Update README.md

README.md

@@ -1,199 +1,183 @@
 ---
 library_name: transformers
-tags: []
+tags:
+- functioncalling
+license: apache-2.0
+language:
+- it
+pipeline_tag: text2text-generation
 ---
+<img src="https://hoodie-creator.s3.eu-west-1.amazonaws.com/2c331689-original.png" alt="gorilla-llm" border="0" width="400px">
 
-# Model Card for Model ID
+## Introduction
+Zefiro functioncalling extends Large Language Model(LLM) Chat Completion feature to formulate 
+executable APIs call given Italian based natural language instructions and API context. With OpenFunctions v2,
 
-<!-- Provide a quick summary of what the model is/does. -->
+we now support:
+1. Relevance detection - when chatting, chat. When asked for function, returns a function
+2. REST - native REST support
 
 
+## Model description
 
-## Model Details
+- **Model type:** A 7B parameter GPT-like model fine-tuned on a mix of publicly available, synthetic datasets.
+- **Language(s) (NLP):** Primarily Italian
+- **License:** Apache 2
+- **Finetuned from model:** [gorilla-llm](https://https://huggingface.co/gorilla-llm/gorilla-openfunctions-v2)
+- **Developed by:** [zefiro.ai](https://zefiro.ai)
+- **Sponsored by:** [Seeweb](https://seeweb.it)
 
-### Model Description
 
-<!-- Provide a longer summary of what this model is. -->
+## Models Available
+|Model | Functionality|
+|---|---|
+|zefiro-funcioncalling-v0.3-alpha | Given a function, and user intent, returns properly formatted json with the right arguments|
 
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
+All of our models are hosted on our Huggingface mii-community org: [zefiro-functioncalling-v0.3-alpha](https://huggingface.co/mii-community/zefiro-functioncalling-v0.3-alpha).
 
-- **Developed by:** [More Information Needed]
-- **Funded by [optional]:** [More Information Needed]
-- **Shared by [optional]:** [More Information Needed]
-- **Model type:** [More Information Needed]
-- **Language(s) (NLP):** [More Information Needed]
-- **License:** [More Information Needed]
-- **Finetuned from model [optional]:** [More Information Needed]
+## Training
 
-### Model Sources [optional]
+Zefiro functioncalling alpha is a 7B parameter model, and  is fine tuned version of [gorilla-llm](https://huggingface.co/gorilla-llm/gorilla-openfunctions-v2) that is built on top of the [deepseek coder](https://huggingface.co/deepseek-ai/deepseek-coder-7b-instruct-v1.5) LLM.
 
-<!-- Provide the basic links for the model. -->
 
-- **Repository:** [More Information Needed]
-- **Paper [optional]:** [More Information Needed]
-- **Demo [optional]:** [More Information Needed]
 
-## Uses
+## Example Usage (Local)
 
-<!-- Address questions around how the model is intended to be used, including the foreseeable users of the model and those affected by the model. -->
 
-### Direct Use
+1. OpenFunctions is compatible with OpenAI Functions
 
-<!-- This section is for the model use without fine-tuning or plugging into a larger ecosystem/app. -->
+```bash
+!pip install openai==0.28.1, transformers
+```
 
-[More Information Needed]
+2. Load the model
 
-### Downstream Use [optional]
+```python
+from transformers import AutoModelForCausalLM, AutoTokenizer
 
-<!-- This section is for the model use when fine-tuned for a task, or when plugged into a larger ecosystem/app -->
+model_id = "mii-community/zefiro-functioncalling-v0.3-alpha"
+model = AutoModelForCausalLM.from_pretrained(model_id)
+model.to('cuda')
+tokenizer = AutoTokenizer.from_pretrained(model_id)
 
-[More Information Needed]
+```
 
-### Out-of-Scope Use
+3. Prepare your data with a system prompt and an array of json openapi compatible: only the description key should be in Italian all the json in english a part all description keys. 
 
-<!-- This section addresses misuse, malicious use, and uses that the model will not work well for. -->
+```python
+json_arr = [{"name": "order_dinner", "description": "Ordina una cena al ristorante", "parameters": {"type": "object", "properties": {"restaurant_name": {"type": "string", "description": "il nome del ristorante", "enum" : ['Bufalo Bill','Pazzas']}}, "required": ["restaurant_name"]}},
+            {"name": "get_weather", "description": "Ottieni le previsioni del tempo meteorologica", "parameters": {"type": "object", "properties": {"location": {"type": "string", "description": "Il nome del luogo "}}, "required": ["location"]}},
+            {"name": "create_product", "description": "Crea un prodotto da vendere", "parameters": {"type": "object", "properties": {"product_name": {"type": "string", "description": "Il nome del prodotto "}, "size": {"type": "string", "description": "la taglia del prodotto"}, "price": {"type": "integer", "description": "Il prezzo del prodotto "}}, "required": ["product_name", "size", "price"]}},
+            {"name": "get_news", "description": "Dammi le ultime notizie", "parameters": {"type": "object", "properties": {"argument": {"type": "string", "description": "L'argomento su cui fare la ricerca"}}, "required": ["argument"]}},
+            ]
+json_string = ' '.join([json.dumps(json_obj) for json_obj in json_arr])
+system_prompt = 'Tu sei un assistenze utile che ha accesso alle seguenti funzioni. Usa le funzioni solo se necessario - \n ' + json_string + ' \n '
+print(system_prompt)
 
-[More Information Needed]
+test_message = [{'role' : 'system' , 'content' : system_prompt2},
+                {'role' : 'user' ,'content' : 'Crea un prodotto di nome AIR size L price 100'}]
+```
 
-## Bias, Risks, and Limitations
+4. Call the model
 
-<!-- This section is meant to convey both technical and sociotechnical limitations. -->
+```python
+def generate_text():
+    prompt = tokenizer.apply_chat_template(test_message, tokenize=False)
+    model_inputs = tokenizer([prompt], return_tensors="pt").to("cuda")
+    generated_ids = model.generate(**model_inputs, max_new_tokens=1024)
+    return tokenizer.batch_decode(generated_ids, skip_special_tokens=True)[0]
 
-[More Information Needed]
 
-### Recommendations
+text_response = generate_text()
+```
 
-<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->
+5. Parse the response
 
-Users (both direct and downstream) should be made aware of the risks, biases and limitations of the model. More information needed for further recommendations.
+```python
+FN_CALL_DELIMITER = "<<functioncall>>"
 
-## How to Get Started with the Model
+def strip_function_calls(content: str) -> list[str]:
+    """
+    Split the content by the function call delimiter and remove empty strings
+    """
+    return [element.replace('\n', '') for element in content.split(FN_CALL_DELIMITER)[1:] if element ]
 
-Use the code below to get started with the model.
 
-[More Information Needed]
+functions_string = strip_function_calls(text_response)
 
-## Training Details
+# Output: [' {"name": "create_product", "arguments": \'{"product_name": "AIR", "size": "L", "price": 100}\'}']
+```
 
-### Training Data
+6. Create an object representation of the string
 
-<!-- This should link to a Dataset Card, perhaps with a short stub of information on what the training data is all about as well as documentation related to data pre-processing or additional filtering. -->
+```python
+# if functions_string contains a function string create a json cleaning
+# multiple functions not supported yet
+if functions_string: 
+    obj_to_call = json.loads(functions_string[0].replace('\'', ''))
+else: 
+    print('nothing to do or return a normal chat response')
 
-[More Information Needed]
+# Output: {'name': 'create_product', 'arguments': {'product_name': 'AIR', 'size': 'L', 'price': 100}}
+```
 
-### Training Procedure
 
-<!-- This relates heavily to the Technical Specifications. Content here should link to that section when it is relevant to the training procedure. -->
+7.  Prepare data to be OpenAI compatible
+   
+```python
+def obj_to_func(obj):
+    arguments_keys = obj['arguments'].keys()
+    params = []
+    for key in arguments_keys:
+        param = f'{key}=\"{obj["arguments"][key]}\"'
+        params.append(param)
+    func_params = ','.join(params)
+    print(f'{obj["name"]}({func_params})') 
+    return f'{obj["name"]}({func_params})'
 
-#### Preprocessing [optional]
+func_str = obj_to_func(obj_to_call)
 
-[More Information Needed]
+openai_response = {
+  "index": 0,
+  "message": {
+    "role": "assistant",
+    "content": func_str,
+    "function_call": [
+      obj_to_call
+    ]
+  },
+  "finish_reason": "stop"
+}
 
 
-#### Training Hyperparameters
+'''
+Output OpenAI compatible Dictionary
+{'index': 0,
+ 'message': {
+              'role': 'assistant',
+              'content': 'create_product(product_name="AIR",size="L",price="100")',
+              'function_call': [{'name': 'create_product', 'arguments': {'product_name': 'AIR', 'size': 'L', 'price': 100}}]
+            },
+'finish_reason': 'stop'
+}
+'''
+```
 
-- **Training regime:** [More Information Needed] <!--fp32, fp16 mixed precision, bf16 mixed precision, bf16 non-mixed precision, fp16 non-mixed precision, fp8 mixed precision -->
+JSON to be OpenAI compatible.
+
+## Limitation
+The model has some bug and some unexpected behaviour for example the more json you pass the less accurate it become filling the json output but
+the interesting thing is that those are pattern that i did not consider in the data. It will be enough to improove the cases in the data to fix the bugs.
+Stay tuned for a better version soon. 
 
-#### Speeds, Sizes, Times [optional]
 
-<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
+## License
 
-[More Information Needed]
+Zefiro-functioncalling is distributed under the Apache 2.0 license as the base model Gorilla-LLM v0.2. This software incorporates elements from the Deepseek model. Consequently, the licensing of Gorilla OpenFunctions v2 adheres to the Apache 2.0 license, with additional terms as outlined in [Appendix A](https://github.com/deepseek-ai/DeepSeek-LLM/blob/6712a86bfb7dd25c73383c5ad2eb7a8db540258b/LICENSE-MODEL) of the Deepseek license.
 
-## Evaluation
+## Contributing
+Please email us your comments, criticism, and questions. More information about the project can be found at [https://zefiro.ai](https://zefiro.ai)
 
-<!-- This section describes the evaluation protocols and provides the results. -->
 
-### Testing Data, Factors & Metrics
-
-#### Testing Data
-
-<!-- This should link to a Dataset Card if possible. -->
-
-[More Information Needed]
-
-#### Factors
-
-<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
-
-[More Information Needed]
-
-#### Metrics
-
-<!-- These are the evaluation metrics being used, ideally with a description of why. -->
-
-[More Information Needed]
-
-### Results
-
-[More Information Needed]
-
-#### Summary
-
-
-
-## Model Examination [optional]
-
-<!-- Relevant interpretability work for the model goes here -->
-
-[More Information Needed]
-
-## Environmental Impact
-
-<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
-
-Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
-
-- **Hardware Type:** [More Information Needed]
-- **Hours used:** [More Information Needed]
-- **Cloud Provider:** [More Information Needed]
-- **Compute Region:** [More Information Needed]
-- **Carbon Emitted:** [More Information Needed]
-
-## Technical Specifications [optional]
-
-### Model Architecture and Objective
-
-[More Information Needed]
-
-### Compute Infrastructure
-
-[More Information Needed]
-
-#### Hardware
-
-[More Information Needed]
-
-#### Software
-
-[More Information Needed]
-
-## Citation [optional]
-
-<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
-
-**BibTeX:**
-
-[More Information Needed]
-
-**APA:**
-
-[More Information Needed]
-
-## Glossary [optional]
-
-<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
-
-[More Information Needed]
-
-## More Information [optional]
-
-[More Information Needed]
-
-## Model Card Authors [optional]
-
-[More Information Needed]
-
-## Model Card Contact
-
-[More Information Needed]
+## Citation
+This work is based  on Gorilla an open source effort from UC Berkeley and we welcome contributors.