fix mix up updates
This commit is contained in:
OwusuBlessing
@@ -0,0 +1 @@
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python=3.11
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+24
-22
@@ -1,23 +1,25 @@
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openai
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pandas
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python-dotenv
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fastapi
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uvicorn
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langchain-community
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langchain-openai
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pydantic
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pypdf
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pypandoc
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Spire.Doc
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openai==1.72.0
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pandas==2.2.3
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python-dotenv==1.1.0
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fastapi==0.115.9
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uvicorn==0.34.0
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langchain-community==0.3.21
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langchain-openai==0.3.12
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pydantic==2.11.3
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pypdf==5.4.0
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pypandoc==1.15
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plum-dispatch==1.7.4
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scikit-learn
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werkzeug
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python-multipart
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langgraph
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tiktoken
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langchainhub
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chromadb
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langchain
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langchain-text-splitters
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beautifulsoup4
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langchain-core
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scikit-learn==1.6.1
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Werkzeug==3.1.3
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python-multipart==0.0.20
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langgraph==0.3.27
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tiktoken==0.9.0
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langchainhub==0.1.21
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chromadb==1.0.3
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langchain==0.3.23
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langchain-text-splitters==0.3.8
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beautifulsoup4==4.13.3
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langchain-core==0.3.51
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PyPDF2==3.0.1
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reportlab==4.3.1
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python-docx==1.1.2
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@@ -149,10 +149,18 @@ def generate_quiz(startpop_pdf, quiz_type=None) -> dict:
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- Conclude strongly, avoiding phrases like “and so yeah…”.
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----END------
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NOTE: THE QUIZ FOCUES ON BULIDNG USER CONFIDENCE BY ANANLYZING THE QUESTIONS AND FRAMEWORK FOR EACH QUESTION IN THE STARTPOP FRAMEWORK PDF,SOLELY USE THIS PDF PROVIDED BY THE USER
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BASED ON THIS FRAMEWORK , CREATE INTERVIEW BASED QUIZ FOR FIRE FIGHTING ROLE BY ANALYZING THIS DOCUMENT
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NOTE : THE QUIZ SHOULD NOT BE BASED ON STARTPOP FRAMEWORK ITSELF BUT ANALYZE THE STARTPOP FRAMEWORK PRESENTED TO GENERATE INTERVIEW BASED QUIZ
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e.g "The STARTPOP framework is specifically designed for firefighter interviews", THIS KIND OF QUESTION SHOULD NOT BE ASKED IN THE QUIZ....
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### Instructions:
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- Analyze the provided STARTPOP PDF to extract relevant themes and concepts.
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- Generate a quiz that builds user confidence by focusing on interview-based scenarios.
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- Avoid questions directly about the STARTPOP framework itself (e.g., "What is STARTPOP?").
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- Use the specified quiz type (`quiz_type`) to determine the output format.
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- Generate at least 15 questions and above
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NOTE: The quiz focuses on building user confidence by analyzing the questions and framework presented in the STARTPOP PDF provided by the user.
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Based on this framework, create an interview-based quiz specifically for firefighting roles by thoroughly analyzing the document.
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IMPORTANT: The quiz should not directly reference the STARTPOP framework itself. Instead, it should generate interview-based questions derived from the insights of the STARTPOP framework.
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For example, avoid questions like "The STARTPOP framework is specifically designed for firefighter interviews." Such questions should not be included in the quiz.
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Thank you for your thorough and precise processing!
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STARTPOP FULL PDF :{startpop_pdf}
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question type : {quiz_type}
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@@ -0,0 +1,61 @@
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import subprocess
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import re
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# List of packages you want to include
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packages = [
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"openai",
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"pandas",
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"python-dotenv",
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"fastapi",
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"uvicorn",
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"langchain-community",
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"langchain-openai",
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"pydantic",
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"pypdf",
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"pypandoc",
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"plum-dispatch==1.7.4", # You specified exact version here
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"scikit-learn",
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"werkzeug",
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"python-multipart",
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"langgraph",
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"tiktoken",
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"langchainhub",
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"chromadb",
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"langchain",
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"langchain-text-splitters",
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"beautifulsoup4",
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"langchain-core",
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"PyPDF2",
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"reportlab",
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"python-docx"
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]
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# Get all installed packages with versions
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result = subprocess.run(["pip", "freeze"], capture_output=True, text=True)
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installed_packages = result.stdout.strip().split('\n')
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# Create a dictionary of package names to their full name with version
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package_dict = {}
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for pkg in installed_packages:
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if '==' in pkg:
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name = pkg.split('==')[0].lower()
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package_dict[name] = pkg
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# Write only the requested packages to requirements.txt
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with open('requirements.txt', 'w') as f:
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for package in packages:
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# Handle cases where version is already specifixed
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if '==' in package:
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f.write(f"{package}\n")
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continue
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# Try to find the package in installed packages
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pkg_name = package.lower()
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if pkg_name in package_dict:
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f.write(f"{package_dict[pkg_name]}\n")
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else:
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# If not found, just write the package name
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f.write(f"{package}\n")
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print(f"Warning: {package} not found in installed packages")
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print("requirements.txt has been generated.")
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+32
-14
@@ -1,32 +1,45 @@
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import os
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from spire.doc import Document, FileFormat
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from langchain_community.document_loaders import PyPDFLoader
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from docx import Document as DocxDocument
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from reportlab.lib.pagesizes import letter
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from reportlab.platypus import SimpleDocTemplate, Paragraph, Spacer
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from reportlab.lib.styles import getSampleStyleSheet
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from langchain_community.document_loaders import PyPDFLoader, UnstructuredWordDocumentLoader
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def convert_word_to_pdf(doc_path: str) -> str:
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"""
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Convert a .doc or .docx file to PDF using Spire.Doc.
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Convert a .docx file to PDF using python-docx and reportlab.
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Args:
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doc_path (str): The path to the .doc or .docx file.
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doc_path (str): The path to the .docx file.
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Returns:
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str: The path to the converted PDF file.
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"""
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pdf_path = os.path.splitext(doc_path)[0] + '.pdf'
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# Create a Document object
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document = Document()
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# Load the Word document
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document.LoadFromFile(doc_path)
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# Save as PDF
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document.SaveToFile(pdf_path, FileFormat.PDF)
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document.Close()
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doc = DocxDocument(doc_path)
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# Create a PDF
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pdf = SimpleDocTemplate(pdf_path, pagesize=letter)
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styles = getSampleStyleSheet()
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flowables = []
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# Extract text from paragraphs and add to PDF
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for para in doc.paragraphs:
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if para.text:
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p = Paragraph(para.text, styles['Normal'])
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flowables.append(p)
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flowables.append(Spacer(1, 12))
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# Build the PDF
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pdf.build(flowables)
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return pdf_path
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def load_document(file_path: str):
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"""
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Utility function to load a PDF, DOCX, or DOC file by first converting it to PDF.
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Utility function to load a PDF, DOCX, or DOC file.
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Args:
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file_path (str): The path to the file to load.
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@@ -38,16 +51,21 @@ def load_document(file_path: str):
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try:
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extension = os.path.splitext(file_path)[1].lower()
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if extension in ['.doc', '.docx']:
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# Convert .doc or .docx to PDF first
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if extension == '.docx':
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# For .docx files, use UnstructuredWordDocumentLoader directly
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loader = UnstructuredWordDocumentLoader(file_path)
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return loader.load()
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elif extension == '.doc':
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# Convert .doc to .pdf first
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pdf_path = convert_word_to_pdf(file_path)
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loader = PyPDFLoader(pdf_path)
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return loader.load()
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elif extension == '.pdf':
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loader = PyPDFLoader(file_path)
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return loader.load()
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else:
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raise ValueError(f"Unsupported file type: {extension}. Only .pdf, .docx, and .doc are supported.")
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return loader.load()
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except Exception as e:
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print(f"Error loading document: {str(e)}")
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return None
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