YouTubeKnowledgeBase 遍历 YouTube URL 列表,提取视频字幕,将它们转换为向量嵌入,并将它们加载到向量数据库中。
from agno.knowledge.youtube import YouTubeKnowledgeBase
from agno.vectordb.pgvector import PgVector
knowledge_base = YouTubeKnowledgeBase(
urls=["https://www.youtube.com/watch?v=CDC3GOuJyZ0"],
# 表名: ai.website_documents
vector_db=PgVector(
table_name="youtube_documents",
db_url="postgresql+psycopg://ai:ai@localhost:5532/ai",
),
)
然后将 knowledge_base
与 Agent
一起使用:
from agno.agent import Agent
from knowledge_base import knowledge_base
agent = Agent(
knowledge=knowledge_base,
search_knowledge=True,
)
agent.knowledge.load(recreate=False)
agent.print_response("Ask me about something from the knowledge base")
YouTubeKnowledgeBase 也支持异步加载。
pip install qdrant-client
我们在此示例中使用本地 Qdrant 数据库。确保它正在运行
import asyncio
from agno.agent import Agent
from agno.knowledge.youtube import YouTubeKnowledgeBase, YouTubeReader
from agno.vectordb.qdrant import Qdrant
COLLECTION_NAME = "youtube-reader"
vector_db = Qdrant(collection=COLLECTION_NAME, url="http://localhost:6333")
knowledge_base = YouTubeKnowledgeBase(
urls=[
"https://www.youtube.com/watch?v=CDC3GOuJyZ0",
"https://www.youtube.com/watch?v=JbF_8g1EXj4",
],
vector_db=vector_db,
reader=YouTubeReader(chunk=True),
)
agent = Agent(
knowledge=knowledge_base,
search_knowledge=True,
)
if __name__ == "__main__":
# 首次运行时注释掉此行
asyncio.run(knowledge_base.aload(recreate=False))
# 创建并使用代理
asyncio.run(
agent.aprint_response(
"What is the major focus of the knowledge provided in both the videos, explain briefly.",
markdown=True,
)
)
参数 | 类型 | 默认值 | 描述 |
---|
urls | List[str] | [] | 要读取的视频的 URL |
reader | Optional[YouTubeReader] | None | 一个 YouTubeReader ,用于读取 URL 处的视频字幕,并将它们转换为 Documents 以便导入向量数据库。 |
YouTubeKnowledgeBase
是 AgentKnowledge 类的一个子类,可以访问相同的参数。
开发者资源
Responses are generated using AI and may contain mistakes.