Skip to main content

MangoDesk CLI

A wrapper around tau-bench that adds cloud dashboard and trajectory tracking capabilities.

Installation

# Using pipx (recommended)
pipx install mangodesk

# Using pip
pip install mangodesk

Updating

# Using pipx
pipx upgrade mangodesk

# Using pip
pip install --upgrade mangodesk

Quick Start

# 1. Initialize tau-bench (clones and installs the repository)
mangodesk init

# 2. Set your API keys
mangodesk set MANGO_API_KEY=sk-mango-xxx      # From https://mangodesk-api-ezq8.onrender.com
mangodesk set OPENAI_API_KEY=sk-xxx           # For OpenAI models
mangodesk set ANTHROPIC_API_KEY=sk-xxx        # For Anthropic models

# 3. Run evaluation
mangodesk eval --env retail --model gpt-4o --model-provider openai

# 4. View results in the dashboard
# The URL is printed after the evaluation completes

Commands

Initialize tau-bench

# Clone to ~/.mangodesk/tau-bench (default)
mangodesk init

# Clone to a custom location
mangodesk init /path/to/tau-bench

Downloads and installs the tau-bench repository.

Run evaluation

mangodesk eval --env <environment> --model <model> [options]

Required:

  • --env, -e - Environment name (retail, airline, telecom)
  • --model, -m - Model name (e.g., gpt-4o, claude-3-5-sonnet)

Optional:

  • --model-provider, -p - Model provider (openai, anthropic, google, mistral). Auto-detected from model name.
  • --agent-strategy - Agent strategy: tool-calling (default), react, act
  • --user-model - User simulator model (defaults to --model)
  • --user-model-provider - User simulator provider (defaults to --model-provider)
  • --user-strategy - User strategy: llm (default), react, verify, reflection
  • --max-concurrency - Parallel task execution (default: 1)
  • --task-ids, -t - Comma-separated list of task IDs to run
  • --trials - Number of trials per task for pass^k metrics (default: 1)
  • --no-upload - Skip uploading results to MangoDesk cloud
  • --tau-bench-path - Path to tau-bench installation (auto-detected)

Examples:

# Basic evaluation
mangodesk eval --env retail --model gpt-4o --model-provider openai

# With Anthropic Claude
mangodesk eval --env airline --model claude-3-5-sonnet --model-provider anthropic

# Full configuration
mangodesk eval --env retail \
    --model gpt-4o --model-provider openai \
    --user-model gpt-4o --user-strategy llm \
    --agent-strategy tool-calling \
    --max-concurrency 10

# Run specific tasks
mangodesk eval --env retail -m gpt-4o -p openai --task-ids 1,2,3

# Multiple trials for pass^k metrics
mangodesk eval --env retail -m gpt-4o -p openai --trials 3

Configuration

# Set a configuration value
mangodesk set KEY=value

# View current configuration
mangodesk config

Configuration Keys:

  • MANGO_API_KEY - MangoDesk API key for cloud upload
  • OPENAI_API_KEY - OpenAI API key
  • ANTHROPIC_API_KEY - Anthropic API key
  • TAU_BENCH_PATH - Path to tau-bench installation
  • API_URL - MangoDesk API URL (for self-hosted)

tau-bench Environments

MangoDesk supports all tau-bench environments:

  • retail - E-commerce customer service
  • airline - Flight booking and management
  • telecom - Telecommunications support

See the tau-bench repository for environment details.

License

Proprietary - Copyright © MangoDesk Inc. All rights reserved.

Metadata

Release files for mangodesk 0.5.4

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for mangodesk 0.5.4
File Size Uploaded Provenance Actions
mangodesk-0.5.4.tar.gz 13.6 kB With provenance Details for mangodesk-0.5.4.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for mangodesk 0.5.4
File Interpreter ABI Platform Actions
mangodesk-0.5.4-py3-none-any.whl Python 3 none any Details for mangodesk-0.5.4-py3-none-any.whl

Total release size: 30.3 kB

Release files / mangodesk-0.5.4.tar.gz

Download URL mangodesk-0.5.4.tar.gz
Size 13.6 kB
Tags Source
SHA-256 checksum
How to use checksums
cfbbaada274051c6bea14afe6b532c67230066574ec3c173dd6ccb0c1de36bab
BLAKE2b-256 checksum
How to use checksums
64e60e7885f29b71d938023376ca9778e88079a3901aab81e0c3f5163231a142
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jan 2, 2026.

Transparency log

Release files / mangodesk-0.5.4-py3-none-any.whl

Download URL mangodesk-0.5.4-py3-none-any.whl
Size 16.7 kB
Tags Python 3
SHA-256 checksum
How to use checksums
ff93a855c9da7f7725bb578502002170904227f5b5ff038307fbdf628d63be03
BLAKE2b-256 checksum
How to use checksums
c3ffb7350b679ec672efba8832f796fe856758906609def25109ed4296a52db0
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
Yes
Uploaded via twine/6.1.0 CPython/3.13.7

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jan 2, 2026.

Transparency log

Security for mangodesk 0.5.4

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

Full provenance

All 2 files in this release have been uploaded with provenance metadata.

Select from 2 files

Attestation for mangodesk-0.5.4.tar.gz

PyPI Publish Attestation

PyPI verified that this artifact, at this checksum, originated from the publisher listed below.

Signed by GitHub Actions, verified by PyPI on Jan 2, 2026.

Transparency log

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page