v0.1.5 (#122)

* models - openai - argument none (#97)

* docs(readme): add open PRs badge + link to samples repo + change 'Docs' to 'Documentation' (#100)

* docs(readme): add logo (#101)

* docs(readme): add logo, title, badges, links to other repos, standardize headings (#102)

* style(readme): use dark logo for clearer visibility when system is using light color scheme (#104)

* fix(readme): use logo that changes color automatically depending on user's color preference scheme (#105)

* feat(handlers): add reasoning text to callback handler and related tests (#109)

* feat(handlers): add reasoning text to callback handler and related tests

* feat(handlers): removed redundant comment in .gitignore file

* feat(handlers): Updated reasoningText type as (Optional[str]

* feat: Add dynamic system prompt override functionality (#108)

* Modularizing Event Loop (#106)

* fix(telemetry): fix agent span start and end when using Agent.stream_async() (#119)

* feat: Update SlidingWindowConversationManager (#120)

* v0.1.5

---------

Co-authored-by: Patrick Gray <[email protected]>
Co-authored-by: Gokhan (Joe) Gultekin <[email protected]>
Co-authored-by: Shubham Raut <[email protected]>
Co-authored-by: fede-dash <[email protected]>
Co-authored-by: Nick Clegg <[email protected]>

Author: 6 people

.gitignore

@@ -7,3 +7,4 @@ __pycache__*
 .pytest_cache
 .ruff_cache
 *.bak
+.vscode

README.md

@@ -1,23 +1,34 @@
-# Strands Agents
-
 <div align="center">
+  <div>
+    <a href="https://strandsagents.com">
+      <img src="https://strandsagents.com/latest/assets/logo-auto.svg" alt="Strands Agents" width="55px" height="105px">
+    </a>
+  </div>
+
+  <h1>
+    Strands Agents
+  </h1>
+
   <h2>
     A model-driven approach to building AI agents in just a few lines of code.
   </h2>
 
   <div align="center">
     <a href="https://github.com/strands-agents/sdk-python/graphs/commit-activity"><img alt="GitHub commit activity" src="https://img.shields.io/github/commit-activity/m/strands-agents/sdk-python"/></a>
     <a href="https://github.com/strands-agents/sdk-python/issues"><img alt="GitHub open issues" src="https://img.shields.io/github/issues/strands-agents/sdk-python"/></a>
+    <a href="https://github.com/strands-agents/sdk-python/pulls"><img alt="GitHub open pull requests" src="https://img.shields.io/github/issues-pr/strands-agents/sdk-python"/></a>
     <a href="https://github.com/strands-agents/sdk-python/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/github/license/strands-agents/sdk-python"/></a>
     <a href="https://pypi.org/project/strands-agents/"><img alt="PyPI version" src="https://img.shields.io/pypi/v/strands-agents"/></a>
     <a href="https://python.org"><img alt="Python versions" src="https://img.shields.io/pypi/pyversions/strands-agents"/></a>
   </div>
 
   <p>
-    <a href="https://strandsagents.com/">Docs</a>
-    ◆ <a href="https://github.com/strands-agents/docs/tree/main/docs/examples">Samples</a>
+    <a href="https://strandsagents.com/">Documentation</a>
+    ◆ <a href="https://github.com/strands-agents/samples">Samples</a>
+    ◆ <a href="https://github.com/strands-agents/sdk-python">Python SDK</a>
     ◆ <a href="https://github.com/strands-agents/tools">Tools</a>
     ◆ <a href="https://github.com/strands-agents/agent-builder">Agent Builder</a>
+    ◆ <a href="https://github.com/strands-agents/mcp-server">MCP Server</a>
   </p>
 </div>
 
@@ -26,7 +37,7 @@ Strands Agents is a simple yet powerful SDK that takes a model-driven approach t
 ## Feature Overview
 
 - **Lightweight & Flexible**: Simple agent loop that just works and is fully customizable
-- **Model Agnostic**: Support for Amazon Bedrock, Anthropic, Llama, Ollama, and custom providers
+- **Model Agnostic**: Support for Amazon Bedrock, Anthropic, LiteLLM, Llama, Ollama, OpenAI, and custom providers
 - **Advanced Capabilities**: Multi-agent systems, autonomous agents, and streaming support
 - **Built-in MCP**: Native support for Model Context Protocol (MCP) servers, enabling access to thousands of pre-built tools
 
@@ -138,6 +149,7 @@ Built-in providers:
  - [LiteLLM](https://strandsagents.com/latest/user-guide/concepts/model-providers/litellm/)
  - [LlamaAPI](https://strandsagents.com/latest/user-guide/concepts/model-providers/llamaapi/)
  - [Ollama](https://strandsagents.com/latest/user-guide/concepts/model-providers/ollama/)
+ - [OpenAI](https://strandsagents.com/latest/user-guide/concepts/model-providers/openai/)
 
 Custom providers can be implemented using [Custom Providers](https://strandsagents.com/latest/user-guide/concepts/model-providers/custom_model_provider/)
 
@@ -165,9 +177,9 @@ For detailed guidance & examples, explore our documentation:
 - [API Reference](https://strandsagents.com/latest/api-reference/agent/)
 - [Production & Deployment Guide](https://strandsagents.com/latest/user-guide/deploy/operating-agents-in-production/)
 
-## Contributing
+## Contributing ❤️
 
-We welcome contributions! See our [Contributing Guide](https://github.com/strands-agents/sdk-python/blob/main/CONTRIBUTING.md) for details on:
+We welcome contributions! See our [Contributing Guide](CONTRIBUTING.md) for details on:
 - Reporting bugs & features
 - Development setup
 - Contributing via Pull Requests
@@ -178,6 +190,10 @@ We welcome contributions! See our [Contributing Guide](https://github.com/strand
 
 This project is licensed under the Apache License 2.0 - see the [LICENSE](LICENSE) file for details.
 
+## Security
+
+See [CONTRIBUTING](CONTRIBUTING.md#security-issue-notifications) for more information.
+
 ## ⚠️ Preview Status
 
 Strands Agents is currently in public preview. During this period:

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "hatchling.build"
 
 [project]
 name = "strands-agents"
-version = "0.1.4"
+version = "0.1.5"
 description = "A model-driven approach to building AI agents in just a few lines of code"
 readme = "README.md"
 requires-python = ">=3.10"

src/strands/agent/agent.py

@@ -328,27 +328,17 @@ def __call__(self, prompt: str, **kwargs: Any) -> AgentResult:
                 - metrics: Performance metrics from the event loop
                 - state: The final state of the event loop
         """
-        model_id = self.model.config.get("model_id") if hasattr(self.model, "config") else None
-
-        self.trace_span = self.tracer.start_agent_span(
-            prompt=prompt,
-            model_id=model_id,
-            tools=self.tool_names,
-            system_prompt=self.system_prompt,
-            custom_trace_attributes=self.trace_attributes,
-        )
+        self._start_agent_trace_span(prompt)
 
         try:
             # Run the event loop and get the result
             result = self._run_loop(prompt, kwargs)
 
-            if self.trace_span:
-                self.tracer.end_agent_span(span=self.trace_span, response=result)
+            self._end_agent_trace_span(response=result)
 
             return result
         except Exception as e:
-            if self.trace_span:
-                self.tracer.end_agent_span(span=self.trace_span, error=e)
+            self._end_agent_trace_span(error=e)
 
             # Re-raise the exception to preserve original behavior
             raise
@@ -383,6 +373,8 @@ async def stream_async(self, prompt: str, **kwargs: Any) -> AsyncIterator[Any]:
                     yield event["data"]
             ```
         """
+        self._start_agent_trace_span(prompt)
+
         _stop_event = uuid4()
 
         queue = asyncio.Queue[Any]()
@@ -400,8 +392,10 @@ def target_callback() -> None:
             nonlocal kwargs
 
             try:
-                self._run_loop(prompt, kwargs, supplementary_callback_handler=queuing_callback_handler)
-            except BaseException as e:
+                result = self._run_loop(prompt, kwargs, supplementary_callback_handler=queuing_callback_handler)
+                self._end_agent_trace_span(response=result)
+            except Exception as e:
+                self._end_agent_trace_span(error=e)
                 enqueue(e)
             finally:
                 enqueue(_stop_event)
@@ -414,7 +408,7 @@ def target_callback() -> None:
                 item = await queue.get()
                 if item == _stop_event:
                     break
-                if isinstance(item, BaseException):
+                if isinstance(item, Exception):
                     raise item
                 yield item
         finally:
@@ -457,27 +451,28 @@ def _execute_event_loop_cycle(self, callback_handler: Callable, kwargs: dict[str
         Returns:
             The result of the event loop cycle.
         """
-        kwargs.pop("agent", None)
-        kwargs.pop("model", None)
-        kwargs.pop("system_prompt", None)
-        kwargs.pop("tool_execution_handler", None)
-        kwargs.pop("event_loop_metrics", None)
-        kwargs.pop("callback_handler", None)
-        kwargs.pop("tool_handler", None)
-        kwargs.pop("messages", None)
-        kwargs.pop("tool_config", None)
+        # Extract parameters with fallbacks to instance values
+        system_prompt = kwargs.pop("system_prompt", self.system_prompt)
+        model = kwargs.pop("model", self.model)
+        tool_execution_handler = kwargs.pop("tool_execution_handler", self.thread_pool_wrapper)
+        event_loop_metrics = kwargs.pop("event_loop_metrics", self.event_loop_metrics)
+        callback_handler_override = kwargs.pop("callback_handler", callback_handler)
+        tool_handler = kwargs.pop("tool_handler", self.tool_handler)
+        messages = kwargs.pop("messages", self.messages)
+        tool_config = kwargs.pop("tool_config", self.tool_config)
+        kwargs.pop("agent", None)  # Remove agent to avoid conflicts
 
         try:
             # Execute the main event loop cycle
             stop_reason, message, metrics, state = event_loop_cycle(
-                model=self.model,
-                system_prompt=self.system_prompt,
-                messages=self.messages,  # will be modified by event_loop_cycle
-                tool_config=self.tool_config,
-                callback_handler=callback_handler,
-                tool_handler=self.tool_handler,
-                tool_execution_handler=self.thread_pool_wrapper,
-                event_loop_metrics=self.event_loop_metrics,
+                model=model,
+                system_prompt=system_prompt,
+                messages=messages,  # will be modified by event_loop_cycle
+                tool_config=tool_config,
+                callback_handler=callback_handler_override,
+                tool_handler=tool_handler,
+                tool_execution_handler=tool_execution_handler,
+                event_loop_metrics=event_loop_metrics,
                 agent=self,
                 event_loop_parent_span=self.trace_span,
                 **kwargs,
@@ -488,8 +483,8 @@ def _execute_event_loop_cycle(self, callback_handler: Callable, kwargs: dict[str
         except ContextWindowOverflowException as e:
             # Try reducing the context size and retrying
 
-            self.conversation_manager.reduce_context(self.messages, e=e)
-            return self._execute_event_loop_cycle(callback_handler, kwargs)
+            self.conversation_manager.reduce_context(messages, e=e)
+            return self._execute_event_loop_cycle(callback_handler_override, kwargs)
 
     def _record_tool_execution(
         self,
@@ -545,3 +540,43 @@ def _record_tool_execution(
         messages.append(tool_use_msg)
         messages.append(tool_result_msg)
         messages.append(assistant_msg)
+
+    def _start_agent_trace_span(self, prompt: str) -> None:
+        """Starts a trace span for the agent.
+
+        Args:
+            prompt: The natural language prompt from the user.
+        """
+        model_id = self.model.config.get("model_id") if hasattr(self.model, "config") else None
+
+        self.trace_span = self.tracer.start_agent_span(
+            prompt=prompt,
+            model_id=model_id,
+            tools=self.tool_names,
+            system_prompt=self.system_prompt,
+            custom_trace_attributes=self.trace_attributes,
+        )
+
+    def _end_agent_trace_span(
+        self,
+        response: Optional[AgentResult] = None,
+        error: Optional[Exception] = None,
+    ) -> None:
+        """Ends a trace span for the agent.
+
+        Args:
+            span: The span to end.
+            response: Response to record as a trace attribute.
+            error: Error to record as a trace attribute.
+        """
+        if self.trace_span:
+            trace_attributes: Dict[str, Any] = {
+                "span": self.trace_span,
+            }
+
+            if response:
+                trace_attributes["response"] = response
+            if error:
+                trace_attributes["error"] = error
+
+            self.tracer.end_agent_span(**trace_attributes)

src/strands/agent/conversation_manager/sliding_window_conversation_manager.py

@@ -1,12 +1,10 @@
 """Sliding window conversation history management."""
 
-import json
 import logging
-from typing import List, Optional, cast
+from typing import Optional
 
-from ...types.content import ContentBlock, Message, Messages
+from ...types.content import Message, Messages
 from ...types.exceptions import ContextWindowOverflowException
-from ...types.tools import ToolResult
 from .conversation_manager import ConversationManager
 
 logger = logging.getLogger(__name__)
@@ -110,8 +108,9 @@ def _remove_dangling_messages(self, messages: Messages) -> None:
     def reduce_context(self, messages: Messages, e: Optional[Exception] = None) -> None:
         """Trim the oldest messages to reduce the conversation context size.
 
-        The method handles special cases where tool results need to be converted to regular content blocks to maintain
-        conversation coherence after trimming.
+        The method handles special cases where trimming the messages leads to:
+         - toolResult with no corresponding toolUse
+         - toolUse with no corresponding toolResult
 
         Args:
             messages: The messages to reduce.
@@ -126,52 +125,24 @@ def reduce_context(self, messages: Messages, e: Optional[Exception] = None) -> N
         # If the number of messages is less than the window_size, then we default to 2, otherwise, trim to window size
         trim_index = 2 if len(messages) <= self.window_size else len(messages) - self.window_size
 
-        # Throw if we cannot trim any messages from the conversation
-        if trim_index >= len(messages):
-            raise ContextWindowOverflowException("Unable to trim conversation context!") from e
-
-        # If the message at the cut index has ToolResultContent, then we map that to ContentBlock. This gets around the
-        # limitation of needing ToolUse and ToolResults to be paired.
-        if any("toolResult" in content for content in messages[trim_index]["content"]):
-            if len(messages[trim_index]["content"]) == 1:
-                messages[trim_index]["content"] = self._map_tool_result_content(
-                    cast(ToolResult, messages[trim_index]["content"][0]["toolResult"])
+        # Find the next valid trim_index
+        while trim_index < len(messages):
+            if (
+                # Oldest message cannot be a toolResult because it needs a toolUse preceding it
+                any("toolResult" in content for content in messages[trim_index]["content"])
+                or (
+                    # Oldest message can be a toolUse only if a toolResult immediately follows it.
+                    any("toolUse" in content for content in messages[trim_index]["content"])
+                    and trim_index + 1 < len(messages)
+                    and not any("toolResult" in content for content in messages[trim_index + 1]["content"])
                 )
-
-            # If there is more content than just one ToolResultContent, then we cannot cut at this index.
+            ):
+                trim_index += 1
             else:
-                raise ContextWindowOverflowException("Unable to trim conversation context!") from e
+                break
+        else:
+            # If we didn't find a valid trim_index, then we throw
+            raise ContextWindowOverflowException("Unable to trim conversation context!") from e
 
         # Overwrite message history
         messages[:] = messages[trim_index:]
-
-    def _map_tool_result_content(self, tool_result: ToolResult) -> List[ContentBlock]:
-        """Convert a ToolResult to a list of standard ContentBlocks.
-
-        This method transforms tool result content into standard content blocks that can be preserved when trimming the
-        conversation history.
-
-        Args:
-            tool_result: The ToolResult to convert.
-
-        Returns:
-            A list of content blocks representing the tool result.
-        """
-        contents = []
-        text_content = "Tool Result Status: " + tool_result["status"] if tool_result["status"] else ""
-
-        for tool_result_content in tool_result["content"]:
-            if "text" in tool_result_content:
-                text_content = "\nTool Result Text Content: " + tool_result_content["text"] + f"\n{text_content}"
-            elif "json" in tool_result_content:
-                text_content = (
-                    "\nTool Result JSON Content: " + json.dumps(tool_result_content["json"]) + f"\n{text_content}"
-                )
-            elif "image" in tool_result_content:
-                contents.append(ContentBlock(image=tool_result_content["image"]))
-            elif "document" in tool_result_content:
-                contents.append(ContentBlock(document=tool_result_content["document"]))
-            else:
-                logger.warning("unsupported content type")
-        contents.append(ContentBlock(text=text_content))
-        return contents