Telegram-AngelOne Auto Trading Bot

@ASSAMWEB

Greetings, I have reviewed your project posting. However, the description doesn’t include enough details to accurately assess the scope. Please open a chat so we can discuss your requirements in detail and identify the best solution for your needs. Regards

@longngoc2307

==== Hi - Truong here ==== "TELEGRAM-TO-ANGELONE AUTO TRADING" — you need signals parsed instantly and turned into the correct entry, exit, SL and target orders. I’d use Python with Telegram listeners, OCR fallback for images, strict signal validation, and AngelOne order checks before execution. The key edge case is preventing a bad OCR read from placing a wrong trade. Q1 - Can you share 2–3 real Telegram signal examples, including both text and image formats? Q2 - Should the bot support only the exact AngelOne symbols you currently trade, or dynamically resolve contracts and expiries? Looking forward to work with you.

@loxtic

Hi, how are you doing? I have considerable experience building Telegram-to-broker bridges and fast automated trading tools, including work with OCR to parse signals and execute via broker APIs; I’ve deployed similar setups with Python and can adapt quickly to AngelOne SmartAPI and Telegram Bot API. I can deliver clean source with comments, a small config file, a short demo, and post-handover support, all focused on low latency and robust error handling. Let me know further if interested.

@arqamm904

With extensive experience in software development, particularly in Python, and a strong background in building highly functional and efficient systems, I believe I am the freelancer you're looking for to create your Telegram-AngelOne Auto Trading Bot. I'm well-versed in API integration, such as AngelOne SmartAPI, which is crucial to the success of this project. I'm also familiar with image processing libraries like Tesseract or EasyOCR that will be instrumental in the OCR aspects required to parse and interpret trade details from images. My expertise in delivering real-time information using Chatbots is another added advantage I bring to the table. As a python developer, I deliver fast execution times maintaining a low latency for better performance which aligns perfectly with this project's need for smooth scalping process. Moreover, I strongly emphasize on scalable codes that ensures long-term growth and easy redeployment on a different machine. With my commitment to meeting deadlines without compromising quality and performance, you can be assured of receiving the deliverables on time. To top that off, my effective communication skills further streamline the project flow due to clearly conveyed progress checks and discussions. Choose me for this project and we’ll build an efficient bot that will enhance your trading experience while ensuring flawless implementation throughout.

@Digitalizers010

Hi, a bridge that reads your signal channel and fires the matching AngelOne order, text or screenshot either way. OCR is the risky half: a misread strike is a real position. Plan: a Telethon listener, rules parsing for text and OCR only on images, normalised to symbol, strike, side and qty, then checked against the SmartAPI instrument dump. SL and target ride with the order, a websocket watches fills, every state change posts back. Anything it can't parse cleanly is held, not guessed. How many signals a day? We have built this over a broker API before, queued so nothing drops. Happy to take the first milestone so you can watch it on paper trades. Regards, Digitalizers

@mollyl53

I can build this Telegram-to-AngelOne trading bot in Python, with the full flow automated from signal detection to order execution, SL/target handling, and Telegram confirmations. The bot will monitor your private Telegram channel in real time and handle both text and image signals. For images, I can use Tesseract or EasyOCR with preprocessing, then validate the extracted symbol, strike, quantity, order type, SL, and target before placing anything. For Telegram access, I can use Bot API if the bot has channel access, or Telethon/Pyrogram if a client-based setup is needed. On the AngelOne side, I’ll integrate SmartAPI, map Nifty, BankNifty, and Sensex signals to the correct contracts, and handle both entry and exit orders. I’ll also add duplicate protection, retries, session recovery, logging, partial-fill/error handling, and safeguards for fast scalping. You’ll get Telegram updates for order sent, filled, rejected, SL/target hit, exit, or any error. I’ll keep the code modular so adding brokers, channels, trailing SL, dashboards, or new rules later is easy. If you share a few sample text signals and screenshots, I can tune the parser and OCR around your exact format from the start. Best regards

@xiaoven

I have experience with Python, Telegram Bot API, REST APIs, and OCR using Tesseract/EasyOCR. I can implement real-time signal parsing, AngelOne SmartAPI order mapping, entry/exit management, SL/target monitoring, and Telegram confirmations. I will deliver commented source, README, config file, and demo. Robust error handling and low-latency design included.

@ammad1709

The difficult part of a Telegram-to-broker bridge isn’t sending an API order. It’s reliably turning inconsistent signals into the correct contract and handling every failure between signal, order, fill, and exit. I can build this in Python with a modular pipeline: Telegram listener → text/OCR extraction → signal validation → AngelOne contract mapping → order execution → position/SL/target monitoring → Telegram confirmations. For image-based calls, I can integrate OCR with preprocessing and validation rules so common OCR mistakes don’t immediately become trading actions. The execution layer can also include duplicate-signal protection, API error handling, order-status polling, logging, configurable quantity multipliers, and configurable SL/target rules. I’ll keep credentials and channel/configuration values outside the source code and provide a clean config/README setup for redeployment. One important point: for a system capable of placing real-money trades, I’d recommend validating the complete flow in a controlled/paper or test environment first, then enabling live execution once the parsing and safeguards are verified. I can provide the source, deployment documentation, demo, and initial setup support as requested.

@zxngxtsu

Hi! I can build the Telegram-to-AngelOne automation in Python, including text/image signal parsing, OCR, broker API integration, order status tracking, confirmations, logging and a configurable settings file. I would develop it in stages, starting with a dry-run mode to validate signal parsing and instrument mapping before enabling live execution. The project is significantly larger than the posted minimum budget due to OCR, broker integration, order lifecycle handling and reliability requirements. My estimate: ₹25,000 INR / 7-10days I can provide the source code, README, configuration file and setup support.

@bizvivo

I propose to build a fully automated trading bridge that listens to your private Telegram channel, parses both text and image‑based signals, and instantly places corresponding orders in your AngelOne account via SmartAPI. My background in Python automation, broker API integrations, and low‑latency trading systems makes me well‑suited to deliver a robust, production‑ready solution. ? Key Capabilities Real‑time Monitoring: Continuous listening to Telegram messages and images. OCR Integration: Use Tesseract/EasyOCR to extract trade details from screenshots. Signal Interpretation: Map parsed data (buy/sell, symbol, strike, qty, SL/target) to AngelOne contracts. Automated Execution: Fire entry and exit orders via SmartAPI with error handling. Feedback Loop: Push concise confirmations (order sent, filled, SL/target hit, errors) back to Telegram. ? Deliverables Source Code – Clean, well‑commented Python scripts with README for redeployment. Config File – Editable parameters (channel ID, API keys, multipliers, SL/target defaults). Demo – Screenshare/recorded proof of end‑to‑end execution. Support – Assistance with initial setup and environment configuration. ? Value Proposition Low Latency: Optimized pipeline for fast scalping execution. Reliability: Structured error handling and logging for auditability. Flexibility: Configurable parameters for quick adjustments. Scalability: Foundation ready for future enhancements (risk management, dashboards).

@nandezgarcia

Hi, I can build your Telegram to AngelOne auto-trading bridge in Python. The bot will monitor a private Telegram channel, parse trade signals from text and images using OCR, and place orders instantly via AngelOne API. I will include error handling, logging, and a test mode for safe validation. I have experience with trading bots, broker APIs and Telegram automation. Ready to start immediately.