Nat TaylorBlog, AI, Product Management & Tinkering

Test Drive: controlflow

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Today I’m test driving ControlFlow, “a Python framework for building agentic AI workflows.” I thought I’d take a document and turn it into a NotebookLM-deep-dive-style podcast script. The process was:

  1. Install controlflow
  2. Do the Seinfield converstaion example
  3. Update the example to do the deepdive

Well… I didn’t make much progress and I’ll explain below. I put my code below, which does technically produce some output, just not what I hoped and often with errors. My accomplishment of the day was turning on debug logging and also tracing with this code:

from langtrace_python_sdk import langtrace
langtrace.init(**config)
import openai
import logging
logging.getLogger("controlflow").setLevel(logging.DEBUG)
logging.getLogger("openai").setLevel(logging.DEBUG)

That was helpful, but still not enough.

"""toy attempt to clone of NotebookLM deep dive"""
import textwrap
import controlflow as cf

bill = cf.Agent(
    name="Bill",
    model="openai/gpt-4o-mini",
    description="Charismatic podcast host",
    instructions="""
    You excel at finding interesting things in the text,
    referring to those things and engaging your co-host,
    to create an entertaining podcast.
    Your objective is to say sentences that your co-host can react to.
    """,
)

hillary = cf.Agent(
    name="Hillary",
    model="openai/gpt-4o-mini",
    description="Funny podcast sidekick.",
    instructions="""
    You react to what your cost host says, often by asking a question.
    Your objective is to react to what your co-host says.
    """,
)

@cf.flow
def deepdive(text: str):
    task = cf.Task(
        "Deep dive a text",
        agents=[bill, hillary],
        completion_agents=[bill],
        # result_type=None,
        context=dict(text=text),
        instructions=textwrap.dedent("""\
            only one agent per turn. Keep responses to 1 sentence max.
            react to what the other agent says.
            bill references interesting passages from the text
            Start with an introduction.
            Probe the topics in the text
            Finish with a brief outro.""")
    )
    task.run()



if __name__ == "__main__":
    with open('transcript.txt', 'r') as file:
        text = file.read()
    deepdive(text=text[:5000])
╭─ Agent: Bill ────────────────────────────────────────────────────────────────────────────────────╮
│                                                                                                  │
│  Welcome to today's deep dive! We're diving into a fascinating oral history from East Boston,    │
│  specifically reflecting on how the neighborhood has changed since 1906. What do you think       │
│  about the transformation from coal yards to modern developments?                                │
│                                                                                                  │
╰────────────────────────────────────────────────────────────────────────────────────  4:12:22 PM ─╯
╭─ Agent: Bill ────────────────────────────────────────────────────────────────────────────────────╮
│                                                                                                  │
│  ✅ Tool call: "delegate_to_agent"                                                               │
│                                                                                                  │
│     Tool args: {'agent_id': '1837267a'}                                                          │
│                                                                                                  │
│     Tool result: Delegated to agent Hillary with ID 1837267a                                     │
│                                                                                                  │
╰────────────────────────────────────────────────────────────────────────────────────  4:12:23 PM ─╯
╭─ Agent: Hillary ─────────────────────────────────────────────────────────────────────────────────╮
│                                                                                                  │
│  ✅ Tool call: "delegate_to_agent"                                                               │
│                                                                                                  │
│     Tool args: {'agent_id': '1837267a'}                                                          │
│                                                                                                  │
│     Tool result: Delegated to agent Hillary with ID 1837267a                                     │
│                                                                                                  │
╰────────────────────────────────────────────────────────────────────────────────────  4:12:24 PM ─╯
╭─ Agent: Hillary ─────────────────────────────────────────────────────────────────────────────────╮
│                                                                                                  │
│  Wow, it's wild to think about all that history! What do you think the community misses most     │
│  about those coal yard days?                                                                     │
│                                                                                                  │
╰────────────────────────────────────────────────────────────────────────────────────  4:12:25 PM ─╯
╭─ Agent: Hillary ─────────────────────────────────────────────────────────────────────────────────╮
│                                                                                                  │
│  ✅ Tool call: "delegate_to_agent"                                                               │
│                                                                                                  │
│     Tool args: {'agent_id': '076eea10'}                                                          │
│                                                                                                  │
│     Tool result: Delegated to agent Bill with ID 076eea10                                        │
│                                                                                                  │
╰────────────────────────────────────────────────────────────────────────────────────  4:12:25 PM ─╯
╭─ Agent: Bill ────────────────────────────────────────────────────────────────────────────────────╮
│                                                                                                  │
│  ✅ Tool call: "delegate_to_agent"                                                               │
│                                                                                                  │
│     Tool args: {'agent_id': '076eea10'}                                                          │
│                                                                                                  │
│     Tool result: Delegated to agent Bill with ID 076eea10                                        │
│                                                                                                  │
╰────────────────────────────────────────────────────────────────────────────────────  4:12:26 PM ─╯
╭─ Agent: Bill ────────────────────────────────────────────────────────────────────────────────────╮
│                                                                                                  │
│  ✅ Tool call: "mark_task_a99578bf_successful"                                                   │
│                                                                                                  │
│     Tool args: {'result': 'The community likely misses the sense of camaraderie and shared       │
│     culture that came from those days, as they relied on one another in a close-knit             │
│     neighborhood.'}                                                                              │
│                                                                                                  │
│     Tool result: Task #a99578bf ("Deep dive a text") marked successful.                          │
│                                                                                                  │
╰────────────────────────────────────────────────────────────────────────────────────  4:12:27 PM ─

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