Smol world (ADV-163) #3
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rlouf
reviewed
Oct 21, 2024
| def instruct_prompt(question, functions, tokenizer): | ||
| messages = [ | ||
| {"role": "user", "content": SYSTEM_PROMPT_FOR_CHAT_MODEL.format(functions=format_functions(functions))}, | ||
| {"role": "assistant", "content": ASSISTANT_PROMPT_FOR_CHAT_MODEL }, |
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I like the idea of injecting a first assistant response. Does that improve the subsequent generations?
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Like most prompt engineering things I feel like it does improve outcomes, but hard to say without proper evaluations. Right now it's definitely in the AI-superstition category.
rlouf
reviewed
Oct 21, 2024
rlouf
reviewed
Oct 21, 2024
| "items": {"type": "float"} | ||
| }) | ||
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| def build_standard_fc_regex(function_data): |
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Would you mind documenting these functions? I opened an issue on Outlines to provide an interface for multi-functions function calling and we will probably use this code as a first draft.
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Just a few minor comments, otherwise this is looking great! |
cpfiffer
reviewed
Oct 21, 2024
| @@ -0,0 +1,3 @@ | |||
| outlines==0.1.0 | |||
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Suggested change
| outlines==0.1.0 | |
| outlines==0.1.1 |
Might be able to go up to 0.1.1
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| def format_functions(functions): | ||
| formatted_functions = [] | ||
| for func in functions: | ||
| function_info = f"{func['name']}: {func['description']}\n" | ||
| if 'parameters' in func and 'properties' in func['parameters']: | ||
| for arg, details in func['parameters']['properties'].items(): | ||
| description = details.get('description', 'No description provided') | ||
| function_info += f"- {arg}: {description}\n" | ||
| formatted_functions.append(function_info) | ||
| return "\n".join(formatted_functions) |
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Suggested change
| def format_functions(functions): | |
| formatted_functions = [] | |
| for func in functions: | |
| function_info = f"{func['name']}: {func['description']}\n" | |
| if 'parameters' in func and 'properties' in func['parameters']: | |
| for arg, details in func['parameters']['properties'].items(): | |
| description = details.get('description', 'No description provided') | |
| function_info += f"- {arg}: {description}\n" | |
| formatted_functions.append(function_info) | |
| return "\n".join(formatted_functions) | |
| def format_functions(functions): | |
| """ | |
| Formats the functions in the given list of functions into a list | |
| of human-readable strings. | |
| Example output: | |
| [ | |
| 'send_text: Send a text message to a contact | |
| - to: The name of the contact to send the text to. | |
| - message: The message to send to the contact.', | |
| 'send_email: Send an email to a contact | |
| - to: The name of the contact to send the email to. | |
| - subject: The subject of the email. | |
| - message: The message to send to the contact.' | |
| ] | |
| """ | |
| formatted_functions = [] | |
| for func in functions: | |
| function_info = f"{func['name']}: {func['description']}\n" | |
| if 'parameters' in func and 'properties' in func['parameters']: | |
| for arg, details in func['parameters']['properties'].items(): | |
| description = details.get('description', 'No description provided') | |
| function_info += f"- {arg}: {description}\n" | |
| formatted_functions.append(function_info) | |
| return "\n".join(formatted_functions) |
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rlouf
approved these changes
Oct 25, 2024
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This is the basic implementation of a demo of the HF SMoL model being used as a NL interface for calling applications. The current supported functions are:
The user is prompted to ask a question and the model should translate this into a function call (which could presumable be mapped to a real application in the future).