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from langchain.text_splitter import RecursiveCharacterTextSplitter | |
from langchain_community.document_loaders import PyPDFLoader | |
from llama_cpp import Llama | |
def load_llm_model(): | |
try: | |
llm = Llama( | |
model_path="/home/user/app/Llama-3.2-1B-Instruct-Q8_0.gguf", | |
n_gpu_layers = -1, | |
n_ctx=100000, | |
n_batch=4096, | |
) | |
print("LLM model loaded successfully") | |
return llm | |
except Exception as e: | |
print(f"Error loading LLM model: {e}") | |
raise | |
def get_text_from_pdf(file): | |
loader = PyPDFLoader(file) | |
pages = loader.load_and_split() | |
text_splitter = RecursiveCharacterTextSplitter(chunk_size=250, chunk_overlap=50) | |
texts = text_splitter.split_documents(pages) | |
final_text = "" | |
for text in texts: | |
if text.page_content.startswith("REFERENCES"): | |
break | |
else: | |
final_text = final_text + text.page_content | |
research_paper = "" | |
for text in final_text: | |
if text.startswith(("REFERENCES", "REFERENCESREFERENCES", "REFERENCESREFERENCESREFERENCES")): | |
break | |
else: | |
research_paper = research_paper + text | |
return research_paper[:10000] | |
def generate_prompt(research_paper): | |
prompt = f''' | |
As a text script expert, please help me to write a short text script with the topic \\"{research_paper}\\".Your output should only and strictly use the following template:\\n# {{Title}}\\n## {{Subtitle01}}\\n- {{Emoji01}} Bulletpoint01\\n- {{Emoji02}} Bulletpoint02\\n## {{Subtitle02}}\\n- {{Emoji03}} Bulletpoint03\\n- {{Emoji04}} Bulletpoint04\\n\\nSummarize the giving topic to generate a mind map (as many subtitles as possible, with a minimum of three subtitles) structure markdown.\\n Do not include anything in the response, that is not the part of mindmap.\\n Importantly your output must use language \\"English\\"" | |
''' | |
return prompt | |
def generate_mindmap_structure(llm, prompt): | |
response = llm.create_chat_completion( | |
messages = [ | |
{'role':'system', | |
'content': 'You are a helpful research assistant for generating well-formatted mindmaps in MarkDown format from scientific research papers.'}, | |
{'role':'user', | |
'content': prompt} | |
], | |
temperature=0.7, | |
top_k=200, | |
top_p=3.0, | |
) | |
mindmap_data = response['choices'][0]['message']['content'] | |
return mindmap_data | |
def generate_markdown(llm, file): | |
final_text = get_text_from_pdf(file) | |
prompt = generate_prompt(final_text) | |
mindmap_markdown = generate_mindmap_structure(llm, prompt) | |
if "**" in mindmap_markdown: | |
mindmap_markdown = mindmap_markdown.replace("- **", "### ") | |
mindmap_markdown = mindmap_markdown.replace("**", "") | |
else: | |
pass | |
return mindmap_markdown | |
def sanitize_markdown(llm, mindmap_markdown): | |
prompt = f''' | |
As an experienced coder and programmer, help me convert the text \\"{mindmap_markdown}\\" into a well-formatted markdown. Your output should only and strictly use the following template:\\n# {{Title}}\\n## {{Subtitle01}}\\n- {{Emoji01}} Bulletpoint01\\n- {{Emoji02}} Bulletpoint02\\n## {{Subtitle02}}\\n- {{Emoji03}} Bulletpoint03\\n- {{Emoji04}} Bulletpoint04\\n\\nDo not include anything in the response, that is not the part of mindmap." | |
''' | |
sanitized_markdown = generate_mindmap_structure(llm, prompt) | |
return sanitized_markdown |