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Saifeddine ALOUI 2024-07-11 01:24:10 +02:00
parent 4c9592c0b0
commit d29bde9d0a
1 changed files with 17 additions and 17 deletions
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lollms/personality.py
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@ -3744,7 +3744,7 @@ class APScript(StateMachine):
"""
return self.personality.fast_gen(prompt=prompt,max_generation_size=max_generation_size,placeholders=placeholders, sacrifice=sacrifice, debug=debug, callback=callback, show_progress=show_progress)
def mix_it_up(self, prompt: str, models, master_model, max_generation_size: int= None, placeholders: dict = {}, sacrifice: list = ["previous_discussion"], debug: bool = False, callback=None, show_progress=False) -> dict:
def mix_it_up(self, prompt: str, models, master_model, nb_rounds=2, max_generation_size: int= None, placeholders: dict = {}, sacrifice: list = ["previous_discussion"], debug: bool = False, callback=None, show_progress=False) -> dict:
"""
Fast generates text using multiple LLMs with detailed round tracking. Each LLM sees the initial prompt plus the formatted outputs of the previous rounds.
The master model then completes the job by creating a unique answer inspired by the last round outputs.
@ -3769,22 +3769,22 @@ class APScript(StateMachine):
'initial_prompt': prompt,
'rounds': []
}
for idx, model_id in enumerate(models):
binding_name, model_name = model_id.split("::")
self.select_model(binding_name, model_name)
# Concatenate previous outputs with formatting
formatted_previous_outputs = "\n".join([f"Model {m}: {o}" for m, o in previous_outputs])
round_prompt = context + "\n" + formatted_previous_outputs
output = self.fast_gen(prompt=round_prompt, max_generation_size=max_generation_size, placeholders=placeholders, sacrifice=sacrifice, debug=debug, callback=callback, show_progress=show_progress)
rounds_info['rounds'].append({
'model': model_id,
'round_prompt': round_prompt,
'output': output
})
previous_outputs.append((model_id, output)) # Update for the next round
for rounds in range(nb_rounds):
for idx, model_id in enumerate(models):
binding_name, model_name = model_id.split("::")
self.select_model(binding_name, model_name)
# Concatenate previous outputs with formatting
formatted_previous_outputs = "\n".join([f"Model {m}: {o}" for m, o in previous_outputs])
round_prompt = context + "\n" + formatted_previous_outputs
output = self.fast_gen(prompt=round_prompt, max_generation_size=max_generation_size, placeholders=placeholders, sacrifice=sacrifice, debug=debug, callback=callback, show_progress=show_progress)
rounds_info['rounds'].append({
'model': model_id,
'round_prompt': round_prompt,
'output': output
})
previous_outputs.append((model_id, output)) # Update for the next round
# Final round with the master model
self.select_model(*master_model.split("::"))