parlant

Build reliable customer-facing AI agents with Parlant: an interaction control harness optimized for controlled, consistent, and predictable LLM interactions.

GitHub Website

GraphCanon updated Sep 20, 2026 · GitHub synced Sep 20, 2026

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18k stars1.6k forksLast push Jul 12, 2026 Python Apache-2.0

Decision brief

Parlant is a specialized interaction control harness designed to ensure that AI agents, particularly those in customer service roles, behave predictably and align with predefined rules.

Good fit when

When you need precise control over the actions of AI agents based on specific conditions or observations.
For scenarios where responses must adapt to user behavior, such as distinguishing between technical experts and beginners among customers.

Avoid when

When the requirements for agent interactions do not demand granular rules based on observable user behavior or conditions, making this level of control unnecessary.
In cases where the flexibility and spontaneous responses from general-purpose LLMs are preferred without being restricted by controlled guidelines.

Pricing:: freemium - The open-source version offers community-supported functionalities which are free to use but might lack advanced support services.

Observed Jul 11, 2026 · Source: enrich:decision_facts

parlant alternatives Trust report

parlant vs botpress parlant vs composio parlant vs agentscope

Verify the decision

Maintenance and security

Full trust report

Maintenance: Steady (69d since push); As of Sep 20, 2026
Provenance: Not a fork · Organization account; As of Sep 20, 2026
Security (OSV): No lockfile; As of Sep 6, 2026

Public GitHub metadata and optional OSV scans. Signals, not a guarantee. Trust methodology.

Install

pip install parlant

PyPI

How it fits your stack(12)

Typed graph edges - alternatives, integrations, successors, and dependencies. Ranked by relationship type, not raw GitHub stars.

Alternative

agentscope

Agentscope is designed similarly to Parlant for building agents you can rely on for customer-facing interactions, emphasizing trust and understandability.

alternative

composio

Composio also builds AI agents that turn intent into action, offering an alternative to Parlant's approach for controlled and consistent LLM interactions.

alternative

LangBot

LangBot and Parlant both create AI agents for customer interaction, though the specific features and use cases they target might differ slightly.

alternative

Integrates

mem0

Parlant could potentially integrate with Mem0 as a universal memory layer for AI Agents to provide the necessary contextual information and continuity that Parlant's interaction control harness requires.

integrates

GenAI_Agents

GenAI_Agents provides a comprehensive repository for development and implementation which could integrate with Parlant to build production-ready AI-driven agents.

integrates

text-generation-inference

Text Generation Inference can be used as the backend for generating responses in Parlant, where it aids in building reliable customer-facing AI agents.

integrates

langflow

Both Parlant and langflow are aimed at building robust AI agents, though they serve slightly different focuses. LangFlow is more general-purpose and focuses on building workflows with AI, while Parlant emphasizes controlled, consistent LLM interactions for customer-facing services.

langchain

Parlant and LangChain both deal with the development of AI agents but from different angles. Parlant focuses on interaction control for customer-facing applications, whereas LangChain provides a broader platform for agent engineering.

prompt-optimizer

Both aim at improving AI agent reliability and performance but through different aspects: Prompt Optimizer by refining prompts, and Parlant by offering an observability framework ensuring reliable customer-facing agents.

Relationship graph

Optional deeper exploration of typed edges and category neighbours.

Similar tools

Same-category neighbours not already linked as typed edges.

anything-llm

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AgentGPT

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promptfoo

Test prompts, agents, and RAGs. Compare performance of various LLMs.

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Evidence and technical details

Sourced facts, taxonomy, compatibility claims, README excerpt, and machine-readable endpoints.

Overview

Parlant is a tool designed to create and manage AI agents for customer service purposes. It allows developers to define conditions under which specific agent actions are triggered or excluded, ensuring that responses are appropriate and in line with predefined guidelines.

Capability facts

CLI: CLI entrypoint
Source: pyproject.toml:[project.scripts] · Sep 20, 2026
Languages: python
Source: github.language+pyproject.toml · Sep 20, 2026

Graph entities

LangGraphframework DSPyframework

Compatibility

Sourced claims from the README excerpt - not unsourced marketing copy.

Python runtimePython

Source: README excerpt (regex_v1, Sep 20, 2026)

```python import parlant.sdk as p

Source link

README

Getting started Follow the 5 minute quickstart for a full walkthrough. License Apache 2.0 — free for commercial use. <div align="center" Try it now • Join Discord • Read the docs Built by the team at Emcie </div

For agents

This page has a .md twin and JSON over the API.

/tools/emcie-co-parlant.md GET /api/graphcanon/tools/emcie-co-parlant GET /api/graphcanon/graph?tool=emcie-co-parlant

parlant

Decision brief

Good fit when

Avoid when

Verify the decision

Maintenance and security

Install

How it fits your stack(12)

Alternative

Integrates

Related

Relationship graph

Similar tools

Evidence and technical details

Overview

Capability facts

Categories

Graph entities

Compatibility

Tags

README

For agents