feat(export): export harnesses to standalone Strands agents with connections

src/assets/__tests__/__snapshots__/assets.snapshot.test.ts.snap

@@ -831,6 +831,7 @@ exports[`Assets Directory Snapshots > File listing > should match the expected f
   "python/http/strands/base/mcp_client/client.py",
   "python/http/strands/base/model/__init__.py",
   "python/http/strands/base/model/load.py",
+  "python/http/strands/base/model/mantle_compat.py",
   "python/http/strands/base/pyproject.toml",
   "python/http/strands/base/skills/fetcher.py",
   "python/http/strands/capabilities/execution-limits/hooks/execution_limits.py",
@@ -5276,7 +5277,7 @@ from mcp_client.client import get_streamable_http_mcp_client
 from memory.session import get_memory_session_manager
 {{/if}}
 {{#unless hasFileOperations}}
-{{#if (or needsOs (some gitSkills "credentialArn"))}}
+{{#if (or needsOs browserIdentifierEnvVar codeInterpreterIdentifierEnvVar (some gitSkills "credentialArn"))}}
 import os
 {{/if}}
 {{/unless}}
@@ -5362,10 +5363,20 @@ tools.append(add_numbers)
 {{/unless}}
 {{/if}}
 {{#if hasBrowser}}
-tools.append(AgentCoreBrowser({{#if browserIdentifier}}identifier="{{browserIdentifier}}"{{/if}}).browser)
+{{#if browserIdentifierEnvVar}}
+_browser_id = os.getenv("{{browserIdentifierEnvVar}}")
+tools.append(AgentCoreBrowser(**({"identifier": _browser_id} if _browser_id else {})).browser)
+{{else}}
+tools.append(AgentCoreBrowser().browser)
+{{/if}}
 {{/if}}
 {{#if hasCodeInterpreter}}
-tools.append(AgentCoreCodeInterpreter({{#if codeInterpreterIdentifier}}identifier="{{codeInterpreterIdentifier}}"{{/if}}).code_interpreter)
+{{#if codeInterpreterIdentifierEnvVar}}
+_code_interpreter_id = os.getenv("{{codeInterpreterIdentifierEnvVar}}")
+tools.append(AgentCoreCodeInterpreter(**({"identifier": _code_interpreter_id} if _code_interpreter_id else {})).code_interpreter)
+{{else}}
+tools.append(AgentCoreCodeInterpreter().code_interpreter)
+{{/if}}
 {{/if}}
 {{#if hasShell}}
 @tool
@@ -5908,7 +5919,10 @@ from bedrock_agentcore.identity import requires_access_token
 @requires_access_token(
     provider_name="{{credentialProviderName}}",
     scopes=[{{#if scopes}}"{{scopes}}"{{/if}}],
-    auth_flow="M2M",
+    auth_flow="{{#if authFlow}}{{authFlow}}{{else}}M2M{{/if}}",
+{{#if customParameters}}
+    custom_parameters={{safeJson customParameters}},
+{{/if}}
 )
 def _get_bearer_token_{{snakeCase name}}(*, access_token: str):
     """Obtain OAuth access token via AgentCore Identity for {{name}}."""
@@ -6011,13 +6025,75 @@ exports[`Assets Directory Snapshots > Python framework assets > python/python/ht
 
 exports[`Assets Directory Snapshots > Python framework assets > python/python/http/strands/base/model/load.py should match snapshot 1`] = `
 "{{#if (eq modelProvider "Bedrock")}}
+{{#if bedrockMantle}}
+import os
+
+from aws_bedrock_token_generator import provide_token
+{{#if (eq mantleApiFormat "chat_completions")}}
+from strands.models.openai import OpenAIModel
+{{else}}
+{{#if mantleProprietary}}
+from strands.models.openai_responses import OpenAIResponsesModel
+{{else}}
+from model.mantle_compat import MantleCompatResponsesModel
+{{/if}}
+{{/if}}
+
+MODEL_ID = "{{modelId}}"
+
+
+def load_model():
+    """
+    Get a Bedrock Mantle model client. These OpenAI-compatible models (e.g. openai.gpt-5.5,
+    openai.gpt-oss-120b) are served via the Bedrock Mantle endpoint, NOT the Converse API — so they
+    are invoked through an OpenAI-style client authenticated with a short-lived Bedrock bearer token.
+    Region is read from AWS_REGION (set by the AgentCore runtime).
+    """
+    region = os.environ.get("AWS_REGION", os.environ.get("AWS_DEFAULT_REGION", "us-east-1"))
+    token = provide_token(region=region)
+    {{#if mantleProprietary}}
+    # Proprietary OpenAI models only work on the /openai/v1 Mantle path.
+    base_url = f"https://bedrock-mantle.{region}.api.aws/openai/v1"
+    {{else}}
+    # Open-source OpenAI models (gpt-oss-*) only work on the /v1 Mantle path.
+    base_url = f"https://bedrock-mantle.{region}.api.aws/v1"
+    {{/if}}
+    client_args = {"api_key": token, "base_url": base_url}
+
+    params = {}
+    {{#if modelMaxTokens}}
+    {{#if (eq mantleApiFormat "chat_completions")}}
+    params["max_completion_tokens"] = {{modelMaxTokens}}
+    {{else}}
+    params["max_output_tokens"] = {{modelMaxTokens}}
+    {{/if}}
+    {{/if}}
+    {{#if modelTemperature}}
+    params["temperature"] = {{modelTemperature}}
+    {{/if}}
+    {{#if modelTopP}}
+    params["top_p"] = {{modelTopP}}
+    {{/if}}
+    {{#if (eq mantleApiFormat "chat_completions")}}
+    return OpenAIModel(client_args=client_args, model_id=MODEL_ID, params=params)
+    {{else}}
+    # Responses API: Mantle does not persist responses, so disable server-side storage.
+    params["store"] = False
+    {{#if mantleProprietary}}
+    return OpenAIResponsesModel(client_args=client_args, model_id=MODEL_ID, params=params)
+    {{else}}
+    return MantleCompatResponsesModel(client_args=client_args, model_id=MODEL_ID, params=params)
+    {{/if}}
+    {{/if}}
+{{else}}
 from strands.models.bedrock import BedrockModel
 
 
 def load_model() -> BedrockModel:
     """Get Bedrock model client using IAM credentials."""
     return BedrockModel(model_id="{{#if modelId}}{{modelId}}{{else}}global.anthropic.claude-sonnet-4-5-20250929-v1:0{{/if}}")
 {{/if}}
+{{/if}}
 {{#if (eq modelProvider "Anthropic")}}
 import os
 
@@ -6133,6 +6209,85 @@ def load_model() -> GeminiModel:
         model_id="{{#if modelId}}{{modelId}}{{else}}gemini-2.5-flash{{/if}}",
     )
 {{/if}}
+{{#if (eq modelProvider "LiteLLM")}}
+import os
+{{#if litellmAdditionalParams}}
+import json
+{{/if}}
+
+from strands.models.litellm import LiteLLMModel
+{{#if identityProviders.[0].name}}
+from bedrock_agentcore.identity.auth import requires_api_key
+
+IDENTITY_PROVIDER_NAME = "{{identityProviders.[0].name}}"
+IDENTITY_ENV_VAR = "{{identityProviders.[0].envVarName}}"
+
+
+@requires_api_key(provider_name=IDENTITY_PROVIDER_NAME)
+def _agentcore_identity_api_key_provider(api_key: str) -> str:
+    """Fetch API key from AgentCore Identity."""
+    return api_key
+
+
+def _get_api_key() -> str:
+    """
+    Uses AgentCore Identity for API key management in deployed environments.
+    For local development, run via 'agentcore dev' which loads agentcore/.env.
+    """
+    if os.getenv("LOCAL_DEV") == "1":
+        api_key = os.getenv(IDENTITY_ENV_VAR)
+        if not api_key:
+            raise RuntimeError(
+                f"{IDENTITY_ENV_VAR} not found. Add {IDENTITY_ENV_VAR}=your-key to .env.local"
+            )
+        return api_key
+    return _agentcore_identity_api_key_provider()
+{{/if}}
+
+
+
+
+def load_model() -> LiteLLMModel:
+    """Get a LiteLLM model client (proxies to the provider encoded in model_id)."""
+    client_args = {}
+    {{#if identityProviders.[0].name}}
+    client_args["api_key"] = _get_api_key()
+    {{/if}}
+    {{#if litellmApiBase}}
+    client_args["api_base"] = {{safeJson litellmApiBase}}
+    {{/if}}
+    params = {{#if litellmAdditionalParams}}json.loads({{pyJsonStr litellmAdditionalParams}}){{else}}{}{{/if}}
+    return LiteLLMModel(
+        client_args=client_args,
+        model_id="{{#if modelId}}{{modelId}}{{else}}bedrock/us.anthropic.claude-sonnet-4-5-20250514-v1:0{{/if}}",
+        params=params,
+    )
+{{/if}}
+"
+`;
+
+exports[`Assets Directory Snapshots > Python framework assets > python/python/http/strands/base/model/mantle_compat.py should match snapshot 1`] = `
+"from strands.models.openai_responses import OpenAIResponsesModel
+
+
+class MantleCompatResponsesModel(OpenAIResponsesModel):
+    """Workaround for Bedrock Mantle rejecting output_text in EasyInputMessage content arrays.
+
+    Mantle's Pydantic validation only accepts content as a plain string for assistant messages, while
+    real OpenAI accepts both formats. Flatten assistant content arrays to strings so multi-turn works.
+    Used for open-source OpenAI models (gpt-oss-*) on the /v1 Mantle path; proprietary models use the
+    plain OpenAIResponsesModel on /openai/v1.
+    """
+
+    @classmethod
+    def _format_request_messages(cls, messages):
+        formatted = super()._format_request_messages(messages)
+        for msg in formatted:
+            if msg.get("role") == "assistant" and isinstance(msg.get("content"), list):
+                msg["content"] = "".join(
+                    part.get("text", "") for part in msg["content"] if part.get("type") == "output_text"
+                )
+        return formatted
 "
 `;
 
@@ -6155,6 +6310,9 @@ dependencies = [
     {{#if (eq modelProvider "Gemini")}}"google-genai >= 1.0.0",
     {{/if}}"mcp >= 1.19.0",
     {{#if (eq modelProvider "OpenAI")}}"openai >= 1.0.0",
+    {{/if}}{{#if (eq modelProvider "LiteLLM")}}"litellm >= 1.0.0",
+    {{/if}}{{#if bedrockMantle}}"openai >= 1.0.0",
+    "aws-bedrock-token-generator >= 1.0.0",
     {{/if}}"strands-agents >= 1.15.0",
     {{#if (or hasBrowser hasCodeInterpreter)}}"strands-agents-tools >= 0.1.0",
     {{/if}}{{#if hasBrowser}}"nest-asyncio >= 1.5.0",

src/assets/python/http/strands/base/main.py

@@ -66,7 +66,7 @@
 from memory.session import get_memory_session_manager
 {{/if}}
 {{#unless hasFileOperations}}
-{{#if (or needsOs (some gitSkills "credentialArn"))}}
+{{#if (or needsOs browserIdentifierEnvVar codeInterpreterIdentifierEnvVar (some gitSkills "credentialArn"))}}
 import os
 {{/if}}
 {{/unless}}
@@ -152,10 +152,20 @@ def add_numbers(a: int, b: int) -> int:
 {{/unless}}
 {{/if}}
 {{#if hasBrowser}}
-tools.append(AgentCoreBrowser({{#if browserIdentifier}}identifier="{{browserIdentifier}}"{{/if}}).browser)
+{{#if browserIdentifierEnvVar}}
+_browser_id = os.getenv("{{browserIdentifierEnvVar}}")
+tools.append(AgentCoreBrowser(**({"identifier": _browser_id} if _browser_id else {})).browser)
+{{else}}
+tools.append(AgentCoreBrowser().browser)
+{{/if}}
 {{/if}}
 {{#if hasCodeInterpreter}}
-tools.append(AgentCoreCodeInterpreter({{#if codeInterpreterIdentifier}}identifier="{{codeInterpreterIdentifier}}"{{/if}}).code_interpreter)
+{{#if codeInterpreterIdentifierEnvVar}}
+_code_interpreter_id = os.getenv("{{codeInterpreterIdentifierEnvVar}}")
+tools.append(AgentCoreCodeInterpreter(**({"identifier": _code_interpreter_id} if _code_interpreter_id else {})).code_interpreter)
+{{else}}
+tools.append(AgentCoreCodeInterpreter().code_interpreter)
+{{/if}}
 {{/if}}
 {{#if hasShell}}
 @tool

src/assets/python/http/strands/base/mcp_client/client.py

@@ -18,7 +18,10 @@
 @requires_access_token(
     provider_name="{{credentialProviderName}}",
     scopes=[{{#if scopes}}"{{scopes}}"{{/if}}],
-    auth_flow="M2M",
+    auth_flow="{{#if authFlow}}{{authFlow}}{{else}}M2M{{/if}}",
+{{#if customParameters}}
+    custom_parameters={{safeJson customParameters}},
+{{/if}}
 )
 def _get_bearer_token_{{snakeCase name}}(*, access_token: str):
     """Obtain OAuth access token via AgentCore Identity for {{name}}."""

src/assets/python/http/strands/base/model/load.py

@@ -1,11 +1,73 @@
 {{#if (eq modelProvider "Bedrock")}}
+{{#if bedrockMantle}}
+import os
+
+from aws_bedrock_token_generator import provide_token
+{{#if (eq mantleApiFormat "chat_completions")}}
+from strands.models.openai import OpenAIModel
+{{else}}
+{{#if mantleProprietary}}
+from strands.models.openai_responses import OpenAIResponsesModel
+{{else}}
+from model.mantle_compat import MantleCompatResponsesModel
+{{/if}}
+{{/if}}
+
+MODEL_ID = "{{modelId}}"
+
+
+def load_model():
+    """
+    Get a Bedrock Mantle model client. These OpenAI-compatible models (e.g. openai.gpt-5.5,
+    openai.gpt-oss-120b) are served via the Bedrock Mantle endpoint, NOT the Converse API — so they
+    are invoked through an OpenAI-style client authenticated with a short-lived Bedrock bearer token.
+    Region is read from AWS_REGION (set by the AgentCore runtime).
+    """
+    region = os.environ.get("AWS_REGION", os.environ.get("AWS_DEFAULT_REGION", "us-east-1"))
+    token = provide_token(region=region)
+    {{#if mantleProprietary}}
+    # Proprietary OpenAI models only work on the /openai/v1 Mantle path.
+    base_url = f"https://bedrock-mantle.{region}.api.aws/openai/v1"
+    {{else}}
+    # Open-source OpenAI models (gpt-oss-*) only work on the /v1 Mantle path.
+    base_url = f"https://bedrock-mantle.{region}.api.aws/v1"
+    {{/if}}
+    client_args = {"api_key": token, "base_url": base_url}
+
+    params = {}
+    {{#if modelMaxTokens}}
+    {{#if (eq mantleApiFormat "chat_completions")}}
+    params["max_completion_tokens"] = {{modelMaxTokens}}
+    {{else}}
+    params["max_output_tokens"] = {{modelMaxTokens}}
+    {{/if}}
+    {{/if}}
+    {{#if modelTemperature}}
+    params["temperature"] = {{modelTemperature}}
+    {{/if}}
+    {{#if modelTopP}}
+    params["top_p"] = {{modelTopP}}
+    {{/if}}
+    {{#if (eq mantleApiFormat "chat_completions")}}
+    return OpenAIModel(client_args=client_args, model_id=MODEL_ID, params=params)
+    {{else}}
+    # Responses API: Mantle does not persist responses, so disable server-side storage.
+    params["store"] = False
+    {{#if mantleProprietary}}
+    return OpenAIResponsesModel(client_args=client_args, model_id=MODEL_ID, params=params)
+    {{else}}
+    return MantleCompatResponsesModel(client_args=client_args, model_id=MODEL_ID, params=params)
+    {{/if}}
+    {{/if}}
+{{else}}
 from strands.models.bedrock import BedrockModel
 
 
 def load_model() -> BedrockModel:
     """Get Bedrock model client using IAM credentials."""
     return BedrockModel(model_id="{{#if modelId}}{{modelId}}{{else}}global.anthropic.claude-sonnet-4-5-20250929-v1:0{{/if}}")
 {{/if}}
+{{/if}}
 {{#if (eq modelProvider "Anthropic")}}
 import os
 
@@ -121,3 +183,57 @@ def load_model() -> GeminiModel:
         model_id="{{#if modelId}}{{modelId}}{{else}}gemini-2.5-flash{{/if}}",
     )
 {{/if}}
+{{#if (eq modelProvider "LiteLLM")}}
+import os
+{{#if litellmAdditionalParams}}
+import json
+{{/if}}
+
+from strands.models.litellm import LiteLLMModel
+{{#if identityProviders.[0].name}}
+from bedrock_agentcore.identity.auth import requires_api_key
+
+IDENTITY_PROVIDER_NAME = "{{identityProviders.[0].name}}"
+IDENTITY_ENV_VAR = "{{identityProviders.[0].envVarName}}"
+
+
+@requires_api_key(provider_name=IDENTITY_PROVIDER_NAME)
+def _agentcore_identity_api_key_provider(api_key: str) -> str:
+    """Fetch API key from AgentCore Identity."""
+    return api_key
+
+
+def _get_api_key() -> str:
+    """
+    Uses AgentCore Identity for API key management in deployed environments.
+    For local development, run via 'agentcore dev' which loads agentcore/.env.
+    """
+    if os.getenv("LOCAL_DEV") == "1":
+        api_key = os.getenv(IDENTITY_ENV_VAR)
+        if not api_key:
+            raise RuntimeError(
+                f"{IDENTITY_ENV_VAR} not found. Add {IDENTITY_ENV_VAR}=your-key to .env.local"
+            )
+        return api_key
+    return _agentcore_identity_api_key_provider()
+{{/if}}
+
+
+
+
+def load_model() -> LiteLLMModel:
+    """Get a LiteLLM model client (proxies to the provider encoded in model_id)."""
+    client_args = {}
+    {{#if identityProviders.[0].name}}
+    client_args["api_key"] = _get_api_key()
+    {{/if}}
+    {{#if litellmApiBase}}
+    client_args["api_base"] = {{safeJson litellmApiBase}}
+    {{/if}}
+    params = {{#if litellmAdditionalParams}}json.loads({{pyJsonStr litellmAdditionalParams}}){{else}}{}{{/if}}
+    return LiteLLMModel(
+        client_args=client_args,
+        model_id="{{#if modelId}}{{modelId}}{{else}}bedrock/us.anthropic.claude-sonnet-4-5-20250514-v1:0{{/if}}",
+        params=params,
+    )
+{{/if}}