Agent Showcase Build AI agents at the speed of thought Speed up your AI development with Prompt Composer. Display your data, the prompt, and its result, side by side in a single view. Develop and iterate your prompt interactively with AI assistance, and immediately see the result of changes...
See the OpenAI AI assistant cookbook in the core library for reference. Why is this needed? Assistant is useful single agent abstraction used by many applications. Activity ekzhuadded feature proj-agentchat on Oct 4, 2024 github-actionsadded needs-triage on Oct 4, 2024 ekzhuremoved needs-...
You need the Cognitive Services OpenAI User role assigned to use the Azure AI Services resource. Install the Azure CLI and the machine learning extension. If you have the CLI already installed, make sure it's updated to the latest version. Set up your Azure AI Hub and Agent project The fo...
publicstaticSystem.Threading.Tasks.Task<Microsoft.SemanticKernel.Agents.OpenAI.OpenAIAssistantAgent> CreateAsync (Microsoft.SemanticKernel.Kernel kernel, Microsoft.SemanticKernel.Agents.OpenAI.OpenAIClientProvider clientProvider, Microsoft.SemanticKernel.Agents.OpenAI.OpenAIAssistantDefinition definition, System....
Actions –Allows you to create and import Conversational and AI Plugins that can be used in your agent. Activity –Displays the agent's Generative AI activity, including calls to the Azure OpenAI GPT service. Analytics –Provides analytical details that are related to the performance and usage of...
import openai from openai_function_call import openai_function @openai_function def sum(a:int, b:int) -> int: """Sum description adds a + b""" return a + b completion = openai.ChatCompletion.create( model="gpt-3.5-turbo-0613", temperature=0, functions=[sum.openai_schema], messages=...
this module provides access to some variables used or maintained by the interpreter and functions that interact with the interpreter. openai : the openai python library provides convenient access to the openai api from applications written in python. it includes ...
Tools: Choose from a variety of agent tools (functions called by the LLM), such as: Code Interpreter: Executes Python code in a secure Jupyter notebook environment Artifact Code Generator: Generates code artifacts that can be run in a sandbox ...
load_dotenv("azure.env")# Azure Open AIopenai_api_type=os.getenv("azure")openai_api_base=os.getenv("AZURE_OPENAI_ENDPOINT")openai_api_version=os.getenv("AZURE_API_VERSION")openai_api_key=os.getenv("AZURE_OPENAI_KEY")# Azure Cognitive Searchacs_endpoint=os.getenv...
Information sources defined in the Generative answers node override sources you specified at the agent level, which functions as a fallback. When using generative answers nodes, you have the option of using modern Knowledge sources or Classic data. Knowledge sources include: External sources: Public...