Llama 2Jobs
...support and training to our internal team for managing and further training the system. - Document the entire architecture and implementation processes. Essential Technical Requirements: - Familiarity with Windows Server environment and managing hardware resources for AI. - Deep understanding of Large Language Models (LLMs) and their architectures. - Proven experience with open-source LLMs (e.g., Llama, Falcon, Mistral, etc.). - Hands-on experience in installing and configuring on-premise LLMs on Windows servers. - Familiarity with fine-tuning techniques, RAG (Retrieval Augmented Generation), and continuous learning. Desirable Requirements: - Previous experience in AI projects within the financial sector. ----- Would you like to bid on this project? ----- To best evaluate you...
...prototypes into production-ready systems, then keep scaling them until they can handle real-world, mission-critical workloads. Here’s what the role looks like day to day: • Architect and code large-scale agentic functions, swarms and orchestration layers that can reason, plan and act with minimal human guidance. • Integrate and benchmark state-of-the-art language models (OpenAI, Anthropic, Llama 2/3, etc.) alongside tools like LangChain, CrewAI, Semantic Kernel or your own preferred framework. • Optimise memory, context and tool-calling pipelines; deploy to cloud (AWS/GCP/Azure) with containerisation and CI/CD. • Rapidly iterate—our team works long, focused hours on bleeding-edge ideas, so you’ll ship, measure, and refine in ti...
I want to build an AI agent that can pose the same research question to at least five different large-language-model APIs (e.g. GPT-4, Claude, Cohere, Palm, Llama-2 via Hugging Face) and capture every answer in real time inside a single Google Sheet. The workflow should look like this: 1. I type or paste a prompt once. 2. The agent forwards that prompt concurrently to each chosen LLM. 3. As soon as each model replies, the agent writes a new row to my Google Sheet with these columns: timestamp, prompt, model name, full response, and any cost/latency data you can easily expose. 4. When all models have answered, the sheet shows a complete, side-by-side record that I can analyse for research purposes. Language and stack are flexible; pick whatever lets you move fas...
My small creative production studio needs a local, fully private AI stack that will sit on a 16 GB Mac Mini and behave like an operations assistant. I have already chosen the ai-stack-homelab project as the base; it ships with Dockerised n8n, Ollama (running Llama 3.2-class models), Open WebUI, PostgreSQL + pgvector, LiteLLM proxy and MCP integration. Your job is to install, configure and fine-tune that stack so it automates day-to-day admin without ever touching the public cloud. Immediate focus • Highest-priority workflow: detect inbound enquiries arriving via email, run them through the local LLM, then log each enquiry as a structured page inside my Notion space. No automatic replies for now—just clean, reliable capture so I can review and follow up manually. &bul...
...cross-referenced with real, clickable citations from the integrated databases. Real-time Streaming: Polish the WebSocket stream so that research synthesis appears live in the frontend panels. Biomedical Reflection: Refine the "Reflection Agent" (currently using a fine-tuned biomedical Llama model) to perform a secondary quality check on the literature review output. Technical Stack: Backend: Deno v2 (TypeScript), WebSockets. Frontend: React, Vite, Tailwind CSS, Framer Motion. AI Logic: LangGraph, LangChain. Models: Groq (Llama 3.3 70B Orchestrator) & Local Ollama (Biomedical fine-tuned SLM). What’s Already Done: ✅ Stable Multi-agent state graph and orchestration logic. ✅ Professional, responsive dashboard with glassmorphism effects. ✅ Backend/Frontend c...
...with reliable OCR so information buried in images feeds directly into at least one generated question. The tone and vocabulary need to suit secondary-school students, keeping accuracy on scientific terminology while staying readable. Behind the scenes, I expect a clean workflow: PDF parsing, OCR for images, semantic parsing, and question generation through a large-language-model layer (GPT-4, Llama 2, or an equivalent locally hosted model), followed by quality checks that filter hallucinations and enforce a grade-appropriate readability score. Output should come back in a structured format such as JSON or CSV so I can drop it straight into my LMS. Acceptance criteria • Handles a 20-page, mixed-media medicine PDF with at least 90 % extraction accuracy • Gener...
Backend for a my app using FastAPI, WebSockets/WebRTC, and modern AI services (Whisper STT, LLaMA-style LLMs, Kokoro/Coqui/Piper TTS, Wav2Lip for avatar video). The system powers realtime speech transcription, AI-assisted text polishing, and interactive avatar-based conversations. Responsibilities Backend ownership: Design, maintain, and extend FastAPI HTTP + WebSocket/WebRTC endpoints. AI integration: Connect and optimize Whisper STT, LLMs, and TTS services for low latency and high reliability. Audio/video pipelines: Handle streaming audio (buffering, resampling, normalization). Integrate avatar video generation with Wav2Lip and related tools. Data & performance Work with MongoDB (and/or relational databases) for schemas, indexing, and efficient queries. Implement caching an...
1. Project Objective To build a high-performance mobile application capable of seamless speech-to-speech and text translation without an internet connection. 2. Technical Stack AI Models: * Translation (NMT/LLM): Quantized (4-bit/8-bit) SLMs, specifically Gemma 2 2B, Llama 3.2 (1B/3B), or Phi-3.5 Mini. Speech-to-Text (STT): Offline Whisper models (Tiny or Base variants). Text-to-Speech (TTS): Integration of system libraries (Google TTS for Android / AVFoundation for iOS). Deployment Frameworks: * Inference Engines: Google MediaPipe LLM Inference API, TensorFlow Lite, or ONNX Runtime. Hardware Acceleration: Mandatory optimization for NPU and GPU (Apple A-series, Snapdragon, and Dimensity) to ensure energy efficiency. Development Platforms: Native development (Swi...
1. Project Objective To build a high-performance mobile application capable of seamless speech-to-speech and text translation without an internet connection. 2. Technical Stack AI Models: * Translation (NMT/LLM): Quantized (4-bit/8-bit) SLMs, specifically Gemma 2 2B, Llama 3.2 (1B/3B), or Phi-3.5 Mini. Speech-to-Text (STT): Offline Whisper models (Tiny or Base variants). Text-to-Speech (TTS): Integration of system libraries (Google TTS for Android / AVFoundation for iOS). Deployment Frameworks: * Inference Engines: Google MediaPipe LLM Inference API, TensorFlow Lite, or ONNX Runtime. Hardware Acceleration: Mandatory optimization for NPU and GPU (Apple A-series, Snapdragon, and Dimensity) to ensure energy efficiency. Development Platforms: Native development (Swi...
...social media, and print. 2. Reference Image Attached file: havokhair draft The logo features: A black llama silhouette with a wild, spiky mane Bold slab-serif text: "HAVOK" Tagline text below: "UNLEASH YOUR STYLE" Currently on a cream/off-white background (needs transparent background) 3. Logo Polish Scope 3.1 Lion Graphic Keep 99% as-is. We like the llama. Do NOT redesign it. Clean any obvious rough edges, stray artifacts, or infill gaps from the auto-trace Ensure paths are clean with no stray points or overlapping shapes Compound paths correctly defined 3.2 "HAVOK" Text The current text is traced pixel shapes, not real font outlines — it needs replacing Replace with a proper font that matches the current bold slab-serif feel...
...marketing la idea es este . toda la familia unida platicando y después de un rato tocan el tema que comeran el dia de mañana y elijen un caldo de pollo , y se preguntan en donde se compraria el pollo crudo y uno dice que conoce una pollería que les puede traer el pollo y es recién sacrificado, fresco y tienen envio a domicilio gratuito, y uno de sus familiares le pregunta como se llama el negocio y le responde se llama polleria express . se ponen de acuerdo y le envian mensaje al whatsapp de la polleria y piden un pollo fresco , del mayor kg que alla le dicen que en 30m ya esta el pollo llegando a su domicilio , llega el pedido lo preparan y de último toda la familia toman asiento en una mesa circular se sirven y empiezan a comer y de &...
...persuasive witness statements. - Diarizing litigation deadlines for effective case management. The model should be API-ready so clients can easily integrate it into their existing CRM or financial platforms. Building on strong open-source foundation models (e.g., Llama-2, GPT-J, Falcon) with fine-tuning, reinforcement learning, or retrieval-augmented techniques is encouraged for legal accuracy and citation fidelity. Because the advice produced carries legal weight, I will require: 1. Transparent data-sourcing and cleaning methodology 2. A validation suite that stress-tests the model against realistic debt-recovery scenarios while ensuring statutory compliance and low hallucination rates 3. Explainable outputs (chain-of-thought hiding toggled off by default bu...
Hola, ¿cómo estás? Estoy interesado en que me diseñes un portafolio profesional de precios para mi estudio, similar en estructura al estilo tipo catálogo / revista visual (te adjunto referencia). Mi estudio se llama: DATA CREATIVE Fotografía & Podcast Studio Independencia No. 505, Condominio Santurce, Local 101-C Distrito Nacional Es un estudio con local físico dedicado a fotografía profesional y producción de podcast. PORTAFOLIO QUE NECESITO Quiero un diseño moderno, elegante y profesional, no recargado, con identidad visual sólida. Estructura aproximada (12–15 páginas): 1️⃣ Portada impactante 2️⃣ Mensaje de bienvenida 3️⃣ Detalles importantes (reserva, entrega, políticas)...
...Implement Faster-Whisper (Large-v3-Turbo) on a GPU-accelerated environment (RunPod/AWS/Lambda Labs). Contextual Accuracy: Use Initial Prompting techniques to ensure high accuracy for specific restaurant menus (dishes, modifiers, doneness levels). Real-time Processing: Experience with WebSockets for streaming audio and achieving <1s end-to-end latency. Parsing: Integrate an LLM (GPT-4o-mini or local Llama-3) to convert raw transcribed text into structured JSON. Infrastructure: Knowledge of Serverless GPUs or Dockerized GPU deployments to ensure scalability for 100+ concurrent restaurants. Specific Challenges: The system must be optimized for "Arabic-Hebrew" hybrid speech (Local dialect). Experience with VAD (Voice Activity Detection) like Silero is a plus to hand...
...un backend en PHP/Laravel en que gestione la mensajería de WhatsApp usando WhatsApp Cloud API de Meta (Graph API), para que usuarios registrados puedan hacer Check-in / Check-out con botones, y que el sistema llame al backend correspondiente de cada empresa (). Importante: no se usará Twilio ni pasarelas/BSP. Integración directa con WhatsApp Cloud API. 2) Concepto general El usuario escribe cualquier mensaje por WhatsApp (“hola”, “fichar”, etc.). El backend identifica al usuario por su número de teléfono (E.164). Cada usuario tiene configurado manualmente un api_base_url (ej. ) porque cada empresa tiene su propio backend. El backend consulta a esa API el último registro del usuario (IN/OUT). Según el...
...Renacer Centro Transforma Estoy buscando una landing page de alta conversión para un programa online en vivo orientado a personas que atraviesan un proceso de duelo por fallecimiento. El objetivo no es solo que se vea “bonita”, sino que: • Transmita profesionalismo y estructura • Genere confianza inmediata • Instale la idea de método claro • Convierta visitantes en inscripciones El programa se llama: Programa de Duelo – Método Renacer Proceso guiado en cinco etapas. ⸻ DIRECCIÓN GENERAL La página debe equilibrar: Institucional + Humano. No quiero: • Estética de coaching motivacional genérico • Exceso de minimalismo frío • Dramatismo emocional • Imáge...
...Responsibilities Manage complex technical projects from conception to delivery Utilize advanced AI tools to improve processes and solutions Coordinate and manage remote teams Contribute to digital marketing strategies and process optimization using AI Make strategic decisions and solve complex problems efficiently Required Skills & Experience Proficiency in cutting-edge AI tools: GPT‑4, Gemini, Claude, LLaMA, Midjourney Proven experience in technical project management and remote team coordination Ability to work autonomously and manage multiple projects simultaneously Experience in digital marketing and AI-driven process optimization (a plus) Excellent communication, organizational, and time management skills Fluent English, both written and spoken Conditions R...
I am looking for an experienced AI/ML developer to build a ChatGPT-like chatbot without using OpenAI or any external API. Requirements: Use an open-source LLM (such as LLaMA, Mistral, or similar). The model must be hosted on my own server (VPS or dedicated server). Web-based interface (chat UI). Ability to fine-tune or train on custom data (optional but preferred). Secure and optimized performance. Technical expectations: Python (FastAPI / Flask) or Node.js backend. Experience with Hugging Face / Transformers. Knowledge of GPU deployment (preferred). Please include: Previous AI/LLM projects. Recommended model and hardware requirements. Estimated server specs (RAM, GPU)
...download an open-weight GPT-like model that can reasonably run on local hardware (e.g., Llama-2, Mistral, or another suitable alternative). • Set up the execution environment—Python, CUDA, PyTorch or TensorFlow—plus any supporting libraries (LangChain, FastAPI, uvicorn, etc.). • Create or refine an inference script that keeps response times low enough for smooth chat. • Build a lightweight API (REST or WebSocket) so the website can pass the user’s prompt and receive the model’s reply. • Hand me clear, repeatable launch instructions (ideally Docker-based) so I can restart or migrate the service without hassle. Acceptance criteria 1. Model loads and answers a sample prompt locally with no external calls. 2. My w...
...IA avanzado con las siguientes capacidades: * Memoria a largo plazo (RAG): La IA debe ser capaz de recordar y basar sus respuestas en documentos internos de la empresa. * Agentes Autónomos: Desarrollo de agentes capaces de ejecutar tareas de manera independiente. * Flexibilidad Multi-LLM: La arquitectura debe permitir cambiar fácilmente entre diferentes modelos de lenguaje (GPT-4, Claude, Llama 3, etc.) según las necesidades. Las responsabilidades clave incluyen: Consultoría Estratégica: * Asesoramiento experto sobre la elección de modelos de IA (Open Source vs. Propietarios) para asegurar la máxima privacidad de los datos corporativos. Desarrollo Técnico (Hands-on): * Diseño e implementación de...
...1) Real-Time Data Fetching & Aggregation Pull BTC/USD prices from 10–15+ reliable sources every 3–5 seconds via APIs/WebSockets Sources to include (at minimum): CEX: Binance, Coinbase, Kraken, Bybit, OKX Oracles: Pyth Network, CoinGecko (free tier), Chainlink feeds if accessible DEX/Aggregators: Uniswap (via DexScreener or subgraph), DeFi Llama API Bridge/Wrapped Tokens: WBTC (Ethereum), cbBTC (Base), BTC.b (Avalanche), tBTC, etc. — fetch via DeFi Llama or direct contract reads if possible Price Deviation & Latency Scanner Calculate percentage spreads/deviations between every pair of sources Measure and display API response latency for each source Highlight anomalies (e.g., >0.5% spread, high latency spikes) Pairwise comparison matrix/table ...
...(e.g., a laptop, Raspberry Pi, or a high-end tablet) without needing an internet connection. * Custom Knowledge Base (RAG): I will provide a large volume of PDFs, textbooks, and curriculum documents. The developer must implement a Retrieval-Augmented Generation (RAG) system to ensure the AI answers strictly based on this material. * Local LLM Integration: Use efficient open-source models (like Llama 3, Mistral, or Gemma) that are optimized for local use (quantized versions). * User Interface: A simple, student-friendly interface (Web-based local UI or Desktop App) where students can type questions and get instant feedback. * Scalability: The ability to easily add or update the curriculum folders. Technical Preferences (Suggested) * Backend: Python (LangChain or LlamaIndex) ...
...operating in real time before we move forward. The core requirements are straightforward: the agent needs to run in a browser, accept its own knowledge base or document set for context, and ship with source code plus clear documentation. I’m also expecting help getting the code stood up in a SaaS or on-prem environment. I’m flexible on architecture; whether you built it around OpenAI, Claude, Llama, FastAPI, Node.js, Pinecone, FAISS, or Weaviate doesn’t matter as long as it performs reliably at scale. To keep things simple, here’s exactly what I need to review: • A public demo link I can test myself • The industry your agent targets • Short outline of the tech stack • Your price per agent and estimated hand-over timeline If ...
...operating in real time before we move forward. The core requirements are straightforward: the agent needs to run in a browser, accept its own knowledge base or document set for context, and ship with source code plus clear documentation. I’m also expecting help getting the code stood up in a SaaS or on-prem environment. I’m flexible on architecture; whether you built it around OpenAI, Claude, Llama, FastAPI, Node.js, Pinecone, FAISS, or Weaviate doesn’t matter as long as it performs reliably at scale. To keep things simple, here’s exactly what I need to review: • A public demo link I can test myself • The industry your agent targets • Short outline of the tech stack • Your price per agent and estimated hand-over timeline If ...
...instead of simply giving solutions. Safety is critical, so I need content filters, refusal handling, and basic session logging that lets us audit conversations without storing any personal data. I’m open to whichever stack you prefer—Python (FastAPI), Node.js, or a no-code backend—as long as it can interface smoothly with an LLM such as OpenAI GPT-4, Claude, or an open-source alternative (e.g. Llama-2 via LangChain). The current site runs on React, so the front-end widget should drop in with minimal rewiring and respect our existing SSO token to identify the parent account. Deliverables • Conversational AI model pipeline with prompt-engineering layer tuned for K-12 homework support • React embeddable chat widget styled to our design system...
...failing test or stack trace • In-line code review and optimisation feedback before pull-requests are merged Language & tooling The model must reason confidently in Python, JavaScript and Java, because those are the three stacks our teams use daily. You are free to orchestrate it with LangChain, OpenAI, Llama-index, or similar frameworks—whatever lets the prompts stay dynamic and the responses actionable. Desired flow 1. User enters a natural-language request in our IDE or chat UI. 2. Agent classifies the intent (generate, fix, or review). 3. It builds a structured prompt that injects file context, coding standards, and test output. 4. The large-language model produces a response. 5. Agent optionally writes changes to a feature branch or returns...
...creando una infraestructura de inteligencia industrial sostenible a largo plazo. 2. LA SOLUCIÓN: "THE KNOWLEDGE LOOP" Buscamos una plataforma que gestione un ciclo de aprendizaje activo y evolutivo: Consulta Multimodal: El operario consulta vía texto, audio (notas de voz), foto o vídeo corto de la incidencia. RAG Híbrido: El sistema busca en la base de conocimiento interna (manuales, vídeos previos, histórico técnico). Si no hay respuesta, actúa como un Agente de Búsqueda en internet (manuales estándar, foros técnicos), con aislamiento de red y validación de fuentes, traduciendo la información al español. Escalado Humano: Si la IA no conoce la solución, notifica...
..."Ghoul Gives Good Gold" (Halloween) "Stars Stripes & Spot Price" (July 4) "Love at First Offer" (Valentine) Family "Pawn Dad Fuel." "Pawn Mom Club." "Couples Who Pawn Together Stay Together." "Family Business Since Day One." "Next-Gen Pawn Pet Pet Designs: "Paw Shop - Cats Welcome." "Gold Retriever." "Otterly Good Deals." "No Drama Llama Loans." Movie "Wolf of Pawn Street." (wolf of walstreet) Deal Wars – lightsabers (starwars) 2 fast 2 funded– (2 fast 2 furious) Lord of the Rings… and Chains (as in jewelry) (lord of the rings) Game of Loans – (Game of throans) Avengers of Value – (avengers)...
...the medical field. The focus is article-style generation rather than casual chatbot replies or short-form posts, so coherence, correct structure (abstract, introduction, methods, results, discussion, references), and domain-appropriate terminology matter more to me than conversational flair. You’re free to choose the underlying architecture—transformer-based models such as GPT-like variants, T5, Llama, or your own hybrid approach—so long as the final pipeline consistently produces high-quality drafts that read like genuine medical research. I will supply example papers and any additional datasets you ask for; you handle data preparation, fine-tuning, and the evaluation strategy to verify that outputs remain factual, logically organised, and plagiarism-free. De...
...the medical field. The focus is article-style generation rather than casual chatbot replies or short-form posts, so coherence, correct structure (abstract, introduction, methods, results, discussion, references), and domain-appropriate terminology matter more to me than conversational flair. You’re free to choose the underlying architecture—transformer-based models such as GPT-like variants, T5, Llama, or your own hybrid approach—so long as the final pipeline consistently produces high-quality drafts that read like genuine medical research. I will supply example papers and any additional datasets you ask for; you handle data preparation, fine-tuning, and the evaluation strategy to verify that outputs remain factual, logically organised, and plagiarism-free. De...
...feels at home working with large-language-model frameworks to build a text-generation program that will power customer-service chatbot replies. The goal is straightforward: feed the bot a user query and receive a clear, helpful response that sounds natural, stays on-brand, and can be deployed inside our existing support interface. Core needs • Model handling: Need to use offline LLMs, preferably llama 3/opus and gemma as long as latency and accuracy stay competitive. • Prompt/response logic: craft the prompt pipeline so it captures context (conversation history, customer metadata) and returns concise answers without hallucinating policies or numbers. • Safety & tone controls: integrate guardrails for profanity, personally identifiable information, and br...
...(e.g., a laptop, Raspberry Pi, or a high-end tablet) without needing an internet connection. * Custom Knowledge Base (RAG): I will provide a large volume of PDFs, textbooks, and curriculum documents. The developer must implement a Retrieval-Augmented Generation (RAG) system to ensure the AI answers strictly based on this material. * Local LLM Integration: Use efficient open-source models (like Llama 3, Mistral, or Gemma) that are optimized for local use (quantized versions). * User Interface: A simple, student-friendly interface (Web-based local UI or Desktop App) where students can type questions and get instant feedback. * Scalability: The ability to easily add or update the curriculum folders. Technical Preferences (Suggested) * Backend: Python (LangChain or LlamaIndex) ...
...personal reminders, and “why isn’t this code compiling?” questions should also double as a smart vault for our files. Here’s the flow I have in mind: a user logs in, asks a question, drops in a PDF or an image, and later returns on another device to pick up the threaded conversation or retrieve that file with a quick search. The assistant must therefore combine a solid NLP backbone (OpenAI, Llama-based, or another proven model), a structured storage layer for documents, images, and audio/video, and a clean cross-platform interface built with a shared codebase to minimise maintenance. Key outcomes I expect from you • A responsive web client, packaged mobile app, and lightweight desktop build that all point to the same backend • Conversat...
...locally on the user’s device, while the cloud is used only for authentication, payments, token tracking, ads, and optional AI boost. This is a serious, production grade project, planned in 4 structured sprints, with long term collaboration potential beyond Sprint 4. Core Architecture (Must Follow) SuperAI follows an INSTALL + HYBRID architecture: Local First (Primary) • LLMs: DeepSeek / Qwen / LLaMA • Image Generation: SDXL • Speech-to-Text: Whisper • RAG: FAISS / Chroma Cloud (Optional & Metered) • Groq / DeepSeek API (token-limited) • User authentication & authorization • Payments & subscriptions • Token & usage tracking • Ads on heavy operations Local AI is the default. Cloud AI is an opt in accelerator. _____...
...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 test cases Source code in GitHub repository Who Should Apply We are looking for someone who has: Built chatbot or RAG applications before Experience with document ingestion and embeddings Experience with open-source LLMs Strong Python backend skills Understanding of citation-based or enterprise AI systems Ability to work independently and propose technical solutions What to Include in Your Application (Required) Please submit: 1. Project Quote Provide: Total estimated cost (USD) Timeline (in weeks) Breakdown by phase (optional but preferred) 2...
...responsible for: designing the AI architecture implementing a robust RAG pipeline ensuring traceability, source integrity, and answer reliability supporting the transition from POC to production You will work directly with the product 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 orchestrati...
... IPFS or Arweave for storage, plus a Python or Node script that calls GPT-4 / Llama via LangChain or similar. This person must also be familiar with setting up a blockchain and wallets. Specifically using AWS to start, but flexible on learing. Deliverables • Hyperledger smart contract with ownership, transferability, and royalty logic ready for main-net deployment • Data ingestion script that uploads assets, builds metadata, and calls the contract’s mint() function • LLM integration code that analyses each asset bundle and appends the AI-generated output to the metadata • Simple demo (CLI or lightweight web page) showing the full flow from raw files to a minted, AI-enriched NFT • Create and deliver (2) sample blockchains, and (3) i...
... IPFS or Arweave for storage, plus a Python or Node script that calls GPT-4 / Llama via LangChain or similar. This person must also be familiar with setting up a blockchain and wallets. Specifically using AWS to start, but flexible on learing. Deliverables • Hyperledger smart contract with ownership, transferability, and royalty logic ready for main-net deployment • Data ingestion script that uploads assets, builds metadata, and calls the contract’s mint() function • LLM integration code that analyses each asset bundle and appends the AI-generated output to the metadata • Simple demo (CLI or lightweight web page) showing the full flow from raw files to a minted, AI-enriched NFT • Create and deliver (2) sample blockchains, and (3) i...
...chatbot, it is a complete AI suite that combines multiple intelligent modules using open source + low cost APIs. CORE FEATURES TO BUILD 1. Smart Chat (Groq + LLaMA 3) • Normal Chat • Multi-language support • Context memory • Writing assistant • Fast response (Groq API) 2. Deep Research Mode (Perplexity Style) • Live Web Search • Multi source results • Citations • Summaries Search APIs: • Brave Search API • Bing Web Search API 3. Advanced Code / Dev Mode • Frontend code (HTML, React, Flutter) • Backend code (Node.js, FastAPI) • API generation • Code debugging • Folder structure creation Coding Models: • DeepSeek Coder API • Groq Mixtral / LLama 3 4. Image Generation Mode &bull...
Necesito una aplicación móvil nativa que grabe tanto llamadas entrantes como salientes, las convierta a MP3 y almacene cada archivo dentro de la propia app para reproducirlo cuando lo desee. Debe estar disponible en Android y iOS. Quiero que la petición de permisos se gestione de forma au...el usuario sólo tenga que aceptar la solicitud del sistema y pueda empezar a grabar sin configuraciones extra. Se que en iOS la grabación es manual, no automática para cada llamada, pero si que debe quedarse el mp3 o recogerlo del propio dispositivo. Además de la función principal de grabación y reproducción, me interesa integrar: • Lista de contactos interna para identificar rápidamente quién llama. &...
Necesito un logo para un proyecto Se llama InverCar y está relacionado con la inversión en la compra de vehiculos para su posterior venta y beneficio.
...Here’s the flow I have in mind: I paste or type a prompt, select (or skip) a style, then the system automatically produces a responsive site with editable HTML/CSS/JS, generates at least one high-resolution image plus a short promotional video, and finally presents a clean preview along with download/export options. You are free to mix the models and frameworks you prefer—GPT-4, Llama, Stable Diffusion, DALL·E, Runway Gen-2, React, , Django, Node, etc.—so long as the user experience stays fast and intuitive. I will need full source-code transparency from day one. Every milestone should push to my GitHub organisation, and payment will follow those milestones. Deliverables (acceptance criteria) • Web interface that accepts a prompt and ret...
...developing the "nervous system" of our agents, ensuring they can reason through non-deterministic environments while maintaining deterministic reliability. Technical Stack Language: Python (Expert level required). Frameworks: LangGraph, CrewAI, or LangChain (Stateful orchestration experience is a must). LLMs: Deep experience with GPT-4o, Claude 3.5 Sonnet, and fine-tuning open-source models (Llama 3/Mistral). Integrations: Shopify API, Stripe API, AWS Lambda, and Pinecone/Milvus for Vector memory. Infrastructure: AWS (Compute optimization for high-inference loads). What You Will Be Doing Architecting Multi-Agent Flows: Designing state-machines that allow agents to "handoff" tasks to one another (e.g., a Support Agent handing off a logistical error to...
...create offline, self-hostable AI models Architect and develop a scalable backend system for AI workloads Create end-to-end AI pipelines optimized for performance and scalability Integrate third-party APIs and AI services where required Collaborate closely with product and engineering teams to turn ideas into working solutions Required Skills & Experience Strong experience with LLMs (OpenAI, LLaMA, Mistral, Gemma, etc.) Hands-on experience with RAG frameworks (LangChain, LlamaIndex, Haystack, etc.) Experience in OCR & Vision (Tesseract, OpenCV, Vision Transformers, multimodal models) Knowledge of speech systems (TTS, STT, STS) Experience in LLM fine-tuning, quantization, and model optimization Ability to deploy self-hosted / offline AI models Strong backend dev...
...them into actionable steps → executes via multiple specialized agents → returns a consolidated output. User Experience: Seamless, interactive, human-like, multi-modal (text + file + optional voice). --- 2️⃣ Core Features User Side 1. Goal Input: Accept free-text or structured user objectives. Example: “Prepare my study plan for JEE Advanced in 3 months, focusing on Chemistry & Physics.” 2. Planner Agent (Central AI Brain): Breaks goals into sub-tasks. Prioritizes, sequences, and assigns tasks to worker agents. Handles contingencies (“what if resources missing”). 3. Worker Agents (Specialized AI Modules): Research Agent: Collects references, articles, or past papers. Writer Agent: Drafts content, emails, resumes, SOPs, or re...
...targets developer-centric queries. • Select or fine-tune an appropriate large language model (OpenAI API, Claude, Meta Llama, etc.) and wire it up through a lightweight backend (Python/FastAPI, Node/Express—your call). • Implement sentiment detection to adjust responses dynamically (e.g., calming frustrated users). • Provide a short training pipeline so I can expand intents or retrain embeddings without touching core code. • Supply deployment instructions and sample integration snippets so I can drop the agent into my preferred chat UI immediately. Acceptance criteria 1. Agent answers at least 80 % of a provided developer FAQ set correctly in a test chat session. 2. Sentiment flip test: when fed identical questions phrased angrily vs....
Tengo varios clips de pantallas y platos listos y un guion por cada pieza; necesito que los transformes en reels verticales con un acabado clásico y elegante. El trabajo incluye: • Edición completa (corte y ritmo) • Ajuste fino de color para resaltar texturas y tonos naturales • Animaciones de tex...YouTube Shorts Trabajo normalmente con Premiere Pro y After Effects, pero acepto DaVinci Resolve si te resulta más ágil, siempre que mantengas la calidad final. Entrego guion, logos y referencias al inicio; tú me devuelves los archivos editables y el master listo para publicar. Busco alguien detallista que disfrute de esa estética sobria y pulida que transmiten los restaurantes de alta cocina. Si te llama la atención, ...
...imagen ejemplo [":i:/g/personal/jgarcia_fhis_gob_hn/IQBACWNBdGUyTJvngqocBzrvAVJ7QXuaaNbON_KrVzXmWjU"] algo asi con array.. ya que por parte del lado del usuario ya está, ahora se requiere desde la app. 2. Al guardar el registro, un flujo (Power Automate) deberá crear, si no existe, una carpeta con ese código único tanto en mi biblioteca de SharePoint como en OneDrive. 3. La foto se sube a ambas carpetas y el flujo devuelve la URL pública (o de uso interno) para almacenarla en el mismo registro de la app que se llama el campo Link Adjuntos Técnico en SharePoint. Acepto recomendaciones sobre licencias, conectores o permisos, pero el resultado debe quedar funcionando end-to-end: capturar, guardar, generar enlaces y mo...
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Have desktop AI chat assistant running local LLMs offline. It's running a Flask web server with a pywebview desktop GUI wrapper, using llama-cpp-python for GGUF model loading and an adaptive AI system that automatically selects models from performance tiers (minimal/low/medium/high) based on hardware detection. The app uses conversation context tracking with topic analysis, reference resolution, and memory monitoring to switch between models when RAM gets tight. Lloading bigger models (like 24B parameter models in the high tier) is failing or crashing - the RAM checks and fallback logic exist but bigger models won't load reliably, possibly due to memory allocation issues during loading, GPU layer configuration problems, or the model switching logic interfering with initi...
