Google PaLM Embeddings¶

注意： 此示例已弃用。请改用 GoogleGenAIEmbedding 类，详细信息请参见此处。

如果您在 Colab 上打开此 Notebook，可能需要安装 LlamaIndex 🦙。

输入 [ ]

%pip install llama-index-embeddings-google

%pip install llama-index-embeddings-google

输入 [ ]

!pip install llama-index

!pip install llama-index

输入 [ ]

# imports
from llama_index.embeddings.google import GooglePaLMEmbedding

# 导入 from llama_index.embeddings.google import GooglePaLMEmbedding

输入 [ ]

# get API key and create embeddings

model_name = "models/embedding-gecko-001"
api_key = "YOUR API KEY"

embed_model = GooglePaLMEmbedding(model_name=model_name, api_key=api_key)

embeddings = embed_model.get_text_embedding("Google PaLM Embeddings.")

# 获取 API 密钥并创建嵌入 model_name = "models/embedding-gecko-001" api_key = "YOUR API KEY" embed_model = GooglePaLMEmbedding(model_name=model_name, api_key=api_key) embeddings = embed_model.get_text_embedding("Google PaLM Embeddings.")

/opt/homebrew/lib/python3.11/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html
  from .autonotebook import tqdm as notebook_tqdm

输入 [ ]

print(f"Dimension of embeddings: {len(embeddings)}")

print(f"嵌入维度: {len(embeddings)}")

Dimension of embeddings: 768

输入 [ ]

embeddings[:5]

embeddings[:5]

输出 [ ]

[0.028517298, -0.0028859433, -0.035110522, 0.021982985, -0.0039763353]