UI-for-examples

examples/example-with-ui/context/.gitignore

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+.venv
+.env
+.mypy_cache
+.chainlite
+

examples/example-with-ui/context/.python-version

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+3.11

examples/example-with-ui/context/README.md

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+# Context
+Check out the OpenAI Agents Python context documentation:
+https://openai.github.io/openai-agents-python/context/
+
+Context in OpenAI Agents Python allows you to provide additional information to the assistant during conversations. This can include relevant documentation, code snippets, or any other text that helps the assistant better understand the task at hand. Context is passed as a list of strings and can be updated dynamically as the conversation progresses.
+
+`uv add openai-agents python-dotenv chainlit`
+
+Give these commands to run the project:
+
+    cd chatbot
+
+    uv venv
+
+On Mac:
+
+    source .venv/bin/activate
+
+Using uv to run the project
+
+    uv run chainlit run app.py -w

examples/example-with-ui/context/app.py

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+import os
+from dotenv import load_dotenv
+from typing import cast, List
+import chainlit as cl
+from agents import Agent, Runner, AsyncOpenAI, OpenAIChatCompletionsModel
+from agents.run import RunConfig
+from agents.tool import function_tool
+from agents.run_context import RunContextWrapper
+
+# Load the environment variables from the .env file
+load_dotenv()
+
+gemini_api_key = os.getenv("GEMINI_API_KEY")
+
+# Check if the API key is present; if not, raise an error
+if not gemini_api_key:
+    raise ValueError(
+        "GEMINI_API_KEY is not set. Please ensure it is defined in your .env file."
+    )
+
+
+@cl.set_starters  # type: ignore
+async def set_starts() -> List[cl.Starter]:
+    return [
+        cl.Starter(
+            label="Greetings",
+            message="Hello! What can you help me with today?",
+        ),
+        cl.Starter(
+            label="Weather",
+            message="Find the weather in Karachi.",
+        ),
+    ]
+
+
+class MyContext:
+    def __init__(self, user_id: str):
+        self.user_id = user_id
+        self.seen_messages = []
+
+
+@function_tool
+@cl.step(type="weather tool")
+def get_weather(location: str, unit: str = "C") -> str:
+    """
+    Fetch the weather for a given location, returning a short description.
+    """
+    # Example logic
+    return f"The weather in {location} is 22 degrees {unit}."
+
+
+@function_tool
+@cl.step(type="greeting tool")
+def greet_user(context: RunContextWrapper[MyContext], greeting: str) -> str:
+    user_id = context.context.user_id
+    return f"Hello {user_id}, you said: {greeting}"
+
+
+@cl.on_chat_start
+async def start():
+    # Reference: https://ai.google.dev/gemini-api/docs/openai
+    external_client = AsyncOpenAI(
+        api_key=gemini_api_key,
+        base_url="https://generativelanguage.googleapis.com/v1beta/openai/",
+    )
+
+    model = OpenAIChatCompletionsModel(
+        model="gemini-2.0-flash", openai_client=external_client
+    )
+
+    config = RunConfig(
+        model=model, model_provider=external_client, tracing_disabled=True
+    )
+    """Set up the chat session when a user connects."""
+    # Initialize an empty chat history in the session.
+    cl.user_session.set("chat_history", [])
+
+    cl.user_session.set("config", config)
+    agent: Agent = Agent(
+        name="Assistant",
+        tools=[greet_user, get_weather],
+        instructions="You are a helpful assistant. Call greet_user tool to greet the user. Always greet the user when session starts.",
+        model=model,
+    )
+
+    cl.user_session.set("agent", agent)
+
+    await cl.Message(
+        content="Welcome to the Ajmal Khan AI Assistant! How can I help you today?"
+    ).send()
+
+
+@cl.on_message
+async def main(message: cl.Message):
+    """Process incoming messages and generate responses."""
+    # Send a thinking message
+    msg = cl.Message(content="Thinking...")
+    await msg.send()
+
+    agent: Agent = cast(Agent, cl.user_session.get("agent"))
+    config: RunConfig = cast(RunConfig, cl.user_session.get("config"))
+
+    # Retrieve the chat history from the session.
+    history = cl.user_session.get("chat_history") or []
+
+    # Append the user's message to the history.
+    history.append({"role": "user", "content": message.content})
+
+    my_ctx = MyContext(user_id="Zia")
+
+    try:
+        print("\n[CALLING_AGENT_WITH_CONTEXT]\n", history, "\n")
+        result = Runner.run_sync(agent, history, run_config=config, context=my_ctx)
+
+        response_content = result.final_output
+
+        # Update the thinking message with the actual response
+        msg.content = response_content
+        await msg.update()
+
+        # Append the assistant's response to the history.
+        history.append({"role": "developer", "content": response_content})
+        # NOTE: Here we are appending the response to the history as a developer message.
+        # This is a BUG in the agents library.
+        # The expected behavior is to append the response to the history as an assistant message.
+
+        # Update the session with the new history.
+        cl.user_session.set("chat_history", history)
+
+        # Optional: Log the interaction
+        print(f"User: {message.content}")
+        print(f"Assistant: {response_content}")
+
+    except Exception as e:
+        msg.content = f"Error: {str(e)}"
+        await msg.update()
+        print(f"Error: {str(e)}")

examples/example-with-ui/context/pyproject.toml

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+[project]
+name = "context"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+authors = [
+    { name = "Ajmal Khan", email = "[email protected]" }
+]
+requires-python = ">=3.11"
+dependencies = [
+    "chainlit>=2.4.1",
+    "openai-agents>=0.0.4",
+    "python-dotenv>=1.0.1",
+]
+
+[project.scripts]
+context = "context:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"