265 lines
13 KiB
Markdown
265 lines
13 KiB
Markdown
<div align="center">
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<img src="./static/image/MiroFish_logo_compressed.jpeg" alt="MiroFish Logo" width="75%"/>
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<a href="https://trendshift.io/repositories/16144" target="_blank"><img src="https://trendshift.io/api/badge/repositories/16144" alt="666ghj%2FMiroFish | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
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简洁通用的群体智能引擎，预测万物
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</br>
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<em>A Simple and Universal Swarm Intelligence Engine, Predicting Anything</em>
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<a href="https://www.shanda.com/" target="_blank"><img src="./static/image/shanda_logo.png" alt="666ghj%2FMiroFish | Shanda" height="40"/></a>
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[](https://github.com/666ghj/MiroFish/stargazers)
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[](https://github.com/666ghj/MiroFish/watchers)
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[](https://github.com/666ghj/MiroFish/network)
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[](https://hub.docker.com/)
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[](https://deepwiki.com/666ghj/MiroFish)
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[](http://discord.gg/ePf5aPaHnA)
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[](https://x.com/mirofish_ai)
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[](https://www.instagram.com/mirofish_ai/)
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[English](./README.md) | [中文文档](./README-ZH.md)
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</div>
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## ⚡ Overview
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**MiroFish** is a next-generation AI prediction engine powered by multi-agent technology. By extracting seed information from the real world (such as breaking news, policy drafts, or financial signals), it automatically constructs a high-fidelity parallel digital world. Within this space, thousands of intelligent agents with independent personalities, long-term memory, and behavioral logic freely interact and undergo social evolution. You can inject variables dynamically from a "God's-eye view" to precisely deduce future trajectories — **rehearse the future in a digital sandbox, and win decisions after countless simulations**.
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> **This is a maintained fork** of [666ghj/MiroFish](https://github.com/666ghj/MiroFish). It swaps Zep Cloud for **Graphiti + FalkorDB** (open source, self-hosted), adds a one-call `POST /api/graph/ingest_text` API for cron automations, and ships a production Docker stack for `agent.profikid.nl`. See [About this fork](#-about-this-fork) below.
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> You only need to: Upload seed materials (data analysis reports or interesting novel stories) and describe your prediction requirements in natural language</br>
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> MiroFish will return: A detailed prediction report and a deeply interactive high-fidelity digital world
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### Our Vision
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MiroFish is dedicated to creating a swarm intelligence mirror that maps reality. By capturing the collective emergence triggered by individual interactions, we break through the limitations of traditional prediction:
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- **At the Macro Level**: We are a rehearsal laboratory for decision-makers, allowing policies and public relations to be tested at zero risk
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- **At the Micro Level**: We are a creative sandbox for individual users — whether deducing novel endings or exploring imaginative scenarios, everything can be fun, playful, and accessible
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From serious predictions to playful simulations, we let every "what if" see its outcome, making it possible to predict anything.
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## 🌐 Live Demo
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Welcome to visit our online demo environment and experience a prediction simulation on trending public opinion events we've prepared for you: [mirofish-live-demo](https://666ghj.github.io/mirofish-demo/)
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## 📸 Screenshots
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<div align="center">
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<table>
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<tr>
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<td><img src="./static/image/Screenshot/运行截图1.png" alt="Screenshot 1" width="100%"/></td>
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<td><img src="./static/image/Screenshot/运行截图2.png" alt="Screenshot 2" width="100%"/></td>
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</tr>
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<tr>
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<td><img src="./static/image/Screenshot/运行截图3.png" alt="Screenshot 3" width="100%"/></td>
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<td><img src="./static/image/Screenshot/运行截图4.png" alt="Screenshot 4" width="100%"/></td>
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</tr>
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<tr>
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<td><img src="./static/image/Screenshot/运行截图5.png" alt="Screenshot 5" width="100%"/></td>
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<td><img src="./static/image/Screenshot/运行截图6.png" alt="Screenshot 6" width="100%"/></td>
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</tr>
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</table>
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</div>
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## 🎬 Demo Videos
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### 1. Wuhan University Public Opinion Simulation + MiroFish Project Introduction
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<div align="center">
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<a href="https://www.bilibili.com/video/BV1VYBsBHEMY/" target="_blank"><img src="./static/image/武大模拟演示封面.png" alt="MiroFish Demo Video" width="75%"/></a>
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Click the image to watch the complete demo video for prediction using BettaFish-generated "Wuhan University Public Opinion Report"
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</div>
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### 2. Dream of the Red Chamber Lost Ending Simulation
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<div align="center">
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<a href="https://www.bilibili.com/video/BV1cPk3BBExq" target="_blank"><img src="./static/image/红楼梦模拟推演封面.jpg" alt="MiroFish Demo Video" width="75%"/></a>
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Click the image to watch MiroFish's deep prediction of the lost ending based on hundreds of thousands of words from the first 80 chapters of "Dream of the Red Chamber"
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</div>
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> **Financial Prediction**, **Political News Prediction** and more examples coming soon...
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## 🔄 Workflow
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1. **Graph Building**: Seed extraction & Individual/collective memory injection & GraphRAG construction
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2. **Environment Setup**: Entity relationship extraction & Persona generation & Agent configuration injection
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3. **Simulation**: Dual-platform parallel simulation & Auto-parse prediction requirements & Dynamic temporal memory updates
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4. **Report Generation**: ReportAgent with rich toolset for deep interaction with post-simulation environment
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5. **Deep Interaction**: Chat with any agent in the simulated world & Interact with ReportAgent
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## 🚀 Quick Start
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### Option 1: Source Code Deployment (Recommended)
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#### Prerequisites
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| Tool | Version | Description | Check Installation |
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|------|---------|-------------|-------------------|
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| **Node.js** | 18+ | Frontend runtime, includes npm | `node -v` |
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| **Python** | ≥3.11, ≤3.12 | Backend runtime | `python --version` |
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| **uv** | Latest | Python package manager | `uv --version` |
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#### 1. Configure Environment Variables
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```bash
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# Copy the example configuration file
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cp .env.example .env
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# Edit the .env file and fill in the required API keys
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```
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**Required Environment Variables:**
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```env
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# LLM API Configuration (supports any LLM API with OpenAI SDK format)
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# Recommended: MiniMax M-series via https://api.minimax.io/v1
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# - MiniMax-M2.7-highspeed : best for cron / high-volume (recommended)
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# - MiniMax-M3 : heavier reasoning, slower, higher quality
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# Alibaba Qwen-plus via Bailian Platform: https://bailian.console.aliyun.com/
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# High consumption, try simulations with fewer than 40 rounds first
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LLM_API_KEY=your_api_key
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LLM_BASE_URL=https://api.minimax.io/v1
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LLM_MODEL_NAME=MiniMax-M2.7-highspeed
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# Graph store (this fork: Graphiti + FalkorDB; no Zep API key needed)
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# FalkorDB runs as a Docker sidecar — see deploy/docker-compose.yml
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FALKORDB_HOST=falkordb
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FALKORDB_PORT=6379
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# Embedding model (local sentence-transformers, pre-downloaded in the image)
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EMBEDDING_MODEL=sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2
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```
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#### 2. Install Dependencies
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```bash
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# One-click installation of all dependencies (root + frontend + backend)
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npm run setup:all
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```
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Or install step by step:
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```bash
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# Install Node dependencies (root + frontend)
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npm run setup
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# Install Python dependencies (backend, auto-creates virtual environment)
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npm run setup:backend
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```
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#### 3. Start Services
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```bash
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# Start both frontend and backend (run from project root)
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npm run dev
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```
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**Service URLs:**
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- Frontend: `http://localhost:3000`
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- Backend API: `http://localhost:5001`
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**Start Individually:**
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```bash
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npm run backend # Start backend only
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npm run frontend # Start frontend only
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```
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### Option 2: Docker Deployment
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```bash
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# 1. Configure environment variables (same as source deployment)
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cp .env.example .env
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# 2. Pull image and start
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docker compose up -d
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```
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Reads `.env` from root directory by default, maps ports `3000 (frontend) / 5001 (backend)`
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> Mirror address for faster pulling is provided as comments in `docker-compose.yml`, replace if needed.
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## 📬 Join the Conversation
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<div align="center">
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<img src="./static/image/QQ群.png" alt="QQ Group" width="60%"/>
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</div>
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The MiroFish team is recruiting full-time/internship positions. If you're interested in multi-agent simulation and LLM applications, feel free to send your resume to: **mirofish@shanda.com**
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## 📄 Acknowledgments
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**MiroFish has received strategic support and incubation from Shanda Group!**
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MiroFish's simulation engine is powered by **[OASIS (Open Agent Social Interaction Simulations)](https://github.com/camel-ai/oasis)**, We sincerely thank the CAMEL-AI team for their open-source contributions!
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## 🔱 About this fork
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This is a maintained fork of [666ghj/MiroFish](https://github.com/666ghj/MiroFish) maintained at [profikid/MiroFish](https://github.com/profikid/MiroFish). It replaces the Zep Cloud dependency with **Graphiti + FalkorDB** (both open source), adds a one-call ingest API, and ships a production-ready Docker deployment for `agent.profikid.nl`.
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### What changed vs upstream
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| | Upstream | This fork |
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| --- | --- | --- |
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| Graph store | Zep Cloud (managed, requires API key) | Graphiti + FalkorDB (self-hosted, Redis protocol) |
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| LLM recommendation | Qwen-plus (DashScope) | MiniMax M-series (M2.7-highspeed for cron, M3 for high-quality) |
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| Ingest API | 3 calls (project → ontology → build) | 1 call: `POST /api/graph/ingest_text` (project + ontology + build) |
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| Deploy | `npm run dev` (dev) / `docker compose up` (Docker Hub) | `deploy/` overlay: Traefik + Let's Encrypt + FalkorDB sidecar + e2e one-shot |
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| E2E test | none shipped | `deploy/e2e_test.py` + `deploy/e2e.sh` (builds a one-shot image, runs against the real briefing seed) |
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| Cron-friendly | not designed for it | `deploy/mirofish_ingest.sh` — one-shot POST + poll, exits 0/2/3/4 |
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| Embeddings | Zep-managed | local `sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2` (pre-downloaded in the image) |
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### Why Graphiti + FalkorDB
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Zep Cloud's free tier is fine for dev, but for a self-hosted cron pipeline (Iran briefing every 12h, entity extraction, simulations) you want:
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- **No per-month API cap** — the cron keeps running on bad days, good days, news spikes
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- **No external service dependency** — graph store lives next to the app as a Docker sidecar
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- **Same engine** — Graphiti is the open-source core that powers Zep Cloud, so the entity/edge quality is identical
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The `backend/app/services/graphiti_service.py` shim is a Zep-shaped facade over a real `Graphiti(graph_driver=FalkorDriver(...))`, so the rest of the MiroFish codebase (which still speaks Zep) didn't have to change.
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### Production deployment
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The `deploy/` directory contains a single-host Docker stack for `agent.profikid.nl`:
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```bash
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# On the host:
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cd /docker/mirofish
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./deploy/up.sh # build image, bring up mirofish + falkordb
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./deploy/e2e.sh # run the e2e test against the real briefing seed
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```
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Traefik (already on the host) auto-issues the Let's Encrypt cert for `mirofish.agent.profikid.nl`. See [deploy/README.md](./deploy/README.md) for the full layout, env vars, and troubleshooting.
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### Cron integration
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The fork was built so that a scheduled OSINT briefing cron can drop the markdown output straight into MiroFish:
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```bash
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# Cron's last-written briefing file -> POST + poll
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briefing="$(ls -t /home/hermes/.hermes/cron/output/<job_id>/*.md | head -1)"
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nohup bash /docker/mirofish/deploy/mirofish_ingest.sh \
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"iran-osint-$(date -u +%Y%m%dT%H%M)" \
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"$briefing" \
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>/tmp/mirofish-ingest.log 2>&1 &
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```
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The script handles ontology generation + async graph build + polling, exits 0 on success with a `nodes=N edges=M` summary in the log.
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## 📈 Project Statistics
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<a href="https://www.star-history.com/#666ghj/MiroFish&type=date&legend=top-left">
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<picture>
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<source media="(prefers-color-scheme: dark)" srcset="https://api.star-history.com/svg?repos=666ghj/MiroFish&type=date&theme=dark&legend=top-left" />
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<source media="(prefers-color-scheme: light)" srcset="https://api.star-history.com/svg?repos=666ghj/MiroFish&type=date&legend=top-left" />
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<img alt="Star History Chart" src="https://api.star-history.com/svg?repos=666ghj/MiroFish&type=date&legend=top-left" />
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</picture>
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</a> |