Configuring model and data sources
To ensure that your AI delivers accurate results, it is crucial to select the right model and train it with relevant data sources. These data sources serve as the knowledge base for an AI.
Devs.ai offers you the flexibility to configure different models and types of data sources for your AI. You can upload various types of files from your computer, connect to cloud storage, or enter website URLs that can be indexed. Your AI can scan through all this information in no time to find solutions to your queries.
Select a language model (LLM)
When creating a new AI agent or editing an existing one, click Model to select a model for your agent.
Select from one of the following options:
| OpenAI | Anthropic | Perplexity | Meta | Cohere | xAI | |
|---|---|---|---|---|---|---|
| GPT-4 Omni | Claude 3.5 Sonnet | Gemini 1.5 Pro | Sonar | LLAMA 4 Maverick Instruct | Command | Grok 3 |
| GPT-4 Omni Mini | Claude 3.5 Haiku | Gemini 2.0 Flash | Sonar Pro | LLAMA 4 Scout Instruct | Command A | Grok 3 Mini |
| GPT-4.1 | Claude 3.7 Sonnet | Gemini 2.0 Flash-Lite | Sonar Reasoning | Command-R Plus | Grok 2 | |
| GPT-4.1 Mini | Claude 4 Sonnet | Gemini 2.5 Pro | Sonar Reasoning Pro | |||
| GPT-4.1 Nano | Claude 4 Opus | Gemini 2.5 Flash | Sonar Deep Research | |||
| o4 Mini | ||||||
| o3 Mini | ||||||
| o1 Mini |
Only the GPT LLMs are provided by Azure OpenAI and they come with enterprise grade privacy features. Here're the details of providers for all supported models:
| Model | Provider | Enterprise Grade Privacy Guarantee |
|---|---|---|
| GPT-4 | Azure OpenAI | Yes |
| GPT-4 w/Assistant API (Beta) | Azure OpenAI | Yes |
| GPT-3.5 | Azure OpenAI | Yes |
| GPT-3.5 w/ Assistant API (Beta) | Azure OpenAI | Yes |
| GPT 4 Turbo | OpenAI | No |
| Anthropic Claude 2.1 | Anthropic | No |
| Anthropic Claude 3 Opus | Anthropic | No |
| Anthropic Claude 3 Sonnet | Anthropic | No |
| Cohere Command | Cohere | No |
| Cohere Command-R | Cohere | No |
| Cohere Command Light | Cohere | No |
| Llama 2 13B | Replicate | No |
| Llama 2 70B | Replicate | No |
After selecting a model, you can adjust various parameters such as temperature, and the number of input and output tokens.
Keep in mind that LLMs have limitations with complex math and calculations. If your use case involves such tasks, it’s important to test the results carefully to ensure accuracy.
Data sources
After selecting an LLM, set up data sources to build a knowledge base for your agent to refer to.
- Previous Data - select a data source you have already configured for another AI.
- Upload Files - upload files from your computer. AIs support most of the widely used document formats.
- Website URLs - enter URLs of websites you want the system to crawl through and index in the knowledge base.
- Google Drive - connect your Google account to import data from your Google Drive .
- Microsoft OneDrive - connect your Microsoft account to import data from your Microsoft OneDrive.
- Confluence and JIRA - connect your Atlassian account to configure Confluence and JIRA as data sources.
- Github - connect your Github account and import data frome one of the repos.
When using cloud storage or an online data source, you can set a frequency for data refresh. This controls how often data is indexed or pages are refreshed.
Adding actions and tools
After configuring datasources, you can set up additional actions and link tools to your AI. In the current version of devs.ai, you can use the API Function action to call external APIs. For more information on AI API actions, see Add AI actions.
Add the Python Interpreter tool so that your AI is able to run Python code.
