प्रैक्टिस में एजेंट मेमोरी

def summarise(old_summary: str, messages: list) -> str:
    # Placeholder: in real code, ask the model to update the summary.
    # Keep facts, decisions and open questions; drop chit-chat.
    lines = [m["role"] + ": " + m["content"][:60] for m in messages]
    return (old_summary + " | " if old_summary else "") + "; ".join(lines)

class Memory:
    def __init__(self, goal: str, keep_last: int = 6):
        self.goal = goal
        self.summary = ""
        self.recent = []
        self.keep_last = keep_last

    def add(self, role: str, content: str):
        self.recent.append({"role": role, "content": content})
        if len(self.recent) > self.keep_last:
            old = self.recent[:-self.keep_last]
            self.recent = self.recent[-self.keep_last:]
            self.summary = summarise(self.summary, old)

    def context(self) -> list:
        head = [{"role": "system", "content": "Goal: " + self.goal}]
        if self.summary:
            head.append({"role": "system", "content": "Earlier (summary): " + self.summary})
        return head + self.recent

mem = Memory("Plan a 3-day Kerala trip under Rs 20,000", keep_last=2)
for text in ["Budget is firm", "Prefer trains", "Vegetarian food", "Start from Kochi"]:
    mem.add("user", text)
for m in mem.context():
    print(m["role"], "->", m["content"])