feat: Added agent example for openai-agents

examples/agents/openai_agents_javelin.py

@@ -0,0 +1,102 @@
+import os
+import asyncio
+
+# OpenAI Agents SDK imports
+from agents import (
+    Agent,
+    Runner,
+    set_default_openai_api,
+    set_default_openai_client,
+    ModelSettings,
+)
+
+from openai import AsyncOpenAI
+from javelin_sdk import JavelinClient, JavelinConfig
+from dotenv import load_dotenv
+
+##############################################################################
+# 1) Environment & Basic Setup
+##############################################################################
+load_dotenv()
+
+# Use Chat Completions endpoint instead of /v1/responses
+set_default_openai_api("chat_completions")
+
+openai_api_key = os.getenv("OPENAI_API_KEY", "")
+javelin_api_key = os.getenv("JAVELIN_API_KEY", "")
+javelin_base_url = os.getenv("JAVELIN_BASE_URL", "")
+
+if not (openai_api_key and javelin_api_key and javelin_base_url):
+    raise ValueError("Missing OPENAI_API_KEY, JAVELIN_API_KEY, or JAVELIN_BASE_URL in .env")
+
+# Create async OpenAI client
+async_openai_client = AsyncOpenAI(api_key=openai_api_key)
+
+# Register with Javelin
+javelin_client = JavelinClient(JavelinConfig(
+    javelin_api_key=javelin_api_key,
+    base_url=javelin_base_url
+))
+javelin_client.register_openai(async_openai_client, route_name="openai_univ")  # Adjust route name if needed
+
+# Let the Agents SDK use this Javelin-patched client globally
+set_default_openai_client(async_openai_client)
+
+##############################################################################
+# 2) Child Agent A: "Faux Search" (actually just an LLM summary)
+##############################################################################
+faux_search_agent = Agent(
+    name="FauxSearchAgent",
+    instructions=(
+        "You pretend to search the web for the user's topic. "
+        "In reality, you only use your internal knowledge to produce a short summary. "
+        "Focus on being concise and factual in describing the topic."
+    ),
+)
+
+##############################################################################
+# 3) Child Agent B: Translator (English → Spanish)
+##############################################################################
+translator_agent = Agent(
+    name="TranslatorAgent",
+    instructions="Translate any English text into Spanish. Keep it concise."
+)
+
+##############################################################################
+# 4) Orchestrator Agent: Must call faux_search, then translator
+##############################################################################
+orchestrator_agent = Agent(
+    name="OrchestratorAgent",
+    instructions=(
+        "You MUST do these steps:\n"
+        "1) Call 'faux_search_agent' to produce a short summary.\n"
+        "2) Pass that summary to 'translator_agent' to translate it into Spanish.\n"
+        "Return only the Spanish text.\n"
+        "Do not skip or respond directly yourself!"
+    ),
+    model_settings=ModelSettings(tool_choice="required"),  # Forcing tool usage
+    tools=[
+        faux_search_agent.as_tool(
+            tool_name="summarize_topic",
+            tool_description="Produce a concise internal summary of the user’s topic."
+        ),
+        translator_agent.as_tool(
+            tool_name="translate_to_spanish",
+            tool_description="Translate text into Spanish."
+        ),
+    ],
+)
+
+##############################################################################
+# 5) Demo Usage
+##############################################################################
+async def main():
+    user_query = "Why is pollution increasing ?"
+    print(f"\n=== User Query: {user_query} ===\n")
+
+    final_result = await Runner.run(orchestrator_agent, user_query)
+    print("=== Final Output ===\n")
+    print(final_result.final_output)
+
+if __name__ == "__main__":
+    asyncio.run(main())