google-genai, google-vertexai: move to langchain-google

libs/partners/google-genai/README.md

@@ -1,78 +1,3 @@
-# langchain-google-genai
+This package has moved!
 
-This package contains the LangChain integrations for Gemini through their generative-ai SDK.
-
-## Installation
-
-```bash
-pip install -U langchain-google-genai
-```
-
-### Image utilities
-To use image utility methods, like loading images from GCS urls, install with extras group 'images':
-
-```bash
-pip install -e "langchain-google-genai[images]"
-```
-
-## 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
-
-
-
-## Embeddings
-
-This package also adds support for google's embeddings models.
-
-```
-from langchain_google_genai import GoogleGenerativeAIEmbeddings
-
-embeddings = GoogleGenerativeAIEmbeddings(model="models/embedding-001")
-embeddings.embed_query("hello, world!")
-```
+https://github.com/langchain-ai/langchain-google/tree/main/libs/genai