metadata
license: apache-2.0
tags:
- function-calling
Fireworks Function Calling (FireFunction) Model V2
FireFunction is a state-of-the-art function calling model with a commercially viable license. Key info and highlights:
🐾 Successor of the FireFunction model
📏 Signifficant quality improvements over FireFunction v1 across the broad range of metrics
🔆 Support of parallel function calling (unlike FireFunction v1) and good instruction following
💡 Hosted on the Fireworks platform
Resources
- Fireworks discord with function calling channel
- Documentation
- UI Demo app
- Try in Fireworks prompt playground UI
Intended Use and Limitations
Supported usecases
The model was tuned to perfom well on a range of usecases including:
- general instruction following
- multi-turn chat mixing vanilla messages with function calls
- single- and parallel function calling
- up to 20 function specs supported at once
- structured information extraction
Out-of-Scope Use
The model was not optimized for the following use cases:
- 100+ function specs
- nested function calling
Example Usage
See documentation for more detail.
from transformers import AutoModelForCausalLM, AutoTokenizer
import json
device = "cuda" # the device to load the model onto
model = AutoModelForCausalLM.from_pretrained("fireworks-ai/firefunction-v2", device_map="auto")
tokenizer = AutoTokenizer.from_pretrained("fireworks-ai/firefunction-v2")
function_spec = [
{
"name": "get_stock_price",
"description": "Get the current stock price",
"parameters": {
"type": "object",
"properties": {
"symbol": {
"type": "string",
"description": "The stock symbol, e.g. AAPL, GOOG"
}
},
"required": [
"symbol"
]
}
},
{
"name": "check_word_anagram",
"description": "Check if two words are anagrams of each other",
"parameters": {
"type": "object",
"properties": {
"word1": {
"type": "string",
"description": "The first word"
},
"word2": {
"type": "string",
"description": "The second word"
}
},
"required": [
"word1",
"word2"
]
}
}
]
functions = json.dumps(function_spec, indent=4)
messages = [
{'role': 'functions', 'content': functions},
{'role': 'system', 'content': 'You are a helpful assistant with access to functions. Use them if required.'},
{'role': 'user', 'content': 'Hi, can you tell me the current stock price of google and netflix?'}
]
model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device)
generated_ids = model.generate(model_inputs, max_new_tokens=128)
decoded = tokenizer.batch_decode(generated_ids)
print(decoded[0])
Demo App
Check our easy-to-extend demo chat app with function calling capabilities built on Firefunction model.