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app.py

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+
+import streamlit as st
+import google.generativeai as genai
+import markdown
+from docx import Document
+from bs4 import BeautifulSoup
+from PyPDF2 import PdfFileReader
+import tempfile
+import os
+
+# Configure the API key
+genai.configure(api_key=os.getenv('gemini_api'))
+
+# Function to convert PDF to text
+def pdf_to_text(file):
+    with open(file, 'rb') as f:
+        pdf = PdfFileReader(f)
+        text = ""
+        for page_num in range(pdf.numPages):
+            page = pdf.getPage(page_num)
+            text += page.extract_text()
+    return text
+
+# Function to upload file to the Generative AI API
+def upload_file(file_path):
+    st.write("Uploading file...")
+    text_file = genai.upload_file(path=file_path)
+    st.write(f"Completed upload: {text_file.uri}")
+    return text_file
+
+# Function to convert text to Markdown
+def to_markdown(text):
+    text = text.replace('•', '  *')
+    return textwrap.indent(text, '> ', predicate=lambda _: True)
+
+chat_session = None
+
+# Function to build the model
+def build_model(text_file):
+    global chat_session
+    generation_config = {
+        "temperature": 0.2,
+        "top_p": 0.95,
+        "top_k": 64,
+        "max_output_tokens": 8192,
+        "response_mime_type": "text/plain",
+    }
+
+    model = genai.GenerativeModel(
+        model_name="gemini-1.5-flash",
+        generation_config=generation_config,
+        system_instruction="""Yüklenen belgedeki bilgilere göre Türkçe cevap ver.
+        Eğer sorunun cevabı belgede bulunmuyorsa 'Belgede Cevap Bulunmuyor' yaz.
+        """,
+    )
+
+    chat_session = model.start_chat(history=[])
+    response = chat_session.send_message(["Yüklenen belgeyi bir cümle ile özetle", text_file])
+
+    st.markdown(to_markdown(response.text))
+
+# Function to interact with the chat model
+def chat(prompt):
+    try:
+        response = chat_session.send_message(prompt)
+        markdown_text = to_markdown(response.text)
+        st.markdown(markdown_text)
+        return response.text
+    except ValueError:
+        st.write(response.prompt_feedback)
+        st.write(response.candidates[0].finish_reason)
+        st.write(response.candidates[0].safety_ratings)
+    except Exception as e:
+        st.write("An unexpected error occurred:", e)
+
+# Function to generate a report based on questions
+def generate_report(questions):
+    report_text = "\n## SORULARINIZ VE CEVAPLARI\n"
+    for question in questions:
+        report_text += f"\n## {question}\n"
+        answer = chat(question)
+        report_text += f"\n{answer}\n"
+    return report_text
+
+# Function to convert Markdown to HTML
+def convert_Markdown_to_HTML(report_text):
+    html_text = markdown.markdown(report_text)
+    return html_text
+
+# Function to add HTML to a Word document
+def add_html_to_word(html_text, doc):
+    soup = BeautifulSoup(html_text, 'html.parser')
+    for element in soup:
+        if element.name == 'h1':
+            doc.add_heading(element.get_text(), level=1)
+        elif element.name == 'h2':
+            doc.add_heading(element.get_text(), level=2)
+        elif element.name == 'h3':
+            doc.add_heading(element.get_text(), level=3)
+        elif element.name == 'h4':
+            doc.add_heading(element.get_text(), level=4)
+        elif element.name == 'h5':
+            doc.add_heading(element.get_text(), level=5)
+        elif element.name == 'h6':
+            doc.add_heading(element.get_text(), level=6)
+        elif element.name == 'p':
+            doc.add_paragraph(element.get_text())
+        elif element.name == 'ul':
+            for li in element.find_all('li'):
+                doc.add_paragraph(li.get_text(), style='List Bullet')
+        elif element.name == 'ol':
+            for li in element.find_all('li'):
+                doc.add_paragraph(li.get_text(), style='List Number')
+        elif element.name:
+            doc.add_paragraph(element.get_text())
+
+# Streamlit interface
+st.title("REPORT GENERATOR: ASK YOUR QUESTIONS TO A PDF FILE BY MURAT KARAKAYA AKADEMI")
+st.write("Upload a PDF to ask questions and get the answers.")
+
+uploaded_file = st.file_uploader("Upload PDF", type="pdf")
+questions_input = st.text_area("Enter Questions", placeholder="Type your questions here, one per line.", height=150)
+
+if uploaded_file and questions_input:
+    with tempfile.NamedTemporaryFile(delete=False) as temp_file:
+        temp_file.write(uploaded_file.read())
+        temp_file_path = temp_file.name
+
+    text_content = pdf_to_text(temp_file_path)
+    text_file = upload_file(temp_file_path)
+    build_model(text_file)
+
+    questions = questions_input.split("\n")
+    report_text = generate_report(questions)
+
+    html_text = convert_Markdown_to_HTML(report_text)
+    doc = Document()
+    add_html_to_word(html_text, doc)
+    
+    doc_name = os.path.basename(temp_file_path).replace(".pdf", ".docx")
+    doc_name = "Rapor " + doc_name
+    doc.save(doc_name)
+    
+    st.markdown(report_text)
+    st.write("Document generated successfully!")
+    
+    with open(doc_name, "rb") as file:
+        st.download_button(label="Download Report", data=file, file_name=doc_name)
+    
+    os.remove(temp_file_path)
+    os.remove(doc_name)
+
+    genai.delete_file(text_file.name)

requirements.txt

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+streamlit
+google-generativeai
+markdown
+python-docx
+beautifulsoup4
+PyPDF2