update docs for merged storage (#195)

kausmeows · web-flow · commit b2b995050753 · 2025-04-04T22:11:20.000+02:00
## What does this PR do?

- at some places in the `Examples` section still `...AgentStorage` was
being used for example `PostgresAgentStorage` instead of just
`PostgresStorage`
diff --git a/agent-ui/introduction.mdx b/agent-ui/introduction.mdx
@@ -71,7 +71,7 @@ Let's start with a local playground server. Create a file `playground.py`
 from agno.agent import Agent
 from agno.models.openai import OpenAIChat
 from agno.playground import Playground, serve_playground_app
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 from agno.tools.yfinance import YFinanceTools
 
@@ -83,7 +83,7 @@ web_agent = Agent(
     tools=[DuckDuckGoTools()],
     instructions=["Always include sources"],
     # Store the agent sessions in a sqlite database
-    storage=SqliteAgentStorage(table_name="web_agent", db_file=agent_storage),
+    storage=SqliteStorage(table_name="web_agent", db_file=agent_storage),
     # Adds the current date and time to the instructions
     add_datetime_to_instructions=True,
     # Adds the history of the conversation to the messages
@@ -99,7 +99,7 @@ finance_agent = Agent(
     model=OpenAIChat(id="gpt-4o"),
     tools=[YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True, company_news=True)],
     instructions=["Always use tables to display data"],
-    storage=SqliteAgentStorage(table_name="finance_agent", db_file=agent_storage),
+    storage=SqliteStorage(table_name="finance_agent", db_file=agent_storage),
     add_datetime_to_instructions=True,
     add_history_to_messages=True,
     num_history_responses=5,
diff --git a/agents/memory.mdx b/agents/memory.mdx
@@ -82,12 +82,12 @@ from rich.json import JSON
 
 from agno.agent import Agent
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 
 agent = Agent(
     model=OpenAIChat(id="gpt-4o"),
     # Store agent sessions in a database
-    storage=SqliteAgentStorage(table_name="agent_sessions", db_file="tmp/agent_storage.db"),
+    storage=SqliteStorage(table_name="agent_sessions", db_file="tmp/agent_storage.db"),
     # Set add_history_to_messages=true to add the previous chat history to the messages sent to the Model.
     add_history_to_messages=True,
     # Number of historical responses to add to the messages.
diff --git a/examples/concepts/memory/memories-and-summaries-postgres.mdx b/examples/concepts/memory/memories-and-summaries-postgres.mdx
@@ -8,7 +8,7 @@ title: Memories and Summaries with Postgres
 from agno.agent import Agent, AgentMemory
 from agno.memory.db.postgres import PgMemoryDb
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from rich.pretty import pprint
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
@@ -21,7 +21,7 @@ agent = Agent(
         create_session_summary=True,
     ),
     # Store agent sessions in a database
-    storage=PostgresAgentStorage(
+    storage=PostgresStorage(
         table_name="personalized_agent_sessions", db_url=db_url
     ),
     # Show debug logs so, you can see the memory being created
diff --git a/examples/concepts/memory/memories-and-summaries-sqlite-async.mdx b/examples/concepts/memory/memories-and-summaries-sqlite-async.mdx
@@ -11,7 +11,7 @@ import json
 from agno.agent import Agent, AgentMemory
 from agno.memory.db.sqlite import SqliteMemoryDb
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from rich.console import Console
 from rich.json import JSON
 from rich.panel import Panel
@@ -39,7 +39,7 @@ agent = Agent(
         update_session_summary_after_run=True,
     ),
     # Store agent sessions in a database
-    storage=SqliteAgentStorage(table_name="agent_sessions", db_file=agent_storage_file),
+    storage=SqliteStorage(table_name="agent_sessions", db_file=agent_storage_file),
     description="You are a helpful assistant that always responds in a polite, upbeat and positive manner.",
     # Show debug logs to see the memory being created
     # debug_mode=True,
diff --git a/examples/concepts/memory/memories-and-summaries.mdx b/examples/concepts/memory/memories-and-summaries.mdx
@@ -10,7 +10,7 @@ import json
 from agno.agent import Agent, AgentMemory
 from agno.memory.db.sqlite import SqliteMemoryDb
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from rich.console import Console
 from rich.json import JSON
 from rich.panel import Panel
@@ -35,7 +35,7 @@ agent = Agent(
         update_session_summary_after_run=True,
     ),
     # Store agent sessions in a database, that persists between runs
-    storage=SqliteAgentStorage(
+    storage=SqliteStorage(
         table_name="agent_sessions", db_file="tmp/agent_storage.db"
     ),
     # add_history_to_messages=true adds the chat history to the messages sent to the Model.
diff --git a/examples/concepts/memory/persistent-memory-mongodb.mdx b/examples/concepts/memory/persistent-memory-mongodb.mdx
@@ -11,7 +11,7 @@ from agno.agent import Agent
 from agno.memory.agent import AgentMemory
 from agno.memory.db.mongodb import MongoMemoryDb
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.mongodb import MongoDbAgentStorage
+from agno.storage.mongodb import MongoDbStorage
 from rich.console import Console
 from rich.json import JSON
 from rich.panel import Panel
@@ -22,7 +22,7 @@ db_url = "mongodb://localhost:27017"
 agent = Agent(
     model=OpenAIChat(id="gpt-4o"),
     # Store agent sessions in MongoDB
-    storage=MongoDbAgentStorage(
+    storage=MongoDbStorage(
         collection_name="agent_sessions", db_url=db_url, db_name="agno"
     ),
     # Store memories in MongoDB
diff --git a/examples/concepts/memory/persistent-memory-postgres.mdx b/examples/concepts/memory/persistent-memory-postgres.mdx
@@ -10,7 +10,7 @@ from typing import List, Optional
 import typer
 from agno.agent import Agent
 from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.vectordb.pgvector import PgVector, SearchType
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
@@ -21,7 +21,7 @@ knowledge_base = PDFUrlKnowledgeBase(
     ),
 )
 
-storage = PostgresAgentStorage(table_name="pdf_agent", db_url=db_url)
+storage = PostgresStorage(table_name="pdf_agent", db_url=db_url)
 
 
 def pdf_agent(new: bool = False, user: str = "user"):
diff --git a/examples/concepts/memory/persistent-memory.mdx b/examples/concepts/memory/persistent-memory.mdx
@@ -9,15 +9,15 @@ import json
 
 from agno.agent import Agent
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from rich.console import Console
 from rich.json import JSON
 from rich.panel import Panel
 
 agent = Agent(
     model=OpenAIChat(id="gpt-4o"),
     # Store agent sessions in a database
-    storage=SqliteAgentStorage(
+    storage=SqliteStorage(
         table_name="agent_sessions", db_file="tmp/agent_storage.db"
     ),
     # Set add_history_to_messages=true to add the previous chat history to the messages sent to the Model.
diff --git a/examples/concepts/rag/agentic-rag-agent-ui.mdx b/examples/concepts/rag/agentic-rag-agent-ui.mdx
@@ -10,7 +10,7 @@ from agno.embedder.openai import OpenAIEmbedder
 from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
 from agno.models.openai import OpenAIChat
 from agno.playground import Playground, serve_playground_app
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.vectordb.pgvector import PgVector, SearchType
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
@@ -37,7 +37,7 @@ rag_agent = Agent(
     # Add a tool to read chat history.
     read_chat_history=True,
     # Store the agent sessions in the `ai.rag_agent_sessions` table
-    storage=PostgresAgentStorage(table_name="rag_agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="rag_agent_sessions", db_url=db_url),
     instructions=[
         "Always search your knowledge base first and use it if available.",
         "Share the page number or source URL of the information you used in your response.",
diff --git a/examples/concepts/rag/rag-with-lance-db-and-sqlite.mdx b/examples/concepts/rag/rag-with-lance-db-and-sqlite.mdx
@@ -9,7 +9,7 @@ from agno.agent import Agent
 from agno.embedder.ollama import OllamaEmbedder
 from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
 from agno.models.ollama import Ollama
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from agno.vectordb.lancedb import LanceDb
 
 # Define the database URL where the vector database will be stored
@@ -38,7 +38,7 @@ knowledge_base = PDFUrlKnowledgeBase(
 knowledge_base.load(recreate=False)
 
 # Set up SQL storage for the agent's data
-storage = SqliteAgentStorage(table_name="recipes", db_file="data.db")
+storage = SqliteStorage(table_name="recipes", db_file="data.db")
 storage.create()  # Create the storage if it doesn't exist
 
 # Initialize the Agent with various configurations including the knowledge base and storage
diff --git a/examples/concepts/vectordb/clickhouse.mdx b/examples/concepts/vectordb/clickhouse.mdx
@@ -7,11 +7,11 @@ title: Clickhouse Integration
 ```python cookbook/agent_concepts/vector_dbs/clickhouse.py
 from agno.agent import Agent
 from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from agno.vectordb.clickhouse import Clickhouse
 
 agent = Agent(
-    storage=SqliteAgentStorage(table_name="recipe_agent"),
+    storage=SqliteStorage(table_name="recipe_agent"),
     knowledge=PDFUrlKnowledgeBase(
         urls=["https://agno-public.s3.amazonaws.com/recipes/ThaiRecipes.pdf"],
         vector_db=Clickhouse(
diff --git a/examples/getting-started/agent-session.mdx b/examples/getting-started/agent-session.mdx
@@ -18,7 +18,7 @@ from typing import Optional
 import typer
 from agno.agent import Agent
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from rich.console import Console
 from rich.json import JSON
 from rich.panel import Panel
@@ -35,7 +35,7 @@ def create_agent(user: str = "user"):
     new = typer.confirm("Do you want to start a new session?")
 
     # Get existing session if user doesn't want a new one
-    agent_storage = SqliteAgentStorage(
+    agent_storage = SqliteStorage(
         table_name="agent_sessions", db_file="tmp/agents.db"
     )
 
diff --git a/examples/getting-started/agent-with-storage.mdx b/examples/getting-started/agent-with-storage.mdx
@@ -23,7 +23,7 @@ from agno.agent import Agent
 from agno.embedder.openai import OpenAIEmbedder
 from agno.knowledge.pdf_url import PDFUrlKnowledgeBase
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 from agno.vectordb.lancedb import LanceDb, SearchType
 from rich import print
@@ -38,7 +38,7 @@ agent_knowledge = PDFUrlKnowledgeBase(
     ),
 )
 
-agent_storage = SqliteAgentStorage(table_name="recipe_agent", db_file="tmp/agents.db")
+agent_storage = SqliteStorage(table_name="recipe_agent", db_file="tmp/agents.db")
 
 
 def recipe_agent(user: str = "user"):
diff --git a/examples/getting-started/user-memories.mdx b/examples/getting-started/user-memories.mdx
@@ -31,7 +31,7 @@ import typer
 from agno.agent import Agent, AgentMemory
 from agno.memory.db.sqlite import SqliteMemoryDb
 from agno.models.openai import OpenAIChat
-from agno.storage.agent.sqlite import SqliteAgentStorage
+from agno.storage.sqlite import SqliteStorage
 from rich.console import Console
 from rich.json import JSON
 from rich.panel import Panel
@@ -45,7 +45,7 @@ def create_agent(user: str = "user"):
     new = typer.confirm("Do you want to start a new session?")
 
     # Initialize storage for both agent sessions and memories
-    agent_storage = SqliteAgentStorage(
+    agent_storage = SqliteStorage(
         table_name="agent_memories", db_file="tmp/agents.db"
     )
 
diff --git a/examples/models/anthropic/storage.mdx b/examples/models/anthropic/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/anthropic/storage.py
 from agno.agent import Agent
 from agno.models.anthropic import Claude
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=Claude(id="claude-3-5-sonnet-20241022"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/aws/bedrock/storage.mdx b/examples/models/aws/bedrock/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/aws/bedrock/storage.py
 from agno.agent import Agent
 from agno.models.aws import AwsBedrock
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=AwsBedrock(id="mistral.mistral-large-2402-v1:0"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/aws/claude/storage.mdx b/examples/models/aws/claude/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/aws/claude/storage.py
 from agno.agent import Agent
 from agno.models.aws import Claude
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=Claude(id="anthropic.claude-3-5-sonnet-20240620-v1:0"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/azure/ai_foundry/storage.mdx b/examples/models/azure/ai_foundry/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/azure/ai_foundry/storage.py
 from agno.agent import Agent
 from agno.models.azure import AzureAIFoundry
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=AzureAIFoundry(id="Cohere-command-r-08-2024"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/azure/openai/storage.mdx b/examples/models/azure/openai/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/azure/openai/storage.py
 from agno.agent import Agent
 from agno.models.azure import AzureOpenAI
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=AzureOpenAI(id="gpt-4o"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/cohere/storage.mdx b/examples/models/cohere/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/cohere/storage.py
 from agno.agent import Agent
 from agno.models.cohere import Cohere
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=Cohere(id="command-r-08-2024"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/gemini/storage.mdx b/examples/models/gemini/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/google/gemini/storage.py
 from agno.agent import Agent
 from agno.models.google import Gemini
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=Gemini(id="gemini-2.0-flash-exp"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/groq/storage.mdx b/examples/models/groq/storage.mdx
@@ -7,14 +7,14 @@ title: Agent with Storage
 ```python cookbook/models/groq/storage.py
 from agno.agent import Agent
 from agno.models.groq import Groq
-from agno.storage.agent.postgres import PostgresAgentStorage
+from agno.storage.postgres import PostgresStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
 db_url = "postgresql+psycopg://ai:ai@localhost:5532/ai"
 
 agent = Agent(
     model=Groq(id="llama-3.3-70b-versatile"),
-    storage=PostgresAgentStorage(table_name="agent_sessions", db_url=db_url),
+    storage=PostgresStorage(table_name="agent_sessions", db_url=db_url),
     tools=[DuckDuckGoTools()],
     add_history_to_messages=True,
 )
diff --git a/examples/models/ibm/storage.mdx b/examples/models/ibm/storage.mdx
diff --git a/examples/models/lmstudio/storage.mdx b/examples/models/lmstudio/storage.mdx
diff --git a/examples/models/ollama/storage.mdx b/examples/models/ollama/storage.mdx
diff --git a/examples/models/openai/storage.mdx b/examples/models/openai/storage.mdx
diff --git a/how-to/local-docker-guide.mdx b/how-to/local-docker-guide.mdx
diff --git a/introduction/playground.mdx b/introduction/playground.mdx
diff --git a/storage/postgres.mdx b/storage/postgres.mdx
diff --git a/vectordb/clickhouse.mdx b/vectordb/clickhouse.mdx
