Meta AI
by Meta
Access Meta's Llama models - open-source large language models for chat, reasoning, and analysis
How agents use Meta AI
- ✓Agent uses open-source Llama models as a cost-effective reasoning engine for text and chat tasks
- ✓Agent generates text embeddings to enable semantic search or document similarity matching
- ✓Agent classifies or moderates content using a fine-tuned Llama model as a step in a pipeline
- ✓Agent runs inference on Meta's models without vendor lock-in for privacy-sensitive workflows
Agent actions
Inputs: messages, model, temperature, maxTokens, topP, topK, stream
Returns: content, usage, finishReason
Inputs: image, prompt, model, maxTokens
Returns: analysis, usage
Inputs: prompt, model, maxTokens, temperature, stopSequences
Returns: text, usage
Inputs: prompt, language, model
Returns: code, explanation
Inputs: messages, tools, toolChoice, model
Returns: toolCalls, content, usage
Inputs: input, model
Returns: embeddings, usage
Example workflows
Simple Chat
Basic conversation with Llama
Vision Analysis
Analyze an image with Llama Vision
Code Generation
Generate Python code
Function Calling
Use Llama with custom tools
Long Context Analysis
Analyze long documents with Llama 3.1
About Meta AI
- Vendor
- Meta
- Pricing Always review details with the vendor
- Free / Paid — Free tier available for smaller models, usage-based pricing for larger models. Open-source models can also be self-hosted
- Authentication
- API key
- Rate limit Always review details with the vendor
- 100 requests / minute
- Compatible nodes
- AgentResource
- Website
- https://ai.meta.com
Put Meta AI behind your AI agent
Set up Meta AI alongside your other tools in the planner — no code — so AI can act on it for your customers.
Open the planner