feat: add BedrockTransport + wire all Bedrock transport paths

agent/transports/__init__.py

@@ -45,3 +45,7 @@ def _discover_transports() -> None:
         import agent.transports.chat_completions  # noqa: F401
     except ImportError:
         pass
+    try:
+        import agent.transports.bedrock  # noqa: F401
+    except ImportError:
+        pass

agent/transports/bedrock.py

@@ -0,0 +1,154 @@
+"""AWS Bedrock Converse API transport.
+
+Delegates to the existing adapter functions in agent/bedrock_adapter.py.
+Bedrock uses its own boto3 client (not the OpenAI SDK), so the transport
+owns format conversion and normalization, while client construction and
+boto3 calls stay on AIAgent.
+"""
+
+from typing import Any, Dict, List, Optional
+
+from agent.transports.base import ProviderTransport
+from agent.transports.types import NormalizedResponse, ToolCall, Usage
+
+
+class BedrockTransport(ProviderTransport):
+    """Transport for api_mode='bedrock_converse'."""
+
+    @property
+    def api_mode(self) -> str:
+        return "bedrock_converse"
+
+    def convert_messages(self, messages: List[Dict[str, Any]], **kwargs) -> Any:
+        """Convert OpenAI messages to Bedrock Converse format."""
+        from agent.bedrock_adapter import convert_messages_to_converse
+        return convert_messages_to_converse(messages)
+
+    def convert_tools(self, tools: List[Dict[str, Any]]) -> Any:
+        """Convert OpenAI tool schemas to Bedrock Converse toolConfig."""
+        from agent.bedrock_adapter import convert_tools_to_converse
+        return convert_tools_to_converse(tools)
+
+    def build_kwargs(
+        self,
+        model: str,
+        messages: List[Dict[str, Any]],
+        tools: Optional[List[Dict[str, Any]]] = None,
+        **params,
+    ) -> Dict[str, Any]:
+        """Build Bedrock converse() kwargs.
+
+        Calls convert_messages and convert_tools internally.
+
+        params:
+            max_tokens: int — output token limit (default 4096)
+            temperature: float | None
+            guardrail_config: dict | None — Bedrock guardrails
+            region: str — AWS region (default 'us-east-1')
+        """
+        from agent.bedrock_adapter import build_converse_kwargs
+
+        region = params.get("region", "us-east-1")
+        guardrail = params.get("guardrail_config")
+
+        kwargs = build_converse_kwargs(
+            model=model,
+            messages=messages,
+            tools=tools,
+            max_tokens=params.get("max_tokens", 4096),
+            temperature=params.get("temperature"),
+            guardrail_config=guardrail,
+        )
+        # Sentinel keys for dispatch — agent pops these before the boto3 call
+        kwargs["__bedrock_converse__"] = True
+        kwargs["__bedrock_region__"] = region
+        return kwargs
+
+    def normalize_response(self, response: Any, **kwargs) -> NormalizedResponse:
+        """Normalize Bedrock response to NormalizedResponse.
+
+        Handles two shapes:
+        1. Raw boto3 dict (from direct converse() calls)
+        2. Already-normalized SimpleNamespace with .choices (from dispatch site)
+        """
+        from agent.bedrock_adapter import normalize_converse_response
+
+        # Normalize to OpenAI-compatible SimpleNamespace
+        if hasattr(response, "choices") and response.choices:
+            # Already normalized at dispatch site
+            ns = response
+        else:
+            # Raw boto3 dict
+            ns = normalize_converse_response(response)
+
+        choice = ns.choices[0]
+        msg = choice.message
+        finish_reason = choice.finish_reason or "stop"
+
+        tool_calls = None
+        if msg.tool_calls:
+            tool_calls = [
+                ToolCall(
+                    id=tc.id,
+                    name=tc.function.name,
+                    arguments=tc.function.arguments,
+                )
+                for tc in msg.tool_calls
+            ]
+
+        usage = None
+        if hasattr(ns, "usage") and ns.usage:
+            u = ns.usage
+            usage = Usage(
+                prompt_tokens=getattr(u, "prompt_tokens", 0) or 0,
+                completion_tokens=getattr(u, "completion_tokens", 0) or 0,
+                total_tokens=getattr(u, "total_tokens", 0) or 0,
+            )
+
+        reasoning = getattr(msg, "reasoning", None) or getattr(msg, "reasoning_content", None)
+
+        return NormalizedResponse(
+            content=msg.content,
+            tool_calls=tool_calls,
+            finish_reason=finish_reason,
+            reasoning=reasoning,
+            usage=usage,
+        )
+
+    def validate_response(self, response: Any) -> bool:
+        """Check Bedrock response structure.
+
+        After normalize_converse_response, the response has OpenAI-compatible
+        .choices — same check as chat_completions.
+        """
+        if response is None:
+            return False
+        # Raw Bedrock dict response — check for 'output' key
+        if isinstance(response, dict):
+            return "output" in response
+        # Already-normalized SimpleNamespace
+        if hasattr(response, "choices"):
+            return bool(response.choices)
+        return False
+
+    def map_finish_reason(self, raw_reason: str) -> str:
+        """Map Bedrock stop reason to OpenAI finish_reason.
+
+        The adapter already does this mapping inside normalize_converse_response,
+        so this is only used for direct access to raw responses.
+        """
+        _MAP = {
+            "end_turn": "stop",
+            "tool_use": "tool_calls",
+            "max_tokens": "length",
+            "stop_sequence": "stop",
+            "guardrail_intervened": "content_filter",
+            "content_filtered": "content_filter",
+        }
+        return _MAP.get(raw_reason, "stop")
+
+
+# Auto-register on import
+from agent.transports import register_transport  # noqa: E402
+
+register_transport("bedrock_converse", BedrockTransport)

run_agent.py

@@ -6583,6 +6583,15 @@ def _get_chat_completions_transport(self):
             self._chat_completions_transport = t
         return t
 
+    def _get_bedrock_transport(self):
+        """Return the cached BedrockTransport instance (lazy singleton)."""
+        t = getattr(self, "_bedrock_transport", None)
+        if t is None:
+            from agent.transports import get_transport
+            t = get_transport("bedrock_converse")
+            self._bedrock_transport = t
+        return t
+
     def _prepare_anthropic_messages_for_api(self, api_messages: list) -> list:
         if not any(
             isinstance(msg, dict) and self._content_has_image_parts(msg.get("content"))
@@ -6722,21 +6731,17 @@ def _build_api_kwargs(self, api_messages: list) -> dict:
         # AWS Bedrock native Converse API — bypasses the OpenAI client entirely.
         # The adapter handles message/tool conversion and boto3 calls directly.
         if self.api_mode == "bedrock_converse":
-            from agent.bedrock_adapter import build_converse_kwargs
+            _bt = self._get_bedrock_transport()
             region = getattr(self, "_bedrock_region", None) or "us-east-1"
             guardrail = getattr(self, "_bedrock_guardrail_config", None)
-            return {
-                "__bedrock_converse__": True,
-                "__bedrock_region__": region,
-                **build_converse_kwargs(
-                    model=self.model,
-                    messages=api_messages,
-                    tools=self.tools,
-                    max_tokens=self.max_tokens or 4096,
-                    temperature=None,  # Let the model use its default
-                    guardrail_config=guardrail,
-                ),
-            }
+            return _bt.build_kwargs(
+                model=self.model,
+                messages=api_messages,
+                tools=self.tools,
+                max_tokens=self.max_tokens or 4096,
+                region=region,
+                guardrail_config=guardrail,
+            )
 
         if self.api_mode == "codex_responses":
             _ct = self._get_codex_transport()
@@ -9250,6 +9255,14 @@ def _stop_spinner():
                                 error_details.append("response is None")
                             else:
                                 error_details.append("response.content invalid (not a non-empty list)")
+                    elif self.api_mode == "bedrock_converse":
+                        _btv = self._get_bedrock_transport()
+                        if not _btv.validate_response(response):
+                            response_invalid = True
+                            if response is None:
+                                error_details.append("response is None")
+                            else:
+                                error_details.append("Bedrock response invalid (no output or choices)")
                     else:
                         _ctv = self._get_chat_completions_transport()
                         if not _ctv.validate_response(response):
@@ -9413,6 +9426,10 @@ def _stop_spinner():
                     elif self.api_mode == "anthropic_messages":
                         _tfr = self._get_anthropic_transport()
                         finish_reason = _tfr.map_finish_reason(response.stop_reason)
+                    elif self.api_mode == "bedrock_converse":
+                        # Bedrock response is already normalized at dispatch — finish_reason
+                        # is already in OpenAI format via normalize_converse_response()
+                        finish_reason = response.choices[0].finish_reason if hasattr(response, "choices") and response.choices else "stop"
                     else:
                         finish_reason = response.choices[0].finish_reason
                         assistant_message = response.choices[0].message