Merge branch 'main' of https://github.com/strands-agents/sdk-python into async-tools

Author: pgrayy

.github/workflows/integration-test.yml

@@ -69,4 +69,4 @@ jobs:
           AWS_REGION_NAME: us-east-1 # Needed for LiteLLM
         id: tests
         run: |
-          hatch test tests-integ
+          hatch test tests_integ

pyproject.toml

@@ -35,6 +35,7 @@ dependencies = [
     "watchdog>=6.0.0,<7.0.0",
     "opentelemetry-api>=1.30.0,<2.0.0",
     "opentelemetry-sdk>=1.30.0,<2.0.0",
+    "opentelemetry-instrumentation-threading>=0.51b0,<1.00b0",
 ]
 
 [project.urls]
@@ -82,8 +83,12 @@ openai = [
 otel = [
     "opentelemetry-exporter-otlp-proto-http>=1.30.0,<2.0.0",
 ]
+writer = [
+    "writer-sdk>=2.2.0,<3.0.0"
+]
+
 a2a = [
-    "a2a-sdk>=0.2.6",
+    "a2a-sdk[sql]>=0.2.11",
     "uvicorn>=0.34.2",
     "httpx>=0.28.1",
     "fastapi>=0.115.12",
@@ -95,7 +100,7 @@ a2a = [
 source = "vcs"
 
 [tool.hatch.envs.hatch-static-analysis]
-features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel","mistral"]
+features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel", "mistral", "writer"]
 dependencies = [
   "mypy>=1.15.0,<2.0.0",
   "ruff>=0.11.6,<0.12.0",
@@ -119,7 +124,7 @@ lint-fix = [
 ]
 
 [tool.hatch.envs.hatch-test]
-features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel","mistral"]
+features = ["anthropic", "litellm", "llamaapi", "ollama", "openai", "otel", "mistral", "writer"]
 extra-dependencies = [
     "moto>=5.1.0,<6.0.0",
     "pytest>=8.0.0,<9.0.0",
@@ -135,7 +140,7 @@ extra-args = [
 
 [tool.hatch.envs.dev]
 dev-mode = true
-features = ["dev", "docs", "anthropic", "litellm", "llamaapi", "ollama", "otel","mistral"]
+features = ["dev", "docs", "anthropic", "litellm", "llamaapi", "ollama", "otel", "mistral", "writer"]
 
 [tool.hatch.envs.a2a]
 dev-mode = true
@@ -190,7 +195,7 @@ test = [
     "hatch test --cover --cov-report html --cov-report xml {args}"
 ]
 test-integ = [
-    "hatch test tests-integ {args}"
+    "hatch test tests_integ {args}"
 ]
 prepare = [
     "hatch fmt --linter",
@@ -225,7 +230,7 @@ ignore_missing_imports = true
 
 [tool.ruff]
 line-length = 120
-include = ["examples/**/*.py", "src/**/*.py", "tests/**/*.py", "tests-integ/**/*.py"]
+include = ["examples/**/*.py", "src/**/*.py", "tests/**/*.py", "tests_integ/**/*.py"]
 
 [tool.ruff.lint]
 select = [

src/strands/agent/agent.py

@@ -30,7 +30,7 @@
 from ..types.content import ContentBlock, Message, Messages
 from ..types.exceptions import ContextWindowOverflowException
 from ..types.models import Model
-from ..types.tools import ToolConfig, ToolResult, ToolUse
+from ..types.tools import ToolResult, ToolUse
 from ..types.traces import AttributeValue
 from .agent_result import AgentResult
 from .conversation_manager import (
@@ -324,15 +324,6 @@ def tool_names(self) -> list[str]:
         all_tools = self.tool_registry.get_all_tools_config()
         return list(all_tools.keys())
 
-    @property
-    def tool_config(self) -> ToolConfig:
-        """Get the tool configuration for this agent.
-
-        Returns:
-            The complete tool configuration.
-        """
-        return self.tool_registry.initialize_tool_config()
-
     def __call__(self, prompt: str, **kwargs: Any) -> AgentResult:
         """Process a natural language prompt through the agent's event loop.
 

src/strands/event_loop/event_loop.py

@@ -11,7 +11,7 @@
 import logging
 import time
 import uuid
-from typing import TYPE_CHECKING, Any, AsyncGenerator
+from typing import TYPE_CHECKING, Any, AsyncGenerator, cast
 
 from ..experimental.hooks import AfterToolInvocationEvent, BeforeToolInvocationEvent
 from ..experimental.hooks.registry import get_registry
@@ -21,7 +21,7 @@
 from ..types.content import Message
 from ..types.exceptions import ContextWindowOverflowException, EventLoopException, ModelThrottledException
 from ..types.streaming import Metrics, StopReason
-from ..types.tools import ToolGenerator, ToolResult, ToolUse
+from ..types.tools import ToolChoice, ToolChoiceAuto, ToolConfig, ToolGenerator, ToolResult, ToolUse
 from .message_processor import clean_orphaned_empty_tool_uses
 from .streaming import stream_messages
 
@@ -112,10 +112,12 @@ async def event_loop_cycle(agent: "Agent", kwargs: dict[str, Any]) -> AsyncGener
             model_id=model_id,
         )
 
+        tool_specs = agent.tool_registry.get_all_tool_specs()
+
         try:
             # TODO: To maintain backwards compatibility, we need to combine the stream event with kwargs before yielding
             #       to the callback handler. This will be revisited when migrating to strongly typed events.
-            async for event in stream_messages(agent.model, agent.system_prompt, agent.messages, agent.tool_config):
+            async for event in stream_messages(agent.model, agent.system_prompt, agent.messages, tool_specs):
                 if "callback" in event:
                     yield {"callback": {**event["callback"], **(kwargs if "delta" in event["callback"] else {})}}
 
@@ -172,12 +174,6 @@ async def event_loop_cycle(agent: "Agent", kwargs: dict[str, Any]) -> AsyncGener
 
         # If the model is requesting to use tools
         if stop_reason == "tool_use":
-            if agent.tool_config is None:
-                raise EventLoopException(
-                    Exception("Model requested tool use but no tool config provided"),
-                    kwargs["request_state"],
-                )
-
             # Handle tool execution
             events = _handle_tool_execution(
                 stop_reason,
@@ -282,7 +278,10 @@ async def run_tool(agent: "Agent", tool_use: ToolUse, kwargs: dict[str, Any]) ->
             "model": agent.model,
             "system_prompt": agent.system_prompt,
             "messages": agent.messages,
-            "tool_config": agent.tool_config,
+            "tool_config": ToolConfig(  # for backwards compatability
+                tools=[{"toolSpec": tool_spec} for tool_spec in agent.tool_registry.get_all_tool_specs()],
+                toolChoice=cast(ToolChoice, {"auto": ToolChoiceAuto()}),
+            ),
         }
     )
 

src/strands/event_loop/streaming.py

@@ -19,7 +19,7 @@
     StreamEvent,
     Usage,
 )
-from ..types.tools import ToolConfig, ToolUse
+from ..types.tools import ToolSpec, ToolUse
 
 logger = logging.getLogger(__name__)
 
@@ -304,24 +304,23 @@ async def stream_messages(
     model: Model,
     system_prompt: Optional[str],
     messages: Messages,
-    tool_config: Optional[ToolConfig],
+    tool_specs: list[ToolSpec],
 ) -> AsyncGenerator[dict[str, Any], None]:
     """Streams messages to the model and processes the response.
 
     Args:
         model: Model provider.
         system_prompt: The system prompt to send.
         messages: List of messages to send.
-        tool_config: Configuration for the tools to use.
+        tool_specs: The list of tool specs.
 
     Returns:
         The reason for stopping, the final message, and the usage metrics
     """
     logger.debug("model=<%s> | streaming messages", model)
 
     messages = remove_blank_messages_content_text(messages)
-    tool_specs = [tool["toolSpec"] for tool in tool_config.get("tools", [])] or None if tool_config else None
 
-    chunks = model.converse(messages, tool_specs, system_prompt)
+    chunks = model.converse(messages, tool_specs if tool_specs else None, system_prompt)
     async for event in process_stream(chunks, messages):
         yield event