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Runtime error
DSXiangLi
commited on
Commit
•
54f0839
1
Parent(s):
99291c5
- app.py +3 -4
- requirements.txt +2 -1
- self/generate.py +2 -2
app.py
CHANGED
@@ -95,16 +95,15 @@ with gr.Blocks(title="Automatic Prompt Engineer", theme=gr.themes.Glass()) as de
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with gr.Row():
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with gr.Column():
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openai_key2 = gr.Textbox(type='password', label='输入 API key')
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-
n_human = gr.Slider(label="人工指令数", minimum=1, maximum=5, step=1, value=
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n_machine = gr.Slider(label="机器指令数", minimum=1, maximum=5, step=1, value=1)
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n_instruct = gr.Slider(label="生成指令数", minimum=1, maximum=100, step=
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seed_file = gr.File(label='上传json文件, 格式参考./self/data/seed_task.json')
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with gr.Column():
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self_prompt_input = gr.Textbox(max_lines=100, lines=20, interative=True,
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placeholder=self_prompt,
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value='', label="Prompt for self-instruct")
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-
init_self = gr.Button("初始化")
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self_instance = gr.State()
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gr.Markdown('\n\n')
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@@ -152,7 +151,7 @@ with gr.Blocks(title="Automatic Prompt Engineer", theme=gr.themes.Glass()) as de
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SELF Callback
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"""
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# 1. 加载种子文件
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-
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outputs=[self_instance])
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# 2. 生成
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with gr.Row():
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with gr.Column():
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openai_key2 = gr.Textbox(type='password', label='输入 API key')
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+
n_human = gr.Slider(label="人工指令数", minimum=1, maximum=5, step=1, value=2)
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n_machine = gr.Slider(label="机器指令数", minimum=1, maximum=5, step=1, value=1)
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n_instruct = gr.Slider(label="生成指令数", minimum=1, maximum=100, step=1, value=4, help="生成指令数>人工+机器")
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seed_file = gr.File(label='上传json文件, 格式参考./self/data/seed_task.json')
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with gr.Column():
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self_prompt_input = gr.Textbox(max_lines=100, lines=20, interative=True,
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placeholder=self_prompt,
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value='', label="Prompt for self-instruct")
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self_instance = gr.State()
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gr.Markdown('\n\n')
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SELF Callback
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"""
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# 1. 加载种子文件
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seed_file.submit(init_instance, inputs=[seed_file, openai_key2, n_human, n_machine, n_instruct, self_prompt_input],
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outputs=[self_instance])
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# 2. 生成
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requirements.txt
CHANGED
@@ -4,4 +4,5 @@ openai
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langchain
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pandas
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rouge_score
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-
transformers
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langchain
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pandas
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rouge_score
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+
transformers
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+
pytorch
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self/generate.py
CHANGED
@@ -89,10 +89,8 @@ class SELF(object):
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# build few-shot
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few_shot = gen_few_shot_prompt(self.sample_few_shot)
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few_shot += SELF.prefix.format(id=self.first_id) # 新生成的指令
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print(few_shot)
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# generate
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result = self.chain({'few_shot': few_shot, 'n_instruct': self.n_instruct})
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print(result)
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return result
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def decode_response(self, response):
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@@ -142,6 +140,8 @@ class SELF(object):
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with Pool(os.cpu_count()) as p:
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rouge_scores = p.map(partial(rouge_scorer._score_lcs, self.all_instruction_tokens), inst_tokens)
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rouge_l = [score.fmeasure for score in rouge_scores]
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top10_sim_inst = {
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self.all_instruction[i]: rouge_l[i] for i in np.argsort(rouge_l)[-10:][::-1]
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}
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# build few-shot
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few_shot = gen_few_shot_prompt(self.sample_few_shot)
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few_shot += SELF.prefix.format(id=self.first_id) # 新生成的指令
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# generate
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result = self.chain({'few_shot': few_shot, 'n_instruct': self.n_instruct})
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return result
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def decode_response(self, response):
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with Pool(os.cpu_count()) as p:
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rouge_scores = p.map(partial(rouge_scorer._score_lcs, self.all_instruction_tokens), inst_tokens)
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rouge_l = [score.fmeasure for score in rouge_scores]
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+
print(rouge_scores)
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+
print(rouge_l)
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top10_sim_inst = {
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self.all_instruction[i]: rouge_l[i] for i in np.argsort(rouge_l)[-10:][::-1]
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}
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