Document AI Chatbot Prototype with Source Citations by Tahir AliDocument AI Chatbot Prototype with Source Citations by Tahir Ali
Document AI Chatbot Prototype with Source CitationsTahir Ali
Build a document assistant that retrieves relevant passages from your supplied material and returns answers with source references.
STARTER SCOPE — $420 / 2 weeks
A proof of concept for up to 10 text-readable PDF or text files, one language, a simple web chat interface, document ingestion, source references and an unsupported-question response. Two revision rounds, source code and setup notes are included.
IMPLEMENTATION
Python, FastAPI, Ollama, ChromaDB and LangChain where they fit the agreed deployment. My VOX project provides relevant experience with local retrieval, multilingual voice and human handoff.
ACCEPTANCE
We agree 10–20 sample questions and expected source passages, then review retrieval and answers together. This is not a guarantee that every answer is correct. Local-only processing depends on the selected components and hardware.
SEPARATE SCOPE
OCR, large document collections, multiple languages, permissions, production hardening, integrations and ongoing maintenance. Hosting, model APIs and infrastructure costs are separate.
TO START
Send redacted sample documents, the file count and formats, allowed data destinations, hosting details and sample questions. Do not send passwords or sensitive records through an initial inquiry.
NEXT STEP
Message me on Contra with your design or workflow, required features and deadline. I will review the requirements and confirm a clear scope before work begins.
Document AI Chatbot Prototype with Source CitationsTahir Ali
Starting at$420
Duration2 weeks
Tags
Ollama
Python
AI Developer
Build a document assistant that retrieves relevant passages from your supplied material and returns answers with source references.
STARTER SCOPE — $420 / 2 weeks
A proof of concept for up to 10 text-readable PDF or text files, one language, a simple web chat interface, document ingestion, source references and an unsupported-question response. Two revision rounds, source code and setup notes are included.
IMPLEMENTATION
Python, FastAPI, Ollama, ChromaDB and LangChain where they fit the agreed deployment. My VOX project provides relevant experience with local retrieval, multilingual voice and human handoff.
ACCEPTANCE
We agree 10–20 sample questions and expected source passages, then review retrieval and answers together. This is not a guarantee that every answer is correct. Local-only processing depends on the selected components and hardware.
SEPARATE SCOPE
OCR, large document collections, multiple languages, permissions, production hardening, integrations and ongoing maintenance. Hosting, model APIs and infrastructure costs are separate.
TO START
Send redacted sample documents, the file count and formats, allowed data destinations, hosting details and sample questions. Do not send passwords or sensitive records through an initial inquiry.
NEXT STEP
Message me on Contra with your design or workflow, required features and deadline. I will review the requirements and confirm a clear scope before work begins.