feat : update studio docs

agent-os/studio/agents.mdx

@@ -3,21 +3,28 @@ title: "Agents"
 description: "Build and configure agents visually in AgentOS Studio."
 ---
 
-Build production-grade agents via AgentOS Studio’s visual canvas. Wire up models, tools, 
-and structured I/O into complex agentic workflows. Deploy instantly. No-code required.
+Build production-grade agents via AgentOS Studio’s. Wire up models, tools, 
+instructions, knowledge, memory, and more. Deploy instantly. No-code required.
 
 ## Creating Agents
 
 Create a new agent by selecting components from your [Registry](/agent-os/studio/registry) and configuring them in the properties panel:
 
-| Setting | Description |
-|---------|-------------|
-| **Model** | Select from registered models |
-| **Tools** | Attach registered tools and toolkits |
-| **Instructions** | System-level instructions for the agent |
-| **Input/Output Schema** | Structured I/O using registered Pydantic schemas |
-| **Memory** | Enable memory for multi-turn conversations |
-| **Knowledge** | Attach knowledge bases for RAG |
+- **Model**: select from registered models.
+- **Tools**: attach registered tools and toolkits.
+- **Instructions**: system-level instructions for the agent.
+- **Input/Output Schema**: structured I/O using registered Pydantic schemas.
+- **Database**: attach a database for the agent to use.
+- **Context Management**: configure session summary manager, enable session summaries, number of history runs, add history to context, and add session summary to context.
+- **Memory**: configure memory manager, enable agentic memory, update memory on run, and add memories to context.
+- **Knowledge**: configure knowledge, search knowledge, and add knowledge to context.
+- **Session State**: configure session state, add session state to context, and enable agentic state.
+
+<img
+  src="/images/agent-os-studio-create-agent.png"
+  alt="Create an agent in AgentOS Studio"
+  style={{ borderRadius: "8px" }}
+/>
 
 <Tip>
 Switch to the advanced JSON config editor for fine-grained control over agent settings.
@@ -31,14 +38,6 @@ Use Studio-built Agents in multiple ways:
 - **Add to Teams** for multi-agent collaboration
 - **Use in Workflows** as step executors for automation pipelines
 
-## Save and Run
-
-Once your agent is configured:
-
-1. **Save** your agent to persist it to the registry
-2. Navigate to the **Chat page** to interact with your agent
-3. Send messages and receive responses in real-time
-4. View tool calls, reasoning, and outputs as the agent works
 
 ## Code Equivalent
 

agent-os/studio/introduction.mdx

@@ -3,25 +3,36 @@
 description: "A visual editor in AgentOS to build Agents, Teams, and Workflows."
 ---
 
-Drag, drop, and orchestrate Agents, Teams, and Workflows on a live canvas to deploy production-ready agentic systems with AgentOS Studio.
+Build and orchestrate Agents, Teams, and Workflows on a live canvas to deploy production-ready agentic systems with AgentOS Studio.
 
 ## Concepts
 
-| Concept                                 | Description                                                                         |
-| --------------------------------------- | ----------------------------------------------------------------------------------- |
-| [Agents](/agent-os/studio/agents)       | Build and configure agents with models, tools, and instructions                     |
-| [Teams](/agent-os/studio/teams)         | Compose multi-agent teams with coordination modes                                   |
-| [Workflows](/agent-os/studio/workflows) | Design step-based workflows with conditions, loops, routers, and parallel execution |
-| [Registry](/agent-os/studio/registry)   | Browse and manage registered tools, models, databases, and schemas                  |
+**[Agents](/agent-os/studio/agents)**
+Build agent by giving it a model, tools, and instructions. Add knowledge and memory to ground its responses and remember context.
+
+**[Teams](/agent-os/studio/teams)**
+Build multi-agents team that works toward a shared goal. Choose how the leader coordinates with members using `coordinate`, `route`, `broadcast`, or `tasks` mode.
+
+**[Workflows](/agent-os/studio/workflows)**
+Orchestrate agents and teams into step-based pipelines. Control the flow with loops, conditions, routers, and parallel execution.
+
+use functions or cel expressions to evaluate conditions and selectors.
+
+**[Registry](/agent-os/studio/registry)**
+Add tools, models, databases, and schemas that Studio can use to build agents, teams, and workflows.
+
+Register agents and teams in the `Registry` to reuse them as members in Studio teams and as steps in Studio workflows.
+
+Register `knowledge`, `memory_managers`, and `session_summary_managers` for agents and teams to use.
 
 ## How It Works
 
 Studio connects to your running AgentOS instance and uses a Registry to populate available components.
 Build visually, test interactively, and publish when ready.
 
-1. Register your components in a `Registry`
+1. Register your tools, models, databases, and schemas in a `Registry`
 2. Pass the registry **and a database** to `AgentOS`
-3. Open Studio in the control plane to start building
+3. Open Studio in the [AgentOS Control Plane](https://os.agno.com/studio/agents) to start building
 
 ```python
 from agno.os import AgentOS
@@ -54,38 +65,70 @@
 
 ### 1. Build
 
-Create your agent, team, or workflow using the visual builder. Drag components from the Registry, configure properties, and wire everything together.
+Create your agent, team, or workflow using the visual builder. use tools, models, and knowledge bases from the Registry, add instructions and configure the settings.
+
+
+  <img
+    src="/images/agent-os-studio-create.png"
+    alt="Create an agent in Studio"
+  />
 
-### 2. Save Draft
 
-Save your work as a draft version. Drafts are not accessible via the API but can be tested, restored, and published later. You can save multiple draft versions to checkpoint your progress.
+
+### 2. Save Draft or publish directly
+
+- Save your work as a draft or publish directly. Drafts can be edited and updated. Drafts helps you test your component before publishing it.
+- Publish or Draft multiple versions to checkpoint your progress.
+  <img
+    src="/images/agent-os-studio-draft-publish-btn.png"
+    alt="Save draft or publish directly in Studio"
+    style={{ borderRadius: "8px" }}
+  />
 
 ### 3. Test
 
-Once saved, test your draft in the AgentOS Control Plane:
+Once saved, test your draft or published version in the AgentOS:
+
+- **Chat Page**: 
+  - Interact with your agent, team, or workflow in real-time
+  - run specific version of the component by selecting it in the dropdown.
+
+  <img
+    src="/images/agent-os-studio-chat-page-versioning.png"
+    alt="Run specific version of the component in the chat page"
+    style={{ borderRadius: "8px" }}
+  />      
 
-- **Chat Page**: Interact with your agent, team, or workflow in real-time
 - **View Traces**: Inspect tool calls, model responses, and reasoning for each run
 - **Debug Mode**: Enable verbose logging to troubleshoot issues
 
+
 <Warning>
   Before publishing, test and make sure your agent handles edge cases and
   unexpected inputs gracefully.
 </Warning>
 
-### 4. Publish
+### 4. Delete
 
-Move from draft to production with one click. Publish the visual blueprint of your agentic system after verification.
-Manage multiple versions of your system blueprint. Every published version is immediately
-accessible via a unique API endpoint. Set any version as _Current_ to make it the default for your production API.
+- Delete the component from the Studio.
 
 ### 5. Manage Versions
 
 Access the full version history for any agent, team, or workflow:
 
-- **Restore**: Load any previous version into the editor
+<img
+  src="/images/agent-os-studio-versions-page.png"
+  alt="Versions page in Studio"
+  style={{ borderRadius: "16px" }}
+/>
+- **Restore**: edit and update the draft version.
 - **Set Current**: Choose which published version is used by default when running via the API
-- **Delete**: Remove old versions you no longer need
+
+- only draft versions can be updated and edited in the Studio.
+- published versions are immutable and can only be updated by publishing a new version.
+- draft version cannot be set as current.
+- only draft versions can be deleted from versions page , published versions and current config cannot be deleted.
+
 
 <Tip>
   Use descriptive version labels like `v1.2-improved-instructions` or

agent-os/studio/registry.mdx

@@ -4,7 +4,33 @@
 description: "Register tools, models, databases, and schemas for use in AgentOS Studio."
 ---
 
-**The Registry manages non-serializable components (tools, models, databases, schemas, functions) that Studio depends on.**
+**The Registry manages non-serializable components (tools, models, databases, schemas, functions, etc.) that Studio depends on.**
+
+
+## Component Types
+
+- **Tools** : `Toolkit` instances, `Function` objects, or plain callables.
+- **Models** : model provider instances (OpenAI, Anthropic, etc.).
+- **Databases** : `BaseDb` instances for storage.
+- **Vector DBs** : `VectorDb` instances for knowledge bases.
+- **Schemas** : Pydantic `BaseModel` subclasses for structured I/O.
+- **Functions** : Python callables used as workflow evaluators, selectors, or executors.
+- **Knowledge** : `Knowledge` instances for RAG.
+- **Memory Managers** : `MemoryManager` instances for memory management.
+- **Session Summary Managers** : `SessionSummaryManager` instances for session summary management.
+- **Teams** : `Team` instances to reuse as members in teams and workflows.
+- **Agents** : `Agent` instances to reuse as members in teams and workflows.
+
+
+<img
+  src="/images/agent-os-studio-registry.png"
+  alt="Open Studio Registry from the Studio navigation"
+  style={{ borderRadius: "8px" }}
+/>
+
+
+
+example of registry configuration:
 
 ```python
 from agno.db.postgres import PostgresDb
@@ -25,6 +51,27 @@
     return "urgent" in input.lower()
 
 db = PostgresDb(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai", id="postgres_db")
+user_memory_manager = MemoryManager(
+    model=Claude(id="claude-opus-4-7"),
+    db=db,
+     additional_instructions="""
+    IMPORTANT: Don't store any memories about the user's name. Just say "The User" instead of referencing the user's name.
+    """,
+)
+concise_summary_manager = SessionSummaryManager(
+    model=OpenAIResponses(id="gpt-5-mini"),
+    session_summary_prompt=(
+        "Summarize the conversation in 3-5 bullet points focused on decisions, "
+        "open questions, and any follow-ups required."
+    ),
+    last_n_runs=10,
+)
+agent_knowledge = Knowledge(
+    name="Agent Knowledge",
+    description="Example knowledge base for agents",
+    vector_db=PgVector(table_name="agent_knowledge_documents", db_url=DB_URL),
+    contents_db=db,
+)
 
 registry = Registry(
     name="My Registry",
@@ -34,23 +81,14 @@
     vector_dbs=[PgVector(db_url="postgresql+psycopg://ai:ai@localhost:5532/ai", table_name="embeddings")],
     schemas=[InputSchema],
     functions=[custom_evaluator],
+    memory_managers=[user_memory_manager],
+    session_summary_managers=[concise_summary_manager],
+    knowledge=[agent_knowledge],
 )
 
 agent_os = AgentOS(id="my-app", registry=registry, db=db)
 app = agent_os.get_app()
 ```
-
-## Component Types
-
-| Type | Field | Description |
-|------|-------|-------------|
-| Tools | `tools` | `Toolkit` instances, `Function` objects, or plain callables |
-| Models | `models` | Model provider instances (OpenAI, Anthropic, etc.) |
-| Databases | `dbs` | `BaseDb` instances for storage |
-| Vector DBs | `vector_dbs` | `VectorDb` instances for knowledge bases |
-| Schemas | `schemas` | Pydantic `BaseModel` subclasses for structured I/O |
-| Functions | `functions` | Python callables used as workflow evaluators, selectors, or executors |
-
 ## Registry API
 
 The registry exposes a `GET /registry` endpoint through AgentOS with filtering and pagination.
@@ -76,6 +114,11 @@
 | Vector DB | `collection`, `table_name` |
 | Schema | JSON schema definition |
 | Function | `signature`, `parameters` |
+| Knowledge | `name`, `description`, `vector_db`, `contents_db` |
+| Memory Manager | `model`, `additional_instructions`, `db` |
+| Session Summary Manager | `model`, `session_summary_prompt`, `last_n_runs` |
+| Team | `name`, `type`, `id`, `metadata` |
+| Agent | `name`, `type`, `id`, `metadata` |
 
 ## Developer Resources
 

agent-os/studio/teams.mdx

@@ -9,14 +9,33 @@ No code required. Drag agents onto the canvas, configure coordination, and run t
 
 ## Creating Teams
 
-Create a new team by dragging agents from your [Registry](/agent-os/studio/registry) and configuring the team settings:
-
-| Setting | Description |
-|---------|-------------|
-| **Members** | Drag and drop agents to include in the team |
-| **Mode** | Coordination mode: `coordinate`, `route`, or `collaborate` |
-| **Instructions** | Team-level instructions for the leader agent |
-| **Success Criteria** | Define when the team's task is complete |
+Create a new team by using existing agents and teams from your Registry or built in Studio, and configuring the team settings:
+
+- **Team Members and Execution**: select agents or teams to include as members, and set the team mode and delegation behavior. read more about [team members and execution](/agent-os/studio/teams#team-members-and-execution) here.
+- **Instructions**: team-level instructions for the leader agent.
+- **Success Criteria**: define when the team's task is complete.
+- **Context Management**: configure session summary manager, enable session summaries, number of history runs, add history to context, and add session summary to context.
+- **Memory**: configure memory manager, enable agentic memory, update memory on run, and add memories to context.
+- **Knowledge**: configure knowledge, search knowledge, and add knowledge to context.
+- **Session State**: configure session state, add session state to context, and enable agentic state.
+
+<img
+  src="/images/agent-os-studio-create-team.png"
+  alt="Create a team in AgentOS Studio"
+  style={{ borderRadius: "8px" }}
+/>
+
+### Team Members and Execution
+
+- **Members**: select the agents or teams to include as members.
+- **Team Mode** _(optional)_: controls how the team leader coordinates work with member agents:
+  - **None**
+  - **Coordinate** (default)
+  - **Route**
+  - **Broadcast**
+  - **Tasks**
+- **Respond Directly**: let the team leader respond on its own instead of delegating.
+- **Delegate to All Members**: send the task to every member at once.
 
 <Tip>
 Agents can be created directly in Studio or registered via code—both are available for team composition.
@@ -29,15 +48,6 @@ Teams built in Studio can be used in multiple ways:
 - **Chat directly** with the team via the Chat page
 - **Use in Workflows** as step executors for complex automation
 
-## Save and Run
-
-Once your team is configured:
-
-1. **Save** your team to persist it to the registry
-2. Navigate to the **Chat page** to interact with your team
-3. Send tasks and watch agents collaborate in real-time
-4. View individual agent contributions and coordination flow
-
 ## Code Equivalent
 
 A team instance created in Studio directly maps to the SDK `Team` class:

agent-os/studio/workflows.mdx

@@ -13,7 +13,7 @@ Drag a step onto the canvas and configure its executor type in the properties pa
 |---------------|-------------|
 | **Agent** | Execute the step using a registered agent from your OS |
 | **Team** | Delegate the step to a multi-agent team for collaborative execution |
-| **Custom Executor** | Use a custom function or script for specialized logic |
+| **Custom Executor** | Use a custom function  |
 
 ## Step Types
 
@@ -28,6 +28,12 @@ Beyond basic steps, you can build complex workflows using these step types:
 | `Router` | Select a step based on a selector function or CEL expression |
 | `Parallel` | Execute multiple steps concurrently |
 
+<img
+  src="/images/agent-os-studio-workflow-create.png"
+  alt="Create a workflow in AgentOS Studio"
+  style={{ borderRadius: "8px" }}
+/>
+
 These step types can be nested and composed together to build sophisticated automation pipelines while maintaining visual clarity.
 
 ### Configuring Complex Steps
@@ -55,21 +61,21 @@ condition = Condition(
     evaluator=is_apple,
 )
 ```
+<img
+  src="/images/agent-os-studio-workflow-cel.png"
+  alt="Configure a CEL expression in AgentOS Studio"
+
+  style={{ clipPath: "inset(0 10px 0 0)" }}
+/>
+
 
 ## CEL Expressions
 
 Workflow steps support [CEL (Common Expression Language)](https://github.com/google/cel-spec) as an alternative to Python functions for evaluators, end conditions, and selectors. CEL expressions are strings that can be serialized and edited directly in Studio without code.
 
 See [CEL Expressions](/agent-os/studio/cel-expressions) for full usage, context variables, and examples.
 
-## Save and Run
-
-Once your workflow is designed:
 
-1. **Save** your workflow to persist it to the registry
-2. Navigate to the **Chat page** to run your workflow interactively
-3. Provide input and watch the workflow execute step-by-step
-4. View results and logs for each step in real-time
 
 ## Developer Resources