ProspectAI - Multi-Agent Investment Analysis System

Overview

ProspectAI is a multi-agent investment analysis system built on the CrewAI framework. It leverages four specialized AI agents to provide comprehensive investment recommendations through a systematic analysis workflow. The system supports Anthropic Claude models (default) and local Ollama models.

Current release: v1.0.1

⚠️ Important Disclaimer

ProspectAI is built for educational purposes to help developers get initiated in Agentic AI development.

🚨 INVESTMENT WARNING: This tool should NOT be used as an investment tool without proper knowledge of the investment domain. The analysis provided is for educational demonstration of AI capabilities and should not be considered as financial advice. Always consult with qualified financial professionals before making investment decisions.

Features

• Multi-Agent System: Four specialized AI agents for different aspects of investment analysis
• Anthropic Claude: Powered by Claude models (Sonnet, Opus) by default
• Ollama Support: Run fully locally with Ollama models
• Real Reddit Integration: Live Reddit sentiment analysis using public JSON endpoints — no credentials required
• Sector Analysis: Analyze 5 major sectors (Technology, Healthcare, Finance, Energy, Consumer)
• Command-Line Interface: Easy-to-use CLI with flexible configuration
• Environment-Based Config: Secure .env-based configuration with startup validation
• Structured Output: Consistent, machine-readable JSON analysis results
• CrewAI Framework: Professional multi-agent orchestration via LiteLLM

Architecture

The system consists of four specialized agents working in sequence:

MarketAnalystAgent → TechnicalAnalystAgent → FundamentalAnalystAgent → InvestorStrategicAgent

Each agent receives the full output of all prior agents as context.

Market Analyst Agent

• Purpose: Entry point of the investment pipeline
• Function: Analyzes Reddit discussions to identify trending stocks at the current moment in time, incorporating macro/geopolitical context
• Data Sources: Reddit public JSON API with Serper web search as fallback
• Output: Top 5 candidate stocks with sentiment scores and relevance metrics

Technical Analyst Agent

• Purpose: Quantitative technical analysis
• Function: Runs 13+ technical indicators per ticker using yfinance + ta library
• Indicators: RSI, MACD, Bollinger Bands, ATR, SMA, EMA, VWAP, ADX, and more
• Output: Per-stock signals, momentum scores (1–10), risk levels, entry zones, stop-loss levels

Fundamental Analyst Agent

• Purpose: Financial statement and valuation analysis
• Function: Fetches real P/E, margins, debt ratios, FCF, and growth rates via yfinance
• Output: Valuation grades (CHEAP/FAIR/EXPENSIVE), financial health ratings, growth outlook

Investor Strategic Agent

• Purpose: Final synthesis and portfolio construction
• Function: Applies the composite score formula and builds portfolio allocations
• Composite Score: 30 pts sentiment + 40 pts momentum + 30 pts fundamentals (max 100)
• Recommendations: STRONG_BUY / BUY / HOLD / REDUCE / AVOID
• Output: Machine-readable JSON with allocation percentages summing to 100%

Installation

Prerequisites

• Python 3.9+
• An Anthropic API key or a local Ollama installation

Install via pip

pip install prospectai

That's it. All dependencies (CrewAI, yfinance, ta, requests, etc.) are installed automatically.

Configure Environment

Create a .env file in the directory where you'll run prospectai:

# Anthropic [REQUIRED]
ANTHROPIC_API_KEY=your_key_here
ANTHROPIC_MODEL=claude-sonnet-4-6

# Serper web search — used as fallback when Reddit returns no results [RECOMMENDED]
SERPER_API_KEY=your_key_here

# Ollama [OPTIONAL] — only needed when running with --ollama
OLLAMA_BASE_URL=http://localhost:11434
OLLAMA_MODEL=qwen3.5:9b

Reddit credentials are no longer required. ProspectAI uses Reddit's public JSON endpoints directly.

Getting your API keys

• Anthropic: console.anthropic.com
• Serper (optional fallback): serper.dev

Ollama setup (optional — local models)

# Install Ollama
# https://ollama.com/download

ollama serve
ollama pull qwen3.5:9b

Usage

# Analyze Technology sector (default)
prospectai

# Analyze a specific sector
prospectai --sector Healthcare
prospectai --sector Finance
prospectai --sector Energy
prospectai --sector Consumer

# Override the Claude model for a single run
prospectai --model claude-opus-4-6 --sector Technology

# Use a local Ollama model
prospectai --ollama --sector Technology
prospectai --ollama --model llama3.2:8b --sector Healthcare
prospectai --ollama --url http://192.168.1.100:11434 --sector Finance

CLI Reference

Configuration

Environment Variables

Anthropic Claude Models

Ollama Models

Per-Agent Model Override

Each agent can use a different model by editing config/agents.yaml inside the package, or by placing an overriding agents.yaml in your working directory. Example:

market_analyst:
  llm:
    provider: "anthropic"
    model: "claude-opus-4-6"   # Opus for the most context-heavy agent

technical_analyst:
  llm:
    provider: "anthropic"
    model: "claude-sonnet-4-6"

See AGENT_LLM_CONFIGURATION.md for full details.

Development

To contribute or run from source:

git clone https://github.com/moisesprat/ProspectAI.git
cd ProspectAI
python -m venv .venv
source .venv/bin/activate       # Windows: .venv\Scripts\activate
pip install -e .

After installing in editable mode the prospectai command is available and picks up any local changes immediately.

Project Structure

ProspectAI/
├── agents/                          # AI agent implementations
│   ├── base_agent.py
│   ├── market_analyst_agent.py
│   ├── technical_analyst_agent.py
│   ├── fundamental_analyst_agent.py
│   └── investor_strategic_agent.py
├── config/
│   ├── agents.yaml                  # Agent behavior (role, goal, model, temperature)
│   ├── tasks.yaml                   # Task definitions (descriptions, output schemas)
│   ├── agent_config_loader.py
│   ├── task_config_loader.py
│   └── config.py
├── utils/
│   ├── reddit_sentiment_tool.py     # Reddit public JSON sentiment tool
│   ├── technical_analysis_tool.py
│   └── fundamental_data_tool.py
├── tests/
├── main.py                          # CLI entry point (prospectai command)
├── prospect_ai_crew.py              # CrewAI orchestration
├── pyproject.toml
└── README.md

Running Tests

python tests/test_skeleton.py
python tests/test_reddit_output.py Technology
python tests/test_technical_analyst.py
python tests/test_market_analyst_llm.py

Building and Publishing

pip install build twine
python -m build
twine upload dist/*

Troubleshooting

Roadmap

v1.1 - Enhanced Market Analysis

• Integration with financial news APIs (Bloomberg, Reuters)
• Real-time market sentiment from multiple sources
• Enhanced sector rotation analysis

v1.2 - Agent Improvements

• Enhanced financial modeling capabilities
• More sophisticated valuation algorithms
• Advanced portfolio optimization

v1.3 - Advanced Risk Management

• Monte Carlo simulations for portfolio scenarios
• Advanced risk metrics (VaR, CVaR, Sharpe ratios)
• Dynamic risk adjustment based on market conditions

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes with tests where applicable
4. Submit a pull request

License

MIT License — see LICENSE for details.

Acknowledgments

• Built on the CrewAI framework
• LLM routing via LiteLLM
• Inspired by modern multi-agent AI systems
• Author webpage