AI Chatbot Skills Engine - Backend + Frontend (Python/FastAPI + React)

@ZohaibRoy

⭐⭐⭐⭐⭐ Build an Efficient Skills Module for Your AI Chatbot Platform ❇️ Hi My Friend, I hope you're doing well. I've reviewed your project needs and see you're looking for a developer to create a Skills module for your AI chatbot. You can stop searching; Zohaib is here to assist! My team has successfully completed over 50 similar projects for chatbot functionalities. I will build a standalone module that integrates seamlessly with your existing platform, ensuring all features work as intended. ➡️ Why Me? I can easily build your Skills module as I have 5 years of experience in developing automation engines, API integrations, and frontend systems. My expertise includes Python, FastAPI, React, and database management. I also have a strong grip on AI technologies like OpenAI API and vector databases. ➡️ Let's have a quick chat to discuss your project in detail, and I can show you examples of my previous work. I look forward to our conversation! ➡️ Skills & Experience: ✅ Python Development ✅ FastAPI Framework ✅ React.js ✅ PostgreSQL ✅ API Integration ✅ Workflow Automation ✅ AI/LLM Integration ✅ Data Transformation ✅ Credential Management ✅ Docker Setup ✅ JSON Handling ✅ UI/UX Design Waiting for your response! Best Regards, Zohaib

@gunslinger

This feels like less about building APIs and more about getting the execution model right so skills don’t turn into tangled logic over time. I’d approach it as a clean DAG based engine with explicit state handling and separation between the runner, skill definitions, and integrations, so each workflow stays predictable and reusable. I’ve worked on similar API orchestration and automation flows (including AI integrations), so translating this into a stable FastAPI module with a matching React Flow builder is very much in my lane. If useful, I can sketch a simple structure and timeline before we start.

@toni5705

Hi, A standalone Skills module for an AI chatbot SaaS platform — DAG-based workflow engine, intent detection, AI-powered skill builder, MCP integration, and a React Flow visual editor. This is a sophisticated, well-specified build and we have the hands-on experience across every layer of the stack to deliver it as a clean, isolated module ready for your team to integrate. What we deliver: - DAG execution engine in FastAPI: topological sort, conditional branching, resumable execution, and per-session state storage - Eight action types: API Call, AI Generate, Data Transform, Knowledge Lookup, Send Email, Webhook, Human Escalation, and UI Prompt - AES-256-GCM credential vault with OAuth2 authorization code flow support scoped per bot/organization - Embedding-based intent detection using OpenAI text-embedding-3-small and Pinecone vector index - Multi-agent AI skill builder: orchestrator + builder LLMs generating complete skill configurations from natural language, with iterative refinement support - MCP client over JSON-RPC 2.0 with Streamable HTTP and SSE transport - React Flow visual editor: drag-and-drop canvas, configuration panels, edge conditions, test panel, template browser, and AI generation wizard - Full API documentation, Docker demo, and integration specification document We'd love to walk through your existing platform's integration spec and discuss milestone structure on a quick call — everything stays private. Are you available this week? Anthony Muñoz

@diektech

Hi, This is Elias from Miami. I checked your project description and understand you’re looking to build a Skills module for your AI chatbot SaaS platform. This will involve both backend and frontend development using Python/FastAPI and React. I’ve worked on several similar platforms and understand the key technical challenges involved. I’m confident that my experience with AI chatbot development and API integration will help us create a seamless and efficient Skills module. I’d be happy to go through the details and suggest the best technical approach. I have a few questions to get a better understanding: Q1 – What specific user roles will the Skills module need to support? Q2 – Are there any existing systems or APIs that we need to integrate with? Q3 – What are your scalability requirements for this module as user demand grows? Looking forward to hearing from you.

@irsolutions

With over a decade of experience in building high-performance systems, I understand the importance of creating a seamless AI Chatbot Skills Engine for your SaaS platform. Your project goal of developing a standalone Skills module that integrates seamlessly aligns perfectly with my background in scaling systems for over 1 million users and handling complex FinTech security challenges. As a strategic insight, ensuring scalability and security in the Skill Execution Engine is crucial. Drawing from my experience in building a Telegram Mini App serving over a million users, I am confident in implementing a DAG-based workflow engine that executes multi-step skills efficiently. I encourage you to reach out to discuss how we can collaborate to bring your AI Chatbot Skills Engine project to life. Let's connect to further discuss the roadmap and ensure the successful implementation of this pivotal module for your platform.

@corpmember29

HELLO, WE HAVE WORKED ON SIMILAR PROJECTS AND CAN PROVIDE EXAMPLES WE COMPLETELY UNDERSTAND YOUR REQUIREMENT FOR A DAG-BASED AI SKILL EXECUTION ENGINE WITH FASTAPI BACKEND, OPENAI INTEGRATION, MCP SUPPORT, AND A REACT FLOW VISUAL BUILDER. With over 10+ years of experience in backend systems, AI agent architectures, and workflow automation engines, I can design and build a modular, production-ready system that is fully isolated and integration-friendly. WORKING FLOW → Architecture Design → define DAG execution engine with state management, topological execution, and resumable workflows Backend Development → FastAPI services for skills, executions, credentials vault, and intent detection system Execution Engine → node-based DAG runner supporting API calls, LLM steps, transformations, webhooks, and human-in-loop pauses AI Pipeline → OpenAI-based skill generator (orchestrator + builder agents) with iterative refinement support Intent Detection → embedding-based matching using OpenAI text-embedding-3-small + vector search (Pinecone) MCP Integration → JSON-RPC client for tool discovery and execution via Streamable HTTP/SSE Frontend Builder → React Flow-based visual editor with node configs, edge conditions, and test execution panel I eagerly await your positive response. Thanks.

@Herculesz

Hi I have strong experience building standalone workflow and automation modules with Python, FastAPI, PostgreSQL, raw SQL, and resumable execution patterns for multi-step systems. The main technical challenge here is designing a DAG-based skill engine that supports branching, paused/resumed runs, variable interpolation, external tool calls, and secure credential handling without coupling it tightly to your existing chatbot platform. I would structure this as an isolated backend module with a graph executor, session state store, intent-matching layer, encrypted credential vault, MCP client, and AI skill-generation pipeline, all exposed through clean FastAPI routes. On the frontend side, I have experience building visual editors with React and graph-based UI patterns, and I can use React Flow to deliver a maintainable skill builder with node configs, edge conditions, test execution tracing, templates, and AI-assisted generation. I also work extensively with OpenAI APIs, embeddings, prompt pipelines, and agent-style orchestration for structured JSON outputs and iterative refinement. For intent detection and knowledge lookup, I can wire OpenAI embeddings with Pinecone cleanly so skill triggering and retrieval actions stay modular and easy to extend. The result would be a self-contained deliverable with clear integration boundaries, Docker-based local testing, and documentation your team can plug into the existing SaaS safely. Thanks, Hercules

@ShaikhAneesa

Hi there, I’ve conducted a comprehensive review of your technical requirements and understand the need for a high-performance, isolated "Skills" module to extend your chatbot’s capabilities. I am confident I can architect a robust DAG execution engine and a React Flow-based visual builder that bridges the gap between natural language intent and complex multi-step automation. My approach begins with a structural audit of your desired node types to ensure a "Source of Truth" for your DAG execution engine using FastAPI and raw SQL. I will engineer a stateful, resumable execution layer that handles topological sorting, conditional branching, and secure credential storage via AES-256-GCM. Next, I will develop the AI-powered Skill Builder and intent detection system utilizing OpenAI’s latest models and Pinecone to transform natural language prompts into complete, valid skill JSONs. Finally, I will build the React-based visual editor using React Flow and plain CSS, delivering a backend-ready, standalone package that includes an MCP client and a full Docker-compose demo for seamless integration. Beyond the deliverables, I prioritize "integration-ready" code, ensuring that the standalone module communicates perfectly with your existing SaaS architecture via the provided specifications. Would you like the state persistence to store only the final output of each node, or a full execution log for debugging within the test panel? Let’s get started now! Warm regards, Aneesa.

@kareemmaize

Hi, this is a strong spec and the right approach for building a scalable skills system. I’ve worked on workflow engines with stateful execution, branching, and API orchestration, where each node follows strict input/output contracts and resumable flows. For this, I’d structure the engine around a validated DAG executor with session state, then layer modular action handlers (API, AI, transform, etc.) and a credential vault with encrypted storage and OAuth support. On the AI side, I’ve built multi-step pipelines using OpenAI (planner → builder → validator) to generate structured outputs safely. For the frontend, I’ve implemented node-based editors similar to React Flow with dynamic config panels and edge conditions synced to backend schemas. I’d deliver this in phases: core engine, state + credentials, AI builder, then visual editor and templates, ensuring everything stays aligned and production-ready.

@shadabkhan92

Hi there! My name is Shadab and I lead a stellar full stack engineering team with diverse expertise, specializing in areas such as AI, enterprise ERP systems, and even hardware development. Our past work includes building intelligent systems that go beyond basic automation, including autonomous AI agents and computer vision tasks. We have significant exposure to AI integration within existing workflows, which aligns perfectly with your project requirement for an automated Skills module. On the backend side of things, we're expert in Python and experienced with building workflow engines that follow directed acyclic graphs (DAGs) just as you require. We've built similar engines for executing multi-step processes, having nodes connected by transitions. Additionally, our skills extend to OAuth2 authorization code flow, which is crucial when it comes to storing encrypted credentials for skill execution involving external APIs. Moving on to your second requirement of Skill Intent Detection; at times one can struggle with generating appropriate intent phrases but we are confident in our abilities to tackle this challenge effectively. We are versed in embedding-based matching using OpenAI's text-embedding-3-small which in combination with your desire for embedding user messages allows us to provide highly accurate responses.

@AITSoft

Hi there! I'm Shamshad, a seasoned software developer who specializes in AI-powered technologies, including AI Chatbot Development. With over a decade of diverse experience in Backend and Frontend development using Python/FastAPI and React respectively, I would be an excellent fit for your project. Drawing from my strong background in APIs and familiarity with Python's extended libraries, I can build the Skill Execution Engine your project requires. My profound understanding of data structures and graph-based systems also means I can implement the directed acyclic graph efficiently to achieve resumable skill execution and conditional branching. With regards to Credential Vault development, I've worked extensively with encryption techniques like AES-256-GCM which will be beneficial for implementing secure storage. Another crucial aspect is skill intent detection. Here, my familiarity with embedding-based matching and OpenAI's text-embedding-3-small will enable me to develop a robust solution that accurately detects the skill based on user messages while optimizing the efficiency. Additionally, my fluency in natural language processing will significantly contribute to building the AI-Powered Skill Builder pipeline that is essential for your project.

@juanjosec63

Hi, I have strong experience in Python, FastAPI, PostgreSQL, React, React Flow, OpenAI API, Pinecone, and building AI workflow systems with DAG execution, resumable state handling, and modular service design. I would structure this as an isolated backend and frontend module where the execution engine manages skill graphs with persisted session state, variable interpolation, branching, credential vault security, and MCP tool calls, while the React Flow builder gives your team a clean way to generate, test, and refine skills visually with AI-assisted creation and template-based workflows. I also have real hands-on experience building agent pipelines, LLM-powered automation flows, vector search integrations, and custom backend systems that need to be delivered as standalone packages with clean API contracts, Docker setup, and integration-ready documentation, so this is very close to the type of architecture work I already do. You can expect clear communication, fast turnaround, and a high-quality result that fits seamlessly into your existing workflow. Best regards, Juan

@kamran2012

Hi there, I will deliver the full Skills module — DAG execution engine with resumable state, visual React Flow builder, AI skill generator, MCP client, and credential vault — as a standalone package with Docker demo. For the execution engine, I will model each skill as a adjacency list persisted in PostgreSQL, run topological sort at execution time, and store per-session state as a JSONB column keyed by action ID. This makes resumability straightforward — when a UI Prompt pauses execution, the engine picks up from the exact node using the stored cursor and accumulated outputs. Questions: 1) For conditional branching, do you need only simple field/operator/value comparisons, or also compound conditions with AND/OR logic? 2) Should the MCP client support persistent SSE connections per bot, or connect on-demand per tool invocation? Looking forward to talking through the details. Kamran

@maximg10

⭐Hi, I’m ready to assist you right away!⭐ I believe I’d be a great fit for your project since I have extensive experience in developing AI chatbot modules and workflow engines. My technical expertise in Python, FastAPI, React, and AI model development align perfectly with the requirements of building the Skills module for your chatbot platform. I have a proven track record of designing and implementing complex workflow engines, including directed acyclic graph (DAG) structures to execute multi-step skills efficiently. Additionally, I specialize in integrating API calls, AI generation, data transformation, and knowledge lookups to create seamless automated workflows. This project aims to enhance your chatbot platform by providing a standalone Skills module that streamlines processes, automates tasks, and enables efficient user interactions. By leveraging my skills and experience, I can ensure the successful implementation of this module to meet your specific requirements. If you have any questions, would like to discuss the project in more detail, or would like to know how I can help, we can schedule a meeting. Thank you. Maxim

@rpivato

The main risk here is not the features, but ending up with a workflow engine that becomes unstable with branching, async steps, and LLM variability. The solution is a deterministic execution layer with persisted state, so every step is traceable, resumable, and reliable under real usage. I’ve worked on similar API/LLM pipelines where unpredictability is the norm, and the key is stabilizing flows with retries, validation, and strict contracts between steps. That fits directly here by isolating actions with clear input/output and controlled transitions, keeping the system extensible without breaking the core.

@iglobalvn

I can build your Skills module as a clean, isolated backend/frontend deliverable that plugs into your SaaS without rework. I’ve shipped FastAPI systems with workflow orchestration, AI integrations, and secure credential handling, so this project matches my core experience closely. What I’ll deliver: - A DAG-based skill execution engine with topological execution, conditional branching, resumable state, and per-session execution tracking - Support for API calls, LLM generation, JSON/data transforms, Pinecone knowledge lookup, email/webhook actions, human escalation, and UI prompts - Secure encrypted credential vault with CRUD, OAuth2 auth-code flow, token refresh, and org/bot scoping - Embedding-based intent matching using OpenAI embeddings and configurable confidence thresholds I focus on production-ready architecture: clean FastAPI services, well-structured React UI, robust state management, and clear interfaces for easy integration into your existing platform. I’ll also make sure variable interpolation, action outputs, and resume logic are reliable and testable. My approach is to define the data model and execution contract first, then implement the engine, credential layer, intent matcher, and frontend builder in parallel, with testing throughout. If you want, I can walk you through the architecture and delivery milestones before we start.

@smaryum

Hi there, I have completely read your project details, and we are ready to start immediately. We will surely develop a robust, scalable Skill module with an interactive frontend and backend, integrating AI-powered workflows and DAG-based execution to enhance your chatbot platform. Our approach will focus on building a seamless execution engine, visual skill builder, and integrating automation to handle tasks such as API calls, AI generation, data transformation, and lead detection—all while ensuring smooth communication with your existing platform. 1. Have you identified any specific workflows or actions that should be prioritized in the first iteration of this system? 2. Will the system need to integrate with any additional third-party services or APIs apart from OpenAI and Pinecone? I would love to chat with you about your project in more detail. Looking forward to connecting with you! Regards, Saima

@FaizalShaik80

Hello, I can deliver what you need. I have reviewed your project and noticed that it is very similar to a task I completed two months ago. I am a skilled freelancer with 6+ years of experience in Python, FastAPI, API Development and I can deliver the results as quickly as possible. You can visit my profile to check my latest work and recent reviews. Connect in chat to discuss details and next steps. Regards.

@SmartCodeDev

Hello. I can build your standalone Skills module with a scalable DAG-based execution engine, AI pipeline, and full React visual builder. Architecture approach: Backend (FastAPI) will include a modular execution engine that parses skill DAGs, performs topological execution, and persists state per session in PostgreSQL. Each action type will be a pluggable handler (API, AI, transform, Pinecone, email, webhook, MCP, etc.) with a shared context system for variable interpolation. Intent detection will use embeddings + Pinecone index with threshold-based matching. AI Skill Builder will use a multi-step orchestrator + builder LLM pipeline with structured JSON outputs and refinement support. Credential vault will use AES-256-GCM with scoped access and OAuth2 flows. MCP client will support JSON-RPC over HTTP/SSE for tool discovery and execution. Frontend (React + React Flow) will provide a full visual builder with node config panels, condition editor, test runner, templates, and AI generation wizard using clean modular components and plain CSS. Timeline (approx): Week 1–2: Core backend (DB schema, execution engine, action handlers) Week 3: Intent detection, credential vault, MCP client Week 4: AI Skill Builder + refinement loop Week 5: React visual builder + test panel Week 6: Templates, polish, Docker setup, docs I can share relevant workflow/AI system work and discuss a fixed-price based on milestones.