8000 Weather openAI (single turn) (#18) · microsoft/Agents-for-python@eca4fce · GitHub
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Weather openAI (single turn) (#18)
* WIP Weather openAI * Single-turn weather openai working
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‎libraries/Builder/microsoft-agents-builder/microsoft/agents/builder/message_factory.py

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@@ -25,12 +25,13 @@ def attachment_activity(
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type=ActivityTypes.message,
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attachment_layout=attachment_layout,
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attachments=attachments,
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input_hint=input_hint,
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)
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if text:
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message.text = text
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if speak:
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message.speak = speak
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if input_hint:
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message.input_hint = input_hint
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return message
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‎test_samples/weather-agent-open-ai/app.py

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# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License.
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import os
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from agents import set_tracing_export_api_key
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from dotenv import load_dotenv
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from aiohttp.web import Application, Request, Response, run_app
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from microsoft.agents.builder import RestChannelServiceClientFactory
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from microsoft.agents.hosting.aiohttp import CloudAdapter, jwt_authorization_middleware
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from microsoft.agents.authorization import (
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Connections,
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AccessTokenProviderBase,
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ClaimsIdentity,
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)
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from microsoft.agents.authentication.msal import MsalAuth
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from openai import AsyncAzureOpenAI
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from weather_agent import WeatherAgent
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from config import DefaultConfig
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load_dotenv()
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CONFIG = DefaultConfig()
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AUTH_PROVIDER = MsalAuth(DefaultConfig())
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class DefaultConnection(Connections):
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def get_default_connection(self) -> AccessTokenProviderBase:
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pass
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def get_token_provider(
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self, claims_identity: ClaimsIdentity, service_url: str
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) -> AccessTokenProviderBase:
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return AUTH_PROVIDER
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def get_connection(self, connection_name: str) -> AccessTokenProviderBase:
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pass
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CHANNEL_CLIENT_FACTORY = RestChannelServiceClientFactory(CONFIG, DefaultConnection())
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# Create adapter.
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ADAPTER = CloudAdapter(CHANNEL_CLIENT_FACTORY)
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# gets the API Key from environment variable AZURE_OPENAI_API_KEY
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CLIENT = AsyncAzureOpenAI(
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api_version=CONFIG.AZURE_OPENAI_API_VERSION,
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azure_endpoint=CONFIG.AZURE_OPENAI_ENDPOINT,
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)
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# Create the Agent
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AGENT = WeatherAgent(client=CLIENT)
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# Listen for incoming requests on /api/messages
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async def messages(req: Request) -> Response:
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adapter: CloudAdapter = req.app["adapter"]
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return await adapter.process(req, AGENT)
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APP = Application(middlewares=[jwt_authorization_middleware])
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APP.router.add_post("/api/messages", messages)
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APP["agent_configuration"] = CONFIG
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APP["adapter"] = ADAPTER
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if __name__ == "__main__":
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try:
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run_app(APP, host="localhost", port=CONFIG.PORT)
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except Exception as error:
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raise error

‎test_samples/weather-agent-open-ai/config.py

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from os import environ
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from microsoft.agents.authentication.msal import AuthTypes, MsalAuthConfiguration
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class DefaultConfig(MsalAuthConfiguration):
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"""Agent Configuration"""
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def __init__(self) -> None:
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self.AUTH_TYPE = AuthTypes.client_secret
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self.TENANT_ID = "" or environ.get("TENANT_ID")
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self.CLIENT_ID = "" or environ.get("CLIENT_ID")
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self.CLIENT_SECRET = "" or environ.get("CLIENT_SECRET")
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self.AZURE_OPENAI_API_KEY = "" or environ.get("AZURE_OPENAI_API_KEY")
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self.AZURE_OPENAI_ENDPOINT = "" or environ.get("AZURE_OPENAI_ENDPOINT")
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self.AZURE_OPENAI_API_VERSION = "" or environ.get(
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"AZURE_OPENAI_API_VERSION", "2024-06-01"
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)
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self.PORT = 3978

‎test_samples/weather-agent-open-ai/requirements.txt

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openai
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openai-agents

‎test_samples/weather-agent-open-ai/tools/date_time_tool.py

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from agents import function_tool
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from datetime import datetime
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@function_tool
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def get_date() -> str:
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"""
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A function tool that returns the current date and time.
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"""
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return datetime.now().isoformat()

‎test_samples/weather-agent-open-ai/tools/get_weather_tool.py

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import random
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from pydantic import BaseModel
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from agents import function_tool
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class Weather(BaseModel):
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city: str
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temperature: str
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conditions: str
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date: str
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@function_tool
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def get_weather(city: str, date: str) -> Weather:
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print("[debug] get_weather called")
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temperature = random.randint(8, 21)
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return Weather(
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city=city,
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temperature=f"{temperature}C",
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conditions="Sunny with wind.",
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date=date,
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)

‎test_samples/weather-agent-open-ai/weather_agent.py

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from __future__ import annotations
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from typing import Union
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from microsoft.agents.builder import ActivityHandler, MessageFactory, TurnContext
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from microsoft.agents.core.models import ChannelAccount, Attachment
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from agents import (
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Agent as OpenAIAgent,
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Model,
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ModelProvider,
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OpenAIChatCompletionsModel,
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RunConfig,
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Runner,
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)
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from openai import AsyncAzureOpenAI
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from pydantic import BaseModel, Field
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from tools.get_weather_tool import get_weather
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from tools.date_time_tool import get_date
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class WeatherForecastAgentResponse(BaseModel):
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contentType: str = Field(pattern=r"^(Text|AdaptiveCard)$")
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content: Union[dict, str]
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class WeatherAgent(ActivityHandler):
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def __init__(self, client: AsyncAzureOpenAI):
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self.agent = OpenAIAgent(
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name="WeatherAgent",
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instructions=""""
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You are a friendly assistant that helps people find a weather forecast for a given time and place.
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Do not reply with MD format nor plain text. You can ONLY respond in JSON format with the following JSON schema
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{
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"contentType": "'Text' if you don't have a forecast or 'AdaptiveCard' if you do",
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"content": "{The content of the response, may be plain text, or JSON based adaptive card}"
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}
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You may ask follow up questions until you have enough information to answer the customers question,
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but once you have a forecast forecast, make sure to format it nicely using an adaptive card.
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""",
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tools=[get_weather, get_date],
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)
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class CustomModelProvider(ModelProvider):
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def get_model(self, model_name: str | None) -> Model:
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return OpenAIChatCompletionsModel(
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model=model_name or "gpt-4o", openai_client=client
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)
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self.custom_model_provider = CustomModelProvider()
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async def on_members_added_activity(
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self, members_added: list[ChannelAccount], turn_context: TurnContext
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):
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for member in members_added:
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if member.id != turn_context.activity.recipient.id:
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await turn_context.send_activity("Hello and welcome!")
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async def on_message_activity(self, turn_context: TurnContext):
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response = await Runner.run(
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self.agent,
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turn_context.activity.text,
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run_config=RunConfig(
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model_provider=self.custom_model_provider,
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tracing_disabled=True,
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),
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)
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llm_response = WeatherForecastAgentResponse.model_validate_json(
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response.final_output
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)
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if llm_response.contentType == "AdaptiveCard":
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activity = MessageFactory.attachment(
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Attachment(
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content_type="application/vnd.microsoft.card.adaptive",
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content=llm_response.content,
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)
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)
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elif llm_response.contentType == "Text":
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activity = MessageFactory.text(llm_response.content)
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return await turn_context.send_activity(activity)

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