MarketFish – Simulate a market with 128 AI consumers before you launch
MarketFish is a multi-agent market simulation engine built on 6 academic papers and 11 LLM providers. It creates 128 AI consumers with unique identities, budgets, emotions, and biases, then simulates their shopping behavior over 30 rounds to predict product success. Offers Explore, Validate, and Hybrid modes.
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Don't guess. Simulate.
Before you launch, let hundreds of AI consumers vote with their wallets.
MarketFish is a multi-agent market simulation engine. Instead of asking one LLM "will this product succeed?", it builds a digital market with 128+ AI consumers — each with their own identity, budget, emotions, and biases — and lets them shop across 30 rounds. Their purchase decisions, churn patterns, and social influence reveal what real users would do.
Built on 6 academic papers (Generative Agents, OASIS, TwinMarket, Agent Bazaar, EconSimulacra, SMIF) and 11 LLM providers.
中文文档
Quick Start
git clone https://github.com/Key-wxh/market-fish.git cd market-fish cp .env.example .env
Edit .env — add at least ONE LLM API key (DeepSeek is cheapest)
pip install -r requirements.txt streamlit run streamlit_app.py
Open http://localhost:8501 → pick a mode → run.
Screenshots
How It Works
Seed Data (static JSON) → 5-Stage Pipeline
- Ontology — extract market structure
- Knowledge Graph — entities, relationships, pain points
- Agent Factory — 128 heterogeneous AI consumers (6 LLMs)
- Simulation — 30 rounds: decisions, coupling, RL, memory
- Report — evidence: who bought, why, what killed competitors
V6 Modules (6 papers implemented)
Module Paper What it does
Memory Generative Agents (UIST 2023) Agents remember purchases, regrets, reflections
Time Engine OASIS (2025) Realistic 24h activation — not all active every round
RecSys OASIS (2025) Personalized product recommendations
BDI v2 TwinMarket (NeurIPS 2025) 6-step cognitive loop + behavioral biases
Stress EconSimulacra (2026) Financial/social pressure → adjusted willingness to pay
Grounding SMIF (ETASR 2026) RAG + rule constraints for realistic decisions
Modes
Mode Input Output
🔍 Explore Seed data AI discovers product directions, ranked
✅ Validate Your product idea Survival score, buyer profiles, optimal price
⚔️ Hybrid Your product + data Your idea vs AI competitors, same sandbox
Supported LLM Providers
11 providers. One is enough. More = more diverse agents.
| 🇨🇳 China | DeepSeek, Qwen, Doubao, Zhipu, Baidu, Hunyuan | | 🌍 Global | OpenAI, Anthropic, Google, Mistral, Meta |
CLI
python run.py --mode explore # Discover directions python run.py --mode validate --name "My App" --pricing "$10" # Test your idea python run.py --mode explore --reuse-agents # Reuse agents (save cost)
Project Structure
market-fish/ ├── engine/ # Core engine (20+ modules) │ ├── simulator.py, agent_factory.py # Simulation core │ ├── agent_store.py, memory.py # V6: persistence + memory │ ├── temporal.py, recsys.py # V6: time + recommendations │ ├── bdi_v2.py, stress.py, grounding.py # V6: cognition + stress + validation ├── config/ # Model registry + parameters ├── locales/ # EN/ZH i18n (300+ keys) ├── tests/ # 26/26 tests ├── streamlit_app.py # Dashboard ├── run.py # CLI └── .env.example # API key template
Academic Foundation
Paper Venue ID Module
Generative Agents UIST 2023 2304.03442 Memory
OASIS 2025 2411.11581 RecSys + TimeEngine
SMIF ETASR 2026 10.48084/etasr.16536 Grounding
Agent Bazaar Princeton 2026 2605.17698 RL
TwinMarket NeurIPS 2025 2502.01506 BDI v2
EconSimulacra 2026 2606.26883 Stress
vs MiroFish
MiroFish (5.5k ⭐) is the most well-known multi-agent simulation engine. Both projects simulate social/market behavior with AI agents — but with different focuses:
MiroFish MarketFish
Scope General-purpose social simulation Product market prediction
Architecture Flask + Node.js + Docker Streamlit single-app
Memory Zep Cloud (external service) Built-in (local JSON, zero external deps)
LLMs OpenAI-compatible only 11 providers (China + Global)
Data User-uploaded documents 8-source live ingestion pipeline
Language EN/ZH EN/ZH
License AGPL-3.0 MIT
License
MIT — free for personal and commercial use.
Built by Keystart AI · Solo founder · AI-Native
About
Dont guess. Simulate. Multi-agent market prediction engine.
Topics
simulation
multi-agent
agent-based-modeling
product-validation
ai-agents
streamlit
market-simulation
market-prediction
llm
generative-agents
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License
MIT license
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