Dispatch — Autonomous AI Task Engine

Dispatch tasks. AI handles the rest.

Dispatch is a production-grade autonomous AI agent built on LangGraph. It accepts a natural-language task and a success criteria, then autonomously browses the web, executes code, searches, and manages files — looping until an evaluator agent confirms the work is done.

---

Features

• Autonomous worker–evaluator loop — the worker executes the task; a separate evaluator scores the result against your criteria and either accepts or sends feedback for another attempt
• Rich tool suite — Playwright web browsing, Python REPL, file management, Google Serper web search, Wikipedia
• Multi-session — each browser tab gets its own isolated agent session
• Config-driven tool toggles — enable or disable any tool via environment variables; no code changes needed
• Push notifications via Pushover when a long task completes
• Structured logging — rotating file + stderr, DEBUG level to file
• Retry logic — automatic exponential backoff on transient LLM API failures
• Async throughout — fully async/await from UI to LLM calls

---

Architecture

Gradio UI
    │
    └── SessionManager (one DispatchAgent per user session)
            │
            └── DispatchAgent
                    │
                    └── LangGraph workflow
                            ┌───────────────────────────────┐
                            │  START → worker               │
                            │     ↓ (tool calls?)           │
                            │  tools → worker (loop)        │
                            │     ↓ (text reply)            │
                            │  evaluator                    │
                            │     ↓ (criteria met?)         │
                            │  END  ──or──  worker (retry)  │
                            └───────────────────────────────┘

---

Quickstart

1. Clone and install

git clone https://github.com/neerajaanil/dispatch-agent.git
cd dispatch
pip install -r requirements.txt
playwright install chromium

2. Configure

cp .env.example .env
# Edit .env — at minimum set OPENAI_API_KEY

3. Run

python app.py
# or
dispatch run

Open http://localhost:7860 in your browser.

---

Configuration

All settings use the DISPATCH_ prefix and can be set in .env or as environment variables.

Variable	Default	Description
OPENAI_API_KEY	(required)	OpenAI API key
DISPATCH_WORKER_MODEL	gpt-4o-mini	LLM for the worker agent
DISPATCH_EVALUATOR_MODEL	gpt-4o-mini	LLM for the evaluator
DISPATCH_MAX_ITERATIONS	10	Max worker iterations before forcing a stop
DISPATCH_ENABLE_BROWSER	true	Playwright web browsing
DISPATCH_HEADLESS_BROWSER	true	Run browser headlessly
DISPATCH_ENABLE_FILE_TOOLS	true	Read/write files in sandbox/
DISPATCH_ENABLE_CODE_EXECUTION	true	Python REPL
DISPATCH_ENABLE_SEARCH	false	Google Serper + Wikipedia (requires SERPER_API_KEY)
DISPATCH_ENABLE_NOTIFICATIONS	false	Pushover push notifications
SERPER_API_KEY	—	Serper API key
DISPATCH_PUSHOVER_USER	—	Pushover user key
DISPATCH_PUSHOVER_TOKEN	—	Pushover app token

---

Programmatic usage

import asyncio
from dispatch import DispatchAgent

async def main():
    async with DispatchAgent() as agent:
        history = await agent.run(
            message="What are the top 3 trending Python repos on GitHub today?",
            success_criteria="Include repo name, stars, and a one-line description for each.",
            history=[],
        )
    for msg in history:
        print(f"[{msg['role']}] {msg['content']}\n")

asyncio.run(main())

---

Development

pip install -e ".[dev]"
pytest

---

Commercial Applications

Use case	How
Research automation	Dispatch long-running web research tasks; get a push notification when done
Code generation & testing	Describe requirements; agent writes, validates, and saves to sandbox/
Data gathering pipelines	Browse + scrape + summarise across many pages autonomously
Internal tooling	Wrap with your own tools for domain-specific automation
SaaS wrapper	SessionManager already supports multi-user; add auth and billing

---

License

MIT