Optimization of expenses on LLM API (Telegram bot, AI integrations)

Hello, Ivan!
I will help you create a bot in Telegram, taking into account your wishes and specifications.
I have extensive experience in development using Python, React, and specifically in developing bots with various integrations. I hold 2nd place on the platform for Python development. I have experience working with Open AI API.
You can check my portfolio: Freelancehunt
I am waiting for your response for further cooperation and for a more detailed discussion of your project.

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You need to look into the project itself. Some logic can be transferred to vector knowledge bases. Also, set limits on the number of characters for prompts. Remove unnecessary API requests, adjust the temperature of the requests, and so on. Write to me, I have experience working with Open AI API and many other APIs.

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Good day. This is a very relevant and interesting task. I am ready to help you significantly reduce expenses on LLM.
The main strategy is the implementation of a "smart router" for requests. We will use a cascading model: simple and typical requests will be processed by fast and cheap models, while complex ones that require deep analysis will be automatically redirected to more powerful and expensive models.
Additionally, I will optimize your prompts to reduce the number of tokens and implement a caching system for repeated requests. This comprehensive approach will allow us to reduce the cost of each API call by 40-70% without a noticeable loss of quality for the user.

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Hello!
Cost optimization for LLM is exactly the task where the right technical implementation directly affects the budget. I am ready to take on this work.

My experience includes creating high-load Telegram bots with integration of various AI APIs and, crucially, optimizing their performance to reduce costs.

Estimated cost of services: ~1,500 USD (the final amount will depend on the answers to the questions below and the complexity of the architecture).

Preliminary optimization plan:
Analysis and audit: I will study the current architecture of the bot, request logs, and prompt structure. I will identify which requests are the most expensive and why.
…
Multi-level caching: I will implement a response caching system (for example, with Redis). Repeated or similar requests will not go to the API but will be taken from the cache.

Prompt optimization (Prompt Engineering): I will redesign prompts to achieve the same results with fewer tokens (more concise formulations, effective context).

Model selection for the task: I will implement request routing. Not all tasks require a powerful and expensive model (like GPT-4-turbo). For example:

Simple questions → cheap fast models (GPT-3.5, Claude Haiku).

Complex analytical tasks → smarter models (GPT-4, Claude Sonnet).

This will significantly reduce the average cost per request.

Working with context: I will optimize dialogue context management (message history) to avoid sending unnecessary tokens to the API.

Monitoring and analytics: I will set up a dashboard to track costs for each request, which will allow pinpointing and eliminating "expensive" areas.

To propose an accurate solution and cost, I need to understand the details. Please answer the questions:
Technical stack: What is the bot currently written in? (Python, Node.js, PHP + Laravel?) Is there access to the source code?

Current costs and volumes: How many requests does the bot process per day/month? What is the current monthly budget/expense on LLM providers (OpenAI, Anthropic, etc.)?

Use cases: Please describe the main types of user requests? (for example: text generation, document analysis, classification, dialogue). What is the approximate percentage for each type?

Used models: What models and from which providers (OpenAI GPT, Anthropic Claude, others) are currently being used?

Quality of responses: Are there critical scenarios where a drop in response quality is unacceptable? Where can we save a little?

I am ready to discuss all the details in private messages or on a call. Payment can be tied to the result — a percentage of the achieved savings.

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Hello! I have experience in optimizing costs for GPT/Claude in Telegram bots. I can reduce the cost per request without losing quality. Please let me know which models you are currently using and the volume of requests.

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Good day, I am interested in your project. I have extensive experience with LLM. I would like to learn more about the architecture of the project, how many prompts are executed during a single request, and what functions they perform.

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Good day, I am interested in your project. I will propose caching responses, dynamic model selection based on price thresholds, optimization of prompts and batching requests, as well as consumption monitoring. I am ready to discuss the details.

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Good day, Ivan

I can evaluate and optimize your RAG.
Please send all the details in a private message.

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Good day, I can take a look and create convenient fallbacks based on the LLM price conditionally if there is an overspend on one and the second is used little, while another one that spent less money is used on the balance. Also, I would like to see how your batching is arranged; maybe I can improve it so that it costs several times less, for example, instead of 1 request, immediately 10 in 1, distributed across the necessary chats conditionally.
A more detailed description/documentation of the project is needed, how it works, how complex the project is?

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Hello. I have extensive experience in developing Telegram bots. I am ready to help.

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Hello.

I am developing bots for Telegram using NodeJS. I have experience with APIs (ChatGPT, Claude). I am ready to take on the project. Write to me, and we will discuss.

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