langchain/libs/partners/google-genai/README.md
William FH 405d111da6
[Partner] Add langchain-google-genai package (gemini) (#14621)
Add a new ChatGoogleGenerativeAI class in a `langchain-google-genai`
package.
Still todo: add a deprecation warning in PALM

---------

Co-authored-by: Erick Friis <erick@langchain.dev>
Co-authored-by: Leonid Kuligin <lkuligin@yandex.ru>
Co-authored-by: Bagatur <baskaryan@gmail.com>
2023-12-13 11:57:59 -08:00

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1.4 KiB
Markdown

# langchain-google-genai
This package contains the LangChain integrations for Gemini through their generative-ai SDK.
## Installation
```python
pip install -U langchain-google-genai
```
## Chat Models
This package contains the `ChatGoogleGenerativeAI` class, which is the recommended way to interface with the Google Gemini series of models.
To use, install the requirements, and configure your environment.
```bash
export GOOGLE_API_KEY=your-api-key
```
Then initialize
```python
from langchain_google_genai import ChatGoogleGenerativeAI
llm = ChatGoogleGenerativeAI(model="gemini-pro")
llm.invoke("Sing a ballad of LangChain.")
```
#### Multimodal inputs
Gemini vision model supports image inputs when providing a single chat message. Example:
```
from langchain_core.messages import HumanMessage
from langchain_google_genai import ChatGoogleGenerativeAI
llm = ChatGoogleGenerativeAI(model="gemini-pro-vision")
# example
message = HumanMessage(
content=[
{
"type": "text",
"text": "What's in this image?",
}, # You can optionally provide text parts
{"type": "image_url", "image_url": "https://picsum.photos/seed/picsum/200/300"},
]
)
llm.invoke([message])
```
The value of `image_url` can be any of the following:
- A public image URL
- An accessible gcs file (e.g., "gcs://path/to/file.png")
- A local file path
- A base64 encoded image (e.g., `data:image/png;base64,abcd124`)
- A PIL image