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--- |
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license: apache-2.0 |
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tags: |
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- function-calling |
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--- |
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# Fireworks Function Calling (FireFunction) Model V2 |
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64b6f3a72f5a966b9722de88/p2qimncmTIv0Yuy1W_Hhx.png" alt="firefunction" width="400"/> |
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FireFunction is a state-of-the-art function calling model with a commercially viable license. Key info and highlights: |
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🐾 Successor of the [FireFunction](https://fireworks.ai/models/fireworks/firefunction-v2) model |
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📏 Signifficant quality improvements over FireFunction v1 across the broad range of metrics |
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🔆 Support of parallel function calling (unlike FireFunction v1) and good instruction following |
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💡 Hosted on the [Fireworks](https://fireworks.ai/models/fireworks/firefunction-v2) platform |
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## Resources |
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* [Fireworks discord with function calling channel](https://discord.gg/mMqQxvFD9A) |
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* [Documentation](https://readme.fireworks.ai/docs/function-calling) |
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* [UI Demo app](https://functional-chat.vercel.app/) |
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* [Try in Fireworks prompt playground UI](https://fireworks.ai/models/fireworks/firefunction-v2) |
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# Intended Use and Limitations |
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### Supported usecases |
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The model was tuned to perfom well on a range of usecases including: |
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* general instruction following |
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* multi-turn chat mixing vanilla messages with function calls |
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* single- and parallel function calling |
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* up to 20 function specs supported at once |
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* structured information extraction |
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### Out-of-Scope Use |
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The model was not optimized for the following use cases: |
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* 100+ function specs |
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* nested function calling |
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## Example Usage |
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See [documentation](https://readme.fireworks.ai/docs/function-calling) for more detail. |
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```python |
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from transformers import AutoModelForCausalLM, AutoTokenizer |
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import json |
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device = "cuda" # the device to load the model onto |
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model = AutoModelForCausalLM.from_pretrained("fireworks-ai/firefunction-v2", device_map="auto") |
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tokenizer = AutoTokenizer.from_pretrained("fireworks-ai/firefunction-v2") |
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function_spec = [ |
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{ |
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"name": "get_stock_price", |
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"description": "Get the current stock price", |
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"parameters": { |
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"type": "object", |
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"properties": { |
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"symbol": { |
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"type": "string", |
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"description": "The stock symbol, e.g. AAPL, GOOG" |
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} |
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}, |
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"required": [ |
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"symbol" |
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] |
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} |
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}, |
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{ |
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"name": "check_word_anagram", |
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"description": "Check if two words are anagrams of each other", |
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"parameters": { |
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"type": "object", |
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"properties": { |
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"word1": { |
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"type": "string", |
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"description": "The first word" |
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}, |
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"word2": { |
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"type": "string", |
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"description": "The second word" |
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} |
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}, |
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"required": [ |
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"word1", |
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"word2" |
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] |
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} |
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} |
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] |
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functions = json.dumps(function_spec, indent=4) |
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messages = [ |
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{'role': 'functions', 'content': functions}, |
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{'role': 'system', 'content': 'You are a helpful assistant with access to functions. Use them if required.'}, |
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{'role': 'user', 'content': 'Hi, can you tell me the current stock price of google and netflix?'} |
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] |
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model_inputs = tokenizer.apply_chat_template(messages, return_tensors="pt").to(model.device) |
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generated_ids = model.generate(model_inputs, max_new_tokens=128) |
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decoded = tokenizer.batch_decode(generated_ids) |
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print(decoded[0]) |
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``` |
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## Demo App |
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Check our easy-to-extend [demo chat app](https://github.com/fw-ai/forge/tree/main/apps/functional_chat) with function calling capabilities built on Firefunction model. |
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