FastapiJobs

...⸻ 5. AI Learning (Non-Training Based) We do not expect the model itself to retrain automatically. Instead, the system must: • Store AI draft vs final approved reply • Track edit level (none / light / heavy) • Allow prompt improvements and example-based learning • Support prompt versioning and comparison ⸻ Technical Expectations Preferred Stack (open to discussion) • Backend: Python (FastAPI) or Node.js (NestJS) • Database: PostgreSQL • Background jobs: Celery / BullMQ / equivalent • Frontend: React (admin dashboard) • AI: OpenAI API or Azure OpenAI • Hosting: Dockerised, cloud-ready Non-functional Requirements • Clean architecture • Clear separation of concerns • Good error handling and logging ...

...their passions, strengths, market needs, and core values. • An underlying algorithm or ruleset that cross-references those inputs with an open skills taxonomy and returns a short, ranked list of recommended skills. • Clear, well-commented code and a brief README so I can extend the project later. Tech Any modern stack is fine—feel free to propose JavaScript (React or vanilla), Python (Flask/FastAPI), or another lightweight option you prefer. Clean architecture and easy deployment (e.g., Docker or one-click Heroku) are more important than the specific language. Deliverables 1. Source code in a public or private repo. 2. Readable documentation explaining the recommendation logic and how to run the prototype locally. 3. A short video or screenshots that...

...their passions, strengths, market needs, and core values. • An underlying algorithm or ruleset that cross-references those inputs with an open skills taxonomy and returns a short, ranked list of recommended skills. • Clear, well-commented code and a brief README so I can extend the project later. Tech Any modern stack is fine—feel free to propose JavaScript (React or vanilla), Python (Flask/FastAPI), or another lightweight option you prefer. Clean architecture and easy deployment (e.g., Docker or one-click Heroku) are more important than the specific language. Deliverables 1. Source code in a public or private repo. 2. Readable documentation explaining the recommendation logic and how to run the prototype locally. 3. A short video or screenshots that...

...their passions, strengths, market needs, and core values. • An underlying algorithm or ruleset that cross-references those inputs with an open skills taxonomy and returns a short, ranked list of recommended skills. • Clear, well-commented code and a brief README so I can extend the project later. Tech Any modern stack is fine—feel free to propose JavaScript (React or vanilla), Python (Flask/FastAPI), or another lightweight option you prefer. Clean architecture and easy deployment (e.g., Docker or one-click Heroku) are more important than the specific language. Deliverables 1. Source code in a public or private repo. 2. Readable documentation explaining the recommendation logic and how to run the prototype locally. 3. A short video or screenshots that...

...automatic hashing, and immutably storing the hash on a blockchain network (Ethereum or any suitable L2 you recommend) • Instant on-screen validation result plus a shareable verification link • Admin dashboard where I can review submissions, view analytics, and revoke or re-issue hashes when needed Tech notes I’m open to React, , or similar for the front-end, and Node.js, Python (FastAPI), or comparable for the back-end. What matters most is clean code, clear documentation, and a tamper-proof hashing workflow that can scale as usage grows. Deliverables 1. Fully functional web app deployed to a cloud host (AWS, Azure, or Vercel). 2. Source code in a private Git repo with setup instructions. 3. Simple user and admin manuals (PDF or Markdown). 4. A sho...

My Python-based STOCK TRADING AGO web application is suffering from a real-time data issue: background processing runs, but the results reach the client side with a noticeable lag. I need you to trace that bottleneck, bring the pipeline back to true real-time behaviour, and then give the interface a fresh look while you’re in the codebase. Current stack • Python 3.10 with FastAPI • Celery + Redis for background jobs • PostgreSQL 13 • Front-end in plain HTML/CSS with a sprinkling of vanilla JS What I expect from you 1. Diagnose why background tasks aren’t pushing updates instantly—whether it’s queue configuration, database locking, or cache timing—and implement a clean, well-documented fix. 2. Refactor or rewrite an...

...proctoring system with violation detection and session monitoring Built adaptive multi-session interview engine with dynamic question generation Designed real-time admin dashboard using WebSockets Implemented JWT-based authentication and role-based access control Developed analytics module with PDF reporting Optimized performance using lazy loading and API caching Tech Stack: React 18, TypeScript, FastAPI, WebSockets, JWT, PostgreSQL, AI APIs PRIDE – AI-Powered Content Studio Role: Frontend / Full Stack Developer Designed dynamic template management and real-time PDF preview system Developed responsive UI using Tailwind CSS and Framer Motion Implemented accessible components with ARIA standards Managed application state using React Hooks and Context API Integrated dark/lig...

Fraud Detection Platform - Extraction Accuracy & Expansion Project Title **Senior Python Developer Needed for Document Fraud Detection Platform (Ongoing)** --- Project Description I have an 80% complete document fraud detection platform (Fraud X) built with: - **Backend**: Python, FastAPI, PostgreSQL, asyncpg - **Frontend**: React - **Infrastructure**: DigitalOcean VPS, Nginx, Gunicorn/Uvicorn, HTTPS - **OCR**: Multi-provider (Google Document AI, AWS Textract, GPT Vision fallback) Current Status The core system is working: - File upload & scan lifecycle - Multi-provider OCR with scoring - Fraud engine with PASS/CAUTION/FAIL verdicts - Admin dashboard with evidence viewer - JWT authentication & role-based access What Needs to Be Fixed (Phase 1 - Immediate) **1. Pa...

Title Senior Full-Stack & Mobile Engineer (React + FastAPI) — iOS/Android Overview We’re looking for a senior engineer to build, optimize, and scale a property-management web application and deliver native-quality mobile apps for iOS and Android. You’ll take ownership end-to-end: architecture, performance, security, release pipelines, and ongoing product development. Responsibilities • Build and maintain the web app (admin + owner/tenant portals) using React/TypeScript. • Design and implement backend services using FastAPI (Python) and REST APIs. • Integrate and optimize data layer (e.g.,) • PostgreSQL/Supabase/PostgREST or equivalent). •Develop mobile apps for iOS + Android using React Native (preferred) or Flutter/native, inc...

...Audio project management • Download and sharing options ⸻ 10. Performance & Scalability • Queue-based audio processing • Load balancing for AI generation • CDN integration for faster delivery ⸻ Technical Requirements Preferred Tech Stack (Developers can propose alternatives with justification) Frontend • React / / Vue.js • Tailwind / Material UI Backend • Node.js / Python (FastAPI / Django) • REST or GraphQL APIs AI & Voice Processing • Integration with: • ElevenLabs / Coqui / Azure TTS / Custom models • Voice cloning model integration Database • PostgreSQL / MongoDB Storage • AWS S3 / Google Cloud Storage Deployment • Dockerized architecture • AWS / GCP / Azure cloud ho...

...their passions, strengths, market needs, and core values. • An underlying algorithm or ruleset that cross-references those inputs with an open skills taxonomy and returns a short, ranked list of recommended skills. • Clear, well-commented code and a brief README so I can extend the project later. Tech Any modern stack is fine—feel free to propose JavaScript (React or vanilla), Python (Flask/FastAPI), or another lightweight option you prefer. Clean architecture and easy deployment (e.g., Docker or one-click Heroku) are more important than the specific language. Deliverables 1. Source code in a public or private repo. 2. Readable documentation explaining the recommendation logic and how to run the prototype locally. 3. A short video or screenshots that...

...webhooks or Zapier. Handle conversation history/context to avoid repetitive or amnesia-like responses. Escalate qualified leads (e.g., ready-to-sell) to me via email/Slack notifications. Optional: Pull external data (e.g., property comps from Zillow/PropStream API) for hyper-personalized messages. Tech Stack: Launch Control API/webhooks for SMS send/receive. Zapier or custom code (Python with FastAPI, Redis for state management) if needed for advanced automation. Ensure low latency, scalability for high-volume leads, and monitoring for errors. Compliance & Best Practices: Auto-add disclaimers/opt-outs to all messages. Rotate templates to avoid carrier filtering. Test for high engagement rates (aim for 10-20% responses). Testing & Delivery: Start with a small test campa...

...* “Quelles sont mes priorités maintenant ?” * “Optimise mon après-midi” * “Puis-je repousser cette réunion ?” - Réponses de l’IA : texte + audio 5. Débrief du soir (optionnel version 1.1) 6. Stockage des préférences et historique utilisateur (Supabase) 7. Paiement futur via Stripe (optionnel MVP) Stack technique souhaitée : - Frontend : (responsive) - Backend : Node.js ou FastAPI - Base de données : Supabase - IA : OpenAI GPT-4.1 - STT : Whisper ou Google Speech-to-Text - TTS : ElevenLabs ou OpenAI TTS - Intégration Google Calendar + Gmail API - Auth : Google OAuth Livrables attendus : - Web app MVP fonctionnel sur navigateur PC et mobile - Dashboard web...

...front end with ShadCN components, design the conversational flow, and connect everything to a secure Python back end that calls the GPT endpoint. The system must handle user authentication, store chat history in a database, and follow best practices for encrypting and validating any sensitive financial data. Deliverables • Responsive chat UI and supporting pages built with ShadCN • Python (FastAPI preferred) API that proxies GPT-4o, logs context, and rate-limits requests • Database integration—PostgreSQL or similar—for users, sessions, and prompts • Prompt-engineering layer that lets us adjust tone and compliance rules easily • Deployment scripts and a concise README so I can launch on Vercel or AWS This is a fixed-price project of...

Usted debe indicar el costo y tiempo de desarrollo. Debe leer lo presente y revisar la maqueta () antes de realizar consultas. Documento de Requerimientos de Usuario (DRU): Domicilio Digital 1. Visión del Proyecto Plataforma SaaS de notificaciones legales ("Domicilio Digital"). • Arquitectura Híbrida: o Cerebro: Backend en Python (Django/FastAPI) encargado de la lógica de negocio, reglas de seguridad, firma digital, gestión de usuarios, reportes y compilación de estilos. o Músculo: Mailcow (Dockerized) encargado del transporte de correo (MTA), almacenamiento (MDA) y Webmail (SOGo). 2. Personalización Visual Paramétrica (No-Code) El sistema permite una personalización "White-label" gestionada &ia...

Project Title: Build a Multi-Modal AI Productivity Suite (Meeting & Document Intelligence) Project Description I am seeking a developer to collaborate on a high-level AI productivity tool. The goal is to create a system that can process both live audio (meetings) and static documents (PDFs/Reports) to provide intelligent insights. Key Deliverables: Module 1: Speech-to-Summary: Implemen...Analysis: A dashboard component that tracks the "mood" of a conversation or document. Integration: A clean, functional API or Streamlit-based frontend to tie these features together. Required Technical Stack: Language: Python AI Frameworks: LangChain or LlamaIndex Transcription: OpenAI Whisper or AssemblyAI Database: Vector Databases (ChromaDB, Pinecone, or FAISS) Frontend: Streamlit...

...registering to our website or webapp will receive a QR code, where the tip will be paid to (linked to a IBAN bank account) Payment Integration A. Stripe * Apple Pay / Google Pay + cards * Stripe Connect for recipients * Webhooks + automated payouts Tech Requirements Frontend * Mobile-first web app / PWA * React or (preferred) * Fast, simple UI Backend * Node.js (Express/Nest) or Python (FastAPI) * REST API * Webhooks for payments * Cron for threshold payouts * Role-based access (staff/venue/admin) Database * PostgreSQL/MySQL * Entities: Users, Venues, Staff, TipLinks, Transactions, Payouts Security * HTTPS, rate limits, secure tokens * GDPR basics * Logging & monitoring Deliverables 1. Working web app + dashboards 2. Payment integration with webhooks 3. QR generation sy...

...strategy systematically, not a commercial product or institutional platform. What We're Building A personal trading assistant that: 1. Monitors my watchlist of 30-50 stocks 2. Automates entry/exit decisions based on my rules 3. Shows real-time charts and portfolio status 4. Manages risk with simple safety rules 5. Runs reliably on my computer Technology Requirements Essential Stack · Backend: FastAPI (for async handling) · Database: SQLite (with basic persistence) · Frontend: Simple dashboard with TradingView charts · Broker API: DhanHQ (Indian broker) · Libraries: pandas for calculations System Architecture ``` Simple Personal Trading System: 1. Data Layer: Fetches prices from DhanHQ 2. Logic Layer: Applies my trading rules 3. Exec...

...freshness and pipeline execution health. Inference latency and failure rates. A full MLOps stack is not required, but production-awareness is mandatory. Technical Requirements Python (production-quality code, not notebooks) Pandas, NumPy scikit-learn, CatBoost, XGBoost, or equivalent Time-series forecasting techniques SQL for intermediate storage or aggregation (if applicable) REST API framework (FastAPI or similar) Experience designing multi-tenant data systems Cloud provider and infrastructure details are flexible. Deliverables: Modular Python codebase covering: Data ingestion and validation Config-driven preprocessing Demand forecasting model Inventory planning model Price optimization model Clear configuration system for onboarding new clients Inference interfaces or APIs Do...

...runs: * Every trading day * On AWS EC2 Windows instance * Alerts must be filtered strictly to IST market hours * No duplicate or delayed alerts 6. Interactive Charting * Display Point & Figure charts interactively * UX comparable to TradingView or similar * Must support: * Zoom / pan * Timeframe switching * Live updates 7. Tech Stack (Preferred, Not Mandatory) * Backend: Python (FastAPI / Flask / Django) * WebSockets: KiteTicker * Frontend: * React / Vue / plain JS * OR Python-based UI (Streamlit acceptable only if justified) * Hosting:AWS EC2 (Windows) * Alerts: Telegram Bot API 8. Alert based trades * Based on the alerts(buy/sell), proceed to trigger the trade. * The trade should be overnight all the time. * Should have the view to lock the lots and c...

...converts any coaching/self-made Prelims test PDF into: Accurate question extraction (≈100 questions) Question-by-question review with AI-generated solutions Detailed analytics and leaderboard Clean, modern gradient-based UI This is not a test-taking or social platform. Scope is strictly limited to features below. Tech Stack (Preferred / Existing) Frontend: React + Tailwind CSS Backend: FastAPI Database: MongoDB OCR: High-accuracy OCR pipeline (see below) LLM: API-based (for solution generation) Payments: Razorpay Fonts: Inter / Space Grotesk (Google Fonts) Core Features (Mandatory) 1. Authentication Phone number login (OTP-based) Protected routes for logged-in users 2. Test Upload Upload question paper PDF (scanned or digital) Optional answer key upload (...

...lead routing Core Objective Enable consumers to compare GMC vehicles (starting with 2026 GMC Canyon) across regional dealers, rank offers by “best deal,” and route high-intent buyer actions exclusively to Kevin Grover GMC. –––––––––– A. SYSTEM ARCHITECTURE –––––––––– Frontend Web app (React or ) Mobile-first design Search, filters, results grid, vehicle detail pages, lead form Backend API (FastAPI or Node.js) Authentication (admin + dealer dashboard) Lead processing + scoring service Dealer registry service Database PostgreSQL Tables: Dealers Listings Leads Lead status / follow-up Pricing snapshots Search Engine OpenSearch or Elasticsearch for fast f...

...qualifies, presents offer, sends summary + LOI AI schedules human follow-up Human finalizes contract CRM updated automatically Compliance & Safety Human makes initial outbound call AI only engages after warm transfer Consent tracking for SMS/email Opt-out handling No legal advice No fabrication of financial facts Full audit trail Tech Stack (Flexible, but preferred experience) Backend: Python (FastAPI) or Node.js Database: PostgreSQL Queue/workflows: Celery / Temporal / BullMQ Voice: ElevenLabs Telephony: Twilio / SIP / Retell LLMs: OpenAI / Anthropic (tool-calling) CRM APIs E-signature APIs Webhooks & event-driven design Who We’re Looking For This is not an entry-level project. We want: Senior full-stack engineers AI/agent architects Voice AI specialists Small, ...

...users expect immediacy, so both the iOS and Android builds must show: • Real-time data updates pulled directly from the API (WebSockets or Server-Sent Events welcome). • Interactive charts that visualise price movement clearly on small screens. • Push notifications tied into the alert engine described above. Please make the stack explicit in your proposal: the Python framework you prefer (FastAPI, Django Rest Framework, or similar), the charting library you have in mind for the apps, and how you would deploy the solution end-to-end so it scales cleanly under load. I am open to AWS, GCP, or another cloud as long as the path to production is realistic and well documented. Acceptance will hinge on: 1. A Git repo with backend code, Dockerfile, and instruc...

...applicants and update application status. • Message candidates securely. C. Platform Admin • View, suspend, or delete user accounts. • Moderate content and handle reports. • Access secure audit logs. 4 Programming Languages and Frameworks • Operating System: Ubuntu (provided VM) • Database: PostgreSQL (recommended) or MySQL / MongoDB with justification • Web Server: Nginx • Backend: Python (FastAPI/Django), Node.js (Express/Nest), or Java (Spring Boot) • Frontend: React, Vue, or server-rendered pages 5 Milestones and Timeline (January–April) February Milestone 1 [No Credit] (February 13) • Finalize technology stack. • Configure HTTPS with self-signed or CA-issued certificates. • Deploy a skeleton ap...

...applicants and update application status. • Message candidates securely. C. Platform Admin • View, suspend, or delete user accounts. • Moderate content and handle reports. • Access secure audit logs. 4 Programming Languages and Frameworks • Operating System: Ubuntu (provided VM) • Database: PostgreSQL (recommended) or MySQL / MongoDB with justification • Web Server: Nginx • Backend: Python (FastAPI/Django), Node.js (Express/Nest), or Java (Spring Boot) • Frontend: React, Vue, or server-rendered pages 5 Milestones and Timeline (January–April) February Milestone 1 [No Credit] (February 13) • Finalize technology stack. • Configure HTTPS with self-signed or CA-issued certificates. • Deploy a skeleton ap...

...applicants and update application status. • Message candidates securely. C. Platform Admin • View, suspend, or delete user accounts. • Moderate content and handle reports. • Access secure audit logs. 4 Programming Languages and Frameworks • Operating System: Ubuntu (provided VM) • Database: PostgreSQL (recommended) or MySQL / MongoDB with justification • Web Server: Nginx • Backend: Python (FastAPI/Django), Node.js (Express/Nest), or Java (Spring Boot) • Frontend: React, Vue, or server-rendered pages 5 Milestones and Timeline (January–April) February Milestone 1 [No Credit] (February 13) • Finalize technology stack. • Configure HTTPS with self-signed or CA-issued certificates. • Deploy a skeleton ap...

...Perks, Discounts, rates, admin approval & Ranking) * Our Field Staff participate in the same app one app (Accompanying with patients ) all in one app (IOS and Android ) with task checklists (pickup, hospital visits, discharge, Tours , check in and Check out of hotels , lodges , travelling by cars arrangements etc.) Tech Stack (preferred) * Frontend: React (Web), React Native (Mobile) * Backend: FastAPI (Python) or NestJS (Node.js) * Database: PostgreSQL + Redis * Infra: AWS/Azure/GCP, Dockerized, CI/CD ready * Security: HIPAA-grade, Indian IT Act compliance, encrypted storage, audit logs ( Capture Time stamp,DD/MM/YY with time , Who has modified,or changed) Delivery Expectations * Cloud-native monolithic basic MVP (future-ready for microservices on iteration ) * Documentat...

Build, connect, and run AI-powered apps instantly using Streamlit and FastAPI — a lightweight accelerator for creating AI apps with minimal setup AI App Builder - Agentic Pipeline Architecture Overview This project uses an agentic (LangGraph-inspired) architecture to generate modular applications from user queries. The core pipeline consists of specialized agents for planning, editing, verifying, and assembling code for frontend, backend, and logic modules. the app looks good but i want some modifications basically i want that when user enters it requirements then it will give Refined Requirements: App Requirements Summary App Overview Core Features Technologies User Interface Data Requirements Assumptions like this which we can edit according to our need or if we are ok with ...

...an existing Business account. Reliability comes first; every outbound message needs an acknowledgement callback and every inbound message should be captured in a local SQLite or PostgreSQL table for later reporting. Scope highlights • Clean Python 3.x code that wraps the official WhatsApp Business Cloud API (or another compliant gateway if you can justify it) • Simple CLI or minimal Flask/FastAPI endpoint to trigger messages with parameters: recipient, template/body, media (optional) • Webhook listener that records incoming messages, delivery receipts, and errors to the database and writes them to a rotating log • Easy-to-edit config file for credentials and rate-limit settings • , deployment script, and a concise README so I can reproduce the ...

...Results have to work equally well in Hungarian and English; huspacy, spaCy, and Open AI are the preferred tools for language handling and any fallback generation. I expect the codebase in Python 3.10+, organised as two deployable units: • ETL package that connects to the existing tables, performs the vector and category enrichment, and writes into PostgreSQL/pgvector with idempotent reruns. • FastAPI microservice offering endpoints for single-query search and batch queries, with Docker files and a short README explaining environment variables and health checks. Acceptance will be based on end-to-end tests: I run the ETL, hit /search with a Hungarian and an English query, and receive ranked results that include both BM25 and vector hits blended by RRF. Detaled RFQ ...

...(S3-like) with folders Time tracking per task Dependencies (Task A blocks Task B) Gantt view Public share links (view-only) Google Calendar integration Mobile apps (later) Platform + Tech Preferences I’m open to your recommendation, but I want a stack that’s maintainable and scalable. Preferred options: Frontend: React () or equivalent modern framework Backend: Node.js (Nest/Express) or Python (FastAPI) DB: Postgres Real-time: WebSockets (or Firebase-style real-time) Auth: JWT/session-based Hosting: Vercel + Render/Fly/AWS (or your suggestion) If you propose a different stack, include reasons....

...pipelines that analyze recorded conversations (speech → text → structured insights) LLM-based systems for summarization, classification, objection detection, and recommendations RAG pipelines with embeddings, vector search, reranking, and evaluation Scalable FastAPI microservices for AI inference Cost-efficient and low-latency LLM workflows Production-ready systems with monitoring, evals, and performance optimization -Required Experience We are only looking for candidates with real production AI experience, including: Python + FastAPI LLM APIs (OpenAI / Claude / Gemini) RAG pipelines (embeddings, vector DBs, retrieval optimization) Experience shipping AI systems to production Handling hallucinations, evaluation frameworks, and cost optimization Designing scalabl...

...internal use Structured data extraction from technical documents API integrations between AI services and internal tools Deployment of production-ready AI workflows This is not a research role. You will build tools people actually use daily. Core Responsibilities Architect AI workflows using LLMs Design structured prompt systems (reliable outputs, not chat toys) Build backend services (FastAPI / Python preferred) Create data pipelines between AI and business systems Integrate APIs, webhooks, and automation platforms Develop internal AI tools for operational teams Ensure system reliability, version control, and maintainability Required Skills Experience building production LLM applications Strong Python backend development API integration experience (REST, webhooks...

...receives tidy, predictable JSON keys and values. • Basic but rock-solid validation: file type, size, and any other quick checks you normally wire in to keep the service safe. • Sensible error handling—clear status codes and helpful messages. • Simple user authentication so only authorised callers can hit the upload endpoint (token-based is fine). Tech stack is flexible between Python/FastAPI and Node.js/Express; FastAPI is my default choice because of its built-in docs and async flow, but feel free to pitch Express if that’s your home turf. Deliverable: a small repo I can run with Docker-Compose or a straightforward README, plus any environment variables I’ll need for Gemini credentials. A tiny test script or Postman/Insomnia collection s...

I’m building a full-stack trading suite that talks directly to th...the chosen data-vendor API. • Strategy builder with parameter persistence, live trade monitoring, and one-click deploy to real or paper accounts. • Back-testing module using the external historical feed, complete with equity curve and trade log export. • Read-me or short video walkthrough so I can install, connect credentials, and start trading. Compiled in any modern language—Python with FastAPI & PyQt, C# with .NET, or another stack you’re comfortable owning—as long as response times meet exchange standards. Once delivered I’ll run a demo on my machine against the supplier’s sandbox and execute a small live order through Kotak; if everything lines up...

Lead AI / Fullstack Engineer — Project "AZIZA" (Voice-to-Voice AI) ​Project Name: AZIZA Format: Project-based / Remote (with access to local GPU clusters) Tech Stack: PersonaPlex (Moshi-based architecture), PyTorch, TensorRT-LLM, FastAPI, WebRTC, Telegram Mini App (TMA). Hardware Location: Uzbekistan & Kazakhstan (TAS-IX), clusters powered by NVIDIA RTX 4090. ​Project Overview ​AZIZA is an innovative multimodal "Speech-to-Speech" (S2S) ecosystem designed to simulate natural human interaction. We are building an AI assistant that seamlessly transitions between roles: an expert tutor (Chemistry, History, Biology), an empathetic companion, and a simultaneous translator. By processing audio tokens directly, the system achieves unprecedented interaction spee...

...& Premium Layer (Cloud) Goal: Add premium and enterprise-grade features on top of SuperAI. Features • Multi-document comparison • Teacher / Trainer mode • Brand tone memory • Basic browser extension • Cost optimization & scaling logic Deliverable: Cloud-based premium layer integrated into SuperAI. Preferred Tech Stack Frontend • React / • Desktop wrapper: Tauri or Electron Backend • FastAPI or Node.js • REST APIs • Authentication & token services AI / ML • DeepSeek / Qwen / LLaMA (local) • SDXL (image) • Whisper (speech-to-text) • FAISS / Chroma (RAG) • Groq / DeepSeek API (optional cloud) Infrastructure • Hybrid deployment • Lightweight cloud backend • Local compute for heavy...

...docs, Excel files Creating a vector database and metadata store Implementing a RAG-based chatbot that: Only answers when evidence is found Displays citations (document name, excerpt, date, author) Shows confidence level and “as-of” timestamp Developing a simple web UI (FastAPI/Django + React or similar) Using open-source/local LLMs (Ollama, vLLM, etc.) Enforcing security and role-based access (basic level) Preferred Tech Stack (Flexible) Python LangChain or LlamaIndex FAISS or Qdrant PostgreSQL / SQLite FastAPI or Django Local LLMs (Mistral, Llama, etc.) React / simple frontend Deliverables Working chatbot web application Ingestion pipeline scripts Vector search + citation system Documentation for setup and deployment Sample queries and te...

...owner (business + regulatory background). Required Skills Strong Python (production-level) Hands-on experience with LLMs: OpenAI / Azure OpenAI and/or local models (LLaMA, Mistral) RAG architectures: embeddings, chunking strategies, retrieval tuning vector databases (FAISS, Qdrant, Weaviate, Pinecone) Document processing: PDFs, OCR, regulatory texts Prompt engineering + response evaluation FastAPI (or similar) Git, Docker Nice to Have Experience with regulatory, legal, pharma, compliance, or financial documents AI Agents / workflow orchestration Private / on-prem AI setups Hallucination mitigation strategies Monitoring & evaluation of LLM outputs What We Value Most System thinking over hype Ability to explain why an answer is generated Awareness of LLM limitations and...

...through a FastAPI micro-service and wrapped in a multi-agent pipeline (retriever + analyst). Everything ships in Docker, rolls out under Kubernetes via Helm, and already includes a basic monitoring and evaluation loop. Right now the bottleneck is accuracy—specifically the relevance of each answer. I have a fresh batch of curated domain data ready for ingestion, and I’d like that folded into the workflow along with any architecture or hyper-parameter tweaks that further sharpen responses. Key focus areas for today (hard deadline: 7 pm): • Integrate the new dataset, run a quick SFT/LoRA refresh, and redeploy the updated weights to the private Hugging Face repository. • Tune retrieval strategy and analyst prompts so returned answers stay laser-focused on c...

... and on that box, wired up so I can hit them with a simple curl command and get back translated text. Your job is to: • set up the environment (you can advise the best-fit Python 3.x version), • install all dependencies and download the required models for the two libraries, • expose a lightweight REST endpoint (Flask, FastAPI, or similar) that accepts source text, source language and target language, returns the translated string in JSON, and works via curl out of the box, • give me start/stop scripts or a single Dockerfile/compose file so I can recreate the service quickly, • hand over a short README detailing the install steps and an example curl call. The server is Linux, so please assume systemd or docker-compose

...data into a coherent analysis, along with the probability engine that outputs the forecast bars. • Month 3 – Polished, responsive front-end (React/Next or similar), role-based user accounts, CI/CD, automated tests, Dockerised deployment to my AWS account, and hand-over of clean, well-documented code. Technology choices are flexible as long as they suit production (Python-based back-end like FastAPI/Django or a Node alternative, OpenCV or equivalent for vision, and any LLM you’re comfortable orchestrating). Explain your preferred stack, prior CV/LLM examples, and how you’d structure the micro-services so we can agree on scope quickly. Every milestone is payable on working, tested deliverables pushed to a private Git repo and demonstrated on the staging ...

I need a reliable developer who can deliver clean, maintainable code while building out the first version of my backend. The stack is flexible between Node.js (Express, Nest, or similar) and Python (FastAPI, Django REST), but the end result must expose well-structured RESTful APIs tied to a MySQL database. Scope • Design the schema in MySQL and connect it seamlessly to the chosen framework. • Build versioned REST endpoints that follow best practices for naming, status codes, and error handling. • Implement basic security from day one: JWT-based authentication and at-rest / in-transit data encryption. Rate limiting is not required yet, but the architecture should allow us to bolt it on later without refactor pain. • Write concise tests and inline document...

...to a consistent avatar identity. • Morphing: Specific zones (Chest, Shoulders, Arms, Waist, Hips, Thighs) adjust to show scenarios like lean vs. aggressive bulking. • Personalized Videos: Applies the user’s avatar to master animations to render 5–10 second loops, making it appear as if the user is performing the exerc 9. Technical Stack (further described in project TRD) • Backend: Python + FastAPI, PostgreSQL (measurement history). • 3D/Animation: parametric meshes, and GPU-based batch rendering. 4 10. Tasks for each Resource To ensure the development of the AI-Based Personalized 3D Training & Body Forecasting 10. Tasks for each Resource To ensure the development of the AI-Based Personalized 3D Training & Body Forecasting Platform adhe...

...Smooth UX (loading states, transitions, error handling) Preferred stack (flexible): React / (preferred) 2. Backend & APIs: Backend to handle: AI requests (LLM integration), Flight search & pricing APIs (Amadeus or similar) User sessions & preferences Secure API handling (no exposed keys on frontend) Scalable architecture (MVP → future growth) Preferred stack (flexible): Python (FastAPI) or Node.js REST APIs PostgreSQL or equivalent 3. AI Integration (Phase 1) Integrate AI to: Understand user travel queries Convert natural language into structured search requests Return recommendations in a conversational format No need for complex training initially — smart orchestration is enough Must be extensible for future improvements 4. Core Fea...

Build, connect, and run AI-powered apps instantly using Streamlit and FastAPI — a lightweight accelerator for creating AI apps with minimal setup AI App Builder - Agentic Pipeline Architecture Overview This project uses an agentic (LangGraph-inspired) architecture to generate modular applications from user queries. The core pipeline consists of specialized agents for planning, editing, verifying, and assembling code for frontend, backend, and logic modules. the app looks good but i want some modifications basically i want that when user enters it requirements then it will give Refined Requirements: App Requirements Summary App Overview Core Features Technologies User Interface Data Requirements Assumptions like this which we can edit according to our need or if we are ok...

Build, connect, and run AI-powered apps instantly using Streamlit and FastAPI — a lightweight accelerator for creating AI apps with minimal setup AI App Builder - Agentic Pipeline Architecture Overview This project uses an agentic (LangGraph-inspired) architecture to generate modular applications from user queries. The core pipeline consists of specialized agents for planning, editing, verifying, and assembling code for frontend, backend, and logic modules. the app looks good but i want some modifications basically i want that when user enters it requirements then it will give Refined Requirements: App Requirements Summary App Overview Core Features Technologies User Interface Data Requirements Assumptions like this which we can edit according to our need or if we are ok...

Our FastAPI code-base already covers the fundamentals—Firebase auth, user profiles, base service model, a configurable feature-toggle system, Swagger docs, and even an abstract payment-provider interface. What it now needs is a seasoned Python engineer to flesh out the rest of the server features while preserving the clean-architecture approach we started with. Primary goals • Integrate Stripe first, then wire up Razorpay and Adyen on the same abstraction layer. I’m also open to your recommendations for any additional providers that make sense for a global employee platform. • Harden security: role-based access, rate limiting, sensitive-data encryption at rest, plus thorough test coverage to stop regressions before they ship. • Keep everything modul...

I’m putting together an end-to-end agentic AI system that will take a repetitive text-based workflow off my plate and run it automatically. The core of the build will combine an LLM with Retrieval-Augmented Generation, orchestrated through LangGraph and exposed through a FastAPI service that talks to a persistent database. My main objective is simple: automate a very specific task that currently consumes manual effort, using only text data as both input and output. Here’s what I already have in mind: • FastAPI should serve as the public interface, handling requests and routing them through the agent pipeline. • LangGraph (or comparable MCP-style orchestration) will manage the multi-step reasoning and tool usage required by the agent. • The RAG ...