
Node Details
- Name: ChatOllamaFunction
- Type: ChatOllamaFunction
- Version: 1.0
- Category: Chat Models
Parameters
Inputs
Inputs
-
Cache (optional)
- Type: BaseCache
- Description: Caching mechanism for the model
-
Base URL
- Type: string
- Default: “http://localhost:11434”
- Description: The base URL for the Ollama API
-
Model Name
- Type: string
- Description: Name of the compatible function-calling model (e.g., “mistral”)
-
Temperature
- Type: number
- Default: 0.9
- Range: 0 to 1
- Description: Controls the randomness of the model’s output
-
Tool System Prompt Template (optional)
- Type: string
- Description: Custom system prompt template for tool usage
-
Top P (optional)
- Type: number
- Description: Nucleus sampling parameter
-
Top K (optional)
- Type: number
- Description: Top-K sampling parameter
-
Mirostat (optional)
- Type: number
- Description: Mirostat sampling mode
-
Mirostat ETA (optional)
- Type: number
- Description: Mirostat learning rate
-
Mirostat TAU (optional)
- Type: number
- Description: Mirostat target entropy
-
Context Window Size (optional)
- Type: number
- Description: Size of the context window
-
Number of GQA groups (optional)
- Type: number
- Description: Number of GQA groups in the transformer layer
-
Number of GPU (optional)
- Type: number
- Description: Number of layers to send to GPU(s)
-
Number of Thread (optional)
- Type: number
- Description: Number of threads for computation
-
Repeat Last N (optional)
- Type: number
- Description: Look-back window to prevent repetition
-
Repeat Penalty (optional)
- Type: number
- Description: Penalty for repeated tokens
-
Stop Sequence (optional)
- Type: string
- Description: Sequences to stop generation
-
Tail Free Sampling (optional)
- Type: number
- Description: Parameter for Tail Free Sampling
Inputs/Outputs
- Input: Receives messages and optional function definitions
- Output: Generates responses, potentially including function calls
Usage
This node is used in workflows where function-calling capabilities of language models are needed. It’s particularly useful for tasks that require the model to choose and use specific tools or functions based on the input.Special Features
- Supports various Ollama-specific parameters for fine-tuning model behavior
- Can handle both regular chat interactions and function-calling scenarios
- Includes a default