Bug fix. Complete Prompts mode.

app.py

@@ -134,7 +134,7 @@ def wrapped_generator(
         tldr=True, max_kw_refs=10, bib_refs=None, max_tokens_ref=2048,  # references
         knowledge_database=None, max_tokens_kd=2048, query_counts=10,  # domain knowledge
         paper_template="ICLR2022", selected_sections=None, model="gpt-4", prompts_mode=False,  # outputs parameters
-        cache_mode=False # IS_CACHE_AVAILABLE  # handle cache mode
+        cache_mode=IS_CACHE_AVAILABLE  # handle cache mode
 ):
     # if `cache_mode` is True, then follow the following steps:
     #        check if "title"+"description" have been generated before
@@ -271,16 +271,16 @@ with gr.Blocks(theme=theme) as demo:
                     clear_button_pp = gr.Button("Clear")
                     submit_button_pp = gr.Button("Submit", variant="primary")
 
-            with gr.Tab("文献搜索"):
-                gr.Markdown(REFERENCES)
-
-                title_refs = gr.Textbox(value="Playing Atari with Deep Reinforcement Learning", lines=1, max_lines=1,
-                                        label="Title", info="论文标题")
-                slider_refs = gr.Slider(minimum=1, maximum=100, value=5, step=1,
-                                        interactive=True, label="最相关的参考文献数目")
-                with gr.Row():
-                    clear_button_refs = gr.Button("Clear")
-                    submit_button_refs = gr.Button("Submit", variant="primary")
+            # with gr.Tab("文献搜索"):
+            #     gr.Markdown(REFERENCES)
+            #
+            #     title_refs = gr.Textbox(value="Playing Atari with Deep Reinforcement Learning", lines=1, max_lines=1,
+            #                             label="Title", info="论文标题")
+            #     slider_refs = gr.Slider(minimum=1, maximum=100, value=5, step=1,
+            #                             interactive=True, label="最相关的参考文献数目")
+            #     with gr.Row():
+            #         clear_button_refs = gr.Button("Clear")
+            #         submit_button_refs = gr.Button("Submit", variant="primary")
 
             with gr.Tab("文献综述 (Coming soon!)"):
                 gr.Markdown('''
@@ -312,9 +312,9 @@ with gr.Blocks(theme=theme) as demo:
                                    domain_knowledge, max_tokens_kd_slider, query_counts_slider,
                                    template, sections, model_selection, prompts_mode], outputs=file_output)
 
-    clear_button_refs.click(fn=clear_inputs_refs, inputs=[title_refs, slider_refs], outputs=[title_refs, slider_refs])
-    submit_button_refs.click(fn=wrapped_references_generator,
-                             inputs=[title_refs, slider_refs, key], outputs=json_output)
+    # clear_button_refs.click(fn=clear_inputs_refs, inputs=[title_refs, slider_refs], outputs=[title_refs, slider_refs])
+    # submit_button_refs.click(fn=wrapped_references_generator,
+    #                          inputs=[title_refs, slider_refs, key], outputs=json_output)
 
 demo.queue(concurrency_count=1, max_size=5, api_open=False)
 demo.launch(show_error=True)

auto_backgrounds.py

@@ -5,6 +5,7 @@ from utils.knowledge import Knowledge
 from utils.file_operations import hash_name, make_archive, copy_templates
 from utils.tex_processing import create_copies
 from section_generator import section_generation  # figures_generation, section_generation_bg, keywords_generation,
+from utils.prompts import generate_paper_prompts
 import logging
 import time
 from langchain.vectorstores import FAISS
@@ -145,6 +146,7 @@ def _generation_setup(title, description="", template="ICLR2022",
                 print(f"Failed to query from FAISS. Error {e}. Use empty domain knowledge instead.")
                 domain_knowledge = ""
     else:
+        print("Selected database doesn't exist or no database is selected.")
         domain_knowledge = ""
 
     ###################################################################################################################
@@ -249,8 +251,14 @@ def generate_draft(title, description="", # main input
                                                      knowledge_database=knowledge_database)
 
     # main components
+    prompts_dict = {}
     print(f"================PROCESSING================")
     for section in sections:
+        if prompts_mode:
+            prompts = generate_paper_prompts(paper, section)
+            prompts_dict[section] = prompts
+            continue
+
         print(f"Generate {section} part...")
         max_attempts = 4
         attempts_count = 0
@@ -273,7 +281,14 @@ def generate_draft(title, description="", # main input
     input_dict = {"title": title, "description": description, "generator": "generate_draft"}
     filename = hash_name(input_dict) + ".zip"
     print("\nMission completed.\n")
-    return make_archive(destination_folder, filename)
+
+    if prompts_mode:
+        filename = hash_name(input_dict) + ".json"
+        with open(filename, "w") as f:
+            json.dump(prompts_dict, f)
+        return filename
+    else:
+        return make_archive(destination_folder, filename)
 
 
 if __name__ == "__main__":

latex_templates/Default/template.tex

@@ -14,6 +14,11 @@
 \usepackage{algorithm}
 \usepackage{algpseudocode}
 
+\newlength\tindent
+\setlength{\tindent}{\parindent}
+\setlength{\parindent}{0pt}
+\renewcommand{\indent}{\hspace*{\tindent}}
+
 \title{TITLE} 
 \author{GPT-4}
 

utils/prompts.py

@@ -170,7 +170,7 @@ def generate_paper_prompts(paper_info, section):
     # ref_instruction_subprompt - give AI references
     # self_subprompt - give AI existing written parts
     # output_subprompt - tell AI how to output
-    fundamental_subprompt = "Your task is to write the {section} section of the paper with the title '{title}'. {description}\n"
+    fundamental_subprompt = "Your task is to write the {section} section of the paper with the title '{title}'. This paper has the following contributions: {description}\n"
     instruction_subprompt = "\n" \
                             "Your response should follow the following instructions:\n" \
                             "{instruction}\n" \

utils/references.py

@@ -333,6 +333,8 @@ class References:
         #   send (title, .bib file) to evaluate embeddings; recieve truncated papers
         papers = self._get_papers(keyword="_all")
 
+        l = len(papers)
+        print(f"{l} papers will be added to `ref.bib`.")
         # clear the bibtex file
         with open(path_to_bibtex, "w", encoding="utf-8") as file:
             file.write("")
@@ -358,6 +360,7 @@ class References:
             with open(path_to_bibtex, "a", encoding="utf-8") as file:
                 file.write(bibtex_entry)
                 file.write("\n\n")
+                # print(f'{paper["paper_id"]} has been added to `ref.bib`.')
         return paper_ids
 
     def _get_papers(self, keyword="_all"):