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$
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I will build an ai rag chatbot for your PDF documents using langchain
Shaheer H
About this gig
Turn your PDFs and business documents into a searchable AI chatbot. I build custom RAG chatbots in Python using LangChain, with Pinecone, ChromaDB or FAISS for retrieval.
Use it for document Q&A, internal knowledge search or research assistants.
Choose your package:
- Basic: semantic-search RAG over 1 document.
- Standard: hybrid search over up to 5 documents.
- Premium: hybrid search, cross-encoder reranking and LLM-based evaluation.
Supported sources include PDFs, Word files, text and web pages. Share a sample so I can check extraction quality and document size before you order.
My FinSight Pakistan project combines keyword and semantic search over financial reports. I use the same retrieval approach when it fits your use case.
You receive a working demo for the agreed scope. Source code and documentation are available through the Source Code + Docs extra.
Message me with your documents, example questions and preferred model so we can confirm the right package, timeline and any hosting or API costs.
Get to know Shaheer H
Shaheer H
AI Engineer, RAG Systems, LLM FineTuning, LangChain Python
- FromPakistan
- Member sinceApr 2021
- Avg. response time5 hours
- Last delivery3 years
Languages
Urdu, English
I build production-ready AI systems — RAG chatbots, fine-tuned
LLMs, and intelligent Python applications.
My recent work:
→ FinSight Pakistan: Hybrid-search RAG system over 916K words - 75.3%
relevancy score
→ EdgeAlign: Full SFT → DPO fine-tuning pipeline on Qwen3-0.6B
with LoRA adapters — +176% BLEU improvement
What I deliver:
- RAG chatbots over your documents (PDFs, reports, databases)
- Custom LLM fine-tuning on your dataset
- LangChain agents and AI pipelines
- Full-stack AI web apps (React + Node.js + PostgreSQL)
- Python ML scripts and automation
My Portfolio
FAQ
What do you need before I order?
Send a sample document, its page count or size, example questions, your preferred model and where you want to run the chatbot. I will confirm the extraction approach, scope and package before you order.
Which package should I choose?
Basic covers semantic retrieval over 1 document. Standard adds hybrid search over up to 5 documents. Premium adds reranking and LLM-based evaluation. For larger collections, scanned PDFs or extra integrations, message me for a scope review.
Are source code, hosting and API costs included?
Source code and documentation are available through the Source Code + Docs extra. Message me before ordering to confirm hosting, model API and vector database costs, plus any deployment work needed for your setup.
Will the chatbot always give accurate answers?
RAG helps ground answers in your documents, but it cannot guarantee every answer is correct. Retrieval quality depends on your source material and questions. Premium includes evaluation; share representative questions so we can assess results.
What is included in a revision?
Basic includes 1 revision, Standard 2 and Premium 3. Revisions cover adjustments to the delivered chatbot within the agreed documents, features and requirements. New data sources, integrations or features are additional scope and will be quoted separately.
