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I will build a custom rag ai chatbot with langchain
Changbao Z
About this gig
Need a practical AI chatbot that answers from your own documents, website content, or business data?
I will build or fix a RAG based chatbot or LangChain workflow that connects your content to an LLM such as OpenAI, Claude, DeepSeek, Llama, or Gemini. My focus is reliable backend implementation, not just a nice demo.
I can help with:
- PDF or document based Q&A
- RAG retrieval and vector database setup
- LangChain or LangGraph workflows
- OpenAI, Claude, DeepSeek, Llama, or Gemini API integration
- FastAPI or Java Spring Boot backend APIs
- Source citations and structured responses
- Prompt, retrieval, and API bug fixing
You will get clean source code, clear setup instructions, and practical communication about what is possible within your package.
Please message me before ordering if your project includes private data, a large document set, complex agent tools, or an existing codebase.
Get to know Changbao Z
Changbao Z
AI RAG Chatbot and Backend API Developer
- FromChina
- Member sinceJul 2025
- Avg. response time1 hour
Languages
English, Chinese
I help businesses build practical AI chatbots, RAG knowledge bases, and backend API integrations. I have 13+ years of Java, Spring Boot, REST API, MySQL, and Linux experience, and now focus on AI application backends with OpenAI, Claude, DeepSeek, LangChain, LangGraph, vector search, Python FastAPI, and n8n automation. I can build document chatbots, source-cited RAG systems, AI agents, API integrations, and reliable backend services with clean code, clear communication, and setup documentation.
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FAQ
Can you build a chatbot from PDFs or website content?
Yes. I can build a RAG chatbot that answers from your documents, website content, or business knowledge base, with retrieval and source-aware responses.
Do you provide source code?
Yes. Source code is included in all packages unless we agree otherwise before the order starts.
Should I message you before ordering?
Yes, please message first if you have private data, a large document set, agent tools, deployment needs, or an existing codebase.
