Open Source Google Dialogflow Alternatives
A curated collection of the 2 best open source alternatives to Google Dialogflow.
The best open source alternative to Google Dialogflow is Parlant. If that doesn't suit you, we've compiled a ranked list of other open source Google Dialogflow alternatives to help you find a suitable replacement. Other interesting open source alternative to Google Dialogflow is Botpress.
Google Dialogflow alternatives are mainly AI Development Platforms but may also be Automation or AI Interaction & Interfaces. Browse these if you want a narrower list of alternatives or looking for a specific functionality of Google Dialogflow.
Interaction control harness for customer-facing AI agents, giving teams precise behavioral control in regulated and high-stakes conversations.
Parlant is a Python harness for controlling how a customer-facing AI agent behaves. It targets the failure everyone meets in production: the more instructions you add to a system prompt, the faster the model stops paying attention to any of them, and routed graphs turn brittle the moment a real conversation wanders.
Instead of sending one large prompt followed by the raw conversation, the engine assembles a focused context on every turn. You define rules, knowledge and tools once, and the matching engine narrows what reaches the model down to what is relevant right now. Adding more rules therefore sharpens the agent rather than confusing it.
Behavior is defined in code through a handful of primitives.
- Guidelines: behavioral rules as condition and action pairs, evaluated fresh on each conversational turn.
- Relationships: dependencies and exclusions between guidelines, so one rule can suppress another and keep context tight.
- Journeys: multi-turn standard procedures that adapt to how a customer actually interacts.
- Canned responses: pre-approved templates that remove the chance of hallucination at the moments that matter.
- Glossary and tools: domain vocabulary the agent must know, plus external APIs called only when their observation matches.
Every guideline match and decision is traced through OpenTelemetry, which is what makes an answer explainable and auditable afterwards. Installation is a single pip install. The project aims at support, sales, onboarding and advisory agents in regulated domains such as finance, insurance, healthcare and telecom, and reports production deployments in banks.
Chatbot and assistant platform with a CLI, SDK and integration hub, for developers shipping conversational products on Botpress Cloud.
This repository is the open part of Botpress, a platform for building chatbots and assistants. Rather than the product itself, it holds the integrations published on the Botpress Hub, the developer tooling behind them, example bots written entirely as code, and the plugins the Studio will use.
Development starts with the Botpress CLI. Install it globally, run bp init to generate an integration from one of the templates, then edit the definition and implementation files it produces. A deploy pushes the current version into your workspace where every bot can use it, and a public deploy publishes it to the Hub, after which that version is frozen.
The repository is organized around four kinds of content.
- Integrations: the public integrations maintained by Botpress, open to community contributions and new submissions.
- Devtools: the CLI for building and deploying, a type-safe client for the APIs, and the SDK integrations are written against.
- Bots: examples built only from the client, SDK and CLI, offered as a programmatic route rather than the recommended one.
- Plugins: Studio plugins, listed in the repository as coming soon.
Local development needs git, Node.js and pnpm, plus the Microsoft Visual C++ redistributable on Windows, after which install, build and check all run as pnpm scripts. Everything here is MIT licensed. Questions about on-premise Botpress v12 belong in its own repository rather than this one.
