pavlovmilen

az_client = AsyncOpenAI(
    api_key=os.environ.get("AZURE_OPEN_AI_API_KEY_SWEDEN"),  # Use your OpenAI API key
    base_url=os.environ.get("AZURE_OPEN_AI_API_ENDPOINT_SWEDEN"),
)

gpt_model_client = AzureOpenAIChatCompletionClient(
    model="gpt-4.1-mini-2025-04-14",
    api_version="2024-06-01",
    azure_deployment="gpt-4.1-mini",
    azure_endpoint=os.environ.get("AZURE_OPEN_AI_API_ENDPOINT_SWEDEN"),

pavlovmilen

import os
from azure.storage.blob import BlobServiceClient
from datetime import datetime
from dotenv import load_dotenv

load_dotenv()
connection_string = os.getenv('storage_connection_string')

def upload_ai_report(report_summary: str, ticker: str):
    """

pavlovmilen

import os
import sys

from dotenv import load_dotenv

from autogen_agentchat.agents import AssistantAgent
from autogen_agentchat.base import TaskResult
from autogen_agentchat.conditions import MaxMessageTermination, TextMentionTermination
from autogen_agentchat.messages import BaseChatMessage
from autogen_agentchat.teams import SelectorGroupChat

pavlovmilen

runtime = SingleThreadedAgentRuntime()
runtime.start()
message_count = 0
total_prompt_tokens = 0
total_completion_tokens = 0

async for message in market_reserarch_agents_team.run_stream(task="Hello, I would like to know if a stock with ticker=MSFT is a good pick for me to invest in this year?"):

    if isinstance(message, TaskResult):
        print("Stop Reason:", message.stop_reason)

pavlovmilen

gpt_model_client = AzureOpenAIChatCompletionClient(
    model="gpt-4.1-mini-2025-04-14",
    api_version="2024-06-01",
    azure_deployment="gpt-4.1-mini",
    azure_endpoint=os.environ.get("AZURE_OPEN_AI_API_ENDPOINT_SWEDEN"),
    #azure_ad_token_provider=token_provider,  # Optional if you choose key-based authentication.
    api_key=os.environ.get("AZURE_OPEN_AI_API_KEY_SWEDEN"),
)

pavlovmilen

market_reserarch_agents_team = SelectorGroupChat(
    [planning_agent, doji_agent, alpha_vantage_news_sentiment_agent, alpha_vantage_company_info_agent, fomc_summary_fetch_agent, peer_valuation_modeling_agent, report_generator_agent, report_upload_agent], 
    termination_condition=termination, 
    allow_repeated_speaker=True,
    model_client=gpt_model_client,
    selector_prompt=selector_prompt)

pavlovmilen

selector_prompt = """Select an agent to perform task.

{roles}

Current conversation context:
{history}

Read the above conversation, then select an agent from {participants} to perform the next task.
Make sure the planner agent has assigned tasks before other agents start working.
Only select one agent at a time.

pavlovmilen

doji_tool = FunctionTool(get_finance_data, description="Download last 60 days of OHLCV data")
doji_agent = AssistantAgent(
    name="doji_agent",
    model_client=gpt_model_client,
    description="Spot daily doji patterns",
    system_message="""
        You retrieve OHLCV data via doji_tool and detect doji candlesticks.
        A daily bar is a doji when abs(Open – Close) ≤ 0.10 × (High – Low).
        Steps: (1) call the tool, (2) run the test, (3) return a list of dates or an empty list if none.
        Output strictly: comma-separated ISO dates. Provide explanations for the doji dates""",

pavlovmilen

planning_agent = AssistantAgent(
    "PlanningAgent",
    description="An agent for planning tasks, this agent should be the first to engage when given a new task.",
    model_client=gpt_model_client,
    system_message="""
    You are a planning agent.
    Your job is to break down complex tasks into smaller, manageable subtasks.
    Your team members are:
        doji_agent: Identify doji patterns in stock data using doji_tool
        alpha_vantage_news_sentiment_agent: Search for a news sentiment about a stock using the search tool

pavlovmilen

// extract data as a string:

private string GetStringContentFromCrimeDataAIModel(List<CrimesAtLocationResponse> results, string postcode)
{
    if(results == null || !results.Any())
    {
        return "No data found";
    }

    results = results.OrderBy(x => x.month).ToList();