My Chill Dev Research Buddy

conversation_memory = []
MAX_MEMORY = 8
MAX_CHARS = int("[[[MAX_CHARS|6000]]]")


def _clear_memory() -> str:
    global conversation_memory
    conversation_memory = []
    return "ok"


async def process_user_query(query: str) -> str:
    """Handle a friendly coding and research chat request.

    Args:
        query: The user's latest message.

    Returns:
        A helpful conversational response.
    """
    global conversation_memory

    clean_query = (query or "").strip()
    if not clean_query:
        return "Please send a message, and I’ll help with coding, research, or planning."

    clean_query = clean_query[:MAX_CHARS]

    history_lines = []
    for item in conversation_memory[-MAX_MEMORY:]:
        role = item.get("role", "user")
        content = item.get("content", "")[:1200]
        history_lines.append(f"{role.upper()}: {content}")

    history_text = "\n".join(history_lines)

    prompt = (
        "You are continuing a friendly developer and research chat. "
        "Use the conversation when useful. "
        "Be practical, clear, and relaxed. "
        "If the user asks for code, provide code blocks in plain text formatting. "
        "If the user asks for research, give a concise answer with tradeoffs and next steps when helpful.\n\n"
        f"Conversation so far:\n{history_text}\n\n"
        f"User message:\n{clean_query}"
    )

    answer = await agentop_llm.generate(prompt, globals().get("TEMPLATE_SYSTEM_PROMPT", ""))
    answer = (answer or "").strip()

    conversation_memory.append({"role": "user", "content": clean_query})
    conversation_memory.append({"role": "assistant", "content": answer})
    conversation_memory = conversation_memory[-(MAX_MEMORY * 2):]

    return answer or "I’m here and ready — want to try that again with a bit more detail?"