Merge pull request #124 from UiPath/fix/openai_agents_refactoring

fix: refactor open ai code

Author: cristipufu

packages/uipath-openai-agents/samples/agent-as-tools/input.json

@@ -1,3 +1,3 @@
 {
   "message": "Tell me a joke"
-}
+}

packages/uipath-openai-agents/samples/agent-as-tools/main.py

@@ -1,9 +1,8 @@
-import dotenv
-from agents import Agent, AgentOutputSchema, Runner, trace
+from agents import Agent, AgentOutputSchema
+from agents.models import _openai_shared
 from pydantic import BaseModel, Field
-from uipath.tracing import traced
 
-dotenv.load_dotenv()
+from uipath_openai_agents.chat import UiPathChatOpenAI
 
 """
 This example shows the agents-as-tools pattern adapted for UiPath coded agents.
@@ -17,16 +16,6 @@
 """
 
 
-# Required Input/Output models for UiPath coded agents
-class TranslationInput(BaseModel):
-    """Input model for the translation orchestrator."""
-
-    text: str = Field(description="The English text to translate")
-    target_languages: list[str] = Field(
-        description="List of target languages (e.g., ['Spanish', 'French', 'Italian'])"
-    )
-
-
 class TranslationOutput(BaseModel):
     """Output model for the translation orchestrator."""
 
@@ -39,95 +28,63 @@ class TranslationOutput(BaseModel):
     )
 
 
-spanish_agent = Agent(
-    name="spanish_agent",
-    instructions="You translate the user's message to Spanish",
-    handoff_description="An english to spanish translator",
-)
+def main() -> Agent:
+    """Configure UiPath OpenAI client and return the orchestrator agent."""
+    # Configure UiPath OpenAI client for agent execution
+    # This routes all OpenAI API calls through UiPath's LLM Gateway
+    MODEL = "gpt-4o-2024-11-20"
+    uipath_openai_client = UiPathChatOpenAI(model_name=MODEL)
+    _openai_shared.set_default_openai_client(uipath_openai_client.async_client)
+
+    # Define specialized translation agents
+    spanish_agent = Agent(
+        name="spanish_agent",
+        instructions="You translate the user's message to Spanish",
+        handoff_description="An english to spanish translator",
+        model=MODEL,
+    )
 
-french_agent = Agent(
-    name="french_agent",
-    instructions="You translate the user's message to French",
-    handoff_description="An english to french translator",
-)
+    french_agent = Agent(
+        name="french_agent",
+        instructions="You translate the user's message to French",
+        handoff_description="An english to french translator",
+        model=MODEL,
+    )
 
-italian_agent = Agent(
-    name="italian_agent",
-    instructions="You translate the user's message to Italian",
-    handoff_description="An english to italian translator",
-)
+    italian_agent = Agent(
+        name="italian_agent",
+        instructions="You translate the user's message to Italian",
+        handoff_description="An english to italian translator",
+        model=MODEL,
+    )
 
-# Orchestrator agent that uses other agents as tools
-# Uses output_type for structured outputs (native OpenAI Agents pattern)
-# Note: Using AgentOutputSchema with strict_json_schema=False because
-# dict[str, str] is not compatible with OpenAI's strict JSON schema mode
-orchestrator_agent = Agent(
-    name="orchestrator_agent",
-    instructions=(
-        "You are a translation agent. You use the tools given to you to translate. "
-        "If asked for multiple translations, you call the relevant tools in order. "
-        "You never translate on your own, you always use the provided tools."
-    ),
-    tools=[
-        spanish_agent.as_tool(
-            tool_name="translate_to_spanish",
-            tool_description="Translate the user's message to Spanish",
-        ),
-        french_agent.as_tool(
-            tool_name="translate_to_french",
-            tool_description="Translate the user's message to French",
+    # Orchestrator agent that uses other agents as tools
+    # Uses output_type for structured outputs (native OpenAI Agents pattern)
+    # Note: Using AgentOutputSchema with strict_json_schema=False because
+    # dict[str, str] is not compatible with OpenAI's strict JSON schema mode
+    orchestrator_agent = Agent(
+        name="orchestrator_agent",
+        instructions=(
+            "You are a translation agent. You use the tools given to you to translate. "
+            "If asked for multiple translations, you call the relevant tools in order. "
+            "You never translate on your own, you always use the provided tools."
         ),
-        italian_agent.as_tool(
-            tool_name="translate_to_italian",
-            tool_description="Translate the user's message to Italian",
-        ),
-    ],
-    output_type=AgentOutputSchema(TranslationOutput, strict_json_schema=False),
-)
-
-
-@traced(name="Translation Orchestrator Main")
-async def main(input_data: TranslationInput) -> TranslationOutput:
-    """
-    Main function to orchestrate translations using agent-as-tools pattern.
-
-    This function demonstrates parameter inference - the Input/Output models
-    are automatically extracted to generate schemas for UiPath workflows.
-
-    Args:
-        input_data: Input containing text and target languages
-
-    Returns:
-        TranslationOutput: Result containing translations for requested languages
-    """
-    print(f"\nTranslating: '{input_data.text}'")
-    print(f"Target languages: {', '.join(input_data.target_languages)}\n")
-
-    # Build the prompt based on requested languages
-    language_list = ", ".join(input_data.target_languages)
-    prompt = f"Translate this text to {language_list}: {input_data.text}"
-
-    with trace("Translation Orchestrator"):
-        # Run the orchestrator agent
-        result = await Runner.run(
-            starting_agent=orchestrator_agent,
-            input=[{"content": prompt, "role": "user"}],
-        )
-
-        # Extract translations from the response
-        # In a real implementation, you'd parse the structured response
-        final_response = result.final_output
-        print(f"\nAgent response: {final_response}\n")
-
-        # For demonstration, create structured output
-        # In production, you'd parse the agent's structured response
-        translations = {}
-        for lang in input_data.target_languages:
-            # Placeholder - in real usage, extract from agent response
-            translations[lang] = f"[Translation to {lang}]"
-
-    return TranslationOutput(
-        original_text=input_data.text,
-        translations=translations,
-        languages_used=input_data.target_languages,
+        tools=[
+            spanish_agent.as_tool(
+                tool_name="translate_to_spanish",
+                tool_description="Translate the user's message to Spanish",
+            ),
+            french_agent.as_tool(
+                tool_name="translate_to_french",
+                tool_description="Translate the user's message to French",
+            ),
+            italian_agent.as_tool(
+                tool_name="translate_to_italian",
+                tool_description="Translate the user's message to Italian",
+            ),
+        ],
+        output_type=AgentOutputSchema(TranslationOutput, strict_json_schema=False),
+        model=MODEL,
     )
+
+    return orchestrator_agent

packages/uipath-openai-agents/samples/agent-as-tools/openai_agents.json

@@ -1,5 +1,5 @@
 {
   "agents": {
-    "agent": "main.py:orchestrator_agent"
+    "agent": "main.py:main"
   }
 }

packages/uipath-openai-agents/samples/agent-as-tools/pyproject.toml

@@ -5,7 +5,7 @@ description = "Language routing agent example using OpenAI Agents"
 readme = "README.md"
 requires-python = ">=3.11"
 dependencies = [
-    "uipath-openai-agents>=0.1.0, <0.2.0",
+    "uipath-openai-agents>=0.0.1, <0.1.0",
     "openai-agents>=0.6.5",
     "uipath>=2.4.10",
 ]
@@ -14,6 +14,3 @@ dependencies = [
 dev = [
     "uipath-dev>=0.0.8",
 ]
-
-[tool.uv.sources]
-uipath-openai-agents = { path = "../..", editable = true }