This section gives an overview of the Generative AI capabilities in Hymalaia and how Large Language Models (LLMs) are integrated into the system.

​
LLM Options

Hymalaia supports a wide range of cloud-based and self-hosted LLMs:

​
✅ Cloud Providers Supported:

  • OpenAI (e.g., GPT-4, GPT-4o)
  • Anthropic (Claude 3.5 Sonnet)
  • Azure OpenAI
  • HuggingFace
  • Replicate
  • AWS Bedrock
  • Cohere
  • … and many more.

​
🏠 Self-Hosted Options:

  • Ollama
  • GPT4All
  • Any LLM compatible with OpenAI’s API format

Hymalaia relies on the excellent LiteLLM and Langchain libraries to support these integrations.

​
What are Generative AI (LLM) models used for?

LLMs are used to:

  • Interpret relevant documents retrieved via search
  • Extract useful knowledge from those documents
  • Generate human-readable answers to user queries

This is the core of Hymalaia AI Answering functionality.

​
What is the default LLM?

Our default recommendation is:

  • gpt-4 (OpenAI)
  • Claude 3.5 Sonnet (Anthropic)

Other high-quality recommended options:

  • Azure OpenAI
  • Claude via Bedrock
  • Self-hosted LLaMA 3.1 70B / 405B

These provide an excellent balance between quality, latency, and reliability.

​
Why use a different model?

There are several reasons to customize your LLM provider:

  • Use a cheaper or faster model (e.g., gpt-4o)
  • Select a provider with a more favorable data retention policy

    Note: OpenAI and Azure OpenAI retain logs for 30 days for misuse monitoring

  • Self-host your own model for full control and flexibility
  • Choose a fine-tuned model for a specific domain (e.g., legal, medical, technical)

🔐 Generative AI is the only part of Hymalaia that sends data to a third-party service.
You can avoid this by self-hosting a model — but note the potential performance tradeoffs.

​
Hymalaia LLM Configs

To configure LLMs:

  • Go to the Admin Panel > LLMs
  • Add or edit your model configurations

​
✨ Unique to Hymalaia:

You can set up multiple LLM providers and assign them to different assistants.
This allows you to mix and match models based on:

  • Speed
  • Quality
  • Specialization
  • Cost

​
Next Steps

Check out the following examples for how to configure specific LLM providers, or go to the Admin Panel to get started.

🙋 Need help? The Hymalaia team is here — don’t hesitate to reach out!

This section gives an overview of the Generative AI capabilities in Hymalaia and how Large Language Models (LLMs) are integrated into the system.

​
LLM Options

Hymalaia supports a wide range of cloud-based and self-hosted LLMs:

​
✅ Cloud Providers Supported:

  • OpenAI (e.g., GPT-4, GPT-4o)
  • Anthropic (Claude 3.5 Sonnet)
  • Azure OpenAI
  • HuggingFace
  • Replicate
  • AWS Bedrock
  • Cohere
  • … and many more.

​
🏠 Self-Hosted Options:

  • Ollama
  • GPT4All
  • Any LLM compatible with OpenAI’s API format

Hymalaia relies on the excellent LiteLLM and Langchain libraries to support these integrations.

​
What are Generative AI (LLM) models used for?

LLMs are used to:

  • Interpret relevant documents retrieved via search
  • Extract useful knowledge from those documents
  • Generate human-readable answers to user queries

This is the core of Hymalaia AI Answering functionality.

​
What is the default LLM?

Our default recommendation is:

  • gpt-4 (OpenAI)
  • Claude 3.5 Sonnet (Anthropic)

Other high-quality recommended options:

  • Azure OpenAI
  • Claude via Bedrock
  • Self-hosted LLaMA 3.1 70B / 405B

These provide an excellent balance between quality, latency, and reliability.

​
Why use a different model?

There are several reasons to customize your LLM provider:

  • Use a cheaper or faster model (e.g., gpt-4o)
  • Select a provider with a more favorable data retention policy

    Note: OpenAI and Azure OpenAI retain logs for 30 days for misuse monitoring

  • Self-host your own model for full control and flexibility
  • Choose a fine-tuned model for a specific domain (e.g., legal, medical, technical)

🔐 Generative AI is the only part of Hymalaia that sends data to a third-party service.
You can avoid this by self-hosting a model — but note the potential performance tradeoffs.

​
Hymalaia LLM Configs

To configure LLMs:

  • Go to the Admin Panel > LLMs
  • Add or edit your model configurations

​
✨ Unique to Hymalaia:

You can set up multiple LLM providers and assign them to different assistants.
This allows you to mix and match models based on:

  • Speed
  • Quality
  • Specialization
  • Cost

​
Next Steps

Check out the following examples for how to configure specific LLM providers, or go to the Admin Panel to get started.

🙋 Need help? The Hymalaia team is here — don’t hesitate to reach out!