Everything is done clearly, quickly, and without problems.
6
0
Budget: 200 USD Deadline: 1 day
contact us
1
0
Budget: 50 USD Deadline: 1 day
"Hello! The problem with most chat agents is that they have a limited context window and start to 'lag' or lose connections on files larger than 1-2 MB.
I offer a professional solution based on semantic vectors (embeddings). Instead of simple text comparison, my script transforms each event into mathematical code and groups them by meaning. This ensures that events like 'Trump wins' and 'GOP victory' will be correctly combined, regardless of phrasing.
You will receive:
A fully structured file (Excel/CSV) with logical groups.
A Python script that you can use for similar tasks in the future.
I am ready to process a small part of your file (10-20 lines) as a free test, so you can verify the quality of the grouping."
Budget: 250 USD Deadline: 5 days
It can be done, caching can save tokens, and if the pipeline is done well, it may not consume many tokens.
Alisher Abdrakhmanov
Winning proposal
1
0
Budget: 50 USD Deadline: 1 day
Hello. It doesn't look too difficult, but I have a couple of questions: Can I see what the file looks like? And is hosting needed or is a local launch sufficient?
8
1
Budget: 750 USD Deadline: 5 days
There is a good practice of divide and conquer, perhaps it needs to be applied here.
Write in private messages open.
9
0
Budget: 50 USD Deadline: 1 day
Good evening, Artem!
In general, the task is clear, but for an accurate answer regarding deadlines and price, I would like to clarify some questions that arose after analyzing your task.
Please write in private messages — we will discuss the details and your wishes.
0
0
Budget: 100 USD Deadline: 2 days
Hello!
I can implement an intelligent bot for semantic analysis and grouping of Polymarket events, which works reliably with large volumes of text data and is not limited by chat agent constraints.
🔹 What I will do:
I will process the current file (~5 MB) with events (elections, politics, etc.)
I will automatically match events by content, even if the wording is radically different
(for example: "Trump will become president" ↔ "Republicans will win the elections")
I will divide all events into logical groups ("folders") by common meaning
I will implement a mechanism whereby new events:
are automatically added to the corresponding group
or create a new group if the meaning does not match existing ones
🔹 Why this solution works correctly:
I use semantic analysis, not keyword search
The solution does not "lag" and does not lose data, unlike regular chat agents
The architecture is ready for scaling and further development
🔹 What you will receive as a result:
Clearly structured events grouped by content
Fast processing of new data
A ready-to-use tool that can be utilized and expanded
💰 Cost — I will propose after a brief discussion of the data format and requirements
🕒 Deadline — from a few days to 2 days
I am ready to discuss the details and offer the optimal solution specifically for your tasks.
Write to me — I will gladly take on the implementation.
7
0
Budget: 25 USD Deadline: 1 day
I am among the top 5 developers in the category of "Artificial Intelligence and Machine Learning" among ~2100 specialists on the platform. I guarantee:
- Fast and high-quality task execution
- Strict adherence to deadlines
- Regular communication throughout the entire process
I would be happy to discuss the details of your project in private messages.
19
2
Budget: 25 USD Deadline: 1 day
It's funny, but yes - the creation of scripts and bots on Polymarket is gaining popularity.
We also need to consider arbitrage, the commission - it has increased in the last update, if you have read.
It will be difficult to do everything at once and implement it. I suggest breaking down the clear technical specifications into parts and improving the script during the process. Because there is model training, analysis, the more data there is - the higher the probability, and all of this needs to be taken into account. I want to hear the deadline and budget.
1
0
Budget: 150 USD Deadline: 3 days
Good day!
I fully understand the essence of the task: it is not about simple text processing, but about semantic matching of events, where the same idea can be formulated in different ways (for example, "Trump becomes president" and "Republicans win the election").
The problem with token limits and unstable results from chat agents is expected here, so the right solution is to work with data, not with chat context.
I propose implementation through:
preprocessing the file (≈5 MB) without volume restrictions;
calculating semantic vectors (embeddings) for each event;
automatically grouping similar content events into clusters ("folders");
incremental logic: new events are either added to an existing cluster or create a new one if they do not fit in content;
the ability to adjust the "similarity" threshold to avoid false merges.
The solution will be stable, reproducible, and will not depend on LLM context limitations. If needed, I can implement convenient management through a Telegram bot or provide a ready script/service for exporting results.
I am ready to quickly get to work, I can start with analyzing the file and propose an optimal cluster structure even before full implementation.
32
0
Budget: 100 USD Deadline: 3 days
Hello. There are ready scripts. I can process them. If it's relevant - write to me.
13
0
Budget: 220 USD Deadline: 2 days
Hello, in principle, tokens for this still need to be purchased, and I will create a bot that will go through the file without losing meaning, due to the fact that we will initially create different titles for events and then gradually sign each event with titles, limiting the number of characters so that the AI does not lose context, and then just run it from the untouched line and so on until we go through the entire file.
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