wehub-resource-sync
79 lines
3.2 KiB
Python
79 lines
3.2 KiB
Python
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"""This example demonstrates basic use of Prompts, and how to capture and track the Prompt State and
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interaction history."""
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from llmware.prompts import Prompt
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from llmware.resources import PromptState
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def prompt_state(llm_model):
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# Create a new prompter with state persistence
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prompter = Prompt(save_state=True)
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# Capture the prompt_id (which can be used later to reload state)
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prompt_id = prompter.prompt_id
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# Load the model
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prompter.load_model(llm_model, temperature=0.0, sample=False)
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# Define a list of prompts
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prompts = [
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{"query": "How old is Bob?", "context": "John is 43 years old. Bob is 27 years old."},
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{"query": "When did COVID start?", "context": "COVID started in March of 2020 in most of the world."},
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{"query": "What is the current stock price?", "context": "The stock is trading at $26 today."},
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{"query": "When is the big game?", "context": "The big game will be played on November 14, 2023."},
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{"query": "What is the CFO's salary?", "context": "The CFO has a salary of $285,000."},
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{"query": "What grade is Michael in school?", "context": "Michael is starting 11th grade."}
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]
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# Iterate through the prompt which will save each response dict in in the prompt_state
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print (f"> Sending a series of prompts to {llm_model}...")
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for i, prompt in enumerate(prompts):
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print (" - " + prompt["query"])
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response = prompter.prompt_main(prompt["query"] ,context=prompt["context"] ,register_trx=True)
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print(f" - LLM Responses: {response}")
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# Print how many interactions are now in the prompt history
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interaction_history = prompter.interaction_history
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print (f"> Prompt Interaction History now contains {len(interaction_history)} interactions")
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# Use the dialog_tracker to regenerate the conversation with the LLM
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print (f"> Reconstructed Dialog")
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dialog_history = prompter.dialog_tracker
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for i, conversation_turn in enumerate(dialog_history):
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print(" - ", i, "[user]: ", conversation_turn["user"])
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print(" - ", i, "[ bot]: ", conversation_turn["bot"])
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# Saving and clean the prompt state
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prompter.save_state()
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prompter.clear_history()
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# Print the number of interactions
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interaction_history = prompter.interaction_history
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print (f"> Prompt history has been cleared")
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print (f"> Prompt Interaction History now contains {len(interaction_history)} interactions")
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# Reload the prompt state using the prompt_id and print again the number of interactions
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prompter.load_state(prompt_id)
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interaction_history = prompter.interaction_history
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print (f"> The previous prompt state has been re-loaded")
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print (f"> Prompt Interaction History now contains {len(interaction_history)} interactions")
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# Generate a Prompt transaction report
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prompt_transaction_report = PromptState().generate_interaction_report([prompt_id])
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print (f"> A prompt transaction report has been generated: {prompt_transaction_report}")
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return 0
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if __name__ == "__main__":
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model_name = "llmware/bling-1b-0.1"
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print(f"\nExample - basic prompt state and interaction history management.\n")
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prompt_state(model_name)
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