Merge branch 'main' into release/v2.2.6

Author: ysolanky

CONTRIBUTING.md

@@ -95,10 +95,22 @@ Make sure all tests pass before submitting your pull request. If you add new fea
 4. If the Model provider does not support the OpenAI API spec:
    - Reach out to us on [Discord](https://discord.gg/4MtYHHrgA8) or open an issue to discuss the best way to integrate your LLM provider.
    - Checkout [`agno/models/anthropic/claude.py`](https://github.com/agno-agi/agno/blob/main/libs/agno/agno/models/anthropic/claude.py) or [`agno/models/cohere/chat.py`](https://github.com/agno-agi/agno/blob/main/libs/agno/agno/models/cohere/chat.py) for inspiration.
-5. Add a recipe for using your Model provider under `cookbook/models/<your_model>`.
+5. Add your model provider to `libs/agno/agno/models/utils.py`:
+   - Add a new `elif` clause in the `get_model()` function with your provider name
+   - Use the provider name that matches your module directory (e.g., "meta" for `models/meta/`)
+   - Import and return your Model class with the provided `model_id`
+   - This enables users to use the string format: `model="yourprovider:model-name"`
+   - Example:
+     ```python
+     elif provider == "yourprovider":
+         from agno.models.yourprovider import YourModel
+         return YourModel(id=model_id)
+     ```
+6. Add a recipe for using your Model provider under `cookbook/models/<your_model>`.
    - Checkout [`agno/cookbook/models/aws/claude`](https://github.com/agno-agi/agno/tree/main/cookbook/models/aws/claude) for an example.
-6. Important: Format and validate your code by running `./scripts/format.sh` and `./scripts/validate.sh`.
-7. Submit a pull request.
+   - Show both the model class and string syntax in your examples
+7. Important: Format and validate your code by running `./scripts/format.sh` and `./scripts/validate.sh`.
+8. Submit a pull request.
 
 ## Adding a new Tool.
 

cookbook/agent_os/agent_with_input_schema.py

@@ -1,11 +1,11 @@
 from typing import List
 
 from agno.agent import Agent
+from agno.db.sqlite import SqliteDb
 from agno.models.openai import OpenAIChat
 from agno.os import AgentOS
 from agno.tools.hackernews import HackerNewsTools
 from pydantic import BaseModel, Field
-from agno.db.sqlite import SqliteDb
 
 
 class ResearchTopic(BaseModel):

cookbook/agent_os/team_with_input_schema.py

@@ -9,13 +9,14 @@
 from typing import List
 
 from agno.agent import Agent
+from agno.db.sqlite import SqliteDb
 from agno.models.openai import OpenAIChat
 from agno.os import AgentOS
 from agno.team.team import Team
 from agno.tools.duckduckgo import DuckDuckGoTools
 from agno.tools.hackernews import HackerNewsTools
 from pydantic import BaseModel, Field
-from agno.db.sqlite import SqliteDb
+
 
 class ResearchProject(BaseModel):
     """Structured research project with validation requirements."""
@@ -28,9 +29,7 @@ class ResearchProject(BaseModel):
     depth_level: str = Field(
         description="Research depth level", pattern="^(basic|intermediate|advanced)$"
     )
-    max_sources: int = Field(
-        description="Maximum number of sources to use", default=10
-    )
+    max_sources: int = Field(description="Maximum number of sources to use", default=10)
     include_recent_only: bool = Field(
         description="Whether to focus only on recent sources", default=True
     )

cookbook/agents/other/agent_model_string.py

@@ -0,0 +1,10 @@
+"""Example showing how to set the model for an Agent using a model string"""
+
+from agno.agent import Agent
+
+# Model strings follow the format "{provider}:{model_id}", for example:
+model_string = "openai:gpt-4o"
+
+agent = Agent(model=model_string, markdown=True)
+
+agent.print_response("Share a 2 sentence horror story")

cookbook/agents/state/session_state_basic.py

@@ -1,4 +1,4 @@
-from agno.agent import Agent
+from agno.agent import Agent, RunOutput  # noqa
 from agno.db.sqlite import SqliteDb
 from agno.models.openai import OpenAIChat
 
@@ -24,3 +24,7 @@ def add_item(session_state, item: str) -> str:
 # Example usage
 agent.print_response("Add milk, eggs, and bread to the shopping list", stream=True)
 print(f"Final session state: {agent.get_session_state()}")
+
+# Alternatively,
+# response: RunOutput = agent.run("Add milk, eggs, and bread to the shopping list")
+# print(f"Final session state: {response.session_state}")

cookbook/agents/state/session_state_in_event.py

@@ -0,0 +1,30 @@
+from agno.agent import Agent, RunCompletedEvent
+from agno.db.sqlite import SqliteDb
+from agno.models.openai import OpenAIChat
+
+
+def add_item(session_state, item: str) -> str:
+    """Add an item to the shopping list."""
+    session_state["shopping_list"].append(item)  # type: ignore
+    return f"The shopping list is now {session_state['shopping_list']}"  # type: ignore
+
+
+# Create an Agent that maintains state
+agent = Agent(
+    model=OpenAIChat(id="gpt-4o-mini"),
+    # Initialize the session state with a counter starting at 0 (this is the default session state for all users)
+    session_state={"shopping_list": []},
+    db=SqliteDb(db_file="tmp/agents.db"),
+    tools=[add_item],
+    # You can use variables from the session state in the instructions
+    instructions="Current state (shopping list) is: {shopping_list}",
+    markdown=True,
+)
+
+# Example usage
+response = agent.run(
+    "Add milk, eggs, and bread to the shopping list", stream=True, stream_events=True
+)
+for event in response:
+    if isinstance(event, RunCompletedEvent):
+        print(f"Session state: {event.session_state}")

cookbook/examples/teams/multi_purpose_team.py

@@ -123,7 +123,7 @@
 
 agent_team = Team(
     name="Agent Team",
-    model=Claude(id="claude-3-5-sonnet-latest"),
+    model=Claude(id="claude-3-7-sonnet-latest"),
     members=[
         web_agent,
         finance_agent,

cookbook/teams/other/team_model_string.py

@@ -0,0 +1,30 @@
+from agno.agent import Agent
+from agno.team import Team
+from agno.tools.duckduckgo import DuckDuckGoTools
+
+# Model strings follow the format "{provider}:{model_id}", for example:
+model_string = "openai:gpt-4o-mini"
+
+# Create a research team
+team = Team(
+    model=model_string,
+    members=[
+        Agent(
+            model=model_string,
+            name="Sarah",
+            role="Data Researcher",
+            tools=[DuckDuckGoTools()],
+            instructions="Focus on gathering and analyzing data",
+        ),
+        Agent(
+            model=model_string,
+            name="Mike",
+            role="Technical Writer",
+            instructions="Create clear, concise summaries",
+        ),
+    ],
+)
+
+team.print_response(
+    "Search for latest news about the latest AI models",
+)