Dify chatbot development
Budget: $1,500 – $3,000 USD
# Project: Quotebot Upgrade – Multi-Product Handling & File Attachments
## Overview
We're looking for an experienced Dify developer to take our B2B quoting chatbot from MVP to production, and then expand it further. This project has two phases: first, hardening and finalizing the existing MVP for production readiness; then adding new capabilities. Upcoming phases will also include additional API search integrations and expanded microservices. The immediate new features for this engagement are multi-product handling and user file attachments.
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## Current System
The bot runs on a self-hosted Dify server using a custom workflow with 16 LLM nodes, condition nodes, and code nodes. It handles dialog state, classifies the user's product inquiry into a single category, dynamically generates specification fields, and POSTs the collected data to our backend API. The architecture also includes supporting microservices running on Dify. A dual-strategy flow (mobile vs. desktop) optimizes the conversation for different devices. The system is currently at MVP stage and needs to be production-ready before new features are added.
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## Scope of Work
**Phase 1 – Production Readiness** — Review the existing MVP, identify gaps, and ensure the system is stable, reliable, and ready for real user traffic. This includes error handling, edge case coverage, and any necessary refactoring.
**Phase 2 – Multi-Product Support** — Refactor the classifier and specification logic to handle multiple products in one conversation, collecting specs for each sequentially without confusing the user. Update the API payload to send a correctly structured multi-product array.
**Phase 3 – File Attachment Handling** — Enable file uploads (PDFs, images, drawings) and integrate vision/document parsing so the LLM can extract and pre-fill specs from uploaded files, with parsed data included in the final API submission.
**Phase 4 – State & Memory** — Update conversation memory and state tracking to support the above across all nodes, with no regressions in existing fallback, authentication, or routing logic.
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## Deliverables
- Production grade system
- Full regression testing against existing flows
- Technical documentation for new workflow branches
## Overview
We're looking for an experienced Dify developer to take our B2B quoting chatbot from MVP to production, and then expand it further. This project has two phases: first, hardening and finalizing the existing MVP for production readiness; then adding new capabilities. Upcoming phases will also include additional API search integrations and expanded microservices. The immediate new features for this engagement are multi-product handling and user file attachments.
---
## Current System
The bot runs on a self-hosted Dify server using a custom workflow with 16 LLM nodes, condition nodes, and code nodes. It handles dialog state, classifies the user's product inquiry into a single category, dynamically generates specification fields, and POSTs the collected data to our backend API. The architecture also includes supporting microservices running on Dify. A dual-strategy flow (mobile vs. desktop) optimizes the conversation for different devices. The system is currently at MVP stage and needs to be production-ready before new features are added.
---
## Scope of Work
**Phase 1 – Production Readiness** — Review the existing MVP, identify gaps, and ensure the system is stable, reliable, and ready for real user traffic. This includes error handling, edge case coverage, and any necessary refactoring.
**Phase 2 – Multi-Product Support** — Refactor the classifier and specification logic to handle multiple products in one conversation, collecting specs for each sequentially without confusing the user. Update the API payload to send a correctly structured multi-product array.
**Phase 3 – File Attachment Handling** — Enable file uploads (PDFs, images, drawings) and integrate vision/document parsing so the LLM can extract and pre-fill specs from uploaded files, with parsed data included in the final API submission.
**Phase 4 – State & Memory** — Update conversation memory and state tracking to support the above across all nodes, with no regressions in existing fallback, authentication, or routing logic.
---
## Deliverables
- Production grade system
- Full regression testing against existing flows
- Technical documentation for new workflow branches
Related categories:
Automation Codeless Program
Natural Language Processing
AI Chatbot Development
AI Development