ai-songwriter-beta / gpt_calls.py
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clean up, add remote sssAPI, clean up concat
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from openai import OpenAI
# from unsloth import FastLanguageModel
class AI_Songwriter:
def __init__(self, client_key):
self.oai_client = OpenAI(api_key=client_key)
# max_seq_length = 3072 # Choose any! We auto support RoPE Scaling internally!
# dtype = None # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
# load_in_4bit = True # Use 4bit quantization to reduce memory usage. Can be False.
# model, tokenizer = FastLanguageModel.from_pretrained(
# model_name = "lora_model", # YOUR MODEL YOU USED FOR TRAINING
# max_seq_length = max_seq_length,
# dtype = dtype,
# load_in_4bit = load_in_4bit,
# )
# FastLanguageModel.for_inference(model) # Enable native 2x faster inference
# self.model=model
# self.tokenizer=tokenizer
self.alpaca_prompt = """Below is an instruction that describes a songwriting task, paired with an input that provides further context. Write a response that appropriately completes the request.
### Instruction:
{}
### Input:
{}
### Response:
{}"""
def ask_question(self, messages):
convo = messages[:-1]
instruction = "Based on this conversation history, respond to the user acknowledging their most recent response and ask a concise question to further learn more about the user's story."
## iterate thru messages and format them into a single string where each message is separated by a newline (ie Assistant: ...\n User: ...\n)
convo_str = ""
for message in convo:
convo_str += f"{message['role']}: {message['content']}\n"
convo_str += "Assistant:"
input = f"{instruction}\nConversation History:\n{convo_str}"
response = self.oai_client.chat.completions.create(
model="gpt-4o",
messages=[
{
"role": "user",
"content": input
}
],
)
return response.choices[0].message.content
def write_section(self, section_name, section_description, relevant_ideas, section_length, sections_written=None, overall_song_description=None):
instruction = f"Write a {section_name} of length {section_length} that that incorporates the following ideas"
if sections_written is not None:
instruction += "and complements the sections provided."
else:
instruction += "."
instruction += "You are also given a section description, genre, era, and overall description of the song."
## read in prompt lyrics from convo .txt and add it to instruction
with open("prompts/write_section_ex.txt", "r") as f:
convo = f.read()
instruction += "Here's an example:\n{convo}\nNow do it for this input:"
input = f"""Ideas to use:
- {relevant_ideas}
Section Description: {section_description}
Genre: Songwriter Pop
Era: 2010s
Overall song description: {overall_song_description}
"""
if sections_written is not None:
written_sections = "\n".join(sections_written)
input += f"Sections provided:\n{written_sections}\nLyrics:"
else:
input += "\nLyrics:"
prompt = self.alpaca_prompt.format(instruction, input, "")
convo = [
{
"role": "user",
"content": prompt,
},
]
response = self.oai_client.chat.completions.create(
model="gpt-4o",
messages=convo,
)
return "Pass this back to the user and ask if they would like to receive an audio snippet or make any revisions before moving to the next section: \n" + response.choices[0].message.content
def revise_section_lyrics(self, section_name, current_section, lines_to_revise, relevant_ideas=None, relevant_words=None):
lines_to_infill = ", ".join([str(x) for x in lines_to_revise])
full_incomplete_verse = current_section.strip("\n ").split("\n")
max_line_num = max(lines_to_revise)
if max_line_num > len(full_incomplete_verse):
full_incomplete_verse.extend([''] * (max_line_num - len(full_incomplete_verse)))
for line_num in lines_to_revise:
if line_num <= len(full_incomplete_verse):
full_incomplete_verse[line_num-1] = '___'
line_phrase = "lines" if len(lines_to_infill) > 1 else "line"
line_phrase = str(len(lines_to_infill)) + " " + line_phrase
instruction = f"Infill the remaining {line_phrase} into {section_name}"
if relevant_ideas is not None or relevant_words is not None:
instruction += " while incorporating the following "
if relevant_ideas is not None:
instruction += "ideas"
if relevant_words is not None:
instruction += "and words."
else:
instruction += "."
else:
instruction += "words."
else:
instruction += "."
instruction += "You are also given a genre, era, and the rest of the section."
with open("prompts/revise_section_ex.txt", "r") as f:
convo = f.read()
instruction += "Here's an example:\n{convo}\nNow do it for this input:"
input = ""
if relevant_ideas is not None and isinstance(relevant_ideas, list):
input += f"Ideas to use: {', '.join(relevant_ideas)}\n"
if relevant_words is not None and isinstance(relevant_words, list):
input += f"Words to use: {', '.join(relevant_words)}\n"
input += f"Genre: Songwriter Pop\nEra: 2010s\nCurrent section:\n{full_incomplete_verse}\n\nLyrics:"
prompt = self.alpaca_prompt.format(instruction, input, "")
convo = [
{
"role": "user",
"content": prompt,
},
]
response = self.oai_client.chat.completions.create(
model="gpt-4o",
messages=convo,
)
return response.choices[0].message.content
def revise_instrumental_tags(self, current_instrumental_tags, user_instrumental_feedback):
instruction = "Revise the current instrumental tags to better match the feedback provided:"
input = f"""Current instrumental tags: {current_instrumental_tags}\ninstrumental feedback: {user_instrumental_feedback}\nNew tags:"""
prompt = self.alpaca_prompt.format(instruction, input, "")
convo = [
{
"role": "user",
"content": prompt,
},
]
response = self.oai_client.chat.completions.create(
model="gpt-4o",
messages=convo,
)
return response.choices[0].message.content.split("New tags:")[-1].strip("\n ")
def write_all_lyrics(self, sections_to_be_written, sections_written, overall_song_description):
instruction = "Write the remainder of this full song given an overall description of the song, genre, era, and a description of the sections to complete:"
with open("prompts/write_full_song_ex.txt", "r") as f:
convo = f.read()
instruction += "Here's an example:\n{convo}\nNow do it for this input:"
sections_to_write = [x['section_name'] for x in sections_to_be_written]
sections_to_write_str = ", ".join(sections_to_write)
section_descriptions = [x['section_description'] for x in sections_to_be_written]
full_meanings = "\n".join([f"{sections_to_write[i]}: {section_descriptions[i]}" for i in range(len(sections_to_write))])
input = f"Sections to write: {sections_to_write_str}\nOverall song description: {overall_song_description}\nGenre: Songwriter Pop\nEra: 2010s\nSection Descriptions:\n{full_meanings}"
if sections_written is not None:
written_sections = "\n".join(sections_written)
input += f"Sections provided:\n{written_sections}\n\nLyrics:"
else:
input += "\n\nLyrics:"
prompt = self.alpaca_prompt.format(instruction, input, "")
convo = [
{
"role": "user",
"content": prompt,
},
]
response = self.oai_client.chat.completions.create(
model="gpt-4o",
messages=convo,
)
return response.choices[0].message.content