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| import gradio as gr | |
| import os | |
| import openai | |
| from utils.references import References | |
| from utils.gpt_interaction import GPTModel | |
| from utils.prompts import SYSTEM | |
| openai_key = os.getenv("OPENAI_API_KEY") | |
| default_model = os.getenv("DEFAULT_MODEL") | |
| if default_model is None: | |
| # default_model = "gpt-3.5-turbo-16k" | |
| default_model = "gpt-4" | |
| openai.api_key = openai_key | |
| paper_system_prompt = '''You are an assistant designed to propose choices of research direction. | |
| The user will input questions or some keywords of a fields. You need to generate some paper titles and main contributions. Ensure follow the following instructions: | |
| Instruction: | |
| - Your response should follow the JSON format. | |
| - Your response should have the following structure: | |
| { | |
| "your suggested paper title": | |
| { | |
| "summary": "an overview introducing what this paper will include", | |
| "contributions": { | |
| "contribution1": {"statement": "briefly describe this contribution", "reason": "reason why this contribution can make this paper outstanding"}, | |
| "contribution2": {"statement": "briefly describe this contribution", "reason": "reason why this contribution can make this paper outstanding"}, | |
| ... | |
| } | |
| } | |
| "your suggested paper title": | |
| { | |
| "summary": "an overview introducing what this paper will include", | |
| "contributions": { | |
| "contribution1": {"statement": "briefly describe this contribution", "reason": "reason why this contribution can make this paper outstanding"}, | |
| "contribution2": {"statement": "briefly describe this contribution", "reason": "reason why this contribution can make this paper outstanding"}, | |
| ... | |
| } | |
| } | |
| ... | |
| } | |
| - Please list three to five suggested title and at least three contributions for each paper. | |
| ''' | |
| contribution_system_prompt = '''You are an assistant designed to criticize the contributions of a paper. You will be provided Paper's Title, References and Contributions. Ensure follow the following instructions: | |
| Instruction: | |
| - Your response should follow the JSON format. | |
| - Your response should have the following structure: | |
| { | |
| "title": "the title provided by the user", | |
| "comment": "your thoughts on if this title clearly reflects the key ideas of this paper and explain why" | |
| "contributions": { | |
| "contribution1": {"statement": "briefly describe what the contribution is", | |
| "reason": "reason why the user claims it is a contribution", | |
| "judge": "your thought about if this is a novel contribution and explain why", | |
| "suggestion": "your suggestion on how to modify the research direction to enhance the novelty "}, | |
| "contribution2": {"statement": "briefly describe what the contribution is", | |
| "reason": "reason why the user claims it is a contribution", | |
| "judge": "your thought about if this is a novel contribution and explain why", | |
| "suggestion": "your suggestion on how to modify the research direction to enhance the novelty "}, | |
| ... | |
| } | |
| } | |
| - You need to carefully check if the claimed contribution has been made in the provided references, which makes the contribution not novel. | |
| - You also need to propose your concerns on if any of contributions could be incremental or just a mild modification on an existing work. | |
| ''' | |
| ANNOUNCEMENT = """ | |
| <h1 style="text-align: center"><img src='/file=assets/idealab.png' width=36px style="display: inline"/>灵感实验室IdeaLab</h1> | |
| <p>灵感实验室IdeaLab可以为你选择你下一篇论文的研究方向! 输入你的研究领域或者任何想法, 灵感实验室会自动生成若干个论文标题+论文的主要贡献供你选择. </p> | |
| <p>除此之外, 输入你的论文标题+主要贡献, 它会自动搜索相关文献, 来验证这个想法是不是有人做过了.</p> | |
| """ | |
| def criticize_my_idea(title, contributions, max_tokens=4096): | |
| ref = References(title=title, description=f"{contributions}") | |
| keywords, _ = llm(systems=SYSTEM["keywords"], prompts=title, return_json=True) | |
| keywords = {keyword: 10 for keyword in keywords} | |
| ref.collect_papers(keywords) | |
| ref_prompt = ref.to_prompts(max_tokens=max_tokens) | |
| prompt = f"Title: {title}\n References: {ref_prompt}\n Contributions: {contributions}" | |
| output, _ = llm(systems=contribution_system_prompt, prompts=prompt, return_json=True) | |
| return output, ref_prompt | |
| def paste_title(suggestions): | |
| if suggestions: | |
| title = suggestions['title']['new title'] | |
| contributions = suggestions['contributions'] | |
| return title, contributions, {}, {}, {} | |
| else: | |
| return "", "", {}, {}, {} | |
| def generate_choices(thoughts): | |
| output, _ = llm(systems=paper_system_prompt, prompts=thoughts, return_json=True) | |
| return output | |
| # def translate_json(json_input): | |
| # system_prompt = "You are a translation bot. The user will input a JSON format string. You need to translate it into Chinese and return in the same formmat." | |
| # output, _ = llm(systems=system_prompt, prompts=str(json_input), return_json=True) | |
| # return output | |
| with gr.Blocks() as demo: | |
| llm = GPTModel(model=default_model) | |
| gr.HTML(ANNOUNCEMENT) | |
| with gr.Row(): | |
| with gr.Tab("生成论文想法 (Generate Paper Ideas)"): | |
| thoughts_input = gr.Textbox(label="Thoughts") | |
| with gr.Accordion("Show prompts", open=False): | |
| prompts_1 = gr.Textbox(label="Prompts", interactive=False, value=paper_system_prompt) | |
| with gr.Row(): | |
| button_generate_idea = gr.Button("Make it an idea!", variant="primary") | |
| with gr.Tab("验证想法可行性 (Validate Feasibility)"): | |
| title_input = gr.Textbox(label="Title") | |
| contribution_input = gr.Textbox(label="Contributions", lines=5) | |
| with gr.Accordion("Show prompts", open=False): | |
| prompts_2 = gr.Textbox(label="Prompts", interactive=False, value=contribution_system_prompt) | |
| with gr.Row(): | |
| button_submit = gr.Button("Criticize my idea!", variant="primary") | |
| with gr.Tab("生成论文 (Generate Paper)"): | |
| gr.Markdown("...") | |
| with gr.Column(scale=1): | |
| contribution_output = gr.JSON(label="Contributions") | |
| # cn_output = gr.JSON(label="主要贡献") | |
| with gr.Accordion("References", open=False): | |
| references_output = gr.JSON(label="References") | |
| button_submit.click(fn=criticize_my_idea, inputs=[title_input, contribution_input], outputs=[contribution_output, references_output]) | |
| button_generate_idea.click(fn=generate_choices, inputs=thoughts_input, outputs=contribution_output)#.success(translate_json, contribution_output, cn_output) | |
| demo.queue(concurrency_count=1, max_size=5, api_open=False) | |
| demo.launch(show_error=True) | |