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$
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I will build a custom ai chatbot and llm app using langchain rag and python
Abdul Rehman
About this gig
Are you looking for a custom AI chatbot that
understands your business and your data?
I will build a custom AI chatbot using LangChain
and RAG trained on YOUR documents to give accurate
intelligent responses in real-time.
WHAT I OFFER:
- Custom RAG chatbot trained on your documents
- LangChain and LlamaIndex pipeline development
- Vector database integration Pinecone ChromaDB
- Multi-source document processing PDF Word URL
- REST API integration with FastAPI or Django
- Hugging Face and Meta Llama model integration
- Deployment ready clean and documented code
PERFECT FOR:
- Customer support automation
- Internal knowledge base chatbots
- Document question answering systems
- Sales and lead generation assistants
- Educational AI tutoring platforms
- Ecommerce product recommendation bots
WHY CHOOSE ME:
- Expert in LangChain RAG and vector databases
- Open source LLMs no expensive API costs
- Clean production ready Python code
- On-time delivery guaranteed
- Free consultation before ordering
Not sure which package fits your project?
Message me before ordering. I will guide you
to the right solution for your needs.
Let's build your AI system today!
Get to know Abdul Rehman
Abdul Rehman
AI ML Engineer, Computer Vision, YOLO, Deep Learning, Python
- FromPakistan
- Member sinceAug 2024
- Avg. response time1 hour
Languages
English, Urdu, French, German
Hi, I’m Abdul Rehman, an AI/ML Engineer and AI Developer with hands-on professional and project experience in Machine Learning, Deep Learning, Computer Vision, Generative AI, LLMs, NLP, and AI Automation. I build custom AI models, YOLO systems, RAG chatbots, AI agents, web scrapers, Django and FastAPI applications, REST APIs, and cloud-based AI solutions. From data processing and model training to backend development, API integration, deployment, and optimization, I deliver complete and scalable AI solutions with clean code and reliable results.
FAQ
What is a RAG chatbot and how is it different from a normal chatbot?
A RAG chatbot uses Retrieval Augmented Generation to answer questions based on YOUR specific documents and data. Unlike generic chatbots, it reads your files, PDFs, or website and gives accurate answers from your own content. It does not hallucinate or give random responses.
Do I need an OpenAI API key or paid subscription?
No. I use open source LLMs like Meta Llama and Mistral AI which have no expensive API costs. You own the model and can run it on your own server. If you prefer OpenAI or Claude I can integrate those too. Message me to discuss.
What documents and file types can the chatbot read?
The chatbot can read PDF, Word documents, Excel files, plain text, CSV, web URLs, and Notion pages. I use LangChain document loaders to process multiple file types simultaneously. You can provide as many documents as needed.
Which vector database do you use?
I work with Pinecone, ChromaDB, FAISS, and Weaviate depending on your project needs and budget. ChromaDB and FAISS are free and local. Pinecone is cloud based and scales better for large document collections. I will recommend the best option for your specific use case.
Can the chatbot be integrated into my website or application?
Yes. I build a REST API using FastAPI or Django that connects your chatbot to any website, mobile app, or web application. I can also integrate directly into WordPress, React, or custom web apps. Standard and Premium packages include full API integration.
How accurate will the chatbot responses be?
Accuracy depends on the quality of your documents. With clean well structured documents the chatbot achieves very high accuracy on domain specific questions. I use advanced chunking and retrieval strategies to maximize accuracy. I provide full testing before delivery.
Can the chatbot remember previous conversations?
Yes. I implement conversation memory using LangChain memory modules so the chatbot remembers context within a session. For long term memory across sessions I use a database to store conversation history. This is included in Standard and Premium packages.
What information do I need to provide to get started?
You need to provide your documents or data source, describe what questions the chatbot should answer, your preferred deployment environment such as website or API, and any specific tone or personality for the chatbot. I will guide you through everything before we start.
Do you provide the source code after delivery?
Clean and well commented source code is included in Standard and Premium packages. Basic package buyers can add full source code and setup guide for an additional fee using the gig extra. All code is delivered via GitHub repository or ZIP file.
I am not technical. Can you still help me?
Absolutely. Many of my buyers are business owners with no technical background. I handle everything from setup to deployment. I explain the process in simple language and provide full documentation so you can manage the chatbot yourself after delivery. Message me before ordering and I will mak
