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.env

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+# Path to Tesseract executable
+TESSERACT_PATH=C:\Users\GGN06-Ansh\Downloads\Tesseract-OCR\Tesseract-OCR\tesseract.exe
+
+# Path to Poppler for PDF image extraction
+POPPLER_PATH=C:\Users\GGN06-Ansh\Downloads\Release-24.02.0-0\poppler-24.02.0\Library\bin
+
+# Groq API Key
+GROQ_API_KEY=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

.gitignore

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+# Ignore .env file
+.env
+
+# Ignore app.py
+app.py

app.py

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+import gradio as gr
+from groq import Groq, RateLimitError
+import pandas as pd
+from PIL import Image
+import pytesseract
+import pdfplumber
+from pdf2image import convert_from_path
+import os
+import time
+from dotenv import load_dotenv
+
+# Load environment variables from .env file
+load_dotenv()
+
+# Set the path to Tesseract executable
+pytesseract.pytesseract.tesseract_cmd = os.getenv("TESSERACT_CMD")
+
+# Set the path to Poppler for PDF image extraction
+poppler_path = os.getenv("POPPLER_PATH")
+
+# Your Groq API key
+YOUR_GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+
+# Initialize Groq client
+client = Groq(api_key=YOUR_GROQ_API_KEY)
+
+# Global variable to store extracted text
+extracted_text = ""
+
+def extract_text_from_image(image):
+    return pytesseract.image_to_string(image)
+
+def remove_header_footer(image, header_height=3.9, footer_height=2.27):
+    width, height = image.size
+    header_height_pixels = int(header_height * 96)  # Convert inches to pixels (assuming 96 DPI)
+    footer_height_pixels = int(footer_height * 96)
+    cropping_box = (0, header_height_pixels, width, height - footer_height_pixels)
+    return image.crop(cropping_box)
+
+def handle_file(file, page_range=None):
+    global extracted_text
+    extracted_text = ""
+
+    if file is None:
+        return None, "No file uploaded"
+
+    file_name = file.name.lower()
+
+    if file_name.endswith(('png', 'jpg', 'jpeg')):
+        image = Image.open(file)
+        extracted_text = extract_text_from_image(image)
+        return image, extracted_text
+
+    elif file_name.endswith('pdf'):
+        text = ""
+        pdf_images = []
+        start_page = 1
+        end_page = None
+
+        if page_range:
+            try:
+                start_page, end_page = map(int, page_range.split('-'))
+            except ValueError:
+                start_page = int(page_range)
+                end_page = start_page
+
+        with pdfplumber.open(file) as pdf_file:
+            total_pages = len(pdf_file.pages)
+            end_page = end_page or total_pages
+
+            for page_number in range(start_page - 1, end_page):
+                page = pdf_file.pages[page_number]
+                page_text = page.extract_text() or ""
+                text += f"Page {page_number + 1}:\n{page_text}\n"
+
+                try:
+                    page_images = convert_from_path(file.name, first_page=page_number + 1, last_page=page_number + 1, poppler_path=poppler_path)
+                    page_images = [remove_header_footer(img) for img in page_images]
+                    pdf_images.extend(page_images)
+                    for img in page_images:
+                        image_text = extract_text_from_image(img)
+                        text += f"Page {page_number + 1} (Image):\n{image_text}\n"
+                except Exception as e:
+                    text += f"Error processing images on page {page_number + 1}: {e}\n"
+
+        extracted_text = text
+        if pdf_images:
+            return pdf_images[0], extracted_text
+        else:
+            return None, extracted_text
+
+    elif file_name.endswith(('xls', 'xlsx')):
+        df = pd.read_excel(file)
+        extracted_text = df.to_string()
+        return None, extracted_text
+
+    elif file_name.endswith('csv'):
+        df = pd.read_csv(file)
+        extracted_text = df.to_string()
+        return None, extracted_text
+
+    else:
+        return None, "Unsupported file type"
+
+def split_text(text, max_length=2000):
+    words = text.split()
+    chunks = []
+    current_chunk = []
+    current_length = 0
+    for word in words:
+        word_length = len(word) + 1  # +1 for the space or punctuation
+        if current_length + word_length > max_length:
+            chunks.append(" ".join(current_chunk))
+            current_chunk = [word]
+            current_length = word_length
+        else:
+            current_chunk.append(word)
+            current_length += word_length
+    if current_chunk:
+        chunks.append(" ".join(current_chunk))
+    return chunks
+
+def is_rate_limited():
+    # Implement a method to check rate limit status if needed
+    return False
+
+def chat_groq_sync(user_input, history, extracted_text):
+    retries = 5
+    while retries > 0:
+        rate_limit_status = is_rate_limited()
+        if rate_limit_status:
+            return f"{rate_limit_status} Please try again later."
+
+        messages = [{"role": "system", "content": "The following text is extracted from the uploaded file:\n" + extracted_text}]
+        for msg in history:
+            messages.append({"role": "user", "content": msg[0]})
+            messages.append({"role": "assistant", "content": msg[1]})
+        messages.append({"role": "user", "content": user_input})
+
+        try:
+            response = client.chat.completions.create(
+                model="llama3-70b-8192",
+                messages=messages,
+                max_tokens=1000,
+                temperature=0.4
+            )
+
+            response_content = response.choices[0].message.content
+            return response_content
+        except RateLimitError as e:
+            error_info = e.args[0] if e.args else {}
+            error_message = error_info.get('error', {}).get('message', '') if isinstance(error_info, dict) else str(error_info)
+
+            wait_time = 60
+            if 'try again in' in error_message:
+                try:
+                    wait_time = float(error_message.split('try again in ')[-1].split('s')[0])
+                except ValueError:
+                    pass
+
+            print(f"Rate limit error: {error_message}")
+            print(f"Retrying in {wait_time:.2f} seconds...")
+            retries -= 1
+            if retries > 0:
+                time.sleep(wait_time)
+            else:
+                return "Rate limit exceeded. Please try again later."
+        except Exception as e:
+            print(f"An unexpected error occurred: {e}")
+            return "An unexpected error occurred. Please try again later."
+
+def update_chat(user_input, history):
+    global extracted_text
+    response = chat_groq_sync(user_input, history, extracted_text)
+    history.append((user_input, response))
+    return history, history, ""
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        with gr.Column(scale=1):
+            gr.Markdown("# RAG Chatbot")
+            gr.Markdown("Check out the [GitHub](https://github.com/anshh-arora?tab=repositories) for more information.")
+
+            file = gr.File(label="Upload your file")
+            page_range = gr.Textbox(label="If the uploaded document is a PDF and has more than 10 pages, enter the page range (e.g., 1-3) or specific page number (e.g., 2):", lines=1, visible=False, interactive=True)
+            file_upload_button = gr.Button("Upload File")
+            image_display = gr.Image(label="Uploaded Image", visible=False)
+            extracted_text_display = gr.Textbox(label="Extracted Text", interactive=False)
+
+        with gr.Column(scale=3):
+            gr.Markdown("# Chat with your file")
+            history = gr.State([])
+            with gr.Column():
+                chatbot = gr.Chatbot(height=500, bubble_full_width=False)
+                user_input = gr.Textbox(placeholder="Enter Your Query", visible=True, scale=7, interactive=True)
+
+                clear_btn = gr.Button("Clear")
+                undo_btn = gr.Button("Undo")
+
+                user_input.submit(update_chat, [user_input, history], [chatbot, history, user_input])
+                clear_btn.click(lambda: ([], []), None, [chatbot, history])
+                undo_btn.click(lambda h: h[:-2], history, history)
+
+    def show_page_range_input(file):
+        if file and file.name.lower().endswith('pdf'):
+            with pdfplumber.open(file) as pdf_file:
+                if len(pdf_file.pages) > 10:
+                    return gr.update(visible=True)
+        return gr.update(visible=False)
+
+    file.change(show_page_range_input, inputs=file, outputs=page_range)
+    file_upload_button.click(handle_file, [file, page_range], [image_display, extracted_text_display])
+
+if __name__ == "__main__":
+    demo.launch(share=True)