Analysis of the chat in Telegram with the GPT chat

My approach is to create not a full-fledged bot, but an analytical script in Python that performs only the necessary function: collecting, classifying, and forecasting demand for equipment.

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The simplest way is to collect all new messages in a database and then create graphs based on the collected information. AI can be used for analysis. I am implementing this for a modest price because I need reviews for my empty profile.

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Mykhailo, good day.
I have extensive experience working with artificial intelligence, so I will easily create such a program for you.

Deadline: 1 day
Cost: 850 hryvnias

Write to me, we will discuss the details.

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Good day! I am ready to complete this project. Extensive experience in developing various applications.

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Hello, I can create a bot for you that will work on Python, monitor the chats you need, and through the Gemini API will analyze everything and send reports.

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Hello! I can implement it. Write to me privately to discuss all the details. I will be glad to cooperate!

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I have a similar project on the analytics of Telegram chats using GPT. You can view a work example in the portfolio: https://freelancehunt.com/showcase/work/analizator-produktivnosti-pratsivnikiv-na-osnovi/1992126.html.

In this solution, the bot analyzes employee messages, makes meaningful conclusions, and generates reports. By analogy, I can adapt the system to your task — tracking requests for specific models of equipment and generating analytics on interest in products and categories.

It is worth considering that the use of GPT increases both the implementation cost and the regular expenses for the model's operation.

As an alternative, I can offer a simplified version without GPT — analyzing the semantics of text, keywords, and phrases with the detection of specified patterns. This will be a significantly more economical solution and optimal within a limited budget.

I am ready to consult you, after which we will determine the most appropriate approach and agree on further implementation.

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Hello!

I develop bots for Telegram using NodeJS. I have experience with OpenAI. I am ready to take on the project. Write to me, we will discuss.

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Good day, to calculate the frequency of words in the chat, AI is not needed, just mathematics is enough. If demand forecasting depends on the frequency of requests - then this can also be calculated.
Is this your chat?

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Hello!
I will create a simple and reliable service that automatically analyzes your wholesale chat in Telegram: counts requests by models, shows top lists and dynamics for 1/7/30 days, and provides a short forecast for 7 days. Without bulky features and unnecessary services — neat stability and clean reports.

✅ message collection (bot/user account), normalization of models/synonyms
✅ reports in Telegram/Google Sheets: top-10, deltas, alerts for spikes
✅ simple forecast "growing/falling" + confidence interval
✅ economical mode: local database/CSV, transparent logs

Ready to start today — I will show the first live report for your chat in the test channel.

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Good day!
I can implement a simple and budget-friendly solution for analyzing a Telegram chat with wholesale tech suppliers.

What will be done
1. Telegram chat parser
• Connection to the chat via Telegram API or Telegram Export.
• Automatic collection of all new messages.
2. Artificial intelligence analysis
• Detection of model names in the requests.
… • Counting how many times each model was mentioned.
• Determining cyclicality: on which days/hours there are the most requests.
• Building a demand forecast (which models will be relevant in the near future).
3. Simple panel or Google Sheet
• Data is automatically updated.
• Table: model – number of requests – dynamics – demand forecast.
• Graphs (popularity over a week/month).
4. Absolutely budget-friendly solution
• Google Sheets + Telegram bot + cheap AI (without expensive servers).
• Minimal maintenance costs.

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Cost

1,500 – 2,000 UAH for a full MVP version (parser + analysis + table/dashboard).

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Deadline

1–2 days (fully functional prototype).

⸻

What is needed from you
• Access to the chat (via bot or invitation).
• List of models (not mandatory, but will speed up training).

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Hello. I am engaged in bot development and automation using Python. It is important to understand that "AI forecasting" is complex and expensive, while a "limited budget" requires a simple solution.

I propose 2 options:

1. Quick MVP (within budget): We create a simple bot that counts requests to models based on keywords (for example, "looking for iPhone 15 Pro"). You will immediately see the number of requests and cyclicality (for example, in Google Sheets).
Result: cheap, fast, provides 80% of the needed statistics.

2. Full analysis (AI + Forecasting): This is significantly more complex. It requires:
a) Connecting a paid AI (like GPT) for "understanding" each message.
… b) Hiring a data analyst (Data Scientist) for "forecasting" after we collect data over several months (this can also be done using AI, but the volume of data for such analysis needs to be much larger).
Result: long, expensive, but provides 100% depth.

I suggest starting with option 1. You will receive value immediately and begin collecting the data necessary for future forecasts.

I specify the deadline and price for the first option. I am ready to discuss the details.

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Good morning, there is a very similar project already!
We will do everything perfectly)

My bot analyzes Telegram channels for new posts (the topic of the Telegram channels is news), passes them through a neural network, and outputs analyzed news based on the following factors:

Importance, which areas it affects, etc. That is, the technical specifications are quite similar.

I already know how to implement your case, I just need to see what this chat looks like.

… Let's collaborate)

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Hello.
You can connect OpenAI.
Using a bot (if the chat is yours) or a user bot (if the chat is not yours) to parse messages. To save costs, you can also filter the necessary messages with requests by keywords, after which you upload them along with the prompt into the neural network model 3.5 or higher.
Overall, the main expenses here will be for the neural network.

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