chore: use union syntax over pipe syntax for older python version

agntcy_iomapper/base/agent_iomapper.py

@@ -4,7 +4,7 @@
 import logging
 import re
 from abc import abstractmethod
-from typing import ClassVar
+from typing import ClassVar, Optional, Union
 
 import jsonschema
 from jinja2 import Environment
@@ -22,7 +22,7 @@
 
 
 class AgentIOMapperInput(BaseIOMapperInput):
-    message_template: str | None = Field(
+    message_template: Union[str, None] = Field(
         max_length=4096,
         default=None,
         description="Message (user) to send to LLM to effect translation.",
@@ -52,9 +52,9 @@ class AgentIOMapper(BaseIOMapper):
 
     def __init__(
         self,
-        config: AgentIOMapperConfig | None = None,
-        jinja_env: Environment | None = None,
-        jinja_env_async: Environment | None = None,
+        config: Optional[AgentIOMapperConfig] = None,
+        jinja_env: Optional[Environment] = None,
+        jinja_env_async: Optional[Environment] = None,
     ):
         if config is None:
             config = AgentIOMapperConfig()

agntcy_iomapper/base/base.py

@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025 Cisco and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0
 from abc import ABC, abstractmethod
-from typing import Any
+from typing import Any, Union, Optional
 
 from openapi_pydantic import Schema
 from pydantic import BaseModel, Field, model_validator
@@ -14,13 +14,13 @@ class ArgumentsDescription(BaseModel):
     the details necessary to perfom io mapping between two agents
     """
 
-    json_schema: Schema | None = Field(
+    json_schema: Optional[Schema] = Field(
         default=None, description="Data format JSON schema"
     )
-    description: str | None = Field(
+    description: Optional[str] = Field(
         default=None, description="Data (semantic) natural language description"
     )
-    agent_manifest: dict[str, Any] | None = Field(
+    agent_manifest: Optional[dict[str, Any]] = Field(
         default=None,
         description="Agent Manifest definition as per https://agntcy.github.io/acp-spec/openapi.html#model/agentmanifest",
     )
@@ -89,7 +89,7 @@ class BaseIOMapper(ABC):
 
     def __init__(
         self,
-        config: BaseIOMapperConfig | None = None,
+        config: Optional[BaseIOMapperConfig] = None,
     ):
         self.config = config if config is not None else BaseIOMapperConfig()
 

agntcy_iomapper/base/utils.py

@@ -120,7 +120,6 @@ def resolve_ref(ref, current_defs):
 
 def _refine_schema(schema, paths):
     filtered_schema = {}
-    print(f"{paths}-{schema}")
 
     for path in paths:
         path_parts = path.split(".")
@@ -153,7 +152,6 @@ def _refine_schema(schema, paths):
                 properties = _filter_properties(
                     root_schema, curr_properties, path_parts[1:]
                 )
-    print(f" after {paths}-{filtered_schema}")
     return filtered_schema
 
 

agntcy_iomapper/imperative/__init__.py

@@ -6,3 +6,9 @@
     ImperativeIOMapperInput,
     ImperativeIOMapperOutput,
 )
+
+__all__ = [
+    "ImperativeIOMapper",
+    "ImperativeIOMapperInput",
+    "ImperativeIOMapperOutput",
+]

agntcy_iomapper/imperative/imperative.py

@@ -17,7 +17,7 @@
 
 import json
 import logging
-from typing import Any, Callable, Union
+from typing import Any, Callable, Optional, Union
 
 import jsonschema
 from jsonpath_ng.ext import parse
@@ -44,13 +44,15 @@ class ImperativeIOMapper(BaseIOMapper):
 
     def __init__(
         self,
-        field_mapping: dict[str, Union[str, Callable]] | None,
-        config: BaseIOMapperConfig | None = None,
+        field_mapping: Optional[dict[str, Union[str, Callable]]],
+        config: Optional[BaseIOMapperConfig] = None,
     ) -> None:
         super().__init__(config)
         self.field_mapping = field_mapping
 
-    def invoke(self, input: ImperativeIOMapperInput) -> ImperativeIOMapperOutput | None:
+    def invoke(
+        self, input: ImperativeIOMapperInput
+    ) -> Optional[ImperativeIOMapperOutput]:
         if input.data is None:
             return None
         if self.field_mapping is None:
@@ -61,7 +63,7 @@ def invoke(self, input: ImperativeIOMapperInput) -> ImperativeIOMapperOutput | N
 
     def ainvoke(
         self, input: ImperativeIOMapperInput
-    ) -> ImperativeIOMapperOutput | None:
+    ) -> Optional[ImperativeIOMapperOutput]:
         return self.invoke(input)
 
     def _imperative_map(self, input_definition: ImperativeIOMapperInput) -> Any:

agntcy_iomapper/langgraph/langgraph.py

@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025 Cisco and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0
 import logging
-from typing import Any
+from typing import Any, Optional, Union
 
 from langchain.chat_models import init_chat_model
 from langchain_core.language_models import BaseChatModel
@@ -23,7 +23,7 @@
 
 
 class LangGraphIOMapperConfig(AgentIOMapperConfig):
-    llm: BaseChatModel | str = (
+    llm: Union[BaseChatModel, str] = (
         Field(
             ...,
             description="Model to use for translation as LangChain description or model class.",
@@ -34,7 +34,7 @@ class LangGraphIOMapperConfig(AgentIOMapperConfig):
 class _LangGraphAgentIOMapper(AgentIOMapper):
     def __init__(
         self,
-        config: LangGraphIOMapperConfig | None = None,
+        config: Optional[LangGraphIOMapperConfig] = None,
         **kwargs,
     ):
         if config is None:
@@ -50,7 +50,7 @@ def _invoke(
         input: LangGraphIOMapperInput,
         messages: list[dict[str, str]],
         *,
-        config: RunnableConfig | None = None,
+        config: Optional[RunnableConfig] = None,
         **kwargs,
     ) -> str:
         response = self.llm.invoke(messages, config, **kwargs)
@@ -61,7 +61,7 @@ async def _ainvoke(
         input: LangGraphIOMapperOutput,
         messages: list[dict[str, str]],
         *,
-        config: RunnableConfig | None = None,
+        config: Optional[RunnableConfig] = None,
         **kwargs,
     ) -> str:
         response = await self.llm.ainvoke(messages, config, **kwargs)
@@ -72,7 +72,7 @@ class LangGraphIOMapper:
     def __init__(
         self,
         config: LangGraphIOMapperConfig,
-        input: LangGraphIOMapperInput | None = None,
+        input: Optional[LangGraphIOMapperInput] = None,
     ):
         self._iomapper = _LangGraphAgentIOMapper(config)
         self._input = input

agntcy_iomapper/llamaindex/llamaindex.py

@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025 Cisco and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0"
 import logging
-from typing import Any
+from typing import Any, Optional
 
 from llama_index.core.base.llms.base import BaseLLM
 from llama_index.core.llms import ChatMessage
@@ -24,7 +24,7 @@ class LLamaIndexIOMapperConfig(AgentIOMapperConfig):
 class _LLmaIndexAgentIOMapper(AgentIOMapper):
     def __init__(
         self,
-        config: LLamaIndexIOMapperConfig | None = None,
+        config: Optional[LLamaIndexIOMapperConfig] = None,
         **kwargs,
     ):
         if config is None:

agntcy_iomapper/pydantic_ai.py

@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright (c) 2025 Cisco and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0
 import logging
-from typing import Any, Literal, TypedDict
+from typing import Any, Literal, Optional, TypedDict
 
 from openai import AsyncAzureOpenAI
 from pydantic import Field, model_validator
@@ -49,11 +49,11 @@ class AgentModelSettings(TypedDict, total=False):
 
 
 class PydanticAIAgentIOMapperInput(AgentIOMapperInput):
-    model_settings: AgentModelSettings | None = Field(
+    model_settings: Optional[AgentModelSettings] = Field(
         default=None,
         description="Specific arguments for LLM transformation.",
     )
-    model: str | None = Field(
+    model: Optional[str] = Field(
         default=None,
         description="Specific model out of those configured to handle request.",
     )
@@ -67,7 +67,7 @@ class PydanticAIAgentIOMapperConfig(AgentIOMapperConfig):
         default={"azure:gpt-4o-mini": AgentIOModelArgs()},
         description="LLM configuration to use for translation",
     )
-    default_model: str | None = Field(
+    default_model: Optional[str] = Field(
         default="azure:gpt-4o-mini",
         description="Default arguments to LLM completion function by configured model.",
     )