I will build ai chatbot rag app and llm integration with langchain nextjs


About this gig
Need an AI chatbot that answers from your own documents, or an AI feature built into your existing app that works in production?
I built RepoLens, an AI platform ranked #7 Product of the Day on Product Hunt, with grounded chat over indexed code. I also built a system with multi-provider LLM fallback across OpenRouter, Gemini, OpenAI, and Anthropic.
What I can build:
- AI chatbots grounded in your PDFs, docs, database, or website (RAG)
- AI chat widgets for React, Next.js, or any existing site
- LLM dashboards, summarization, and classification
- Automatic tagging, priority scoring, and sentiment analysis
- AI agent workflows with tool calling and multi-step reasoning
- OpenAI, Anthropic, Gemini, and OpenRouter integration via LangChain
- Vector search and embedding pipelines
- Background processing with Redis and BullMQ for long AI jobs
Why this beats a basic API wrapper:
- Multi-provider fallback keeps your app running if one provider fails
- Answers grounded in your real data with source references
- Async processing so users get instant responses
- Zod validation so bad LLM output never breaks your app
Message me before ordering with your use case and data sources.
Get to know Md Mohosin Ali
Full Stack Developer React Nextjs Vue Nodejs SaaS Dashboard Expert
- FromBangladesh
- Member sinceDec 2023
- Last delivery11 months
Languages
Bengali, English
My Portfolio
FAQ
What is a RAG chatbot?
A chatbot that answers only from your own content. Your documents become embeddings that are searched at query time, so answers stay grounded and can cite the source instead of inventing facts.
Which AI providers do you work with?
OpenAI, Anthropic, Google Gemini, and OpenRouter, wired through LangChain so you can switch providers or fall back automatically.
Who pays for the API usage?
You use your own API keys, so you keep control of billing and data. I help set up cost limits and caching to keep usage low.
Can you add AI to my existing app?
Yes. Send the repository or describe your stack and I will integrate the AI layer without rewriting your app.
How do you stop the AI from making things up?
Grounded retrieval, strict JSON-only prompts, schema validation, and confidence signals, plus safe fallbacks when model output fails validation.
Can it handle large document sets or long jobs?
Yes. Redis and BullMQ background workers keep heavy processing off your API and away from your users.

