agent.py

import os
import sys
from datetime import date
from openai import OpenAI

BASE_DIR = os.path.dirname(__file__)
FILES = {
    "today": os.path.join(BASE_DIR, "today.md"),
    "backlog": os.path.join(BASE_DIR, "backlog.md"),
    "log": os.path.join(BASE_DIR, "log.md"),
}

def read(path):
    if not os.path.exists(path):
        return ""
    with open(path, "r", encoding="utf-8") as f:
        return f.read()

def append(path, text):
    with open(path, "a", encoding="utf-8") as f:
        f.write(text)

def multiline_input(prompt):
    print(prompt)
    lines = []
    while True:
        line = input("> ").strip()
        if not line:
            break
        lines.append(line)
    return "\n".join(lines)

client = OpenAI()
today_str = str(date.today())

MODE = "morning"
if "--midday" in sys.argv:
    MODE = "midday"
elif "--done" in sys.argv:
    MODE = "done"

SYSTEM_PROMPTS = {
    "morning": """
You are a daily work planning assistant.

Rules:
- Be realistic about time and energy
- Never plan more than ~70% of available time
- Always choose ONE top priority
- Prefer finishing over starting
- Explicitly suggest what to drop
- No motivational fluff

Output format:
Top priority:
Proposed plan:
Drop if needed:
Rule:
""",
    "midday": """
You are a pragmatic midday replanning assistant.

Rules:
- Assume interruptions happened
- Adjust expectations downward if needed
- Protect the top priority if possible
- Explicitly drop tasks if necessary
- No guilt, no motivation, just reality

Output format:
Updated focus:
Revised plan:
Drop:
Rule for rest of day:
""",
    "done": """
You summarize the workday outcome.

Rules:
- Be factual, not emotional
- Identify what is DONE
- Identify what should carry over
- Keep it short

Output format:
Done:
Partially done:
Carry over:
Notes:
"""
}

user_update = ""
if MODE in ("midday", "done"):
    user_update = multiline_input(
        f"Enter {'midday update' if MODE == 'midday' else 'end-of-day notes'} (finish with empty line):"
    )

USER_PROMPTS = {
    "morning": f"""
TODAY ({today_str}):
{read(FILES["today"])}

BACKLOG:
{read(FILES["backlog"])}
""",
    "midday": f"""
MIDDAY UPDATE ({today_str}):

Planned context:
{read(FILES["today"])}

What actually happened so far:
{user_update}
""",
    "done": f"""
END OF DAY ({today_str}):

Planned context:
{read(FILES["today"])}

What actually happened today:
{user_update}
"""
}

response = client.chat.completions.create(
    model="gpt-4o-mini",
    messages=[
        {"role": "system", "content": SYSTEM_PROMPTS[MODE]},
        {"role": "user", "content": USER_PROMPTS[MODE]},
    ],
)

output = response.choices[0].message.content.strip()

print(f"\n=== {MODE.upper()} OUTPUT ===\n")
print(output)
print("\n===========================\n")

append(
    FILES["log"],
    f"\n## {today_str} — {MODE.capitalize()}\n{output}\n"
)