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Sanjay Choudhary
Sanjay Choudhary

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FlameDesk: Local-First Telegram Voice & Order Desk for Artisanal Businesses

#devchallenge #weekendchallenge #hf26challenge

This is a submission for the Hacktoberfest Weekend Challenge: Build for a Friend

What I Built

I built Kritika for my friend Ananya, who launched a handcrafted candle studio in Bengaluru ahead of the Diwali festive rush.

As order volume grew across social channels, manual order handling became a bottleneck:

  • Customers routinely sent 30-to-60-second voice notes on Telegram in mixed English and Hindi requesting custom candle gift sets and local delivery timelines.
  • Ananya spent upwards of 4 hours each evening listening to audio clips, checking inventory levels, calculating shipping fees, and manually recording customer addresses into spreadsheets.

Kritika is a lightweight, open-source order desk integrated directly into Telegram. It automates customer communication and back-office order logging by:

  • Ingesting incoming Telegram audio voice notes and text messages.
  • Transcribing regional speech into clean text.
  • Extracting structured order metadata (items, quantities, delivery address, preferred dates).
  • Calculating totals, verifying stock availability, and sending instant confirmation summaries back to the user.

How I Built It

The architecture relies entirely on open-weight models, open-source audio tooling, and free-tier infrastructure. The system is designed to run efficiently inside a single Docker container deployed on Render.

       +-------------------------------------------------------+
       |                  Customer on Telegram                 |
       |             (Sends Voice Message or Text)             |
       +---------------------------+---------------------------+
                                   |
                                   v
       +-------------------------------------------------------+
       |             Python FastAPI Engine (Render)            |
       +-------+-------------------+-------------------+-------+
               |                   |                   |
               v                   v                   v
      +-----------------+  +---------------+  +-------------------+
      | Speech Parser   |  | Open LLM      |  | Catalog & Order   |
      | Faster-Whisper  |  | Gemma 2       |  | Database          |
      | & Edge-TTS      |  | (Ollama/Groq) |  | MongoDB Atlas     |
      +-----------------+  +---------------+  +-------------------+
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Technical Implementation Details:

  1. Telegram Webhook Layer (python-telegram-bot): Captures incoming audio files (.ogg) and text payloads, routing them through asynchronous processing queues.
  2. Open Audio Pipeline (Faster-Whisper & Edge-TTS):
    • Transcribes incoming customer voice messages locally without relying on paid speech-to-text APIs.
    • Synthesizes audio responses when customers request spoken status updates.
  3. Language Intelligence (Google Gemma 2):
    • Parses unstructured customer conversations into strict JSON schemas.
    • Handles multi-turn inquiries, stock validation, and shipping address verification.
  4. Data Persistence (MongoDB Atlas):
    • Maintains product catalog records, stock counts, customer conversation histories, and structured order entries.
  5. Observability & Hosting (Render & Sentry):
    • Deployed on Render's web service architecture.
    • Monitored via Sentry Agent Tracing to measure end-to-end voice processing latency and function execution stability.

Why Does Open Innovation Matter?

  1. Zero Marginal Operational Cost: Small independent creators operate on thin margins. Using open-weight language models and open speech engines eliminates per-token and per-minute transcription costs, allowing automated order desks to run affordably at scale.
  2. Accurate Context & Local Speech Adaptation: Proprietary global APIs often fail when transcribing regional accents, local neighborhood landmarks, or mixed-language queries. Open models allow tailored system prompts and localized fine-tuning.
  3. Data Control & Independence: All customer information, contact details, and order transactions remain strictly within open-source databases under the owner's direct control, preventing unauthorized data processing by commercial API vendors.

Prize Categories

  • Best Use of Gemma: Uses Google Gemma 2 as the primary intelligence engine for intent classification, JSON extraction, and conversational responses.
  • Best Use of Render: Hosts the complete FastAPI engine, Telegram webhook worker, and order pipeline on Render.
  • Best Use of MongoDB Atlas: Manages inventory catalogs, vector-based product queries, and structured customer order states.
  • Best Use of Sentry Agent Tracing: Tracks voice transcription latency, tool execution pipelines, and error rates across processing workflows.

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