Cursor buildllm token context protocol 593a

.github/workflows/python-publish.yml

@@ -0,0 +1,70 @@
+# This workflow will upload a Python Package to PyPI when a release is created
+# For more information see: https://docs.github.com/en/actions/automating-builds-and-tests/building-and-testing-python#publishing-to-package-registries
+
+# This workflow uses actions that are not certified by GitHub.
+# They are provided by a third-party and are governed by
+# separate terms of service, privacy policy, and support
+# documentation.
+
+name: Upload Python Package
+
+on:
+  release:
+    types: [published]
+
+permissions:
+  contents: read
+
+jobs:
+  release-build:
+    runs-on: ubuntu-latest
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: actions/setup-python@v5
+        with:
+          python-version: "3.x"
+
+      - name: Build release distributions
+        run: |
+          # NOTE: put your own distribution build steps here.
+          python -m pip install build
+          python -m build
+
+      - name: Upload distributions
+        uses: actions/upload-artifact@v4
+        with:
+          name: release-dists
+          path: dist/
+
+  pypi-publish:
+    runs-on: ubuntu-latest
+    needs:
+      - release-build
+    permissions:
+      # IMPORTANT: this permission is mandatory for trusted publishing
+      id-token: write
+
+    # Dedicated environments with protections for publishing are strongly recommended.
+    # For more information, see: https://docs.github.com/en/actions/deployment/targeting-different-environments/using-environments-for-deployment#deployment-protection-rules
+    environment:
+      name: pypi
+      # OPTIONAL: uncomment and update to include your PyPI project URL in the deployment status:
+      # url: https://pypi.org/p/YOURPROJECT
+      #
+      # ALTERNATIVE: if your GitHub Release name is the PyPI project version string
+      # ALTERNATIVE: exactly, uncomment the following line instead:
+      # url: https://pypi.org/project/YOURPROJECT/${{ github.event.release.name }}
+
+    steps:
+      - name: Retrieve release distributions
+        uses: actions/download-artifact@v4
+        with:
+          name: release-dists
+          path: dist/
+
+      - name: Publish release distributions to PyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          packages-dir: dist/

docs/README.md

@@ -5,6 +5,7 @@ To begin with Agent Zero, follow the links below for detailed guides on various
 - **[Installation](installation.md):** Set up (or [update](installation.md#how-to-update-agent-zero)) Agent Zero on your system.
 - **[Usage Guide](usage.md):** Explore GUI features and usage scenarios.
 - **[Architecture Overview](architecture.md):** Understand the internal workings of the framework.
+- **[Token Compression Protocol](token_compression_protocol.md):** Run the TCP service and integrate it with clients (including browser extensions).
 - **[Contributing](contribution.md):** Learn how to contribute to the Agent Zero project.
 - **[Troubleshooting and FAQ](troubleshooting.md):** Find answers to common issues and questions.
 
@@ -59,6 +60,7 @@ To begin with Agent Zero, follow the links below for detailed guides on various
   - [Making Changes](contribution.md#making-changes)
   - [Submitting a Pull Request](contribution.md#submitting-a-pull-request)
   - [Documentation Stack](contribution.md#documentation-stack)
+- [Token Compression Protocol](token_compression_protocol.md)
 - [Troubleshooting and FAQ](troubleshooting.md)
   - [Frequently Asked Questions](troubleshooting.md#frequently-asked-questions)
   - [Troubleshooting](troubleshooting.md#troubleshooting)

docs/autonomous_listing_service.md

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+# 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.
+
+---
+
+## 11. Co-Development with the Super Agency
+
+- **Mission Diary:** Maintain `docs/programs/autonomous_listing/journal.md` logging every experiment, release, and KPI shift so agents can learn from prior iterations.
+- **Improvement Backlog:** Share a prioritized list (`docs/programs/autonomous_listing/improvements.md`) that feeds into the agency-wide iterative protocol (see Section 15 of `autonomous_super_agency.md`).
+- **Telemetry Handoff:** Telemetry Sentinel publishes listing-service-specific health reports (conversion uplift, response latency, negotiation success rate) for Portfolio Navigator to review weekly.
+- **Prompt Sync:** Copywriter, Buyer Liaison, and Publisher persona prompts live under `prompts/super-agency/roles/listing_*` and reference the same change log as the broader agency to keep behavior updates auditable.
+- **Feedback Routing:** Any seller or buyer feedback entering the Engagement Hub is tagged and stored in `knowledge/custom/main/listings/` so the RAG corpus continuously reflects real-world voice-of-customer insights.
+- **Release Ritual:** Every deployment of the service includes a short “What changed / Metrics impacted / Next bet” record appended to the mission diary, ensuring synchronous evolution of the agency and this product line.
+
+This blueprint provides a detailed path to a serverless, AI-native listing concierge that delights sellers and scales across marketplaces with minimal manual effort.