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Fiverr Pro
English
$
USD
I will build production ready generative ai rag QA chatbot using python and langchain
Sude
About this gig
Turn your Documents into a Powerful, Secure RAG Chatbot.
Are your teams wasting time searching through manuals, PDFs, and internal reports? Traditional AI fails on proprietary company knowledge. I deliver custom Retrieval-Augmented Generation (RAG) systems using Python, LangChain, and FastAPI to connect your specific data to the power of LLMs (GPT/Gemini). Get accurate, context-aware answers instantly.
PACKAGES DIFFERENTIATED:
BASIC (PoC): Functional Proof of Concept. A single-document RAG endpoint to validate the core concept and performance. Perfect for initial testing. Source code included.
STANDARD (Core API): Scalable, robust FastAPI REST API ready for enterprise integration. Includes multi-document handling, SQL/Vector Database integration, and full source code. Ready for production trials.
PREMIUM (Production Ready): A full-stack, turnkey solution. Includes all Standard features, a Functional Web App UI, User Authentication (Security), Multi-language Support, and MLOps/Docker setup for reliable deployment.
WHY CHOOSE ME? I focus on production-grade quality. You receive clean, maintainable Python code built with security best practices, MLOps experience, and deployment expert
Get to know Sude
Sude
- FromTurkey
- Member sinceDec 2025
- Avg. response time21 hours
Languages
English, Turkish, Chinese
Python Backend, Data, and Generative AI
Hello! I am Sude Yaren Kacar, a results-driven Python Developer specializing in Backend Engineering, High-Volume Data Processing, and deploying AI solutions to the Cloud.
I leverage Python, FastAPI, SQL, Docker, and Google Cloud (GCP Fundamentals) to deliver scalable, reliable, and automated solutions that solve your critical business challenges.
1. Niche Description: Generative AI & MLOps Focus (High-Value Service)
This description targets the highest-paying niche: developing and deploying robust Generative AI applications.
Title: Production-Ready
FAQ
What exactly is Retrieval-Augmented Generation (RAG)?
RAG is an AI architecture that uses your documents to retrieve facts and generate contextual, accurate answers via LLMs (GPT/Gemini). It prevents LLMs from "hallucinating" on proprietary data, ensuring 100% data relevance.
How do I integrate the API key after delivery?
I deliver a clear FastAPI (Python) REST API with documentation (Swagger UI). The API key allows easy integration into any web, mobile, or internal application using standard HTTP/S requests. No complex setup is required.
Is the RAG Chatbot secure? How is user data handled?
Security (User Authentication) is included in the Premium package or sold as an extra. I strongly recommend this for production use. I do not retain any customer documents or conversation logs after project finalization.
Can I integrate this bot with my existing systems (e.g., Slack, CRM)?
Yes. The Standard and Premium APIs are designed for seamless integration with any third-party app (Slack, HubSpot, etc.) via simple webhooks or direct HTTP requests. Select the CRM/SaaS Integration extra for guaranteed connection setup.
What types of documents does the RAG system accept?
The system handles structured and semi-structured text data like PDFs, DOCX, Markdown, and custom text files. We confirm your specific data type and formatting during the project kickoff to ensure full compatibility.
