Openai Agents Python Examples. Jan 7, 2024 · Build you own AI agent from scratch in 30 mins usi

Jan 7, 2024 · Build you own AI agent from scratch in 30 mins using simple Python Introduction OpenAI released ChatGPT on November 30, 2022, and due to its success, 2023 became the year of AI chat apps. Core concepts: Agents: LLMs configured with instructions, tools May 28, 2025 · Why this matters The "agents as a tool" pattern is a powerful way to build transparent, auditable, and scalable multi-agent collaboration . middleware import wrap_model_call, ModelRequest, ModelResponse basic_model = ChatOpenAI(model="gpt-4o-mini") advanced_model = ChatOpenAI(model="gpt-4o") @wrap_model_call def dynamic_model_selection(request: ModelRequest, handler Jul 14, 2025 · The openai Python package The openai-agents package An OpenAI API key set as OPENAI_API_KEY in your environment variables 1. Simply follow their instructions for which {PROVIDER}_API_KEY to set and how to write pass the {provider_name}/ {model_name} to the constructor. A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Feb 9, 2024 · This is the first part in a multi-part series on building Agents with OpenAI's Assistant API using the Python SDK. A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Realtime framework for voice, video, and physical AI agents. Get started by installing the SDK using pip: Execute the code with python example. If you want the agent to produce a particular type of output, you can use the output_type parameter. By the end, you will be ready to create and interact with your own simple OpenAI agent. The AI agent we build will have access to tools (Temporal Activities) to answer user questions. A common choice is to use Pydantic objects, but we support any type that can be wrapped in a Pydantic TypeAdapter - dataclasses, lists, TypedDict, etc. The user sets their desired structured output schema, and when the model generates the structured data, it’s captured, validated, and returned in the 'structured_response' key of the agent’s state. Below, you can see how to extract information from unstructured text that conforms to a schema defined in code. This will automatically start and end the trace at the right time. Learn how to integrate Accelo with open-ai-agents-sdk using the Model Context Protocol (MCP). A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python LangChain’s create_agent handles structured output automatically. Traces need to be started and finished. By implementing a simple weather agent across the OpenAI SDK, OpenAI Agents SDK, LangChain, LangGraph, and the Microsoft Agent Framework. For example, this will ignore raw events and stream updates to the user. Feb 3, 2025 · We will define two agents: FileAccessAgent: This agent will read the file and provide the context to the PythonCodeExecAgent. effort="none" with gpt-5. Create stateful interactions with the model, using the output of previous responses as input. Non-GPT-5 models If you pass a non–GPT-5 model name without custom model_settings, the SDK reverts to generic ModelSettings compatible with any model. May 16, 2025 · Introducing Codex: a cloud-based software engineering agent that can work on many tasks in parallel, powered by codex-1. Extend the model's capabilities with built-in tools for file search, web search, computer use, and more. Below we present a number of prompt formats we find work well, but feel free to explore different formats, which may fit your task better. LiveKit CLI Use the LiveKit CLI to manage LiveKit API keys and deploy your agent to LiveKit Cloud. Oct 21, 2025 · The OpenAI Agents SDK is a Python library engineered to simplify the development of AI agents powered by OpenAI’s language models. docs: add ExecPlan guidance and template by @seratch in #2298 Update examples by @seratch in #2300 feat: add examples auto-run skill and refresh example scripts by @seratch in #2303 Add two more agent skills by @seratch in #2304 misc: add docs-sync skill by @seratch in #2306 chore: add release workflows and review prompt by @seratch in #2309 4 days ago · Bring enterprise-grade durability to your AI agents with Restate and OpenAI Agents SDK. A traditional rules engine works like a checklist, flagging transactions based on preset criteria. As a result, real-time mode fails because the SDK always attempts to authenticate against OpenAI’s public API instead of using the Azure client credentials. from langchain_openai import ChatOpenAI from langchain. md file with instructions for using the MCP server and other important information about building agents with LiveKit. Overview OpenAI Swarm OpenAI Swarm is an open‑source, lightweight multi‑agent orchestration framework designed to coordinate many LLM‑driven agents via simple Python and function‑calling, emphasizing simplicity, retrieval‑heavy workflows, and scalable multi‑agent setups. For a deep dive into the architecture and real-world applications of Agent Skills, read Equipping agents for the real world with Agent Skills. e. Learn about their features and how they compare to GPT-4o models. You have a few options for getting started with this repository. In contrast, an LLM agent functions more like a seasoned investigator, evaluating context, considering subtle patterns, and identifying suspicious activity even when clear-cut rules aren't violated. 6 days ago · Check the SIP side for project proj_6ThBeJvaJTKbbGyke5l6Dzah and the example Twilio Call SID (s) above, to see why sip. 1 day ago · Building Autonomous AI Agents: A Practical Guide with LlamaIndex, OpenAI, and Self-Evaluation Can autonomous AI agents truly revolutionize how we interact with technology? Jun 24, 2024 · Semantic Kernel is a lightweight, open-source development kit that lets you easily build AI agents and integrate the latest AI models into your C#, Python, or Java codebase. Agents are systems that intelligently accomplish tasks—from simple goals to complex, open-ended workflows. OpenTelemetry instrumentation for Python modules. MCP: Skills tell Claude how to use tools; MCP provides the tools. In collaboration with Microsoft, OpenAI provides an officially supported API client for C#. The quickest way to get started is Mar 11, 2025 · A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Mar 16, 2025 · spent the weekend exploring the new agents sdk — built a simple multi-llm call workflow and shared my first impressions the code example put together guardrails & streaming too! the code example puts together guardrails & streaming too! thoughts: “agents as tools” vs “handoffs” the built-in traces ui is outstanding guardrails and streaming outputs: room for improvement? sometimes GenAI Agent Framework, the Pydantic way You can learn more about the differences between the Responses API and Chat Completions API in the OpenAI API docs. A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Jan 18, 2023 · Open-source examples and guides for building with the OpenAI API. Non-OpenAI models You can use most other non Explore resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's developer platform. This guide walks you through creating a Python application that combines OpenAI's GPT models with CData Connect AI to enable conversational access to your data. This guide delivers a detailed, technical walkthrough of LangChain is an open source framework with a pre-built agent architecture and integrations for any model or tool — so you can build agents that adapt as fast as the ecosystem evolves Dec 29, 2025 · A curated list of skills, tools, tutorials, and capabilities for AI coding agents (Claude, Codex, Copilot, VS Code) - heilcheng/awesome-agent-skills In addition to supporting JSON Schema in the REST API, the OpenAI SDKs for Python and JavaScript also make it easy to define object schemas using Pydantic and Zod respectively. Those models are free to use for anyone with a GitHub account, up to a daily rate limit. Learn how to deploy and manage containerized AI agents with zero infrastructure setup by using the feature of hosted agents in Microsoft Foundry. Here’s a concise guide to help you get started: // After connecting the OpenAI agent as shown above const realtimeClient = await streamClient. This example demonstrates how to combine deep specialization, parallel execution, and robust orchestration using the OpenAI Agents SDK. Learn how to integrate Replicate with open-ai-agents-sdk using the Model Context Protocol (MCP). 2 days ago · This page demonstrates how to write your first test using the `openai-responses` library. The current trace is tracked via a Python Oct 25, 2020 · The official Python library for the OpenAI API. This function will power our AI agent: Here is the code: A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Skills vs. connectOpenAi({ call, openAiApiKey, agentUserId: "support-agent", }); // Change the voice to 'alloy' realtimeClient. updateSession({ instructions: `You Using the OpenAI API in Python is straightforward, especially with the official OpenAI Python library and available quickstart examples. py. You will learn how to define an agent with specific instructions, run it synchronously using the Runner class, and extract the agent’s final output. This article provides an overview of the Microsoft Foundry SDKs and endpoints and how to get started using them. financial_research_agent: A financial research agent that demonstrates structured research workflows with agents and tools for financial data analysis. Tools & Dependency Injection Example Here is a concise example using Pydantic AI to build a support agent for a bank: Learn how to understand or generate images with the OpenAI API. Some examples: If your provider offers an OpenAI-compatible endpoint, just add an openai/ prefix to your full model name. Code interpreter: allow models to write In DSPy, you can use any of the dozens of LLM providers supported by LiteLLM. This example demonstrates how to use Agno's built-in OpenAI moderation guardrail to detect and block content that violates OpenAI's content policy. Output types By default, agents produce plain text (i. Design real-world AI agents visually using OpenAI’s AgentBuilder—no heavy coding required. Jul 28, 2025 · OpenAI Codex: What is it, how to access it, steps to login, examples on how to use OpenAI Codex for software development tasks. The model layer handles API calls to language models, request. Nov 18, 2025 · This page documents the model abstraction layer that enables the SDK to integrate with multiple LLM providers through a unified interface. The tool simply runs the Codex CLI as a subprocess, so all existing Codex configuration, skills, and capabilities are available without any additional setup. You can also manually call trace. from agents import Agent agent = Agent( name="Math Tutor", instructions="You provide help with math problems. updateSession({ instructions: `You Using the OpenAI API in Python is straightforward with the official OpenAI Python library. Agents as tools: expose an agent as a callable tool without a full handoff. It equips developers with tools to create task-specific agents, integrate external functionalities, manage inter-agent task delegation, enforce input/output validation, and monitor execution flows. Learn how to use Azure OpenAI's new stateful Responses API. as the result of a handoff). Anaconda is a library that includes Python and many useful packages for Python, as well as an environment manager called conda that makes package management simple. You have two options to do so: Recommended: use the trace as a context manager, i. com is returning 400 Bad Request on some INVITEs? // After connecting the OpenAI agent as shown above const realtimeClient = await streamClient. Function calling: wrap any Python function as a tool. Not very interesting yet, but we can easily add tools, dynamic instructions, and structured outputs to build more powerful agents. **Install the OpenAI Pytho OpenAI Computer Use Use OpenAI models with computer use capabilities for browser automation OpenAI’s Computer Use Agent (openai-cua) leverages GPT models with vision and reasoning capabilities for screenshot-based browser automation. The agent can determine which tools to use based on the user's input and execute them as needed. Similarly, AgentUpdatedStreamEvent gives you updates when the current agent changes (e. It covers the minimal setup required to mock OpenAI API calls in a pytest test function using the `@openairesp The official prompt engineering guide by OpenAI is usually the best place to start for prompting tips. Non-strict output types Previous response ID usage customer_service: Example customer service system for an airline. If you run an agent with codex_tool() on a host where Codex is installed, the agent will use Codex as a tool to answer the question. Contribute to langchain-ai/langgraph development by creating an account on GitHub. Aug 29, 2025 · This guide shows how to add persistent memory to your OpenAI Agents using Memori, an open-source memory engine that makes AI agents remember conversations and learn from past interactions. Learn how to integrate Airtable with open-ai-agents-sdk using the Model Context Protocol (MCP). agents. Deep Agents are equipped with a planning tool, a filesystem backend, and the ability to spawn subagents - making them well-equipped Build resilient language agents as graphs. See the docs for conceptual guides, tutorials, and examples on using Agents. The agent factory - Design, customize, manage, and support AI applications and agents at scale. 20 hours ago · This blog demonstrated how the OCI OpenAI package makes it easy to build agentic applications on OCI Generative AI using multiple frameworks. Follow the installation instructions for Anaconda here. Nov 4, 2025 · The process consists of the following steps: Baseline Agent The process begins with a baseline agent. 2 is recommended. This ensures your agent has access to the latest documentation and examples. For lower latency, using reasoning. A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Oct 2, 2025 · In this example, we show you how to build a Durable Agent using the OpenAI Agents SDK Integration for Temporal. This repository provides examples of many popular Python AI agent frameworks using LLMs from GitHub Models. It serves as an efficient middleware that enables rapid delivery of enterprise-grade solutions. Jan 10, 2026 · To prepare AI agents for office work, the company is asking contractors to upload projects from past jobs, leaving it to them to strip out confidential and personally identifiable information. Use the OpenAI Agent Builder to start from templates, compose nodes, preview runs, and export workflows to code. A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Hosted OpenAI tools: run alongside the model on OpenAI servers. Supports text and image inputs, and text outputs. Creating traces You can use the trace() function to create a trace. Share your own examples and guides. For example, an MCP server connects Claude to your database, while a Skill teaches Claude your data model and query patterns. A lightweight, powerful framework for multi-agent workflows - Renol1/openai-agents-python-Nordrelos Responses OpenAI's most advanced interface for generating model responses. In real-world or enterprise settings, the baseline agent could be much more complex. Each agent specializes in either detecting or rewriting a specific type of issue: To use the OpenAI API in Python, you can use the official OpenAI SDK for Python. Contribute to openai/openai-python development by creating an account on GitHub. Step 3: Set up Agentic Orchestration to run the application Learn how to build agents with the OpenAI Agents SDK. A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python LangChain’s create_agent handles structured output automatically. OpenAI provides models with agentic strengths, a toolkit for agent creation and deploys, and dashboard features for monitoring and optimizing agents. with trace() as my_trace. str) outputs. In a few moments, you should see the output of your API request. openai. updateSession({ instructions: `You // After connecting the OpenAI agent as shown above const realtimeClient = await streamClient. In this notebook, we use a deliberately simple example (an agent that summarizes sections of a document) to illustrate the iterative improvement loop. g. OpenAI Agents SDK OpenAI Agents SDK The OpenAI Agents SDK is a lightweight yet powerful framework for building multi-agent workflows. Built-in tools The Responses API has built-in tools that you can use instead of building your own: Web search: allow models to search the web for the latest information before generating a response. Here’s a simple example to get started: 1. This nuanced reasoning capability is exactly what Developer Guide - Build AI-Powered Data Assistants with OpenAI Python SDK Build intelligent data assistants that can query your live data sources using natural language. Contribute to langchain-ai/langchain development by creating an account on GitHub. py file and create a simple function to generate text using the OpenAI API. This allows you to push progress updates at the level of "message generated", "tool ran", etc, instead of each token. Learn how to integrate Pdf4me with open-ai-agents-sdk using the Model Context Protocol (MCP). A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Explore developer resources, tutorials, API docs, and dynamic examples to get the most out of OpenAI's platform. Installing Python ¶ We recommend installing Python through Anaconda. Learn how function calling enables large language models to connect to external data and systems. See the example code and #2320 for more details. updateSession({ voice: "alloy" }); // Set detailed instructions for the AI agent realtimeClient. api. Contribute to open-telemetry/opentelemetry-python-contrib development by creating an account on GitHub. [!NOTE] Looking for the JavaScript/TypeScript version? Check out Agents SDK JS/TS. Explore the capabilities of OpenAI's o1 series for complex reasoning and problem-solving. start() and trace. handoffs: See practical examples of agent handoffs with message filtering. 1 family (including mini and nano variants) also remains a solid choice for building interactive agent apps. memory: Examples of different memory implementations for agents, including: SQLite session storage Advanced SQLite session storage Redis session storage SQLAlchemy session storage Encrypted session storage OpenAI session storage model_providers: Explore how to use non-OpenAI models with the SDK, including custom providers and LiteLLM integration. Agents Reference docs This page contains reference documentation for Agents. Browse a collection of snippets, advanced techniques and walkthroughs. 🦜🔗 The platform for reliable agents. video. Consider the example of payment fraud analysis. Local runtime tools: run in your environment (computer use, shell, apply patch). Aug 27, 2025 · When using the OpenAI Agents SDK in Python with Azure OpenAI as the default model (via the async Azure client), the SDK ignores the Azure configuration and still requires OPENAI_API_KEY. System Overview The prompt optimization system uses a collaborative multi-agent approach to analyze and improve prompts. With Codex, developers can simultaneously deploy multiple agents to independently handle coding tasks such as writing features, answering questions about your codebase, fixing bugs, and proposing pull requests for review. finish(). Explain your reasoning at each step and include examples", ) Apr 30, 2024 · Generate Text with OpenAI API Open the main. Mar 11, 2025 · The OpenAI Agents SDK is a lightweight yet powerful framework for building multi-agent workflows. Step-by-step guide with Python and TypeScript code examples. It is provider-agnostic, supporting the OpenAI Responses and Chat Completions APIs, as well as 100+ other LLMs. PythonCodeExecAgent: This agent will generate the Python code to answer the user's question and execute the code in the Docker container. A lightweight, powerful framework for multi-agent workflows - openai/openai-agents-python Nov 18, 2025 · Model Implementations OpenAIChatCompletionsModel The OpenAIChatCompletionsModel implementation uses OpenAI's Chat Completions API (/v1/chat/completions), which is the standard API for most OpenAI models and compatible providers. The gpt-4. The starter projects also include an AGENTS. agents import create_agent from langchain. This lesson introduces you to the OpenAI Agents SDK in Python, explaining what agents are, how they differ from basic chat LLMs, and how the agent loop works. Deep Agents is an agent harness built on langchain and langgraph.

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