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| from nodes.LLMNode import * | |
| import time | |
| from utils.util import * | |
| class IO: | |
| def __init__(self, fewshot="\n", model_name="text-davinci-003"): | |
| self.fewshot = fewshot | |
| self.model_name = model_name | |
| self.llm = LLMNode("CoT", model_name, input_type=str, output_type=str) | |
| self.context_prompt = "Answer following questions. Respond directly with no extra words.\n" | |
| self.token_unit_price = get_token_unit_price(model_name) | |
| def run(self, input): | |
| result = {} | |
| st = time.time() | |
| prompt = self.context_prompt + self.fewshot + input + '\n' | |
| response = self.llm.run(prompt, log=True) | |
| result["wall_time"] = time.time() - st | |
| result["input"] = response["input"] | |
| result["output"] = response["output"] | |
| result["prompt_tokens"] = response["prompt_tokens"] | |
| result["completion_tokens"] = response["completion_tokens"] | |
| result["total_tokens"] = response["prompt_tokens"] + response["completion_tokens"] | |
| result["token_cost"] = result["total_tokens"] * self.token_unit_price | |
| result["tool_cost"] = 0 | |
| result["total_cost"] = result["token_cost"] + result["tool_cost"] | |
| result["steps"] = 1 | |
| return result | |
| class CoT: | |
| def __init__(self, fewshot="\n", model_name="text-davinci-003"): | |
| self.fewshot = fewshot | |
| self.model_name = model_name | |
| self.llm = LLMNode("CoT", model_name, input_type=str, output_type=str) | |
| self.context_prompt = "Answer following questions. Let's think step by step. Give your reasoning process, and then answer the " \ | |
| "question in a new line directly with no extra words.\n" | |
| self.token_unit_price = get_token_unit_price(model_name) | |
| def run(self, input): | |
| result = {} | |
| st = time.time() | |
| prompt = self.context_prompt + self.fewshot + input + '\n' | |
| response = self.llm.run(prompt, log=True) | |
| result["wall_time"] = time.time() - st | |
| result["input"] = response["input"] | |
| result["output"] = response["output"] | |
| result["prompt_tokens"] = response["prompt_tokens"] | |
| result["completion_tokens"] = response["completion_tokens"] | |
| result["total_tokens"] = response["prompt_tokens"] + response["completion_tokens"] | |
| result["token_cost"] = result["total_tokens"] * self.token_unit_price | |
| result["tool_cost"] = 0 | |
| result["total_cost"] = result["token_cost"] + result["tool_cost"] | |
| result["steps"] = response["output"].count("Step") | |
| return result | |