update with Env Var

This commit is contained in:
VincentXiuyuanZhao 2024-05-30 17:11:39 +08:00
parent 86f6345cfe
commit 4c89e3de9f

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@ -5,20 +5,16 @@ import csv
from http import HTTPStatus from http import HTTPStatus
import dashscope import dashscope
from dashscope import Generation from dashscope import Generation
import os
dashscope.api_key = os.getenv("DASHSCOPE_API_KEY") # Vincent's API key
# todo: delete instruction part or make it optional
def response(prompt, instruction=None):
def pross_instruction(system, rag_dict): messages = [{'role': 'user', 'content': prompt}]
""" if instruction is not None: # 如果提供了指令则添加到messages中
使用format_map()替换字符串中的变量 messages.insert(0, {'role': 'system', 'content': instruction})
"""
return system.format_map(rag_dict)
def response(prompt, instruction):
messages = [{'role': 'system', 'content': instruction},
{'role': 'user', 'content': prompt}]
response = Generation.call(model='qwen-plus', response = Generation.call(model='qwen-plus',
messages=messages, messages=messages,
@ -41,13 +37,14 @@ def response(prompt, instruction):
return f"Error: Could not generate response with Status code: {response.status_code}, error code: {response.code}" return f"Error: Could not generate response with Status code: {response.status_code}, error code: {response.code}"
def format_full_prompt(df): def format_full_prompt(df, introduction):
# 为每个 row 创建 context # 为每个 row 创建 context
df['context'] = df.apply(lambda row: f"{row['RAG1']}-{row['RAG2']}", axis=1) df['context'] = df.apply(lambda row: f"{row['RAG1']}-{row['RAG2']}", axis=1)
# 准备用于 format 的字典 # 准备用于 format 的字典
format_dict = df[['business_use_mark', 'context', 'question']].apply(lambda x: dict(zip(x.index, x)), axis=1) format_dict = df[['business_use_mark', 'context', 'question']].apply(lambda x: dict(zip(x.index, x)), axis=1)
if len(introduction) >= 100:
df['full_prompt'] = introduction
# 使用 apply() 和 lambda 函数格式化 full_prompt 列 # 使用 apply() 和 lambda 函数格式化 full_prompt 列
df['full_prompt'] = df.apply(lambda row: row['full_prompt'].format(**format_dict[row.name]), axis=1) df['full_prompt'] = df.apply(lambda row: row['full_prompt'].format(**format_dict[row.name]), axis=1)
@ -56,14 +53,13 @@ def format_full_prompt(df):
return df return df
def process_xlsx(xlsx_file, instruction): def process_xlsx(xlsx_file, instruction=None): # 这里也使instruction参数变成可选
# 读取xlsx文件到pandas DataFrame # 读取xlsx文件到pandas DataFrame
df = pd.read_excel(xlsx_file) df = pd.read_excel(xlsx_file)
# 格式化prompts # 格式化prompts
formatted_df = format_full_prompt(df) formatted_df = format_full_prompt(df, instruction)
# 假设我们要处理的提示是DataFrame的'full_prompt'列 # 假设我们要处理的提示是DataFrame的'full_prompt'列
# 调用response时根据instruction是否为None自动处理
formatted_df['Response'] = formatted_df['full_prompt'].apply(lambda prompt: response(prompt, instruction)) formatted_df['Response'] = formatted_df['full_prompt'].apply(lambda prompt: response(prompt, instruction))
# 使用tempfile创建一个临时文件路径保存处理后的xlsx # 使用tempfile创建一个临时文件路径保存处理后的xlsx
@ -79,7 +75,7 @@ def main():
with gr.Accordion("输入说明"): with gr.Accordion("输入说明"):
gr.Markdown("请上传一个xlsx文件文件应包含prompts。") gr.Markdown("请上传一个xlsx文件文件应包含prompts。")
system_instruction = gr.Textbox(label="System Instruction", lines=2, system_instruction = gr.Textbox(label="System Instruction", lines=2,
value="A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.") value=" ")
file_input = gr.File(label="上传xlsx文件") file_input = gr.File(label="上传xlsx文件")
submit_button = gr.Button("处理xlsx") submit_button = gr.Button("处理xlsx")