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Browse files- README.md +2 -9
- app.py +96 -0
- gitattributes +35 -0
- requirements.txt +7 -0
README.md
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---
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title:
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colorFrom: purple
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colorTo: green
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sdk: gradio
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sdk_version: 4.44.0
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app_file: app.py
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pinned: false
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license: apache-2.0
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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title: pixtral
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app_file: app.py
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sdk: gradio
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sdk_version: 4.44.0
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---
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app.py
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import base64
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import requests
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from io import BytesIO
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from PIL import Image
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import gradio as gr
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from pymongo import MongoClient
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import time
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import uuid
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# MongoDB setup
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mongo_client = MongoClient("mongodb+srv://atharva2021:[email protected]/")
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db = mongo_client['bajaj']
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collection = db['client']
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# Function to encode the image to base64
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def encode_image(img):
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buffered = BytesIO()
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img.save(buffered, format="PNG")
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encoded_string = base64.b64encode(buffered.getvalue()).decode("utf-8")
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return encoded_string
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# Chat function with Pixtral and MongoDB saving
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def chat_with_pixtral(uploaded_file, mrn_number, user_question):
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if uploaded_file is not None and mrn_number.strip() != "":
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base64_img = encode_image(uploaded_file)
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api = "https://api.hyperbolic.xyz/v1/chat/completions"
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api_key = "eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJzdWIiOiJyZzMyNzAyNEBnbWFpbC5jb20ifQ._frFve-BYZdb0Qo6FIj6xcDcxpY-6QlC2O-ToQxBjkc" # Add your API key here
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headers = {
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"Content-Type": "application/json",
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"Authorization": f"Bearer {api_key}",
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}
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payload = {
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"messages": [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": user_question},
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{
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"type": "image_url",
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"image_url": {"url": f"data:image/jpeg;base64,{base64_img}"},
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},
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],
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}
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],
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"model": "mistralai/Pixtral-12B-2409",
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"max_tokens": 2048,
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"temperature": 0.7,
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"top_p": 0.9,
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}
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response = requests.post(api, headers=headers, json=payload)
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# Process API response
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if response.status_code == 200:
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response_data = response.json()
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if 'choices' in response_data:
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assistant_response = response_data['choices'][0]['message']['content']
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else:
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assistant_response = "Response format is incorrect"
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else:
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assistant_response = f"API request failed: {response.status_code} - {response.text}"
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# Generate a unique ID for the request
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unique_id = str(uuid.uuid4())
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# Save the result to MongoDB with the specified format
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document = {
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'mrn_number': mrn_number,
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'ocr_result': assistant_response, # This will be the OCR/API result
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'unique_id': unique_id,
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'got_mode': "plain texts OCR",
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'timestamp': time.time()
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}
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collection.insert_one(document) # Insert the document into MongoDB
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return assistant_response
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return "Upload your image, enter MRN number, and enter your question."
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# Gradio GUI
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iface = gr.Interface(
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fn=chat_with_pixtral,
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inputs=[
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gr.Image(type="pil", label="Upload Your Image"),
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gr.Textbox(label="Enter MRN Number"),
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gr.Textbox(label="Please enter your question")
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],
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outputs="text",
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title="Pixtral Image Chat",
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description="Upload your Image, enter MRN number, and get insights out of the Image"
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)
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iface.launch(share=True)
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gitattributes
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*.7z filter=lfs diff=lfs merge=lfs -text
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*.arrow filter=lfs diff=lfs merge=lfs -text
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*.bin filter=lfs diff=lfs merge=lfs -text
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*.bz2 filter=lfs diff=lfs merge=lfs -text
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*.ckpt filter=lfs diff=lfs merge=lfs -text
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*.ftz filter=lfs diff=lfs merge=lfs -text
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*.h5 filter=lfs diff=lfs merge=lfs -text
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*.joblib filter=lfs diff=lfs merge=lfs -text
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*.lfs.* filter=lfs diff=lfs merge=lfs -text
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*.mlmodel filter=lfs diff=lfs merge=lfs -text
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*.model filter=lfs diff=lfs merge=lfs -text
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*.msgpack filter=lfs diff=lfs merge=lfs -text
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*.npy filter=lfs diff=lfs merge=lfs -text
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*.onnx filter=lfs diff=lfs merge=lfs -text
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*.pb filter=lfs diff=lfs merge=lfs -text
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*.pickle filter=lfs diff=lfs merge=lfs -text
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*.pt filter=lfs diff=lfs merge=lfs -text
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*.rar filter=lfs diff=lfs merge=lfs -text
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*.safetensors filter=lfs diff=lfs merge=lfs -text
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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requirements.txt
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accelerate
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diffusers
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invisible_watermark
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torch
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transformers
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xformers
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pymongo
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