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I will build langchain rag chatbot or ai agent with fastapi
Haifa
About this gig
Need an AI chatbot or AI agent that answers from your own documents, website, database, or business knowledge?
I will build a LangChain RAG chatbot or LangGraph AI agent using FastAPI, Next.js, vector database, LLM APIs, and production-ready backend architecture.
This is not a basic chatbot. I build source-aware AI systems that understand your business data and help users get accurate answers.
My process:
- Requirement meeting to understand your business problem
- SRS, AI flow, data source plan, and architecture
- Clean UI/UX flow for the chatbot or agent
- FastAPI backend with LangChain or LangGraph
- Vector database, embeddings, retrieval, tools, and API integration
- Testing, bug fixing, deployment, and documentation
I can build PDF chatbots, document Q&A, website knowledge bots, internal support assistants, RAG systems, AI agents, custom GPT-style apps, and AI SaaS backend systems.
Best for businesses that want accurate AI answers from their own knowledge base.
Message me before ordering so we can confirm your data source, AI flow, scope, and package.
Message me before ordering so we can confirm your data source, AI flow, scope, and package.
Get to know Haifa
Haifa
AI Full Stack Developer
- FromBangladesh
- Member sinceNov 2022
- Avg. response time1 hour
Languages
English, French, Dutch, Spanish
Hello! I'm Haifa Binte Habib, an AI Full-Stack Software Engineer with 3+ years of experience building AI-powered custom web applications. I analyze your requirements, create a detailed SRS, design modern UI/UX in Figma, and after approval start development. My team includes expert designers and developers. We build scalable solutions using React, Next.js, Express, FastAPI, and Python with AI tools like LangChain, LangGraph, RAG, and n8n. From idea to deployment, you get a complete end-to-end solution.
FAQ
What is this gig best for?
This gig is best for businesses that want an AI chatbot, RAG system, or AI agent that can answer from their own documents, website, database, or knowledge base.
What is a RAG chatbot?
A RAG chatbot retrieves relevant information from your data source before answering, so the response is based on your business knowledge instead of only generic AI output.
What is the difference between RAG and an AI agent?
A RAG chatbot mainly answers from knowledge. An AI agent can also follow workflows, call tools, use APIs, and perform multi-step actions depending on the scope.
Can you build a PDF or document chatbot?
Yes. I can build a chatbot that answers from PDFs, Word files, text files, FAQs, website content, or structured business documents.
Which technologies do you use?
I use LangChain, LangGraph, FastAPI, Next.js, Tailwind CSS, vector databases, PostgreSQL, MongoDB, OpenAI, Claude, Gemini, or other LLM APIs.
Can you connect the chatbot to my existing app?
Yes. I can integrate the chatbot or AI agent into your existing web app, SaaS, dashboard, or internal business system.
Can the AI show sources?
Yes. I can add source-aware answers so users can see which document, section, or knowledge source the AI used.
Will you test the AI answers?
Yes. I test the chatbot or agent with real use cases and improve prompts, retrieval logic, and flow before final delivery.
Will you deploy the final system?
Deployment can be included depending on the package. I can deploy the frontend, backend, database, and AI service to your preferred platform.
Do you provide support after delivery?
Yes. I provide support for bugs or minor issues related to the delivered scope.
