You will get a custom LLM pipeline or AI agent built with Python
Project details
I build custom LLM pipelines and AI agents using Python and modern language models — clean code, production-ready, not just a demo.
From a simple RAG system that answers questions from your documents, to a multi-step agent that automates complex workflows, to a full AI system with tool use, memory, and API integrations.
What I deliver:
– Clean Python code with detailed comments and docs;
– RAG (document Q&A), multi-agent pipelines, tool-calling systems;
– Works with GPT-5.5, Claude Sonnet 4.6/Opus 4.7, Gemini 3.1, or open-source models (Qwen, DeepSeek, Gemma);
– Output as REST API, Telegram/Slack bot, chatbot UI, or CLI.
Three tiers to match your scope:
Starter — single-purpose LLM pipeline, 1 use case, structured output.
Standard — multi-step agent, up to 4 integrations, async processing.
Advanced — full system with tool use, RAG, API endpoint, deployment-ready code.
From a simple RAG system that answers questions from your documents, to a multi-step agent that automates complex workflows, to a full AI system with tool use, memory, and API integrations.
What I deliver:
– Clean Python code with detailed comments and docs;
– RAG (document Q&A), multi-agent pipelines, tool-calling systems;
– Works with GPT-5.5, Claude Sonnet 4.6/Opus 4.7, Gemini 3.1, or open-source models (Qwen, DeepSeek, Gemma);
– Output as REST API, Telegram/Slack bot, chatbot UI, or CLI.
Three tiers to match your scope:
Starter — single-purpose LLM pipeline, 1 use case, structured output.
Standard — multi-step agent, up to 4 integrations, async processing.
Advanced — full system with tool use, RAG, API endpoint, deployment-ready code.
AI Algorithms
Large Language Model, Transformer ModelAI Applications
AI Chatbot, AI-Generated Code, Natural Language GenerationAI Development Language
PythonAI Tools
GitHub Copilot, Gradio, Hugging Face, PyTorch, Streamlit, TensorFlow, Word2vecAI Models
BERT, ChatGPT, LLaMA, OpenAI CodexWhat's included
| Service Tiers |
Starter
$80
|
Standard
$200
|
Advanced
$375
|
|---|---|---|---|
| Delivery Time | 7 days | 10 days | 14 days |
Number of Revisions | 1 | 2 | 3 |
AI Model Integration | |||
Batch Normalization | - | - | - |
Database Integration | - | ||
Detailed Code Comments | |||
Image Upscaling | - | - | - |
MLOps | - | - | - |
Model Deployment | - | - | |
Model Documentation | - | ||
Model Monitoring | - | - | - |
Model Testing & Optimization | - | - | - |
Model Tuning | - | - | - |
Natural Language Processing | |||
NLP Tokenization | - | - | - |
Pre-Training | - | - | - |
Prompt Engineering | |||
Setup File | - | - | - |
Source Code |
Optional add-ons
You can add these on the next page.
Fast Delivery
+$30 - $80
Additional Revision
+$25About Pavlo
Python Developer | AI Automation & Bot Development
Kyiv, Ukraine - 6:00 am local time
My background: PhD in Computer Engineering (Taras Shevchenko National University of Kyiv), with research focused on LLM fine-tuning and NLP. I've worked hands-on with large language models, neural networks, and agentic systems — not just as a user, but at the implementation level.
What I deliver:
— Python scripts and automation pipelines (web scraping, API integrations, data processing)
— AI agents and LLM-powered workflows (Claude, OpenAI, RAG systems)
— Workflow automation with n8n, Make, or custom Python backends
— Telegram, Discord, and WhatsApp bots
I focus on fixed-scope projects with clear deliverables. If you have a well-defined task, I'll get it done cleanly and on time.
Steps for completing your project
After purchasing the project, send requirements so Pavlo can start the project.
Delivery time starts when Pavlo receives requirements from you.
Pavlo works on your project following the steps below.
Revisions may occur after the delivery date.
Initial review and scope confirmation
I review your requirements, clarify the use case, data sources, and desired output format. We align on the scope before any code is written.
Build & iterative testing
The pipeline or agent is developed and tested against the provided data and requirements. Regular progress updates are communicated throughout the development process.