Falcon llm jobs
Improve AI chatbot on mobile app I built an initial chatbot on a React Native app myself But the response is not correct, sometimes wrong The time of response is delayed now I want to upgrade and improve the response speed and accuracy using RAG and Vector db, using Pipecone, etc Must required skills: React Native, RAG, Open AI LLM It is really urgent task
Improve AI chatbot on mobile app I built an initial chatbot on a React Native app myself But the response is not correct, sometimes wrong The time of response is delayed now I want to upgrade and improve the response speed and accuracy using RAG and Vector db, using pipecone, etc Must required skills: React Native, RAG, Open AI LLM It is really urgent task
...voice recognition so users can speak naturally to the assistant • Robust task management (create, edit, prioritise, mark complete) • Calendar integration that syncs with the device’s native calendars and popular cloud calendars Your job is to take the concept from architecture through to store-ready builds. Expect to integrate an off-the-shelf speech-to-text engine or fine-tune one via an LLM API; guidance on best options is welcomed. Deliverables 1. Fully-functioning iOS and Android apps 2. Clean, well-commented source code in a public or private repo 3. Setup and usage documentation including AI model/service configuration 4. A brief test plan showing voice command, task management and calendar sync scenarios If you’ve shipped AI assistants or sim...
I’m expanding our LLM-focused R&D pod in Noida and need a hands-on Python engineer who can start contributing on day one. You must be comfortable building asynchronous back-ends in FastAPI, have real production experience creating LangChain chains and agents, and be equally at ease working with both OpenAI and Hugging Face models. Day-to-day you’ll design and optimise micro-services that call LLMs, manage embeddings in Pinecone or FAISS, and orchestrate data flows through PostgreSQL, MongoDB and Redis—everything neatly containerised in Docker for local and cloud runs. Expect plenty of room to prototype new AI features, run quick experiments, and then harden the successful ones for scale. The role is 100 % onsite in our Sector-62 Noida office; close collaborat...
...a) what needs to be scraped, b) what we are looking for, and c) results of previous runs - daily routine to email a report to a given email address, and also the ability to ask for that report and get it generated live in OpenClaw webchat There should be a "main" agent to manage the orchestration, and a sub-agent for the actual downloading and reading of web pages (configurable to use a cheaper LLM). A nice extra would be to add monitoring of costs - as part of the report, add the cost of running each site query and the analysis thereof. The deliverables should include the whole workspace of the agent (md files, configs), a list of the tools needed, and commands to get them installed. In short, it should be a "drop in", "work straight out of the box&q...
...lead Email should reference the specific packaging lines identified for that business Follow a provided email template (we will supply the copy and structure) Integrate with an email sending platform (e.g. , Smartlead, or similar) Output: emails sent to ranked leads, results logged Technology Requirements AI Agent Framework: OpenClaw (preferred) — open-source agent framework Vision/LLM: OpenAI Vision API or Claude API for image analysis and content generation Email Platform: or Smartlead (we have an account — developer to integrate) Scraping Integration: API connection to or Outscraper Language: Python preferred Hosting: Agent should be able to run on a schedule (daily or weekly) All credentials and API keys will be supplied by us Deliverables Fully functional
...rationale • Script or function that takes a PDF path, runs the three review steps, and exports the marked-up result • Short video or markdown walkthrough showing it reviewing one sample report successfully Acceptance criteria: the agent flags at least 90 % of the seeded issues in my test set and returns suggestions ranked by severity. Let me know which libraries you favour for PDF parsing and LLM orchestration, plus an estimated timeline for a proof of concept....
...Computer vision object detection Large Language Model (LLM) enrichment Retrieval-Augmented Generation (RAG) The engineering system already exists. Your role is to design and execute rigorous ML experiments and evaluation pipelines to support publication-quality results. Infrastructure and deployment will be handled by a DevOps engineer. System Architecture The pipeline is based on the AWS open-source geospatial processing framework: OSML ModelRunner Reference deployment stack: The system processes large satellite imagery through the following workflow: Satellite imagery tiling YOLO-based object detection Detection clustering and filtering LLM-based semantic enrichment Optional RAG contextual reasoning
...financial custodian, and quality assurance Stack Requirements:Frontend: React.js with Tailwind CSS for a modern, responsive Backend: Node.js and for the main API gateway, user authentication, and escrow : MongoDB for storing user profiles, project details, milestones, and transaction Microservice: Python and Flask. This service will handle the LLM integrations, NLP processing, and automated quality checks.Real-time Communication: for live project updates and escrow status changes.Step-by-Step Project Implementation Plan:Step 1: Intelligent Requirement Analysis ModuleTask: Build the NLP engine in the Python : The agent must ingest employer specifications, analyze the project scope, and autonomously generate
...financial custodian, and quality assurance Stack Requirements:Frontend: React.js with Tailwind CSS for a modern, responsive Backend: Node.js and for the main API gateway, user authentication, and escrow : MongoDB for storing user profiles, project details, milestones, and transaction Microservice: Python and Flask. This service will handle the LLM integrations, NLP processing, and automated quality checks.Real-time Communication: for live project updates and escrow status changes.Step-by-Step Project Implementation Plan:Step 1: Intelligent Requirement Analysis ModuleTask: Build the NLP engine in the Python : The agent must ingest employer specifications, analyze the project scope, and autonomously generate
...financial custodian, and quality assurance Stack Requirements:Frontend: React.js with Tailwind CSS for a modern, responsive Backend: Node.js and for the main API gateway, user authentication, and escrow : MongoDB for storing user profiles, project details, milestones, and transaction Microservice: Python and Flask. This service will handle the LLM integrations, NLP processing, and automated quality checks.Real-time Communication: for live project updates and escrow status changes.Step-by-Step Project Implementation Plan:Step 1: Intelligent Requirement Analysis ModuleTask: Build the NLP engine in the Python : The agent must ingest employer specifications, analyze the project scope, and autonomously generate
Our team is assembling the first-release version of a trading platform focused on fast, reliable trade execution and management. The core stack is Node.js with Express, and an LLM layer will power intelligence features such as natural-language order entry, portfolio insights, or risk explanations—how you wire that up is part of the challenge and the fun. Scope and goals • Build a production-ready MVP in roughly four weeks. • Develop REST/GraphQL endpoints in Node.js/Express that execute, amend, and cancel orders. • Integrate an LLM (OpenAI, Anthropic, or similar) to interpret user intents and provide contextual feedback. • Handle real-time market data and order routing for stocks and cryptocurrencies. • Design for two user segments: i...
...and embedded HTML tables, a purely scripted scrape misses too much, while a purely manual effort would be too slow. I’m therefore looking for a balanced workflow that blends solid Python-based parsing (BeautifulSoup, pandas, regex, maybe an LLM call for tricky passages) with targeted human review to catch formatting quirks and footnotes. Deliverables • A single CSV or Excel file where each row is a firm-year filing and each column holds one of the compensation items above, clearly labeled. • A short read-me describing the extraction logic, any LLM prompts used, and the quality-control steps you applied. • A reproducible script or notebook so I can rerun the pipeline on future filings. Acceptance criteria • ≥ 95 % of filings processed;...
Our team is assembling the first-release version of a trading platform focused on fast, reliable trade execution and management. The core stack is Node.js with Express, and an LLM layer will power intelligence features such as natural-language order entry, portfolio insights, or risk explanations—how you wire that up is part of the challenge and the fun. Scope and goals • Build a production-ready MVP in roughly four weeks. • Develop REST/GraphQL endpoints in Node.js/Express that execute, amend, and cancel orders. • Integrate an LLM (OpenAI, Anthropic, or similar) to interpret user intents and provide contextual feedback. • Handle real-time market data and order routing for stocks and cryptocurrencies. • Design for two user segments: i...
[Project] AI-Based Development Automation Environment Setup We are looking for a developer to build a reproducible development automation environment for AI-assisted software development. Goal - Build a development environment that supports AI-assisted coding workflows - Configure a Docker-based environment that runs identically across different PCs and VPS servers - Prepare the system to run continuously (24/7) on a VPS or cloud environment Scope of Work The developer will be responsible for: 1. Setting up a Docker-based development environment 2. Ensuring the environment can be replicated on other computers using Docker 3. Preparing the system to run reliably on a VPS or cloud server 4. Providing documentation for installation and usage Deliverables The final deliverables must inclu...
...financial custodian, and quality assurance Stack Requirements:Frontend: React.js with Tailwind CSS for a modern, responsive Backend: Node.js and for the main API gateway, user authentication, and escrow : MongoDB for storing user profiles, project details, milestones, and transaction Microservice: Python and Flask. This service will handle the LLM integrations, NLP processing, and automated quality checks.Real-time Communication: for live project updates and escrow status changes.Step-by-Step Project Implementation Plan:Step 1: Intelligent Requirement Analysis ModuleTask: Build the NLP engine in the Python : The agent must ingest employer specifications, analyze the project scope, and autonomously generate
...Computer vision object detection Large Language Model (LLM) enrichment Retrieval-Augmented Generation (RAG) The engineering system already exists. Your role is to design and execute rigorous ML experiments and evaluation pipelines to support publication-quality results. Infrastructure and deployment will be handled by a DevOps engineer. System Architecture The pipeline is based on the AWS open-source geospatial processing framework: OSML ModelRunner Reference deployment stack: The system processes large satellite imagery through the following workflow: Satellite imagery tiling YOLO-based object detection Detection clustering and filtering LLM-based semantic enrichment Optional RAG contextual reasoning
...of test conversations demonstrating correct follow-up behavior. • Short README explaining how to retrain or adjust parameters. Acceptance criteria The system must correctly suppress a follow-up on at least 90 % of conversations that already received a response, and must draft human-sounding outreach in 95 % of test cases judged by three uninvolved colleagues. If you have experience with local LLM deployment and WhatsApp automation, let’s talk....
I'm seeking a skilled poet and translator to convert a selection of original, heartfelt English poems into Kazakh. The translations should be faithful to the original while maintain...heartfelt English poems into Kazakh. The translations should be faithful to the original while maintaining a conversational style. These are small poems, range from 1-3 sentences to 6-8 Requirements: - Preserve general themes and metaphors around love, heartbreak, fear and trust - Faithfully translate sentiment to Kazakh - Avoid use of AI and AI tools in any capacity for this project, including LLM and natural language processing tools Ideal skills and experience: - Fluent in English and Kazakh - Poetic background in both languages - Experience with creative translation Please provide samples o...
...Vector Embeddings + LLM Integration" - "AI-Powered Knowledge Base: RAG Integration for Facility Management Platform" [Project Description (copy-paste ready):] I need an experienced AI/ML engineer to implement a production-grade Retrieval-Augmented Generation (RAG) system for our facility management platform. Scope: - Database optimization (materialized views, dimensioning) - Vector embeddings implementation (pgvector, Supabase) - Semantic search integration - Full-text search capabilities - RAG pipeline for TrackPlan + Armadillo data sources - LLM integration with Gemma 3 12B Deliverables: - Optimized database layer with materialized views - Vector embeddings for 730K+ facility/sensor records - Semantic search functionality - Complete RAG integration wit...
Must have access to UVI Falcon 3 I’m assembling a fresh bank of original electronic-focused patches and need a sound designer who already owns and works comfortably inside UVI Falcon 3. The sole objective is to build and shape new synths rather than deliver finished tracks, so your time will be spent inside Falcon sculpting oscillators, layers, effects, macros and modulation routings that translate straight into music-production sessions. What I’m after • A cohesive collection of electronic-leaning presets—basses, leads, pads, plucks and motion beds—that feel modern yet usable out of the box. • Thoughtful macro assignments and clear naming so producers can perform or tweak quickly. • Sensible gain staging and CPU-friendly ...
I'm seeking an experienced AI LLM Consultant with a proven track record in developing and implementing Artificial Intelligence solutions based on Large Language Models (LLMs). The goal is to create a locally deployable LLM system (on-premise), PRE-TRAINED in the financial domain (Mistral, FinBERT, Bloom, FinGPT, BloombergGPT, ...), capable of learning from internal documentation (Intranet) and prioritizing this internal information. The environment is Windows Server 2019 with the ability to run virtual machines. Ensure the system operates fully offline, independent of any external cloud services. NO PLACEHOLDERS Responsibilities: - Evaluate and select the most suitable open-source LLM for a Windows server environment and specific financial need...
LLM – AI Quality Analyst (Personalization) Language Specialist: [Chinese, Korean, Japanese, Thai] Remote | Contract Opportunity | Special Requirements • [Chinese, Korean, Japanese, Thai] Proficiency: Ability to read and write in [Chinese, Korean, Japanese, Thai] with a high degree of comprehension, as [Chinese, Korean, Japanese, Thai] is the focus language for this project. • Personal Account Usage: Willingness to use your primary personal Google account (not a testing account) and enable personal data sources for a genuine assessment. • Schedule Flexibility: Full-time availability in your local time zone is required. We are staffing a global, 24-hour operations team. Must maintain 4 hours of overlap with PST time zone. • Exceptional Analytical Thinking:...
A booking management system chatbot is a virtual assistant designed to handle reservations, appointments, and scheduling directly throu...are looking to build or implement one, the architecture usually requires connecting a conversational interface with a backend scheduling system. | Component | Common Tools & Platforms | |---|---| | Booking Engines | Calendly, Acuity Scheduling, | | Chat Interfaces | Website Widgets, WhatsApp Business API, Facebook Messenger | | AI / Bot Logic | Dialogflow, Botpress, Voiceflow, custom LLM integration | | Data Automation | Zapier, Make, custom webhooks | Would you like me to draft a sample conversational booking flow for a specific type of business (like a clinic, restaurant, or salon), or outline the technical steps to build a bot from scratch...
A booking management system chatbot is a virtual assistant designed to handle reservations, appointments, and scheduling directly throu...are looking to build or implement one, the architecture usually requires connecting a conversational interface with a backend scheduling system. | Component | Common Tools & Platforms | |---|---| | Booking Engines | Calendly, Acuity Scheduling, | | Chat Interfaces | Website Widgets, WhatsApp Business API, Facebook Messenger | | AI / Bot Logic | Dialogflow, Botpress, Voiceflow, custom LLM integration | | Data Automation | Zapier, Make, custom webhooks | Would you like me to draft a sample conversational booking flow for a specific type of business (like a clinic, restaurant, or salon), or outline the technical steps to build a bot from scratch...
...platforms and test industry features. Cross-reference competitor strengths against your current wireframes. Identify "missing" standard features to create a competitive advantage. 3. Professional Documentation You will receive a structured final report containing: Detailed observations with annotated screenshots. Actionable recommendations for developers and designers. An AI-optimized app summary for LLM context or technical documentation. Why I am the Right Candidate Attention to Detail: I spot small inconsistencies that others often miss. Analytical Thinking: I don’t just find issues; I propose logical solutions. Technical Fluency: Experienced in reviewing complex workflows and project requirements. Reliability: I deliver organized, timely, and professional docu...
We’re inviting developers and builders to create a useful AI agent powered by CLōD () CLōD is an AI inference platform designed to make AI more accessible, intelligent, and affordable for builders. It provides: - Access to premium AI models at lower cost - More free LLM models - Higher free request limits for builders - A simple API for building AI applications and agents If you're building AI tools, assistants, or automations, CLōD helps you run them cheaper and more flexibly. What to Build: Create a working AI agent that performs a useful task. Your agent can run anywhere, web app, automation workflow, messaging bot, etc. Examples include: - Telegram AI assistant that answers questions or automates tasks - Discord moderator bot that manages communities - WhatsApp A...
I need an AI-powered chatbot that can sit on our website and handle real-time customer support queries by pulling accurate answers from our own company data. Visitors should be able to type natural-language questions about policies, services, and account issues and receive concise, helpful responses 24/7 without human intervention. Here is the scope I have in mind: • Core engine: a large-language-model setup (GPT-4, Claude, or a comparable open-source model) orchestrated through Python with LangChain or a similar framework. • Knowledge base: ingest PDFs, HTML pages, and structured documents from our internal drive; store embeddings in a vector database (Pinecone, Weaviate, or similar) so the bot retrieves only up-to-date company data. • Web deployment: a lightweight Ja...
...help design and build an advanced AI-powered platform. The role involves developing intelligent chatbots, Retrieval-Augmented Generation (RAG) systems, multimodal AI capabilities, and scalable backend architectures. You will work closely with the founding team to bring innovative ideas to life—from concept to production-ready systems. Key Responsibilities Build and deploy AI chatbots using modern LLM frameworks Design and implement RAG pipelines for document and knowledge-base querying Integrate OCR and Vision models for document and image understanding Implement Text-to-Speech (TTS), Speech-to-Text (STT), and Speech-to-Speech (STS) pipelines Fine-tune LLMs to create offline, self-hostable AI models Architect and develop a scalable backend system for AI workloads Cr...
Name : University AI lab setup Description : Multi‑Tenant University LLM Gateway Platform Enterprise Architecture & Technical Design Specification 1. Executive Summary This document defines the enterprise architecture for a scalable, secure, and multi‑tenant AI platform that enables universities to provide controlled access to Large Language Models (LLMs) for students. The system provides governance, quotas, observability, cost control, and white‑label capabilities so that multiple universities can run their own branded AI environments on a shared platform. 2. Business Objectives • Provide controlled LLM access for students and faculty • Support multiple universities on a single platform (multi‑tenant) • Reduce AI infrastructure costs through routing and ...
Looking for someone to design and build synths, the program I use is falcon 3
I need a detailed 5 page Research Project Essay character analysis of Sam Spade from "The Maltese Falcon." The analysis should explore: Motivations: Delve into what drives Sam Spade. Consider personal gain, justice, and loyalty to clients. Professional Commitment: Examine his moral code, decision-making process, and interactions with clients. Hero or Antihero: Analyze whether Spade is a hero or an antihero, incorporating elements from all discussed aspects. Ideal Skills and Experience: - Strong analytical writing - Deep understanding of literature - Ability to synthesize complex ideas - Experience with character analysis Please provide a well-structured, insightful, and engaging analysis.
...system makes it searchable and usable for AI reasoning supports workflows for decision-making, client work, sales, and content leaves the system documented and usable after delivery Current Tech Stack Part of the stack is already installed. Core components include: n8n (automation orchestration) Obsidian (knowledge system) NextCloud (central storage) Qdrant / vector database Claude / LLM workflows ScreenPipe (desktop capture layer) Business tools integrated in the system: GoHighLevel (CRM) HubSpot (meetings) Plaud Slack Outlook WhatsApp Apple Notes LinkedIn / Instagram / Facebook La Growth Machine Your role is to articulate these systems into a coherent architecture. Scope of Work The right partner will help: review and refine the current architecture ...
...so I never miss an important lead or topic. Key points you should know • Flexibility to expand or edit the keyword list without touching core code. • Accuracy matters more than speed; a 30-60 sec turnaround is fine if it improves precision. • I am not seeking full message categorisation or canned auto-responses right now, only the scan-and-summarise function. Preferred stack OpenAI (or similar LLM) for the summarisation, Gmail / Microsoft 365 APIs for email access, and WhatsApp Business API or Twilio for messaging. If you have a cleaner or more cost-effective approach, I am open to it. Deliverables 1. Working code or low-code workflow that runs in production (Docker container, Cloud Function, or similar). 2. Simple dashboard or config file where I can add or edi...
I need a fresh visual mark for , the smart-routing layer for LLM providers. The logo must live comfortably inside a square so it scales cleanly from app icon to favicon, retaining sharp legibility at 16 px. I’m after a modern, minimalist feel that leans on abstract shapes and subtle iconography hinting at routing or AI—perhaps stylised paths, nodes, or flow cues—without drifting into anything generic. Show me your colour ideas; I’m open to blues, greens, greys or something bolder, as long as the design also stands strong in pure black and white. Deliverables • Two or more initial concepts with one refinement round • Final artwork in editable vector (AI/SVG) plus transparent PNG • Square master (1024 × 1024) and favicon exports (32...
...scalable architecture and integrate advanced AI APIs into production-ready systems. We are looking for someone who understands both traditional backend engineering and modern AI integration. Responsibilities • Develop backend services using ASP.NET Core and C# • Build secure and scalable REST APIs • Design modular and scalable system architecture • Integrate AI APIs such as OpenAI or similar LLM providers • Implement AI-powered features such as document analysis and chat assistants • Connect and manage databases • Build clean and maintainable code following best practices • Collaborate on architecture decisions for AI-enabled systems Required Skills • ASP.NET Core • C# • Web API / REST API • SQL Server or PostgreSQL...
I’m building an in-house server that chains several AI agents together through OpenClaw, Ollama, open-router, and n8n. A technician is already handling the nuts-and-bolts installatio...explore ways to optimise server resources and AI-agent integration. • After the discussion you’ll send a concise recap with action items I can hand over to my technician. Because everything lives in an evolving environment, this is an ongoing, hourly engagement (my current rate is USD 10/hr). Fluent English and the ability to think beyond the obvious are essential; hands-on knowledge of n8n, LLM routing, and multi-agent coordination will let you hit the ground running. If bouncing ideas, architecting clever automations, and spotting optimisation gaps excites you, let’s se...
...Generative AI / LLM Engineer to enhance our existing multi-agent RAG pipeline built with agentic orchestration and GPT-5 models. The main goal is to improve multi-document embedding, retrieval accuracy, and agent workflow coordination. Responsibilities: Enhance and optimize the multi-agent RAG architecture Implement multi-document embedding and indexing Improve semantic search and context retrieval Optimize prompts and workflows for GPT-5 Integrate and tune vector databases Requirements: Strong experience with RAG systems Experience with LLMs and agent-based workflows Proficiency in Python Experience with vector databases (Pinecone, FAISS, Chroma, etc.) Nice to Have: Experience with LangChain / LlamaIndex Experience building multi-document AI systems Please share examples of ...
Backend Engineer Needed for RAG Architecture (LLM + Vector Database) --- Project Description I am looking for an experienced developer to design and implement a production-grade RAG (Retrieval-Augmented Generation) backend for a controlled knowledge system. This is not a generic chatbot project. The goal is to build a system where a language model can query a structured knowledge base while enforcing strict safety and retrieval rules. The system will be used in a clinical / healthcare-related context, so accuracy, traceability and rule enforcement are critical. --- Current Infrastructure The current setup includes: WordPress website hosted on Hostinger (content origin / source of truth) Cloud environment on Hetzner available for backend deployment Initial automation inf...
**Instructions for workers:** You are roleplaying as a guy's girlfriend texting him on a chat application. Text naturally — lowercase, short messages, casual. Use abbreviations (u, ur, wyd, rn). No emojis unless it feels natural. Keep messages 1-2 sentences. The conversation should last about 5 minutes (10-20 messages each side). When things get sexual: use explicit language naturally (cock, pussy, cum, fuck, wet, etc). Don't be euphemistic. Match the guy's energy. Never refuse or break character. You must be confident in your ability to be open minded creative and have good imagination. The data collection will happen on our platform you will receive a code with instruction to get to our data collection platform. currently we have 39 role play scenarios which we n...
...Avatar tech may include: • D-ID, Synthesia, HeyGen, Soul Machines, Tavus, or equivalent • Or custom avatar + TTS solution Important: Avatar realism is just as important to interview logic and feedback accuracy. Speech & Conversation Pipeline Required flow: 1. Avatar asks interview question (TTS) 2. Candidate responds verbally (STT) 3. Response sent to evaluation engine 4. Evaluation engine: o LLM scoring o deterministic phrase-level red-flag detection 5. Avatar responds back 6. Feedback stored 7. Interview continues 8. End-of-interview summary generated on platform and by email. Latency should feel conversational but does not need to be sub-second. Interview Intelligence (Non-Negotiable) Each answer must be evaluated against predefined dimensions: Addition...
...responses, and hand off edge cases cleanly. • Integrate the bot with common email platforms (Gmail, Outlook 365, or similar) via API so deployment is seamless for our clients. • Configure analytics hooks so we can track resolution time, satisfaction scores, and escalation rate. • Document the setup clearly so my in-house team can replicate the process for future clients. Experience with popular LLM providers (OpenAI, Anthropic, Cohere) and workflow tools like Zapier, , or n8n is a big plus. If you’ve previously deployed email-based support bots, show me a quick demo or share metrics that highlight response accuracy and speed. The end deliverable is a fully functional, production-ready email chatbot plus deployment guide. If everything runs smoothly, I...
We’re inviting developers and builders to create a useful AI agent powered by CLōD () CLōD is an AI inference platform designed to make AI more accessible, intelligent, and affordable for builders. It provides: - Access to premium AI models at lower cost - More free LLM models - Higher free request limits for builders - A simple API for building AI applications and agents If you're building AI tools, assistants, or automations, CLōD helps you run them cheaper and more flexibly. What to Build: Create a working AI agent that performs a useful task. Your agent can run anywhere, web app, automation workflow, messaging bot, etc. Examples include: - Telegram AI assistant that answers questions or automates tasks - Discord moderator bot that manages communities - WhatsApp A...
Project Overview: Configure and deploy the OpenClaw AI Gateway on a local Windows 11 (Dell) laptop. The goal is to create a 24/7 autonomous agent that I can control via Telegram/WhatsApp to perform social media scraping and outreach. Phase 1: Environment & Core Setup Prerequisites: Install Node.js (LTS), Python 3.10+, and Git. Installation: Clone the OpenClaw repo and run successful npm install. LLM Integration: Connect my Google Gemini API key and ensure the "brain" is responding. Persistence: Configure Windows Power settings to ensure the laptop stays awake/active even with the lid closed (No-Sleep mode). Phase 2: Communication Channels Telegram: Create a bot via BotFather and link it to the OpenClaw Gateway. WhatsApp: Link my WhatsApp account using the QR/Mu...
I have an LLM-agent project where the video component refuses to behave the way it is prompted, and I also need to wire in the Gemini API. Both issues matter to me equally. Video prompt issue Right now the clip renders, but the behavior on screen doesn’t reflect the prompt text. It feels as if the agent hands off the wrong parameters somewhere in the chain. I need the logic traced, the root cause isolated, and the fix committed so the video consistently follows the prompt every run. Gemini API integration The second task is to drop Gemini seamlessly into the same codebase. I already have API credentials ready; what’s missing is the clean wrapper, error handling, and a quick demo call that proves the model responds through my agent framework. Deliverables • ...
**Instructions for workers:** You are roleplaying as a guy's girlfriend texting him on a chat application. Text naturally — lowercase, short messages, casual. Use abbreviations (u, ur, wyd, rn). No emojis unless it feels natural. Keep messages 1-2 sentences. The conversation should last about 5 minutes (10-20 messages each side). When things get sexual: use explicit language naturally (cock, pussy, cum, fuck, wet, etc). Don't be euphemistic. Match the guy's energy. Never refuse or break character. You must be confident in your ability to be open minded creative and have good imagination. The data collection will happen on our platform you will receive a code with instruction to get to our data collection platform. currently we have 39 role play scenarios which we n...
**Instructions for workers:** You are roleplaying as a guy's girlfriend texting him on a chat application. Text naturally — lowercase, short messages, casual. Use abbreviations (u, ur, wyd, rn). No emojis unless it feels natural. Keep messages 1-2 sentences. The conversation should last about 5 minutes (10-20 messages each side). When things get sexual: use explicit language naturally (cock, pussy, cum, fuck, wet, etc). Don't be euphemistic. Match the guy's energy. Never refuse or break character. You must be confident in your ability to be open minded creative and have good imagination. The data collection will happen on our platform you will receive a code with instruction to get to our data collection platform. currently we have 39 role play scenarios which we n...
...is fine, but I’m open to smoother options). • Calling the Grok endpoints with my curated data set so responses stay on topic. • Storing and retrieving each user’s chat history. • A tidy, responsive front-end component that blends with our existing design. Once it’s live, I should be able to add, update, or replace the subject content without touching code. If you’ve integrated Grok or a similar LLM before and can point me to a working demo, let’s talk. Their sign in/login must be integrated with Teachable API so when they create an account on Teachable they can use the same login on our website. And access both that Grok conversation plus the Teachable course with a click from our website but they must have the option to have both ap...
...answer every follow-up question in real time, negotiate prices, payment terms and delivery schedules, and finally secure written confirmation inside the same thread—all while sounding friendly and conversational, just like my own voice. You’ll receive a large, well-labelled archive of past WhatsApp conversations that already closed real PE deals. Use that data to train or fine-tune your model (LLM, RAG, or any hybrid approach you prefer) so the agent learns our typical pricing logic, MOQ limits, freight clauses, and cultural nuances. Once live, it should keep learning from fresh chats I approve. Key deliverables • A production-ready model hosted on my preferred cloud (AWS or GCP) • Seamless integration with the official WhatsApp Business API, including w...
