Maxim

1from kern.agent import Agent
2from kern.models.openai import OpenAIResponses
3from kern.tools.yfinance import YFinanceTools
4
5try:
6    from maxim import Maxim
7    from maxim.logger.kern import instrument_agno
8except ImportError:
9    raise ImportError(
10        "`maxim` not installed. Please install using `uv pip install maxim-py`"
11    )
12
13# Instrument Kern with Maxim for automatic tracing and logging
14instrument_agno(Maxim().logger())
15
16# Create and configure the agent
17agent = Agent(
18    name="Stock Price Agent",
19    model=OpenAIResponses(id="gpt-5.2"),
20    tools=[YFinanceTools()],
21    instructions="You are a stock price agent. Answer questions in the style of a stock analyst.",
22    show_tool_calls=True,
23    markdown=True,
24)
25
26# Use the agent
27response = agent.run("What is the current price of Tesla?")
28print(response.content)

1"""
2This example shows how to use Maxim to log agent calls and traces.
3
4Steps to get started with Maxim:
51. Install Maxim: uv pip install maxim-py
62. Add instrument_agno(Maxim().logger()) to initialize tracing
73. Authentication:
8 - Go to https://getmaxim.ai and create an account
9 - Generate your API key from the settings
10 - Export your API key as an environment variable:
11    - export MAXIM_API_KEY=<your-api-key>
12    - export MAXIM_LOG_REPO_ID=<your-repo-id>
134. All agent interactions will be automatically traced and logged to Maxim
14"""
15
16from kern.agent import Agent
17from kern.models.openai import OpenAIResponses
18from kern.team.team import Team
19from kern.tools.hackernews import HackerNewsTools
20from kern.tools.yfinance import YFinanceTools
21
22try:
23    from maxim import Maxim
24    from maxim.logger.kern import instrument_agno
25except ImportError:
26    raise ImportError(
27        "`maxim` not installed. Please install using `uv pip install maxim-py`"
28    )
29
30# Instrument Kern with Maxim for automatic tracing and logging
31instrument_agno(Maxim().logger())
32
33# Web Search Agent: Fetches financial information from the web
34web_search_agent = Agent(
35    name="Web Agent",
36    model=OpenAIResponses(id="gpt-5.2"),
37    tools=[HackerNewsTools()],
38    instructions="Always include sources",
39    markdown=True,
40)
41
42# Finance Agent: Gets financial data using YFinance tools
43finance_agent = Agent(
44    name="Finance Agent",
45    model=OpenAIResponses(id="gpt-5.2"),
46    tools=[YFinanceTools()],
47    instructions="Use tables to display data",
48    markdown=True,
49)
50
51# Aggregate both agents into a multi-agent system
52multi_ai_team = Team(
53    members=[web_search_agent, finance_agent],
54    model=OpenAIResponses(id="gpt-5.2"),
55    instructions="You are a helpful financial assistant. Answer user questions about stocks, companies, and financial data.",
56    markdown=True,
57)
58
59if __name__ == "__main__":
60    print("Welcome to the Financial Conversational Agent! Type 'exit' to quit.")
61    messages = []
62    while True:
63        print("********************************")
64        user_input = input("You: ")
65        if user_input.strip().lower() in ["exit", "quit"]:
66            print("Goodbye!")
67            break
68        messages.append({"role": "user", "content": user_input})
69        conversation = "\n".join(
70            [
71                ("User: " + m["content"])
72                if m["role"] == "user"
73                else ("Agent: " + m["content"])
74                for m in messages
75            ]
76        )
77        response = multi_ai_team.run(
78            f"Conversation so far:\n{conversation}\n\nRespond to the latest user message."
79        )
80        agent_reply = getattr(response, "content", response)
81        print("---------------------------------")
82        print("Agent:", agent_reply)
83        messages.append({"role": "agent", "content": str(agent_reply)})