Llama jobs

...short answer on a small SPI/I²C OLED display. Scope of work • Capture: Trigger the Pi Camera (libcamera or picamera2) and save a frame. • OCR: Use Tesseract, EasyOCR, or another open-source library to read text from the image. The input is always “text from images,” never scanned PDFs or live handwriting. • AI logic: Pass the recognised string to a simple question-answer routine (OpenAI API, Llama .cpp, or any efficient model you prefer) and return a concise, single-sentence reply. No lengthy explanations are needed. • Display: Push that reply to a 128×64 (or similar) monochrome OLED over SPI/I²C using the common SSD1306 driver. Text must be readable and auto-wrap if longer than the screen width. • Repeat or exit cle...

I need a specialist to turn my Windows-based PC into a robust, private AI workstation. The core stack will revolve around Python and must run Llama locally through AnythingLLM while remaining flexible enough to load additional models as they mature. Key capabilities I’m after: • Decades-worth of data ingestion: PDFs, Word files, full Office docs and .eml email archives. • Context retention so I can resume a conversation or analysis session days later without re-feeding content. • Open WebUI access for convenient, browser-based interaction. • Clean restart behaviour, automated backups, and a path to scale out if I later bolt on extra GPUs or move to a small on-prem cluster. I already have the hardware; you bring the know-how to configure, script,...

...professional webmaster toolkit within the software is already in .exe format, I did that myself. Do not attempt to charge me more than $250, it will be declined. dependancies as follows: pip install sounddevice pip install pyaudio pip install soundfile pip install pydub pip install playsound pip install webvtt-py pip install faster-whisper pip install openai-whisper pip install PyQt5 pip install llama-cpp-python pip install pillow pip install numpy pip install pyttsx3 pip install vosk pip install ffmpeg-python pip install scipy pip install cffi pip install pyppeteer pip install diskcache pip install typing-extensions pip install torch pip install PyQt5 pip install PyQtWebEngine pip install PyQt5-sip pip install PyQt5-tools within anaconda environment "final-evolution"...

...Automated Report & Form Generation: User describes requirements → AI generates complete reports in Word/PDF format with tables, charts, and summaries. Knowledge Management: Multiple document collections (workspaces), filtering by department, year, document type, etc. Conversation History & Memory. High Security: All data stays on local server/machine. Preferred Technology Stack: LLM: Ollama (Qwen3, Llama 3.1/3.3, or any strong Vietnamese-supported models). Framework: LangChain or LlamaIndex. Vector Database: ChromaDB, FAISS, or LanceDB. Embedding Model: nomic-embed-text or equivalent. Frontend: Streamlit, Gradio, Open WebUI, or AnythingLLM. Report Export: python-docx, WeasyPrint, ReportLab, Jinja2. Requirements for Freelancer: Proven experience building Local LLM...

Project Overview This project focuses on building: LLM-powered systems that take actions, not just generate outputs Autonomous agent architectures that interact with tools, APIs, and data pipelines A scalable AI system capable of real-world execution and decision-making What You’ll Be Building LLM-powered applications (OpenAI, Anthropic, LLaMA, Mistral) RAG pipelines (retrieval, hybrid search, re-ranking) Agent systems using LangChain / LangGraph Tool-use systems (API integrations, external tools) Data ingestion + retrieval pipelines Monitoring, logging, and evaluation systems Key Responsibilities Architect and develop scalable AI systems Design and optimize RAG pipelines Build and manage multi-agent workflows Improve latency, cost, and performance Implement evaluation fra...

...responsiveness Stable and reliable for daily use Integration Goals: I primarily use Quantower for trading, so the AI should be able to: Help analyze market data (manually input or pasted) Assist with trade ideas, summaries, and strategy insights Ability to connect or interact with Quantower tools via. As Much Access As possible. Technical Preferences (Flexible): Open-source models preferred (e.g., LLaMA-based or similar) Local model management (download, load, switch models if needed) Simple installer or packaged environment (Docker, executable, or similar) What I Do NOT Want: Cloud-based AI systems Anything requiring subscriptions or token-based billing Overly complex setup or maintenance End Goal: A local AI assistant on my PC that behaves similarly to the built-in AI ex...

I am looking for a versatile professional or a small team to handle a multi-stage digital project. This involves web development, AI integration, and brand identity design. Key Requirements: E-commerce Website: Build a fully functional, mobile-respons...product descriptions and blog posts within the platform. Logo & Brand Design: Create a unique, professional logo and brand guidelines that reflect a modern digital business. Technical Skills Needed: Frontend: React.js, , or similar modern frameworks. Backend: Node.js, Python, or Supabase/Firebase. Design: Adobe Illustrator, Photoshop, or Figma. AI: Experience with API integrations (GPT-4/Llama). Deliverables: Complete source code with documentation. High-resolution logo files (SVG, PNG, AI). Fully deployed and bug-free w...

...ones as wrong, so I need a specialist who can put several models through their paces, isolate the causes of these misclassifications, and tune the pipeline until the results are consistently reliable. Speed and consistency will matter later, but first I need the numbers to be right. You’ll have freedom to evaluate any mix of commercial LLMs (GPT-4, Claude, Bard, etc.) and open-source options (Llama 2, Falcon, custom fine-tuned transformers) so long as you keep the comparison fair and reproducible. The current stack is Python with Hugging Face and a small PostgreSQL database for answer keys; if another framework is essential, outline why and how you’ll integrate it back into this environment. Deliverables • A benchmark report showing precision, recall, and...

...content * Implement local AI model for offline usage * Fine-tune model for: - school-level explanations - bilingual support (English + regional language) - curriculum-bound responses * Build APIs and backend for integration with classroom system * Develop synchronization system (offline → central server) * Provide documentation and training Technical Requirements * Experience with LLMs (LLaMA, Mistral, etc.) * Experience with RAG frameworks (LangChain / LlamaIndex) * Vector databases (FAISS / Qdrant / Chroma) * Local AI deployment (Ollama / ) * Python backend (FastAPI preferred) Deliverables * Fully functional AI engine (offline capable) * Documentation * Deployment support * Training for internal team Preferred Experience * EdTech AI systems * Multilingual AI s...

...responsiveness Stable and reliable for daily use Integration Goals: I primarily use Quantower for trading, so the AI should be able to: Help analyze market data (manually input or pasted) Assist with trade ideas, summaries, and strategy insights (Optional) Ability to connect or interact with external tools via API if feasible Technical Preferences (Flexible): Open-source models preferred (e.g., LLaMA-based or similar) Local model management (download, load, switch models if needed) Simple installer or packaged environment (Docker, executable, or similar) What I Do NOT Want: Cloud-based AI systems Anything requiring subscriptions or token-based billing Overly complex setup or maintenance End Goal: A local AI assistant on my PC that behaves similarly to the built-in AI exper...

...ready to introduce an AI-powered concierge on my premium automotive detailing website and need a developer who can take it from concept to production. The assistant must answer real-time questions about services and pricing, booking appointments, and aftercare, drawing exclusively on my business information. Here’s the experience I’m after: ultra-low-latency replies through Groq’s API, running LLaMA 3.3 70B behind the scenes. I want conversation history to persist across a visitor’s session, so Streamlit session_state (or an equally clean solution) is the framework of choice, with python-dotenv keeping keys secure. A polished, on-brand interface, a friendly greeting flow, and easy deployment to a cloud host should round it out. Only English support i...

All-in-One Social Automation Platform (Post + DM + AI + Scheduler) Now powered with advanced automation + AI intelligence, including trend detect...Scheduler * Bulk scheduling * Queue system (Redis + Bull) * AI best-time suggestion Analytics * Post performance * DM logs * Link tracking * Funnel insights Tech Stack Mobile App: Flutter Web Dashboard: React Backend: Node.js + TypeScript Database: PostgreSQL (Supabase) Queue: Redis + Bull Automation Layer: * n8n * OpenClaw APIs: * Meta Graph API * YouTube Data API AI Layer: * OpenAI API * LLaMA / DeepSeek (optional open-source models) Use Cases • Reels creators finding trending audio instantly • Businesses generating viral marketing content • Agencies managing multiple clients • Lead generation through...

Necesito una página de internet profesional , moderna, enfocada en la captación de pacientes, más gráfica que escrita, nuestro grupo se llama ORTOPECTUS Clinica integral y estética torácica. Encargada de brindar manejo integral a las deformidades torácicas (Pectus excavatum, carinatum, poland, etc, etc) tumoraciones de pared, reconstrucciones de pared torácica, trauma torácico (fracturas costilla, esternón), procuraciones de injertos costales para rinoseptumplastias, remodelación costal para el moldeo de cintura, manejo del dolor en pared torácica e hiperhidrosis. Utilizando las técnica tradicionales así como las más innovadoras a nivel mundial y de mínima invasión...

Looking to setup locally on windows (intel Core i7 10th generation) any LLM that can give good quality responses as ChatGPT without internet connection. Preferred is Ollama however it is very slow for llama 3 70B. NOT sure if it can be done via quantize versions of LLMs.

I want to deploy an AI-driven solution that reliably takes over much of our day-to-day customer service and support workload. The core objective is ...with no human intervention. 2. Average customer response time is cut by 60 % or more compared with our current baseline. 3. All data privacy and security requirements for our industry are met, with logs and transcripts stored in an auditable manner. I’m open to your recommendations on the exact natural-language tools, frameworks, and hosting stack you prefer—whether that’s Dialogflow, Rasa, Llama 2, or a custom transformer setup—so long as the final solution is scalable and maintainable. Let me know how you would approach the project, what past work shows you can hit these benchmarks, and an estimated ti...

...Respetar el camino existente y mantener la legibilidad de casillas y zonas de juego. • Entregarme el archivo final listo para impresión (PNG y la fuente editable que utilices). Es un trabajo puntual y sencillo; pago inmediato al recibir el arte aprobado. Si necesitas referencias o guía de paleta, te las paso enseguida. Necesito el rediseño completo de un tablero de juego de mesa. El juego se llama “Exploradores del Saber” y es un juego educativo en el que los jugadores avanzan por un recorrido respondiendo preguntas para reunir cinco sellos de conocimiento y llegar a la meta final. El diseño debe realizarse desde cero. No hay elementos previos que deban respetarse, por lo que el tablero completo, incluyendo fondo y recorrid...

...Bahama Llama Shaved Ice. It should be colorful and fun. The working concept is a llama on the beach, laid back in a beach chair, sunglasses propped up on his forehead and holding a white cup with his bottom feet, with colored shaved ice above the rim of the cup, and perhaps his front feet behind his head like he's relaxing. Or, maybe his back legs are crossed on the chair and one of his front legs (hoof) is holding the snow cone. He is looking at the camera with a relaxed, chill, satisfied grin on his face. We will need to capture a closer up image on the llama for other uses but the larger beach scene will be displayed on the side of a building, approximately 6' wide and 4' tall. We see the llama as light brown. Here is a rough concept ...

...textbooks, formula sheets, and problem sets, then explain the answer step-by-step with rock-solid reasoning. Here is what success looks like from my side: • A working RAG stack (embeddings → vector database → LLM) wired together with modern tooling such as LangChain, LlamaIndex, or an approach you can justify. FAISS, Pinecone, Weaviate, or similar are fine for the vector layer; OpenAI, Claude, Llama 2/3, or comparable models may drive generation. • Retrieval tuned for high recall and low latency—students should see an accurate first response in well under a second for typical queries. • Step-wise explanations that a high-school learner can follow, with all reasoning made explicit and each algebraic transformation clearly spelled out. • ...

I’m taking a proof-of-concept Generative AI system into full production and want a senior engineer who has already solved the real-world problems this move uncovers. The stack is centred on Amazon Bedrock, where we are actively working with Claude 3, Titan, Llama 3 and Mistral. Your track record should show that you have wired those or comparable foundation models into live workloads before. Our orchestration layer relies on LangChain working hand-in-hand with LlamaIndex, Bedrock Agents and a set of custom integrations, so fluency with that trio is essential. Everything is written in modern Python (3.9+), surfaced through API Gateway, executed in Lambda and coordinated with Step Functions. Vector databases drive our semantic search, while Glue and Athena sit behind a serverle...

...source-based response Data Integration Quran dataset (API or local dataset) Basic Hadith dataset (Sahih Bukhari / Muslim preferred) Vector Database Store embeddings for Quran/Hadith Enable fast semantic search Admin Panel (Simple) Ability to add/update/delete knowledge entries Basic Web Chat Interface Simple chat UI (no advanced design needed) Preferred Tech Stack: AI: Ollama (local LLMs like Llama 3 / Qwen) Backend: Python (FastAPI or Flask) Framework: LangChain (or similar) Vector DB: ChromaDB Frontend: React (simple UI) Requirements: Experience with RAG systems Experience with LLMs (OpenAI, Ollama, etc.) Ability to demonstrate previous chatbot/AI work Clean, scalable code Important Notes: Accuracy is critical (Islamic content must not be fabricated) AI ...

...provide an API bridge to report compute metrics. The Tech Strategy (Task Routing, NOT Model Slicing): To fit our strict budget and timeline, we are NOT looking to build complex distributed inference (slicing one massive model across multiple nodes). Instead, we use Task Routing: Each user’s desktop client will locally run a quantized Small Language Model (SLM) – specifically the DeepSeek-R1-Distill-Llama-8B (using frameworks like / GGUF). The Master Server simply routes incoming inference requests (prompts) to available idle nodes, and the nodes return the generated text. Core Responsibilities (MVP Phase 1): 1. The Desktop Client (Windows/macOS): Build a lightweight, secure background app. It must profile the host's hardware (VRAM/RAM), download the quantized SL...

...so feel free to lean on the usual scholarly look (Times, Arial, or whatever works best for clarity). Alongside the text I need a single, clear systems-architecture diagram. I will give you a step-by-step description like the snippet below: • User prompt enters → hits a “Semantic Firewall” layer that screens for PII or toxicity. • If clear, the prompt moves into a secure VPC running a private Llama-3 (or Azure OpenAI) model. • A persistent memory layer (Redis/PostgreSQL) feeds the model with conversation state for deterministic replies. Your job is to visualise this exactly, using tidy icons or labelled boxes so the security boundary and data flow are unambiguous. A vector tool such as Visio, Lucidchart, Figma, or similar is fine—as l...

...quantization and optimization for cost-efficient deployment Hosting and deployment options (cloud, APIs, inference servers) Dataset creation and data annotation pipelines How small teams can build AI startups using existing models Monetization strategies (APIs, SaaS, datasets, AI services) Guidance on building MVPs and scaling AI products Preferred Background Experience working with LLMs (LLaMA, Mistral, HuggingFace models, etc.) Knowledge of model quantization, inference optimization, and deployment Experience with ML/Deep Learning product development Familiar with AI startup ecosystem Preferably based in India or familiar with the Indian AI market Technical Areas of Interest Hugging Face ecosystem Transformers and model fine-tuning LLM inference frameworks (vLLM,...

I need a llama-shaped 100% Arabica instant coffee jar design prepared for 3D printing. I have STL files for reference. Requirements: - Minor modifications needed: - Adjust measurements - Refine surface details - Add/remove small features - Final files in both .amf and .gcode formats Ideal Skills: - Proficiency in 3D modeling and printing - Experience with .amf and .gcode formats - Attention to detail for surface refinement

FREELANCE DEVELOPER NEEDED – STABILIZE & IMPROVE REACT NATIVE MARKETPLACE APP (EXPO + SUPABASE + STRIPE) PROJECT OVERVIEW I am developing a peer-to-peer rental marketplace mobile application where users can list items for rent and others can book them. The concept is similar to platforms like Airbnb or Fat Llama, but focused on renting physical items between users. The application is already built and functional. The current priority is stabilizing and refining the existing system, improving reliability and UI consistency before expanding into additional features. This project is NOT about building an app from scratch. The core product already exists. The main goal now is to strengthen the existing architecture, improve stability, and polish the user experience so the ...

...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...

...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...

...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 tight loo...

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 fast (Python, Jav...

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 • Generates a ...

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 (Swift for iOS, Ko...

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 (Swift for iOS, Ko...

...pixel shapes — not editable font outlines. We need a designer to polish the logo and produce a complete brand identity kit ready for product packaging, web, 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 cur...

...insights. - Generating claim packs and issuing court papers ready for filing. - Drafting legal documents such as robust defenses and 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 statu...

...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...

...confirmación + “Has trabajado Xh Ym” + botón informativo con ese texto (“ Has trabajado Xh Ym”). 3) Requisitos funcionales (casos) 3.1 Usuario no registrado Si el teléfono no existe en BD o está inactivo → responder: “Tu número no está registrado. Contacta con administración.” 3.2 Usuario registrado (flujo normal) Usuario escribe cualquier texto. Backend obtiene su api_base_url. Backend llama a la API empresa para obtener last_status (IN/OUT + timestamp). Responde por WhatsApp con mensaje + botón correcto (Entrar o Salir). Usuario pulsa botón: Entrar → se ejecuta check_in y se confirma. Salir → se ejecuta check_out, luego worked_time, se confirma y se muest...

...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)

...large language model directly on my own machine so I can serve a real-time chatbot embedded on my website. I have the hardware available but need an expert who can install the model, configure all dependencies, and expose an endpoint that my front-end widget can call. Here is what I have in mind: • Select and 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 pa...

...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 &bul...

...generation from high-level specs • Pin-pointed bug-fixing suggestions after reading a 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 pr...

...Pawnmas" (ugly-sweater style) "Luck of the Pawn" (St. Pat's) "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 – (...

...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...