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Reality123b
commited on
Update app.py
Browse files
app.py
CHANGED
@@ -4,6 +4,8 @@ import requests
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import gradio as gr
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from huggingface_hub import InferenceClient
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from dataclasses import dataclass
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@dataclass
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class ChatMessage:
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@@ -71,10 +73,8 @@ class XylariaChat:
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def caption_image(self, image):
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"""
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Caption an uploaded image using Hugging Face API
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Args:
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image (str): Base64 encoded image or file path
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Returns:
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str: Image caption or error message
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"""
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@@ -110,14 +110,35 @@ class XylariaChat:
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except Exception as e:
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return f"Error processing image: {str(e)}"
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def get_response(self, user_input, image=None):
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"""
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Generate a response using chat completions with improved error handling
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Args:
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user_input (str): User's message
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image (optional): Uploaded image
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Returns:
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Stream of chat completions or error message
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"""
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@@ -202,18 +223,31 @@ class XylariaChat:
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def create_interface(self):
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def streaming_response(message, chat_history, image_filepath):
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# Check if an image was actually uploaded
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if image_filepath:
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response_stream = self.get_response(message, image_filepath)
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else:
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response_stream = self.get_response(message)
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# Handle errors in get_response
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if isinstance(response_stream, str):
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# Return immediately with the error message
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updated_history = chat_history + [[message, response_stream]]
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yield "", updated_history, None
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return
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# Prepare for streaming response
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@@ -229,12 +263,12 @@ class XylariaChat:
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# Update the last message in chat history with partial response
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updated_history[-1][1] = full_response
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yield "", updated_history, None
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except Exception as e:
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print(f"Streaming error: {e}")
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# Display error in the chat interface
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updated_history[-1][1] = f"Error during response: {e}"
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yield "", updated_history, None
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return
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# Update conversation history
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@@ -317,6 +351,17 @@ class XylariaChat:
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)
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with gr.Row():
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clear_image_btn = gr.Button("Clear Image")
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# Input row with improved layout
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with gr.Row():
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@@ -341,16 +386,24 @@ class XylariaChat:
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queue=False
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)
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# Submit functionality with streaming and image support
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btn.click(
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fn=streaming_response,
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inputs=[txt, chatbot, img],
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outputs=[txt, chatbot, img]
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)
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txt.submit(
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fn=streaming_response,
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inputs=[txt, chatbot, img],
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outputs=[txt, chatbot, img]
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)
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# Clear conversation history
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import gradio as gr
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from huggingface_hub import InferenceClient
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from dataclasses import dataclass
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import pytesseract
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from PIL import Image
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@dataclass
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class ChatMessage:
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def caption_image(self, image):
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"""
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Caption an uploaded image using Hugging Face API
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Args:
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image (str): Base64 encoded image or file path
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Returns:
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str: Image caption or error message
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"""
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except Exception as e:
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return f"Error processing image: {str(e)}"
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def perform_math_ocr(self, image_path):
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"""
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Perform OCR on an image and return the extracted text.
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Args:
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image_path (str): Path to the image file.
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Returns:
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str: Extracted text from the image, or an error message.
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"""
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try:
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# Open the image using Pillow library
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img = Image.open(image_path)
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# Use Tesseract to do OCR on the image
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text = pytesseract.image_to_string(img)
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# Remove leading/trailing whitespace and return
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return text.strip()
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except Exception as e:
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return f"Error during Math OCR: {e}"
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def get_response(self, user_input, image=None):
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"""
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Generate a response using chat completions with improved error handling
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Args:
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user_input (str): User's message
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image (optional): Uploaded image
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Returns:
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Stream of chat completions or error message
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"""
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def create_interface(self):
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def streaming_response(message, chat_history, image_filepath, math_ocr_image_path):
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ocr_text = ""
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if math_ocr_image_path:
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ocr_text = self.perform_math_ocr(math_ocr_image_path)
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if ocr_text.startswith("Error"):
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# Handle OCR error
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updated_history = chat_history + [[message, ocr_text]]
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yield "", updated_history, None, None
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return
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else:
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message = f"Math OCR Result: {ocr_text}\n\nUser's message: {message}"
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# Check if an image was actually uploaded
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if image_filepath:
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response_stream = self.get_response(message, image_filepath)
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else:
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response_stream = self.get_response(message)
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# Handle errors in get_response
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if isinstance(response_stream, str):
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# Return immediately with the error message
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updated_history = chat_history + [[message, response_stream]]
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yield "", updated_history, None, None
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return
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# Prepare for streaming response
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# Update the last message in chat history with partial response
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updated_history[-1][1] = full_response
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yield "", updated_history, None, None
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except Exception as e:
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print(f"Streaming error: {e}")
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# Display error in the chat interface
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updated_history[-1][1] = f"Error during response: {e}"
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yield "", updated_history, None, None
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return
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# Update conversation history
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)
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with gr.Row():
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clear_image_btn = gr.Button("Clear Image")
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with gr.Accordion("Math Input", open=False):
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with gr.Column():
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math_ocr_img = gr.Image(
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sources=["upload", "webcam"],
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type="filepath",
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label="Upload Image for math",
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elem_classes="image-preview"
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)
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with gr.Row():
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clear_math_ocr_btn = gr.Button("Clear Math Image")
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# Input row with improved layout
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with gr.Row():
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queue=False
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)
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# Clear Math OCR image functionality
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clear_math_ocr_btn.click(
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fn=lambda: None,
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inputs=None,
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outputs=[math_ocr_img],
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queue=False
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)
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# Submit functionality with streaming and image support
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btn.click(
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fn=streaming_response,
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inputs=[txt, chatbot, img, math_ocr_img],
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outputs=[txt, chatbot, img, math_ocr_img]
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)
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txt.submit(
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fn=streaming_response,
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inputs=[txt, chatbot, img, math_ocr_img],
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outputs=[txt, chatbot, img, math_ocr_img]
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)
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# Clear conversation history
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