If you're not sure which provider to start with, **we recommend [OpenAI](#openai)** as it's the most popular and has the **widest range of capabilities**: [💬 text-generation](./features.md#-text-generation) (incl. vision, incl. [🛠️ tools](./features.md#️-built-in-tools-openai-only)), [🖌️ image-generation](./features.md#️image-generation), [🦻 speech-to-text](./features.md#-speech-to-text), [🗣️ text-to-speech](./features.md#️-text-to-speech).
You don't need to choose just one though. The bot supports [mixing & matching models](./features.md#-mixing--matching-models), so you can use multiple providers at the same time.
3. 🤖 **Create one or more agents** in a given room or globally. Next to each provider in the [list below](#supported-providers) you'll see **🗲 Quick start** commands, but you may also refer to the [agent creation guide](./agents.md#creating-agents).
4. 🤝 **Set the new agent as a handler** for a given use-purpose like text-generation, image-generation, etc. The agent creation wizard will tell you how, but you may also refer to the [🤝 Handlers](./configuration/handlers.md) guide.
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/anthropic.yml).
[Groq](https://groq.com/) is an American company developing optimized Language Processing Units (LPU) and offering cloud service which runs various models (built by others) with very high performance.
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/groq.yml).
[LocalAI](https://localai.io/) is the free, Open Source OpenAI alternative. LocalAI act as a drop-in replacement REST API that’s compatible with OpenAI API specifications for local inferencing. It allows you to run LLMs, generate images, audio (and not only) locally or on-prem with consumer grade hardware, supporting multiple model families and architectures.
- 🆔 Identifier: `localai`
- 🔗 Links: [🏠 Home page](https://localai.io/), [📋 Models list](https://localai.io/gallery.html)
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/localai.yml).
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/mistral.yml).
[Ollama](https://ollama.com/) lets you run various models in a [self-hosted](https://github.com/ollama/ollama?tab=readme-ov-file#ollama) way. This is more advanced and requires powerful hardware for running some of the better models, but ensures your data stays with you.
- 🆔 Identifier: `ollama`
- 🔗 Links: [🏠 Home page](https://ollama.com/), [📋 Models list](https://ollama.com/library)
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/ollama.yml).
[OpenAI](https://openai.com/) is an American AI company providing powerful language models.
Use this provider either with the OpenAI API or with other OpenAI-compatible API services which **fully** adhere to the [OpenAI API spec](https://github.com/openai/openai-openapi/).
For services which are not fully compatible with the OpenAI API, consider using the [OpenAI Compatible](#openai-compatible) provider.
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/openai.yml).
This provider allows you to use OpenAI-compatible API services like [OpenRouter](https://openrouter.ai/), [Together AI](https://www.together.ai/), etc.
Some of these popular services already have **shortcut** providers (leading to this one behind the scenes) - this make it easier to get started.
This provider is just as featureful as the [OpenAI](#openai) provider, but is more compatible with services which do not fully adhere to the [OpenAI API spec](https://github.com/openai/openai-openapi/).
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/openai-compatible.yml).
[OpenRouter](https://openrouter.ai/) is a unified interface for LLMs. The platform scouts for the lowest prices and best latencies/throughputs across dozens of providers, and lets you choose how to [prioritize](https://openrouter.ai/docs/provider-routing) them.
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/openrouter.yml).
[Together AI](https://www.together.ai/) makes it easy to run or [fine-tune](https://docs.together.ai/docs/fine-tuning-overview) leading open source models with only a few lines of code.
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/together-ai.yml).
[Venice AI](https://venice.ai/chat?ref=kpXDe6) _(ref link with $10 bonus for you)_ runs inference on Venice-controlled GPUs or zero-data-retention partner infrastructure and stores no prompts or responses, so your conversations don't linger anywhere. It serves both frontier proprietary models and the latest open-source ones.
- 🌟 Capabilities: [🖌️ image-generation](./features.md#️-image-creation) (incl. editing, via the native knob-rich `/image/generate` and `/image/edit` endpoints), [💬 text-generation](./features.md#-text-generation) (incl. vision, file inputs like PDF and DOCX, and prompt caching; native web search via the `venice_parameters` config), [🗣️ text-to-speech](./features.md#️-text-to-speech), [🦻 speech-to-text](./features.md#-speech-to-text)
- create a room-local agent: `!bai agent create-room-local venice my-venice-agent`
- create a global agent: `!bai agent create-global venice my-venice-agent`
💡 When creating an agent, the bot will show you an up-to-date sample configuration for this provider which looks [like this](./sample-provider-configs/venice.yml).
Unlike the [OpenAI Compatible](#openai-compatible) provider (which can talk to Venice but drops images and can't reach its audio or native image endpoints), this is a first-class Venice integration that exposes Venice's full parameter set. Image generation uses the native `/image/generate` endpoint rather than the OpenAI-compatible `/images/generations` shim, so every Venice-specific knob below is available.
#### Configuration reference
Every parameter below is optional unless marked otherwise. Omitting a knob lets Venice apply its own server-side default; this is **not** the same as setting it to `false`, which actively sends `false`.
**`text_generation`** (top-level knobs) — sampling, caching, and reasoning controls that sit directly on `text_generation`, next to `model_id`, `prompt`, `temperature`, `max_response_tokens`, and `max_context_tokens`. They map to top-level fields on Venice's request, separate from the `venice_parameters` bag below.
| Knob | What it does | Default |
|------|--------------|---------|
| `top_p` | Nucleus sampling, `0.0`–`1.0`. An alternative to `temperature`. | — |
| `frequency_penalty` | Penalize tokens by how often they have already appeared, `-2.0`–`2.0`. | — |
| `presence_penalty` | Penalize tokens that have appeared at all, `-2.0`–`2.0`. | — |
| `reasoning_effort` | Reasoning budget for models that support it: `low`, `medium`, `high`. | — |
| `prompt_cache_retention` | How long Venice keeps the prompt prefix cached: `default`, `extended`, or `24h`. `24h` is the lever that makes a long, stable system prompt cheap across a day of conversations. | `24h` |
| `show_reasoning` | Append the model's reasoning (its `reasoning_content`) below the answer, as a collapsible `💭 Reasoning` block that stays folded until clicked. Reads a field separate from the answer text, so it works regardless of `strip_thinking_response`. | `false` |
**`text_generation.venice_parameters`** — Venice-specific request knobs sent in the `venice_parameters` bag. Set any of them to override Venice's behavior. The `Default` column shows the value baibot's sample config ships; a `—` means the knob is left unset, so Venice's own default applies.
| `model_id` | The Venice TTS model (e.g. `tts-kokoro`, `tts-qwen3-1-7b`, `tts-xai-v1`). | `tts-kokoro` |
| `voice` | The voice to synthesize with. Model-specific (Kokoro: `af_*`/`am_*`/`bf_*`/`bm_*`); a cloned-voice handle (`vv_<id>`) also works. | `af_sky` |
