compatible web server\n",
+    ">   - Local Copilot replacement\n",
+    ">   - Function Calling support\n",
+    ">   - Vision API support\n",
+    ">   - Multiple Models\n"
    ]
   },
   {
@@ -80,9 +94,9 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.1"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
- "nbformat_minor": 2
+ "nbformat_minor": 4
 }