Pushing the Files

PDFSummerizorV1/.gitignore

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+.env
+venv/

PDFSummerizorV1/README.md

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+# PDF Summarizer V1
+
+This project is a command-line tool to summarize PDF documents using a two-step process with AI models.
+
+## How it works
+
+1.  **Extracts Text**: The tool first extracts the text content from the provided PDF file.
+2.  **Initial Summary**: It then uses a generative AI model (e.g., `gemma-3-4b-it`) to create an initial summary of the text.
+3.  **Refined Summary**: This initial summary is then passed to a second, potentially more advanced model (e.g., `QwQ-32B`), to refine and improve the summary.
+
+## How to use
+
+1.  Install the required dependencies:
+    ```bash
+    pip install -r requirements.txt
+    ```
+2.  Place your PDF file in the `uploads` directory.
+3.  Run the application from your terminal:
+    ```bash
+    python app.py uploads/your_file.pdf
+    ```

PDFSummerizorV1/app.py

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+import os
+import argparse
+from openai import OpenAI
+import PyPDF2
+from dotenv import load_dotenv
+
+load_dotenv()
+
+# Load the API key from the .env file
+client = OpenAI(api_key=os.environ.get("OPENAI_API_KEY"), base_url="https://genai.ghaymah.systems")
+
+def extract_text_from_pdf(pdf_path):
+    """Extracts text from a PDF file."""
+    print(f"Extracting text from {pdf_path}...")
+    text = ""
+    try:
+        with open(pdf_path, "rb") as f:
+            reader = PyPDF2.PdfReader(f)
+            for page in reader.pages:
+                text += page.extract_text()
+    except FileNotFoundError:
+        print(f"Error: The file at {pdf_path} was not found.")
+        return None
+    except Exception as e:
+        print(f"An error occurred while reading the PDF: {e}")
+        return None
+    print("Text extraction complete.")
+    return text
+
+def summarize_text(text, model="DeepSeek-V3-0324"):
+    """Summarizes the text using a specified model."""
+    print(f"Summarizing text using {model}...")
+    try:
+        response = client.chat.completions.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant that summarizes text."},
+                {"role": "user", "content": f"Please summarize the following text:\n\n{text}"}
+            ]
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        print(f"An error occurred during summarization: {e}")
+        return None
+
+def refine_summary(summary, model="DeepSeek-V3-0324"):
+    """Refines the summary using another model."""
+    print(f"Refining summary using {model}...")
+    try:
+        response = client.chat.completions.create(
+            model=model,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant that refines and improves summaries."},
+                {"role": "user", "content": f"Please refine and improve the following summary:\n\n{summary}"}
+            ]
+        )
+        return response.choices[0].message.content
+    except Exception as e:
+        print(f"An error occurred during summary refinement: {e}")
+        return None
+
+def main():
+    parser = argparse.ArgumentParser(description="Summarize a PDF document using AI models.")
+    parser.add_argument("pdf_path", help="The path to the PDF file to summarize.")
+    args = parser.parse_args()
+
+    # 1. Extract text from the PDF
+    pdf_text = extract_text_from_pdf(args.pdf_path)
+    if pdf_text is None:
+        return
+
+    # 2. Create an initial summary
+    initial_summary = summarize_text(pdf_text)
+    if initial_summary is None:
+        return
+
+    # 3. Refine the summary
+    refined_summary = refine_summary(initial_summary)
+    if refined_summary is None:
+        return
+
+    print("\n--- Initial Summary ---")
+    print(initial_summary)
+    print("\n--- Refined Summary ---")
+    print(refined_summary)
+
+if __name__ == "__main__":
+    main()

PDFSummerizorV1/requirements.txt

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+openai
+PyPDF2
+python-dotenv