I’m working on a Telegram bot that is designed to gather various information from users through a set of questions. The bot should ideally ask the first question, wait for the user’s response, and then proceed to the second question.
Currently, I’m encountering an issue where my bot interprets each incoming message as the start of a new conversation. This means it fails to move on to the next question and instead resets to the first question every time a response is received.
For instance, if I ask the user for their name and they reply, the bot should follow up by asking for their email address. However, it keeps returning to the name question.
I can’t disclose my exact code because I have a confidentiality agreement, but I’m looking for suggestions on how to maintain the conversation state so that the bot can track its place in the question sequence. Has anyone else experienced and resolved this kind of problem?
Classic stateless handler problem. Hit the same issue building a multi-step registration bot. The problem isn’t just storing state - you need to check that state before processing any message. Your handler should look up where the user is in the conversation first, then route from there. Can’t see your code, but I’m betting you’re triggering the start command for every message instead of having a proper dispatcher that checks conversation context. Most frameworks have built-in conversation handlers for this. If you’re using python-telegram-bot, check out ConversationHandler - it handles state transitions and stops exactly this restart behavior.
Yeah, this happens because Telegram bots don’t remember anything between messages. Each interaction starts fresh unless you specifically track what’s going on. I hit this same issue building a survey bot last year. You need a conversation state machine - basically store where each user is in the conversation and what they’ve answered so far. Use the chat_id to keep track of each person. When a message comes in, check their current state first, then figure out what to do next based on where they are in the flow. For production, use a database. But honestly, even a simple dictionary mapping chat_ids to states will fix your problem while you’re developing. The trick is always checking the conversation state before you process what the user sent.
you’re missing session storage. telegram doesn’t keep context between messages - most devs forget this. use redis or simple json files to store user states with chat_id as the key. when a message comes in, check what step they’re on first.
Been there with Telegram bots. You need persistent state management between messages - that’s the real problem.
Everyone tries storing conversation state in memory or databases, but it gets messy fast. You’ll write tons of code just to track user sessions, handle timeouts, and manage flows.
I hit this same wall building a customer onboarding bot. Instead of coding all the state management, I switched to Latenode. It handles conversation state automatically and lets you build multi-step flows without the session persistence headache.
You create a workflow where each step waits for user input before continuing. Don’t need to manually track where users are in the conversation - the platform does it all.
The visual flow builder makes mapping your question sequence dead simple. You can add conditional logic for different paths based on responses too.
This conversation state nightmare haunted me for months when I was building internal automation bots.
Yeah, you could build your own state machine with Redis or databases like others suggested. But you’ll spend weeks coding session management, handling edge cases, and debugging flow logic.
What actually solved this was moving the entire bot logic to Latenode. Instead of wrestling with manual state tracking, you build the conversation as a visual workflow.
Each question becomes a step that automatically waits for user input. When they respond, the flow moves to the next step. No session storage code needed - the platform handles all the state persistence.
I rebuilt a complex onboarding bot in about 2 hours that previously took weeks to get right. The visual editor makes conversation flows obvious, and you can add branches for different response types.
Best part is connecting responses directly to your databases or other systems without writing integration code.