FlowForge AI

An OpenEnv-compatible Reinforcement Learning environment for Enterprise Workflow Automation.

FlowForge simulates actual back-office operations where LLM agents act as automated HR/operations assistants, learning to synthesize information, manage tools, and recover from real-world errors.

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Key Features

• Genuine Enterprise Operations: Move beyond toy environments. Agents read files, search employee databases, run SQL queries, schedule meetings, and send emails.
• Strictly Defined Action Space: Validated entirely via Pydantic -- preventing hallucinatory tool calls.
• Task-Aware Reward Shaping: Dense reward signals that adapt based on the task (e.g., read_file is crucial for hard tasks, but optional for easy ones).
• Anti-Loop Architecture: Punishes infinite loops and duplicate actions to teach agents efficient planning.
• Zero-Cost Baseline: Run locally and test deterministically without eating up OpenAI credits.

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How it Works

graph TD
    A[LLM Agent] -->|Action JSON| B(FlowForge Environment)
    B -->|Validation| C{Valid Tool?}
    C -- No --> D[Error Observation + Negative Reward]
    C -- Yes --> E[Execute Tool]
    E --> F(State Tracker)
    F -->|Objective Check| G{Task Complete?}
    G -- Yes --> H[Success Observation + Finish Reward]
    G -- No --> I[Result Observation + Progress Reward]
    D --> A
    I --> A
    H --> J((Episode End))
    
    classDef default fill:#1f2937,stroke:#3b82f6,stroke-width:2px,color:#f3f4f6;
    classDef logic fill:#374151,stroke:#f59e0b,stroke-width:2px,color:#f3f4f6;
    classDef success fill:#064e3b,stroke:#10b981,stroke-width:2px,color:#d1fae5;
    classDef fail fill:#7f1d1d,stroke:#ef4444,stroke-width:2px,color:#fee2e2;

    class C,G logic;
    class H success;
    class D fail;

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Getting Started

Local Setup

# Set up a virtual environment
python -m venv .venv
source .venv/bin/activate

# Install dependencies
pip install -r requirements.txt

# Run the deterministic baseline inference (tests all 3 tasks)
python inference.py

Docker Deployment

# Build the image
docker build -t flowforge-ai .

# Run the container
docker run -p 7860:7860 --cpus=2 --memory=8g flowforge-ai

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Tech Stack

• Language: Python 3.11+
• RL Framework: OpenEnv-compatible Gymnasium interface
• Validation: Pydantic v2 for strict action schema enforcement
• Containerization: Docker with multi-stage builds
• LLM Integration: Supports any OpenAI-compatible API endpoint

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License

Distributed under the MIT License. See LICENSE for details.