Release 1.3.2 (#2851)

# Changelog

## New Features:

- **Redis Memory DB**: Added Redis as a storage provider for `Memory`.
See here.

## Improvements:

- **Memory Updates**: Various performance improvements made and
convenience functions added:
- `agent.get_session_summary()` → Use to get the previous session
summary from the agent.
- `agent.get_user_memories()` → Use to get the current user’s memories.
- You can also add additional instructions to the `MemoryManager` or
`SessionSummarizer`.
- **Confluence Bypass SSL Verification**: If required, you can now skip
SSL verification for Confluence connections.
- **More Flexibility On Team Prompts**: Added
`add_member_tools_to_system_message` to remove the member tool names
from the system message given to the team leader, which allows
flexibility to make teams transfer functions work in more cases.

## Bug Fixes:

- **LiteLLM Streaming Tool Calls**: Fixed issues with tool call
streaming in LiteLLM.
- **E2B Casing Issue**: Fixed issues with parsed Python code that would
make some values lowercase.
- **Team Member IDs**: Fixed edge-cases with team member IDs causing
teams to break.

---------

Co-authored-by: Yash Pratap Solanky <101447028+ysolanky@users.noreply.github.com>

Author: dirkbrnd

cookbook/agent_concepts/memory/05_agent_with_memory.py

@@ -64,6 +64,7 @@
 session_run = memory.runs[session_id][-1]
 print_chat_history(session_run)
 
-memories = memory.get_user_memories(user_id=john_doe_id)
+# You can also get the user memories from the agent
+memories = agent.get_user_memories(user_id=john_doe_id)
 print("John Doe's memories:")
 pprint(memories)

cookbook/playground/teams_demo.py

@@ -25,7 +25,6 @@
     name="File Upload Agent",
     agent_id="file-upload-agent",
     role="Answer questions about the uploaded files",
-    model=Claude(id="claude-3-7-sonnet-latest"),
     storage=PostgresStorage(
         table_name="agent_sessions", db_url=db_url, auto_upgrade_schema=True
     ),
@@ -41,7 +40,6 @@
 
 video_agent = Agent(
     name="Video Understanding Agent",
-    model=Gemini(id="gemini-2.0-flash"),
     agent_id="video-understanding-agent",
     role="Answer questions about video files",
     storage=PostgresStorage(
@@ -59,7 +57,6 @@
     name="Audio Understanding Agent",
     agent_id="audio-understanding-agent",
     role="Answer questions about audio files",
-    model=OpenAIChat(id="gpt-4o-audio-preview"),
     storage=PostgresStorage(
         table_name="agent_sessions", db_url=db_url, auto_upgrade_schema=True
     ),
@@ -74,7 +71,6 @@
 web_agent = Agent(
     name="Web Agent",
     role="Search the web for information",
-    model=OpenAIChat(id="gpt-4o"),
     tools=[DuckDuckGoTools()],
     agent_id="web_agent",
     instructions=[
@@ -93,7 +89,6 @@
     name="Finance Agent",
     role="Get financial data",
     agent_id="finance_agent",
-    model=OpenAIChat(id="gpt-4o"),
     tools=[
         YFinanceTools(stock_price=True, analyst_recommendations=True, company_info=True)
     ],
@@ -114,7 +109,6 @@
 simple_agent = Agent(
     name="Simple Agent",
     role="Simple agent",
-    model=OpenAIChat(id="gpt-4o"),
     instructions=["You are a simple agent"],
     memory=memory,
     enable_user_memories=True,
@@ -123,7 +117,6 @@
 research_agent = Agent(
     name="Research Agent",
     role="Research agent",
-    model=OpenAIChat(id="gpt-4o"),
     instructions=["You are a research agent"],
     tools=[DuckDuckGoTools(), ExaTools()],
     agent_id="research_agent",
@@ -135,7 +128,6 @@
     name="Research Team",
     description="A team of agents that research the web",
     members=[research_agent, simple_agent],
-    model=OpenAIChat(id="gpt-4o"),
     mode="coordinate",
     team_id="research_team",
     success_criteria=dedent("""\
@@ -191,7 +183,6 @@
         audio_agent,
         video_agent,
     ],
-    model=OpenAIChat(id="gpt-4o"),
     mode="route",
     team_id="financial_news_team",
     instructions=[

cookbook/teams/memory/03_user_memories.py

@@ -113,5 +113,5 @@
 session_run = memory.runs[session_id][-1]
 # -*- Print chat history
 print_chat_history(session_run)
-# -*- Print team memory
-print_team_memory(user_id, memory.get_user_memories(user_id))
+# -*- Print team memory (you can also get the user memories from the team)
+print_team_memory(user_id, team.get_user_memories(user_id))

cookbook/teams/memory/06_team_session_summaries.py

@@ -86,7 +86,6 @@
         )
     )
 
-    session_summary = memory.get_session_summary(
-        user_id=user_id, session_id=session_id_2
-    )
+    # You can also get the session summary from the team
+    session_summary = team.get_session_summary(user_id=user_id, session_id=session_id_2)
     print("Session Summary: ", session_summary.summary)

libs/agno/agno/agent/agent.py

@@ -503,7 +503,24 @@ def set_monitoring(self) -> None:
         if telemetry_env is not None:
             self.telemetry = telemetry_env.lower() == "true"
 
+    def set_default_model(self):
+        # Use the default Model (OpenAIChat) if no model is provided
+        if self.model is None:
+            try:
+                from agno.models.openai import OpenAIChat
+            except ModuleNotFoundError as e:
+                log_exception(e)
+                log_error(
+                    "Agno agents use `openai` as the default model provider. "
+                    "Please provide a `model` or install `openai`."
+                )
+                exit(1)
+
+            log_info("Setting default model to OpenAI Chat")
+            self.model = OpenAIChat(id="gpt-4o")
+
     def initialize_agent(self) -> None:
+        self.set_default_model()
         self.set_storage_mode()
         self.set_debug()
         self.set_agent_id()
@@ -1906,18 +1923,9 @@ def add_tools_to_model(
                 model.set_functions(functions=self._functions_for_model)
 
     def update_model(self, session_id: str, async_mode: bool = False, user_id: Optional[str] = None) -> None:
-        # Use the default Model (OpenAIChat) if no model is provided
-        if self.model is None:
-            try:
-                from agno.models.openai import OpenAIChat
-            except ModuleNotFoundError as e:
-                log_exception(e)
-                log_error(
-                    "Agno agents use `openai` as the default model provider. "
-                    "Please provide a `model` or install `openai` using `pip install openai -U`."
-                )
-                exit(1)
-            self.model = OpenAIChat(id="gpt-4o")
+        self.set_default_model()
+        
+        self.model = cast(Model, self.model)
 
         # Update the response_format on the Model
         if self.response_model is None:
@@ -2885,6 +2893,21 @@ def get_session_summary(self, session_id: Optional[str] = None, user_id: Optiona
         else:
             raise ValueError(f"Memory type {type(self.memory)} not supported")
 
+    def get_user_memories(self, user_id: Optional[str] = None):
+        """Get the user memories for the given user ID."""
+        if self.memory is None:
+            return None
+        user_id = user_id if user_id is not None else self.user_id
+        if user_id is None:
+            user_id = "default"
+
+        if isinstance(self.memory, Memory):
+            return self.memory.get_user_memories(user_id=user_id)
+        elif isinstance(self.memory, AgentMemory):
+            raise ValueError("AgentMemory does not support get_user_memories")
+        else:
+            raise ValueError(f"Memory type {type(self.memory)} not supported")
+
     def deep_copy(self, *, update: Optional[Dict[str, Any]] = None) -> Agent:
         """Create and return a deep copy of this Agent, optionally updating fields.
 

libs/agno/agno/eval/perf.py

@@ -210,6 +210,7 @@ def _measure_time(self) -> float:
         # Return the elapsed time
         return timer.elapsed
 
+        
     def _measure_memory(self, baseline: float) -> float:
         """
         Measures peak memory usage using tracemalloc.
@@ -227,7 +228,7 @@ def _measure_memory(self, baseline: float) -> float:
         tracemalloc.stop()
 
         # Convert to MiB and subtract baseline
-        peak_mib = peak / (1024 * 1024)
+        peak_mib = peak / 1024 / 1024
         adjusted_usage = max(0, peak_mib - baseline)
 
         if self.debug_mode:
@@ -251,7 +252,7 @@ def empty_func():
             empty_func()
             _, peak = tracemalloc.get_traced_memory()
             tracemalloc.stop()
-            results.append(peak / (1024 * 1024))
+            results.append(peak / 1024 / 1024)
 
         return sum(results) / len(results) if results else 0
 

libs/agno/agno/models/azure/openai_chat.py

@@ -49,6 +49,9 @@ class AzureOpenAI(OpenAILike):
     azure_ad_token: Optional[str] = None
     azure_ad_token_provider: Optional[Any] = None
 
+    default_headers: Optional[Dict[str, str]] = None
+    default_query: Optional[Dict[str, Any]] = None
+
     client: Optional[AzureOpenAIClient] = None
     async_client: Optional[AsyncAzureOpenAIClient] = None
 
@@ -69,7 +72,11 @@ def _get_client_params(self) -> Dict[str, Any]:
             "azure_ad_token_provider": self.azure_ad_token_provider,
             "http_client": self.http_client,
         }
-
+        if self.default_headers is not None:
+            _client_params["default_headers"] = self.default_headers
+        if self.default_query is not None:
+            _client_params["default_query"] = self.default_query
+            
         _client_params.update({k: v for k, v in params_mapping.items() if v is not None})
         if self.client_params:
             _client_params.update(self.client_params)

libs/agno/agno/playground/playground.py

@@ -36,13 +36,16 @@ def __init__(
 
         if self.agents:
             for agent in self.agents:
-                if not agent.agent_id:
-                    agent.agent_id = generate_id(agent.name)
+                agent.initialize_agent()
 
         if self.teams:
             for team in self.teams:
-                if not team.team_id:
-                    team.team_id = generate_id(team.name)
+                team.initialize_team()
+                for member in team.members:
+                    if isinstance(member, Agent):
+                        member.initialize_agent()
+                    elif isinstance(member, Team):
+                        member.initialize_team()
 
         if self.workflows:
             for workflow in self.workflows: