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integrations
references update (langchain-ai#25217)
Added missed provider pages. Fixed formats and added descriptions and links. --------- Co-authored-by: Chester Curme <[email protected]>
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# Llama.cpp | ||
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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` | ||
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- 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) | ||
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## Wrappers | ||
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### LLM | ||
## Chat models | ||
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See a [usage example](/docs/integrations/chat/llamacpp). | ||
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```python | ||
from langchain_community.chat_models import ChatLlamaCpp | ||
``` | ||
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## LLMs | ||
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See a [usage example](/docs/integrations/llms/llamacpp). | ||
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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) | ||
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### Embeddings | ||
## Embedding models | ||
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See a [usage example](/docs/integrations/text_embedding/llamacpp). | ||
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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) |
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# MariTalk | ||
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>[MariTalk](https://www.maritaca.ai/en) is an LLM-based chatbot trained to meet the needs of Brazil. | ||
## Installation and Setup | ||
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You have to get the MariTalk API key. | ||
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You also need to install the `httpx` Python package. | ||
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```bash | ||
pip install httpx | ||
``` | ||
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## Chat models | ||
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See a [usage example](/docs/integrations/chat/maritalk). | ||
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```python | ||
from langchain_community.chat_models import ChatMaritalk | ||
``` |
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# MLX | ||
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>[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`. | ||
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## Installation and Setup | ||
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Install several Python packages: | ||
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```bash | ||
pip install mlx-lm transformers huggingface_hub | ||
```` | ||
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## Chat models | ||
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See a [usage example](/docs/integrations/chat/mlx). | ||
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```python | ||
from langchain_community.chat_models.mlx import ChatMLX | ||
``` | ||
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## LLMs | ||
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### MLX Local Pipelines | ||
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See a [usage example](/docs/integrations/llms/mlx_pipelines). | ||
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```python | ||
from langchain_community.llms.mlx_pipeline import MLXPipeline | ||
``` |
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# OctoAI | ||
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>[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. | ||
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## Installation and Setup | ||
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- 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). | ||
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## Chat models | ||
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See a [usage example](/docs/integrations/chat/octoai). | ||
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```python | ||
from langchain_community.chat_models import ChatOctoAI | ||
``` | ||
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## LLMs | ||
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See a [usage example](/docs/integrations/llms/octoai). | ||
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```python | ||
from langchain_community.llms.octoai_endpoint import OctoAIEndpoint | ||
``` | ||
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## Embedding models | ||
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```python | ||
from langchain_community.embeddings.octoai_embeddings import OctoAIEmbeddings | ||
``` |
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# Perplexity | ||
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>[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 | ||
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Install a Python package: | ||
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```bash | ||
pip install openai | ||
```` | ||
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Get your API key from [here](https://docs.perplexity.ai/docs/getting-started). | ||
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## Chat models | ||
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See a [usage example](/docs/integrations/chat/perplexity). | ||
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```python | ||
from langchain_community.chat_models import ChatPerplexity | ||
``` |
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