unsubbed.co

Parlant

The conversational control layer for customer-facing AI agents

Overview

The conversational control layer for customer-facing AI agents - Parlant is a context-engineering framework optimized for controlling customer interactions. The conversational control layer for customer-facing AI agents The project has 18K+ GitHub stars and is licensed under Apache-2.0.

Key Features

Source: GitHub README

  • Guidelines
  • Relationships
  • Journeys
  • Canned Responses
  • Tools
  • Glossary
  • Explainability

Getting Started

Source: GitHub README

pip install parlant
import parlant.sdk as p

async with p.Server():
    agent = await server.create_agent(
        name="Customer Support",
        description="Handles customer inquiries for an airline",
    )

    # Evaluate and call tools only under the right conditions
    expert_customer = await agent.create_observation(
        condition="customer uses financial terminology like DTI or amortization",
        tools=[research_deep_answer],
    )

    # When the expert observation holds, always respond
    # with depth. Set the guideline to automatically match
    # whenever the observation it depends on holds...
    expert_answers = await agent.create_guideline(
        matcher=p.MATCH_ALWAYS,
        action="respond with technical depth",
        dependencies=[expert_customer],
    )

    beginner_answers = await agent.create_guideline(
        condition="customer seems new to the topic",
        action="simplify and use concrete examples",
    )

    # When both match, beginners wins. Neither expert-level
    # tool-data nor instructions can enter the agent's context.
    await beginner_answers.exclude(expert_customer)

Normalized Features

Source: tool-features-normalized.json

charts, pip.

Features

Analytics & Reporting

  • Charts & Graphs