From 6b85faecb485f9069db0de844ee3ffd708efec60 Mon Sep 17 00:00:00 2001 From: Cursor Agent Date: Wed, 10 Dec 2025 12:56:13 +0000 Subject: [PATCH] Add technical blueprint for Autonomous Listing Service Co-authored-by: nicsins --- docs/autonomous_listing_service.md | 175 +++++++++++++++++++++++++++++ 1 file changed, 175 insertions(+) create mode 100644 docs/autonomous_listing_service.md diff --git a/docs/autonomous_listing_service.md b/docs/autonomous_listing_service.md new file mode 100644 index 000000000..5adc7c355 --- /dev/null +++ b/docs/autonomous_listing_service.md @@ -0,0 +1,175 @@ +# Autonomous Listing Service – Technical Blueprint + +This document describes the design of an AI-native service that turns a seller’s raw photos and notes into premium listings, syndicates them across major marketplaces (Craigslist, Mercari, Nextdoor, etc.), and provides a unified conversational interface for negotiating with buyers. The system is intentionally agentic, multi-LLM, and RAG-enabled while running on a lightweight Python container suitable for serverless deployments. + +--- + +## 1. Goals & Constraints +- **Delightful Listings:** Transform mediocre images + short descriptions into polished media and persuasive narratives that boost conversions. +- **One-Click Syndication:** Publish consistently formatted listings to multiple platforms with per-channel compliance. +- **Unified Messaging:** Give sellers a Zoom-like conversational hub to coordinate with AI agents and buyers while listings are live. +- **Autonomous Lifecycle:** Monitor inquiries, negotiate within guardrails, and auto-close listings once an item sells. +- **Portable Runtime:** Deliver as a Python-first, containerized micro-app deployable on Lambda, Cloud Run, or Fargate. + +--- + +## 2. High-Level Architecture + +``` +User → Web/App UI → API Gateway → Python Orchestrator (FastAPI) → Agent Mesh + ↘ Event Bus / Task Queue + ↘ Worker Pods (image, LLM, RAG, integrators) +Storage Layers: Object storage (images), Vector DB (descriptions/market data), Relational DB (listings, chats) +``` + +### Core Services +1. **Ingestion & Auth** + - Accepts photo uploads, metadata, and voice/text notes. + - Performs safe content checks before processing. +2. **AI Creativity Pipeline** + - Image Enhancement Agent: Upscales, denoises, applies lighting corrections, and composes collage thumbnails. + - Styling Agent: Suggests background removal or contextual scenes (e.g., staging furniture). + - Narrative Agent: Generates long-form descriptions leveraging a marketing RAG corpus + sentiment tuning for each marketplace. +3. **Marketplace Integrators** + - Channel-specific adapters for Craigslist, Mercari, Nextdoor, (extensible to Facebook Marketplace, OfferUp, etc.). + - Normalizes categories, pricing, shipping, and handles platform-specific throttling/anti-bot rules. +4. **Engagement Hub** + - Real-time messaging service bridging buyers (email/SMS/in-platform chat) with seller + negotiation agents. + - Shared timeline UI showing offers, counteroffers, and status changes. +5. **Lifecycle Controller** + - Tracks listing states (draft → scheduled → live → pending sale → closed). + - Automatically unlists from all channels once a purchase is confirmed. + +--- + +## 3. Agentic Workflow + +| Step | Agent | Description | LLM Model(s) | +| --- | --- | --- | --- | +| Intake | Concierge Agent | Confirms item details, requests missing info, runs safety checklist. | GPT-4o or Claude 3.5 Sonnet | +| Visual Polish | Vision Stylist & Enhancer | Applies upscaling, background cleanup, style transfer tuned per category. | Stable Diffusion XL / ControlNet + DeepSeek-VL for QA | +| Narrative Crafting | Listing Copywriter | Generates short + long descriptions, bullet highlights, SEO tags, shipping guidance. Uses RAG on market best practices. | GPT-4.1 / Gemini 1.5 Pro | +| Valuation | Pricing Analyst | Benchmarks with comps fetched via search APIs; suggests optimal price tiers. | Claude 3.5 Haiku + internal comps DB | +| Syndication | Channel Publisher | Maps listing to each platform’s schema, posts, and verifies success. | Tool-executing agent via FastAPI + Selenium/API | +| Engagement | Buyer Liaison | Monitors inquiries, drafts responses, escalates to seller when negotiation boundaries hit. | GPT-4o mini (fast) with guardrails | +| Closure | Lifecycle Steward | Detects sale confirmation, auto-closes all channels, generates pick-up instructions. | Rule-based + LLM verification | + +Agents communicate via the existing `call_subordinate` + `knowledge_tool` primitives, storing context in `memory`/`knowledge` for reuse (e.g., pricing heuristics, category guidelines). + +--- + +## 4. AI Pipeline Details + +### 4.1 Image Enhancement +- **Stages:** (1) quality assessment → (2) super-resolution (e.g., Real-ESRGAN) → (3) background cleanup (Matte-ing) → (4) lighting & color grading → (5) layout collage. +- **Outputs:** hero image, 3–5 gallery shots, detail zooms, and optional lifestyle composite scene. +- **Instrumentation:** Each step logs metrics (sharpness delta, noise reduction) for future fine-tuning. + +### 4.2 Description + Sentiment Crafting +- **Inputs:** Seller notes, extracted metadata (dimensions via OCR, brand logos, etc.), prior sales comps. +- **RAG Sources:** Marketing playbooks, brand tone guides, compliance docs per platform. +- **Outputs:** + - Title optimized for SEO, + - Rich paragraph + bullet list, + - Condition disclosures, + - Suggested hashtags and shipping/pickup text. +- **Tone Tuning:** Different prompt templates per platform (e.g., concise for Craigslist, lifestyle-forward for Nextdoor). + +### 4.3 Pricing & Strategy +- Pulls live comps via aggregator APIs (where permitted) or stored datasets. +- Generates price ladder (list price, “fast-sale” price, minimum acceptable). +- Feeds guardrails to Buyer Liaison (auto-approve offers above threshold, escalate otherwise). + +--- + +## 5. Marketplace Integrations + +| Platform | Integration Mode | Notes | +| --- | --- | --- | +| Craigslist | Headless browser automation (Playwright) + email relay for replies. | Needs CAPTCHA-solving strategy (vision model + manual fallback). | +| Mercari | Official API (if available) or mobile-app automation. | Supports shipping label creation; track order IDs. | +| Nextdoor | Web automation w/ community selection. | Monitor community guidelines to avoid spam flags. | +| Custom / Others | Modular adapters via interface `MarketplacePublisher`. | Easy to add OfferUp, eBay, Etsy later. | + +Failure handling: retries with exponential backoff, webhook-like callbacks to update listing state, and anomaly logging for manual review. + +--- + +## 6. Unified Seller Interface + +### UX Tenets +- **Organic Flow:** Minimal forms; conversational onboarding with dynamic checklists. +- **Zoom-like Collab:** Agents appear as avatars, announce actions (e.g., “Copywriter drafting Mercari description”). Seller can join live huddles to approve or tweak content. +- **Inbox View:** Threaded conversations grouped by platform and buyer; AI-suggested replies with quick-edit controls. +- **Visual Dashboard:** Pipeline status (Processing Images → Drafting → Live on X platforms), price ladder, performance analytics. + +### Tech Stack +- **Frontend:** React/Next.js or SvelteKit with WebSockets for live updates. +- **Backend:** Python FastAPI orchestrator running inside a slim container (e.g., distroless + uvicorn). Event-driven tasks handled by Celery/Redis or AWS SQS + Lambda workers. +- **Storage:** + - S3-compatible bucket for assets, + - Postgres for listings/offers, + - Redis/WebSocket gateway for live messaging, + - Vector DB (Qdrant/Pinecone) for RAG corpora. + +--- + +## 7. Serverless / Containerized Deployment + +| Layer | Option | Notes | +| --- | --- | --- | +| API + UI | AWS Lambda (FastAPI via Mangum) or Cloud Run | Handles synchronous interactions. | +| Workers | AWS Fargate / ECS tasks or Cloud Run Jobs | For heavier image/LLM workloads. | +| Event Bus | AWS SQS + EventBridge or Pub/Sub | Decouples ingestion from processing. | +| Media Processing | AWS Lambda w/ GPU (if available) or attached GPU service | For rapid diffusion-based adjustments. | + +CI/CD builds a single container image (FastAPI + worker binaries) pushed to ECR/GCR. Infrastructure-as-code (Terraform/Pulumi) provisions queues, storage, and secrets. + +--- + +## 8. Data & Knowledge Fabric +- **Knowledge Packs:** + - Marketing best practices, + - Platform policy summaries, + - Visual staging tips per category. +- **RAG Pipeline:** + 1. Seller intent + item metadata → embed → retrieve from vector DB, + 2. Feed retrieved snippets into Copywriter prompts, + 3. Store resulting listing in `memory/solutions` for future reuse. +- **Personalization:** Seller preferences (tone, negotiation style) saved to memory and loaded automatically when they return. + +--- + +## 9. Implementation Roadmap + +1. **Foundations** + - Spin up FastAPI skeleton + auth. + - Configure storage buckets, DB, and vector store. +2. **AI Pipeline MVP** + - Integrate image enhancer (ESRGAN) + background removal. + - Build Copywriter agent with GPT-4o + RAG from initial corpus. +3. **Marketplace Adapter Framework** + - Define `MarketplacePublisher` interface. + - Implement Craigslist + Mercari to validate both automation styles. +4. **Engagement Hub** + - Real-time messaging API + UI view. + - Buyer Liaison agent with guardrails + escalation rules. +5. **Lifecycle & Automation** + - Listing state machine, auto-closing logic, unified analytics. +6. **Serverless Packaging** + - Containerize, add IaC, deploy to sandbox environment. +7. **UX Polish** + - Zoom-like collaboration room, hero dashboard, onboarding wizards. +8. **Compliance & Monitoring** + - Logging, anomaly detection, rate-limit watchdogs, content moderation pipeline. + +--- + +## 10. Future Enhancements +- **Smart Negotiation:** Reinforcement-learning agent tuned on successful deal histories. +- **Buyer Discovery:** Cross-post to social channels with auto-generated reels/stories. +- **Shipment Automation:** Integration with UPS/FedEx APIs for instant label creation. +- **Reputation Engine:** Aggregate feedback across platforms to build seller trust profiles. +- **Predictive Demand:** Recommend best posting windows and price adjustments based on market trends. + +This blueprint provides a detailed path to a serverless, AI-native listing concierge that delights sellers and scales across marketplaces with minimal manual effort.