# langchain-gigachat
This is a library integration with [GigaChat](https://giga.chat/).
[](https://github.com/ai-forever/langchain-gigachat/releases)
[](https://github.com/ai-forever/langchain-gigachat/actions/workflows/check_diffs.yml)
[](https://opensource.org/license/MIT)
[](https://pypistats.org/packages/langchain-gigachat)
[](https://star-history.com/#ai-forever/langchain-gigachat)
[](https://github.com/ai-forever/langchain-gigachat/issues)
## Installation
```bash
pip install -U langchain-gigachat
```
## Quickstart
Follow these simple steps to get up and running quickly.
### Installation
To install the package use following command:
```shell
pip install -U langchain-gigachat
```
### Initialization
To initialize chat model:
```python
from langchain_gigachat.chat_models import GigaChat
giga = GigaChat(credentials="YOUR_AUTHORIZATION_KEY", verify_ssl_certs=False)
```
To initialize embeddings:
```python
from langchain_gigachat.embeddings import GigaChatEmbeddings
embedding = GigaChatEmbeddings(
credentials="YOUR_AUTHORIZATION_KEY",
verify_ssl_certs=False
)
```
### Usage
Use the GigaChat object to generate responses:
```python
print(giga.invoke("Hello, world!"))
```
Now you can use the GigaChat object with LangChain's standard primitives to create LLM-applications.
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"description": "# langchain-gigachat\n\nThis is a library integration with [GigaChat](https://giga.chat/).\n\n[](https://github.com/ai-forever/langchain-gigachat/releases)\n[](https://github.com/ai-forever/langchain-gigachat/actions/workflows/check_diffs.yml)\n[](https://opensource.org/license/MIT)\n[](https://pypistats.org/packages/langchain-gigachat)\n[](https://star-history.com/#ai-forever/langchain-gigachat)\n[](https://github.com/ai-forever/langchain-gigachat/issues)\n\n## Installation\n```bash\npip install -U langchain-gigachat\n```\n\n## Quickstart\nFollow these simple steps to get up and running quickly.\n\n### Installation\nTo install the package use following command:\n```shell\npip install -U langchain-gigachat\n```\n\n### Initialization\n\nTo initialize chat model:\n```python\nfrom langchain_gigachat.chat_models import GigaChat\n\ngiga = GigaChat(credentials=\"YOUR_AUTHORIZATION_KEY\", verify_ssl_certs=False)\n```\n\nTo initialize embeddings:\n\n```python\nfrom langchain_gigachat.embeddings import GigaChatEmbeddings\n\nembedding = GigaChatEmbeddings(\n credentials=\"YOUR_AUTHORIZATION_KEY\",\n verify_ssl_certs=False\n)\n```\n\n### Usage\n\nUse the GigaChat object to generate responses:\n\n```python\nprint(giga.invoke(\"Hello, world!\"))\n```\n\nNow you can use the GigaChat object with LangChain's standard primitives to create LLM-applications.",
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