Phoenix - Your AI AssistantBuild a RAG chatbot using your documents and website
Delivery in
4 days
- Views 1
Amount of days required to complete work for this Offer as set by the freelancer.
Rating of the Offer as calculated from other buyers' reviews.
Average time for the freelancer to first reply on the workstream after purchase or contact on this Offer.
What you get with this Offer
Turn your business documents and website content into an intelligent AI assistant.
I will build a custom Retrieval-Augmented Generation (RAG) chatbot that answers questions using your own knowledge base. Unlike a generic chatbot, the assistant retrieves relevant information from your documents before generating its response, helping it provide more accurate and context-aware answers with source citations.
This solution is ideal for:
• Customer support and FAQ automation
• Internal company knowledge bases
• Employee onboarding and HR documents
• Product manuals and technical documentation
• Educational or research content
• Policies, procedures and operational guides
WHAT YOU WILL RECEIVE
• One custom RAG chatbot for a clearly defined use case
• Processing of up to 20 documents or 200 pages
• Support for PDF, DOCX, TXT or selected website pages
• Document cleaning, chunking and embedding
• Semantic search using a vector database
• Integration with one LLM provider
• Answers grounded in your business content
• Source references or citations in the responses
• A basic Streamlit chat interface
• Clean and documented Python source code
• Setup instructions and a README
• Basic testing using your sample questions
• One revision for minor adjustments
The chatbot can be built with technologies such as Python, LangChain or LlamaIndex, ChromaDB or FAISS, and OpenAI, Claude, Gemini or another suitable language model.
BASE OFFER SCOPE
The base offer includes one knowledge source, one chatbot use case and a basic local or demonstration interface.
Website embedding, production deployment, scanned-document OCR, database connections, authentication, advanced analytics and third-party integrations are available as optional add-ons.
API usage, cloud hosting and other third-party service charges are not included. If a paid LLM is selected, the buyer must provide access through their own provider account.
I will build a custom Retrieval-Augmented Generation (RAG) chatbot that answers questions using your own knowledge base. Unlike a generic chatbot, the assistant retrieves relevant information from your documents before generating its response, helping it provide more accurate and context-aware answers with source citations.
This solution is ideal for:
• Customer support and FAQ automation
• Internal company knowledge bases
• Employee onboarding and HR documents
• Product manuals and technical documentation
• Educational or research content
• Policies, procedures and operational guides
WHAT YOU WILL RECEIVE
• One custom RAG chatbot for a clearly defined use case
• Processing of up to 20 documents or 200 pages
• Support for PDF, DOCX, TXT or selected website pages
• Document cleaning, chunking and embedding
• Semantic search using a vector database
• Integration with one LLM provider
• Answers grounded in your business content
• Source references or citations in the responses
• A basic Streamlit chat interface
• Clean and documented Python source code
• Setup instructions and a README
• Basic testing using your sample questions
• One revision for minor adjustments
The chatbot can be built with technologies such as Python, LangChain or LlamaIndex, ChromaDB or FAISS, and OpenAI, Claude, Gemini or another suitable language model.
BASE OFFER SCOPE
The base offer includes one knowledge source, one chatbot use case and a basic local or demonstration interface.
Website embedding, production deployment, scanned-document OCR, database connections, authentication, advanced analytics and third-party integrations are available as optional add-ons.
API usage, cloud hosting and other third-party service charges are not included. If a paid LLM is selected, the buyer must provide access through their own provider account.
What the Freelancer needs to start the work
Please provide:
• A description of the business problem and intended users
• The documents, website pages or knowledge sources to use
• 10 to 20 example questions the chatbot should answer
• Examples of preferred answers, if available
• The required language or languages
• Your preferred LLM provider, if you have one
• Brand tone, chatbot name and welcome message
• Your deployment or website integration requirements
• Any topics the chatbot should avoid or refuse to answer