From dee9ba14774103d29f71492b47ebd049441070a2 Mon Sep 17 00:00:00 2001 From: Ajmal Khan <128520849+Ajmalniz@users.noreply.github.com> Date: Wed, 19 Mar 2025 01:44:17 +0500 Subject: [PATCH] UI-for-examples --- examples/example-with-ui/context/.gitignore | 5 + .../example-with-ui/context/.python-version | 1 + examples/example-with-ui/context/README.md | 21 + examples/example-with-ui/context/app.py | 137 ++ .../example-with-ui/context/pyproject.toml | 21 + examples/example-with-ui/context/uv.lock | 1102 ++++++++++++++++ .../example-with-ui/gruardrails/.gitignore | 5 + .../gruardrails/.python-version | 1 + .../example-with-ui/gruardrails/README.md | 17 + examples/example-with-ui/gruardrails/app.py | 152 +++ .../gruardrails/pyproject.toml | 11 + examples/example-with-ui/gruardrails/uv.lock | 1106 +++++++++++++++++ examples/example-with-ui/handoff/.gitignore | 5 + .../example-with-ui/handoff/.python-version | 1 + examples/example-with-ui/handoff/README.md | 17 + examples/example-with-ui/handoff/main.py | 98 ++ .../example-with-ui/handoff/pyproject.toml | 11 + examples/example-with-ui/handoff/uv.lock | 1102 ++++++++++++++++ .../structured_output/.gitignore | 5 + .../structured_output/.python-version | 1 + .../structured_output/README.md | 17 + .../example-with-ui/structured_output/app.py | 97 ++ .../structured_output/pyproject.toml | 11 + .../example-with-ui/structured_output/uv.lock | 1102 ++++++++++++++++ 24 files changed, 5046 insertions(+) create mode 100644 examples/example-with-ui/context/.gitignore create mode 100644 examples/example-with-ui/context/.python-version create mode 100644 examples/example-with-ui/context/README.md create mode 100644 examples/example-with-ui/context/app.py create mode 100644 examples/example-with-ui/context/pyproject.toml create mode 100644 examples/example-with-ui/context/uv.lock create mode 100644 examples/example-with-ui/gruardrails/.gitignore create mode 100644 examples/example-with-ui/gruardrails/.python-version create mode 100644 examples/example-with-ui/gruardrails/README.md create mode 100644 examples/example-with-ui/gruardrails/app.py create mode 100644 examples/example-with-ui/gruardrails/pyproject.toml create mode 100644 examples/example-with-ui/gruardrails/uv.lock create mode 100644 examples/example-with-ui/handoff/.gitignore create mode 100644 examples/example-with-ui/handoff/.python-version create mode 100644 examples/example-with-ui/handoff/README.md create mode 100644 examples/example-with-ui/handoff/main.py create mode 100644 examples/example-with-ui/handoff/pyproject.toml create mode 100644 examples/example-with-ui/handoff/uv.lock create mode 100644 examples/example-with-ui/structured_output/.gitignore create mode 100644 examples/example-with-ui/structured_output/.python-version create mode 100644 examples/example-with-ui/structured_output/README.md create mode 100644 examples/example-with-ui/structured_output/app.py create mode 100644 examples/example-with-ui/structured_output/pyproject.toml create mode 100644 examples/example-with-ui/structured_output/uv.lock diff --git a/examples/example-with-ui/context/.gitignore b/examples/example-with-ui/context/.gitignore new file mode 100644 index 00000000..ef9d1680 --- /dev/null +++ b/examples/example-with-ui/context/.gitignore @@ -0,0 +1,5 @@ +.venv +.env +.mypy_cache +.chainlite + diff --git a/examples/example-with-ui/context/.python-version b/examples/example-with-ui/context/.python-version new file mode 100644 index 00000000..2c073331 --- /dev/null +++ b/examples/example-with-ui/context/.python-version @@ -0,0 +1 @@ +3.11 diff --git a/examples/example-with-ui/context/README.md b/examples/example-with-ui/context/README.md new file mode 100644 index 00000000..705953b8 --- /dev/null +++ b/examples/example-with-ui/context/README.md @@ -0,0 +1,21 @@ +# 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 \ No newline at end of file diff --git a/examples/example-with-ui/context/app.py b/examples/example-with-ui/context/app.py new file mode 100644 index 00000000..a9eda8b1 --- /dev/null +++ b/examples/example-with-ui/context/app.py @@ -0,0 +1,137 @@ +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)}") \ No newline at end of file diff --git a/examples/example-with-ui/context/pyproject.toml b/examples/example-with-ui/context/pyproject.toml new file mode 100644 index 00000000..65f3c4f7 --- /dev/null +++ b/examples/example-with-ui/context/pyproject.toml @@ -0,0 +1,21 @@ +[project] +name = "context" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +authors = [ + 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new file mode 100644 index 00000000..ba4a4c13 --- /dev/null +++ b/examples/example-with-ui/gruardrails/README.md @@ -0,0 +1,17 @@ +# **Guardrails** +Summary: OpenAI have also included guardrails in the Agents SDK. These come as input guardrails and output guardrails, the input_guardrail checks that the input going into your LLM is "safe" and the output_guardrail checks that the output from your LLM is "safe". + +Guardrails run in parallel to your agents, enabling you to do checks and validations of user input. For example, imagine you have an agent that uses a very smart (and hence slow/expensive) model to help with customer requests. You wouldn't want malicious users to ask the model to help them with their math homework. So, you can run a guardrail with a fast/cheap model. If the guardrail detects malicious usage, it can immediately raise an error, which stops the expensive model from running and saves you time/money. + +There are two kinds of guardrails: + +1. Input guardrails run on the initial user input +2. Output guardrails run on the final agent output + +Reference: +https://openai.github.io/openai-agents-python/guardrails/ + +Using uv to run the project + + uv run chainlit run app.py -w + diff --git a/examples/example-with-ui/gruardrails/app.py b/examples/example-with-ui/gruardrails/app.py new file mode 100644 index 00000000..8dc07c22 --- /dev/null +++ b/examples/example-with-ui/gruardrails/app.py @@ -0,0 +1,152 @@ +import os +from dotenv import load_dotenv +import chainlit as cl +import nest_asyncio +from pydantic import BaseModel +from agents import ( + Agent, + GuardrailFunctionOutput, + InputGuardrailTripwireTriggered, + OutputGuardrailTripwireTriggered, + RunContextWrapper, + Runner, + TResponseInputItem, + input_guardrail, + output_guardrail, + AsyncOpenAI, + OpenAIChatCompletionsModel, + RunConfig +) + +load_dotenv() + +# Apply nest_asyncio for Chainlit's event loop +nest_asyncio.apply() + +# Pydantic models for structured outputs +class MathHomeworkOutput(BaseModel): + is_math_homework: bool + reasoning: str + +class MessageOutput(BaseModel): + response: str + +class MathOutput(BaseModel): + is_math: bool + reasoning: str + +# Input guardrail function +@input_guardrail +async def math_guardrail( + ctx: RunContextWrapper[None], agent: Agent, input: str | list[TResponseInputItem] +) -> GuardrailFunctionOutput: + guardrail_agent = cl.user_session.get("guardrail_agent") + config = cl.user_session.get("config") + result = await Runner.run(guardrail_agent, input, context=ctx.context, run_config=config) + return GuardrailFunctionOutput( + output_info=result.final_output, + tripwire_triggered=result.final_output.is_math_homework, + ) + +# Output guardrail function +@output_guardrail +async def math_guardrail2( + ctx: RunContextWrapper, agent: Agent, output: MessageOutput +) -> GuardrailFunctionOutput: + guardrail_agent2 = cl.user_session.get("guardrail_agent2") + config = cl.user_session.get("config") + result = await Runner.run(guardrail_agent2, output.response, context=ctx.context, run_config=config) + return GuardrailFunctionOutput( + output_info=result.final_output, + tripwire_triggered=result.final_output.is_math, + ) + +# Setup function to initialize agents and config +@cl.on_chat_start +async def setup_agents(): + try: + # Get Gemini API key (adjust based on your environment) + gemini_api_key = os.getenv("GEMINI_API_KEY") + if not gemini_api_key: + raise ValueError("GEMINI_API_KEY is not set.") + + # Configure external client + external_client = AsyncOpenAI( + api_key=gemini_api_key, + base_url="https://generativelanguage.googleapis.com/v1beta/openai/", + ) + + # Configure model + model = OpenAIChatCompletionsModel( + model="gemini-2.0-flash", + openai_client=external_client + ) + + # Configure run settings + config = RunConfig( + model=model, + model_provider=external_client, + tracing_disabled=True + ) + + # Input guardrail agent + guardrail_agent = Agent( + name="Guardrail check", + instructions="Check if the user is asking you to do their math homework.", + output_type=MathHomeworkOutput, + ) + + # Output guardrail agent + guardrail_agent2 = Agent( + name="Guardrail check", + instructions="Check if the output includes any math.", + output_type=MathOutput, + ) + + # Main customer support agent with both guardrails + agent = Agent( + name="Customer support agent", + instructions="You are a customer support agent. You help customers with their questions.", + input_guardrails=[math_guardrail], + output_guardrails=[math_guardrail2], + output_type=MessageOutput, + ) + + # Store everything in session + cl.user_session.set("agent", agent) + cl.user_session.set("guardrail_agent", guardrail_agent) + cl.user_session.set("guardrail_agent2", guardrail_agent2) + cl.user_session.set("config", config) + + await cl.Message( + content="Customer Support Agent is ready! Ask me anything (but no math homework!)." + ).send() + + except Exception as e: + await cl.Message(content=f"Setup error: {str(e)}").send() + +# Message handler +@cl.on_message +async def handle_message(message: cl.Message): + try: + agent = cl.user_session.get("agent") + config = cl.user_session.get("config") + + if not agent or not config: + await cl.Message(content="Agent not initialized. Please restart the chat.").send() + return + + # Run the agent with guardrails + try: + result = await Runner.run(agent, message.content, run_config=config) + response = result.final_output.response if result.final_output else "I couldn't process that request." + await cl.Message(content=response).send() + + except InputGuardrailTripwireTriggered: + await cl.Message(content="Sorry, I can't help with math homework!").send() + except OutputGuardrailTripwireTriggered: + await cl.Message(content="My response contained math, which I'm not allowed to provide.").send() + + except Exception as e: + await cl.Message(content=f"Error: {str(e)}").send() + diff --git a/examples/example-with-ui/gruardrails/pyproject.toml b/examples/example-with-ui/gruardrails/pyproject.toml new file mode 100644 index 00000000..5f3589ca --- /dev/null +++ b/examples/example-with-ui/gruardrails/pyproject.toml @@ -0,0 +1,11 @@ +[project] +name = "gruardrails" +version = "0.1.0" +description = "Add your description here" 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100644 index 00000000..2c073331 --- /dev/null +++ b/examples/example-with-ui/handoff/.python-version @@ -0,0 +1 @@ +3.11 diff --git a/examples/example-with-ui/handoff/README.md b/examples/example-with-ui/handoff/README.md new file mode 100644 index 00000000..80f1ae17 --- /dev/null +++ b/examples/example-with-ui/handoff/README.md @@ -0,0 +1,17 @@ + + + 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 \ No newline at end of file diff --git a/examples/example-with-ui/handoff/main.py b/examples/example-with-ui/handoff/main.py new file mode 100644 index 00000000..6cc01705 --- /dev/null +++ b/examples/example-with-ui/handoff/main.py @@ -0,0 +1,98 @@ +import os +from dotenv import load_dotenv +from typing import cast +import chainlit as cl +from agents import Agent, Runner, AsyncOpenAI, OpenAIChatCompletionsModel, handoff +from agents.run import RunConfig, 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.on_chat_start +async def start(): + external_client = AsyncOpenAI( + api_key=os.getenv("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 + ) + + def on_handoff(agent: Agent, ctx: RunContextWrapper[None]): + agent_name = agent.name + print("--------------------------------") + print(f"Handing off to {agent_name}...") + print("--------------------------------") + cl.Message( + content=f"🔄 **Handing off to {agent_name}...**\n\nI'm transferring your request to our {agent_name.lower()} who will be able to better assist you.", + author="System" + ).send() + + billing_agent = Agent(name="Billing Agent", instructions="You are a billing agent", model=model) + refund_agent = Agent(name="Refund Agent", instructions="You are a refund agent", model=model) + + agent = Agent( + name="Triage Agent", + instructions="You are a triage agent", + model=model, + handoffs=[ + handoff(billing_agent, on_handoff=lambda ctx: on_handoff(billing_agent, ctx)), + handoff(refund_agent, on_handoff=lambda ctx: on_handoff(refund_agent, ctx)) + ] + ) + cl.user_session.set("agent", agent) + cl.user_session.set("config", config) + cl.user_session.set("billing_agent", billing_agent) + cl.user_session.set("refund_agent", refund_agent) + cl.user_session.set("chat_history", []) + + 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.""" + + 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}) + try: + result = Runner.run_sync(agent, history, run_config=config) + + response_content = result.final_output + + # Update the thinking message with the actual response + msg.content = response_content + await msg.update() + history.append({"role": "developer", "content": response_content}) + + # Update session history + cl.user_session.set("chat_history", history) + print(f"History: {history}") + except Exception as e: + msg.content = f"Error: {str(e)}" + await msg.update() + + + + diff --git a/examples/example-with-ui/handoff/pyproject.toml b/examples/example-with-ui/handoff/pyproject.toml new file mode 100644 index 00000000..7ca05664 --- /dev/null +++ b/examples/example-with-ui/handoff/pyproject.toml @@ -0,0 +1,11 @@ +[project] +name = "handoff" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.11" +dependencies = [ + "chainlit>=2.4.1", + "openai-agents>=0.0.4", + "python-dotenv>=1.0.1", +] diff --git a/examples/example-with-ui/handoff/uv.lock b/examples/example-with-ui/handoff/uv.lock new file mode 100644 index 00000000..e7b76315 --- /dev/null +++ b/examples/example-with-ui/handoff/uv.lock @@ -0,0 +1,1102 @@ +version = 1 +requires-python = ">=3.11" + +[[package]] +name = "aiofiles" +version = "24.1.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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b/examples/example-with-ui/structured_output/.python-version new file mode 100644 index 00000000..2c073331 --- /dev/null +++ b/examples/example-with-ui/structured_output/.python-version @@ -0,0 +1 @@ +3.11 diff --git a/examples/example-with-ui/structured_output/README.md b/examples/example-with-ui/structured_output/README.md new file mode 100644 index 00000000..80f96ef6 --- /dev/null +++ b/examples/example-with-ui/structured_output/README.md @@ -0,0 +1,17 @@ +# **Output Types: Structured Output with Pydantic** +Structured outputs are crucial when you need your AI agents to provide data in a predictable and usable format. Instead of free-form text, you can enforce a specific structure, making it easier for your applications to parse and utilize the information. The OpenAI Agents SDK provides mechanisms to achieve this. + +**Why Use Structured Outputs?** + +**Data Parsing**: Easier to extract specific information without complex text parsing. + +**Integration**: Seamless integration with other systems that expect structured data (e.g., databases, APIs). + +**Reliability**: Reduces ambiguity and ensures consistent data formatting. + +**Automation**: Automate workflows that rely on specific data points. + + +Using uv to run the project + + uv run chainlit run app.py -w diff --git a/examples/example-with-ui/structured_output/app.py b/examples/example-with-ui/structured_output/app.py new file mode 100644 index 00000000..d8075508 --- /dev/null +++ b/examples/example-with-ui/structured_output/app.py @@ -0,0 +1,97 @@ +# app.py +import chainlit as cl +import nest_asyncio +from pydantic import BaseModel +from agents import Agent, Runner, AsyncOpenAI, OpenAIChatCompletionsModel, RunConfig +from dotenv import load_dotenv +import os +# Apply nest_asyncio to handle event loop in Chainlit +load_dotenv() +nest_asyncio.apply() + +# Define the WeatherAnswer Pydantic model +class WeatherAnswer(BaseModel): + location: str + temperature_c: float + summary: str + +# Setup function that runs when the app starts +@cl.on_chat_start +async def setup_agent(): + try: + # Get Gemini API key (adjust this based on your environment) + gemini_api_key = os.getenv("GEMINI_API_KEY") + if not gemini_api_key: + raise ValueError("GEMINI_API_KEY is not set. Please ensure it is defined.") + + # Configure the external client for Gemini + external_client = AsyncOpenAI( + api_key=gemini_api_key, + base_url="https://generativelanguage.googleapis.com/v1beta/openai/", + ) + + # Configure the model + model = OpenAIChatCompletionsModel( + model="gemini-2.0-flash", + openai_client=external_client + ) + + # Configure run settings + config = RunConfig( + model=model, + model_provider=external_client, + tracing_disabled=True + ) + + # Create the agent + agent = Agent( + name="StructuredWeatherAgent", + instructions="Use the final_output tool with WeatherAnswer schema.", + output_type=WeatherAnswer + ) + + # Store the agent and config in the user session + cl.user_session.set("agent", agent) + cl.user_session.set("config", config) + + await cl.Message( + content="Weather Agent is ready! Ask me about the weather in any location." + ).send() + + except Exception as e: + await cl.Message(content=f"Error during setup: {str(e)}").send() + +# Main message handler +@cl.on_message +async def handle_message(message: cl.Message): + try: + # Get agent and config from session + agent = cl.user_session.get("agent") + config = cl.user_session.get("config") + + if not agent or not config: + await cl.Message(content="Agent not initialized. Please restart the chat.").send() + return + + # Run the agent with the user's query + result = await Runner.run(agent, message.content, run_config=config) + + # Format the structured output + if result.final_output: + weather = result.final_output + response = f"Weather in {weather.location}:\n" \ + f"Temperature: {weather.temperature_c}°C\n" \ + f"Summary: {weather.summary}" + else: + response = "Sorry, I couldn't get the weather information." + + # Send the response + await cl.Message(content=response).send() + + except Exception as e: + await cl.Message(content=f"Error: {str(e)}").send() + +# Note: To run this, you'll need to: +# 1. Install required packages: pip install chainlit openai-agents pydantic +# 2. Set your GEMINI_API_KEY in your environment +# 3. Run with: chainlit run app.py \ No newline at end of file diff --git a/examples/example-with-ui/structured_output/pyproject.toml b/examples/example-with-ui/structured_output/pyproject.toml new file mode 100644 index 00000000..19ebb4b5 --- /dev/null +++ b/examples/example-with-ui/structured_output/pyproject.toml @@ -0,0 +1,11 @@ +[project] +name = "structured-output" +version = "0.1.0" +description = "Add your description here" +readme = "README.md" +requires-python = ">=3.11" +dependencies = [ + "chainlit>=2.4.1", + "openai-agents>=0.0.4", + "python-dotenv>=1.0.1", +] diff --git a/examples/example-with-ui/structured_output/uv.lock b/examples/example-with-ui/structured_output/uv.lock new file mode 100644 index 00000000..09d063ec --- /dev/null +++ b/examples/example-with-ui/structured_output/uv.lock @@ -0,0 +1,1102 @@ +version = 1 +requires-python = ">=3.11" + +[[package]] +name = "aiofiles" +version = "24.1.0" +source = { registry = "https://pypi.org/simple" } +sdist = { url = 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