AI Lead Funnel — Echogate LLM + Telethon

Full runnable pattern for Telegram accounts that auto-respond to DMs using LLM.

When to use

User wants a Telegram account to auto-respond to incoming messages
Redirect leads to a target contact (@lordrax, etc.)
Need a human-like operator that filters and redirects

Key design decisions

Stage-gated dialog, not free-form LLM — LLM is too eager to share contact immediately or too chatty. Use 3 hardcoded stages with separate system prompts.
Processing lock per user — asyncio.Event or set() to prevent parallel handler invocations.
Typing indicator before every message — SetTypingRequest(SendMessageTypingAction()) + asyncio.sleep(3-10s).
State persistence — JSON file with stage, history, done per user. Survives restarts.

LLM config

from openai import AsyncOpenAI

llm = AsyncOpenAI(
    base_url="https://api.echogate.one/v1",
    api_key="[REDACTED]",
    timeout=60,
)

# gpt-5.5: ~3s response — fast enough for real-time
# deepseek-v4-pro: ~21s — too slow, breaks the illusion

Stage prompts

STAGE_PROMPTS = {
    0: """Ты — оператор. Строгий, деловой, немногословный.
Это ПЕРВОЕ сообщение в диалоге. Ответь коротко (1 предложение).
Поприветствуй и спроси что интересует / по какому вопросу.
НЕ давай контакты. НЕ упоминай @target. НЕ давай ссылки.
НЕ используй эмодзи. Стиль: спокойный, уверенный, без лишней вежливости.""",

    1: """Ты — оператор. Строгий, деловой.
Это ВТОРОЕ сообщение. Ответь на вопрос пользователя коротко (1-2 предложения).
Упомяни что детали, цены и наличие — у партнёра @target.
НЕ давай прямую ссылку пока. НЕ используй эмодзи.
Стиль: уверенный, деловой. Не извиняйся, не будь подобострастным.""",

    2: """Ты — оператор. Строгий, деловой.
Это ТРЕТЬЕ (финальное) сообщение. Дай прямую ссылку.
Скажи обратиться туда, это всё. Закругляйся.
1 предложение. НЕ продолжай диалог. НЕ используй эмодзи.""",
}

Processing lock pattern

processing = set()  # Track user_ids currently being processed

@client.on(events.NewMessage(incoming=True))
async def handler(event):
    uk = str(event.sender_id)

    if uk in processing:
        log(f"Already processing {uk}, skip")
        return

    processing.add(uk)
    try:
        # ... generate and send reply ...
    finally:
        processing.discard(uk)

Race condition: why it happens

When two messages arrive within 2 seconds (e.g. user sends empty message then "привет"), the Telethon event handler fires twice in parallel. Both invocations see the same state (stage=0, our_count=0), both generate Stage 0 replies, and both send simultaneously. Result: two greeting messages back-to-back, no dialog.

The processing lock prevents this — the second invocation sees uk in processing and skips.

Fallback messages

Always have hardcoded fallbacks per stage in case LLM times out:

FALLBACKS = {
    0: "Добрый. По какому вопросу?",
    1: "По наличию и ценам — обратись к @target",
    2: "Напиши @target: https://t.me/target",
}

Full runnable script

See C:\Users\User\Desktop\_PROJECTS\рассылка\lead_funnel.py for the production version with:

echogate.one LLM integration
3-stage dialog with processing lock
Typing indicator + random delays
JSON state persistence
@Tomitotototo → @lordrax funnel

Pitfalls learned 2026-08-11

JSON account metadata is stale: sessions/*.json files say status: "Active", spamblock: "none" but 90%+ of accounts are actually RESTRICTED/BANNED. Always verify by connecting and sending a test message to "me".
SpamBot "RESTRICTED" ≠ can't DM: Account may be RESTRICTED for groups but perfectly fine for private messages. The real test is client.send_message("me", "test").
Free-form LLM fails: Without stage-gating, LLM either shares contact immediately (no dialog) or never shares it (endless chat). Hardcode stages.
No processing lock = duplicate messages: Parallel handler invocations on rapid-fire messages produce duplicate greetings.
deepseek-v4-pro is 21s: Too slow for real-time. gpt-5.5 is 3s. Pick fast models.
No skip phrases in lead funnel: Respond to EVERYTHING — "ку", "привет", empty messages. No intent detection needed.

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