Spaces:
Running
Running
| import gradio as gr | |
| import requests | |
| import os | |
| from PIL import Image | |
| import json | |
| from datetime import datetime | |
| # Example data with placeholder JSON for lab_results and bank_statement | |
| examples = [ | |
| ["bonds_table.png", "Bonds table", "[{\"instrument_name\":\"example\", \"valuation\":0}]"], | |
| ["lab_results.png", "Lab results", "{\"patient_name\": \"example\", \"patient_age\": \"example\", \"patient_pid\": 0, \"lab_results\": [{\"investigation\": \"example\", \"result\": 0.00, \"reference_value\": \"example\", \"unit\": \"example\"}]}"], | |
| ["bank_statement.png", "Bank statement", "*"] | |
| ] | |
| # JSON data for Bonds table | |
| bonds_json = [ | |
| { | |
| "instrument_name": "UNITS BLACKROCK FIX INC DUB FDS PLC ISHS EUR INV GRD CP BD IDX/INST/E", | |
| "valuation": 19049 | |
| }, | |
| { | |
| "instrument_name": "UNITS ISHARES III PLC CORE EUR GOVT BOND UCITS ETF/EUR", | |
| "valuation": 83488 | |
| }, | |
| { | |
| "instrument_name": "UNITS ISHARES III PLC EUR CORP BOND 1-5YR UCITS ETF/EUR", | |
| "valuation": 213030 | |
| }, | |
| { | |
| "instrument_name": "UNIT ISHARES VI PLC/JP MORGAN USD E BOND EUR HED UCITS ETF DIST/HDGD/", | |
| "valuation": 32774 | |
| }, | |
| { | |
| "instrument_name": "UNITS XTRACKERS II SICAV/EUR HY CORP BOND UCITS ETF/-1D-/DISTR.", | |
| "valuation": 23643 | |
| } | |
| ] | |
| lab_results_json = { | |
| "patient_name": "Yash M. Patel", | |
| "patient_age": "21 Years", | |
| "patient_pid": 555, | |
| "lab_results": [ | |
| { | |
| "investigation": "Hemoglobin (Hb)", | |
| "result": 12.5, | |
| "reference_value": "13.0 - 17.0", | |
| "unit": "g/dL" | |
| }, | |
| { | |
| "investigation": "RBC COUNT", | |
| "result": 5.2, | |
| "reference_value": "4.5 - 5.5", | |
| "unit": "mill/cumm" | |
| }, | |
| { | |
| "investigation": "Packed Cell Volume (PCV)", | |
| "result": 57.5, | |
| "reference_value": "40 - 50", | |
| "unit": "%" | |
| }, | |
| { | |
| "investigation": "Mean Corpuscular Volume (MCV)", | |
| "result": 87.75, | |
| "reference_value": "83 - 101", | |
| "unit": "fL" | |
| }, | |
| { | |
| "investigation": "MCH", | |
| "result": 27.2, | |
| "reference_value": "27 - 32", | |
| "unit": "pg" | |
| }, | |
| { | |
| "investigation": "MCHC", | |
| "result": 32.8, | |
| "reference_value": "32.5 - 34.5", | |
| "unit": "g/dL" | |
| }, | |
| { | |
| "investigation": "RDW", | |
| "result": 13.6, | |
| "reference_value": "11.6 - 14.0", | |
| "unit": "%" | |
| }, | |
| { | |
| "investigation": "WBC COUNT", | |
| "result": 9000, | |
| "reference_value": "4000-11000", | |
| "unit": "cumm" | |
| }, | |
| { | |
| "investigation": "Neutrophils", | |
| "result": 60, | |
| "reference_value": "50 - 62", | |
| "unit": "%" | |
| }, | |
| { | |
| "investigation": "Lymphocytes", | |
| "result": 31, | |
| "reference_value": "20 - 40", | |
| "unit": "%" | |
| }, | |
| { | |
| "investigation": "Eosinophils", | |
| "result": 1, | |
| "reference_value": "00 - 06", | |
| "unit": "%" | |
| }, | |
| { | |
| "investigation": "Monocytes", | |
| "result": 7, | |
| "reference_value": "00 - 10", | |
| "unit": "%" | |
| }, | |
| { | |
| "investigation": "Basophils", | |
| "result": 1, | |
| "reference_value": "00 - 02", | |
| "unit": "%" | |
| }, | |
| { | |
| "investigation": "Absolute Neutrophils", | |
| "result": 6000, | |
| "reference_value": "1500 - 7500", | |
| "unit": "cells/mcL" | |
| }, | |
| { | |
| "investigation": "Absolute Lymphocytes", | |
| "result": 3100, | |
| "reference_value": "1300 - 3500", | |
| "unit": "cells/mcL" | |
| }, | |
| { | |
| "investigation": "Absolute Eosinophils", | |
| "result": 100, | |
| "reference_value": "00 - 500", | |
| "unit": "cells/mcL" | |
| }, | |
| { | |
| "investigation": "Absolute Monocytes", | |
| "result": 700, | |
| "reference_value": "200 - 950", | |
| "unit": "cells/mcL" | |
| }, | |
| { | |
| "investigation": "Absolute Basophils", | |
| "result": 100, | |
| "reference_value": "00 - 300", | |
| "unit": "cells/mcL" | |
| }, | |
| { | |
| "investigation": "Platelet Count", | |
| "result": 320000, | |
| "reference_value": "150000 - 410000", | |
| "unit": "cumm" | |
| } | |
| ] | |
| } | |
| bank_statement_json = { | |
| "bank": "First Platypus Bank", | |
| "address": "1234 Kings St., New York, NY 12123", | |
| "account_holder": "Mary G. Orta", | |
| "account_number": "1234567890123", | |
| "statement_date": "3/1/2022", | |
| "period_covered": "2/1/2022 - 3/1/2022", | |
| "account_summary": { | |
| "balance_on_march_1": "$25,032.23", | |
| "total_money_in": "$10,234.23", | |
| "total_money_out": "$10,532.51" | |
| }, | |
| "transactions": [ | |
| { | |
| "date": "02/01", | |
| "description": "PGD EasyPay Debit", | |
| "withdrawal": "203.24", | |
| "deposit": "", | |
| "balance": "22,098.23" | |
| }, | |
| { | |
| "date": "02/02", | |
| "description": "AB&B Online Payment*****", | |
| "withdrawal": "71.23", | |
| "deposit": "", | |
| "balance": "22,027.00" | |
| }, | |
| { | |
| "date": "02/04", | |
| "description": "Check No. 2345", | |
| "withdrawal": "", | |
| "deposit": "450.00", | |
| "balance": "22,477.00" | |
| }, | |
| { | |
| "date": "02/05", | |
| "description": "Payroll Direct Dep 23422342 Giants", | |
| "withdrawal": "", | |
| "deposit": "2,534.65", | |
| "balance": "25,011.65" | |
| }, | |
| { | |
| "date": "02/06", | |
| "description": "Signature POS Debit - TJP", | |
| "withdrawal": "84.50", | |
| "deposit": "", | |
| "balance": "24,927.15" | |
| }, | |
| { | |
| "date": "02/07", | |
| "description": "Check No. 234", | |
| "withdrawal": "1,400.00", | |
| "deposit": "", | |
| "balance": "23,527.15" | |
| }, | |
| { | |
| "date": "02/08", | |
| "description": "Check No. 342", | |
| "withdrawal": "", | |
| "deposit": "25.00", | |
| "balance": "23,552.15" | |
| }, | |
| { | |
| "date": "02/09", | |
| "description": "FPB AutoPay***** Credit Card", | |
| "withdrawal": "456.02", | |
| "deposit": "", | |
| "balance": "23,096.13" | |
| }, | |
| { | |
| "date": "02/08", | |
| "description": "Check No. 123", | |
| "withdrawal": "", | |
| "deposit": "25.00", | |
| "balance": "23,552.15" | |
| }, | |
| { | |
| "date": "02/09", | |
| "description": "FPB AutoPay***** Credit Card", | |
| "withdrawal": "156.02", | |
| "deposit": "", | |
| "balance": "23,096.13" | |
| }, | |
| { | |
| "date": "02/08", | |
| "description": "Cash Deposit", | |
| "withdrawal": "", | |
| "deposit": "25.00", | |
| "balance": "23,552.15" | |
| } | |
| ] | |
| } | |
| def run_inference(image_filepath, query, key): | |
| if image_filepath is None: | |
| return {"error": f"No image provided. Please upload an image before submitting."} | |
| if query is None or query.strip() == "": | |
| return {"error": f"No query provided. Please enter a query before submitting."} | |
| if key is None or key.strip() == "": | |
| return {"error": f"No Sparrow Key provided. Please enter a Sparrow Key before submitting."} | |
| file_path = None | |
| try: | |
| # Open the uploaded image using its filepath | |
| img = Image.open(image_filepath) | |
| # Extract the file extension from the uploaded file | |
| input_image_extension = image_filepath.split('.')[-1].lower() # Extract extension from filepath | |
| # Set file extension based on the original file, otherwise default to PNG | |
| if input_image_extension in ['jpg', 'jpeg', 'png']: | |
| file_extension = input_image_extension | |
| else: | |
| file_extension = 'png' # Default to PNG if extension is unavailable or invalid | |
| # Generate a unique filename using timestamp | |
| timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") | |
| filename = f"image_{timestamp}.{file_extension}" | |
| # Save the image | |
| img.save(filename) | |
| # Get the full path of the saved image | |
| file_path = os.path.abspath(filename) | |
| # Prepare the REST API call | |
| url = 'https://katanaml-sparrow-ml.hf.space/api/v1/sparrow-llm/inference' | |
| headers = { | |
| 'accept': 'application/json' | |
| } | |
| # Open the file in binary mode and send it | |
| with open(filename, "rb") as f: | |
| files = { | |
| 'file': (filename, f, f'image/{file_extension}') | |
| } | |
| # Convert 'query' input to JSON string if needed | |
| try: | |
| # Check if the query is a wildcard '*' | |
| if query.strip() == "*": | |
| query_json = "*" # Directly use the wildcard as valid input | |
| else: | |
| # Attempt to parse the query as JSON | |
| query_json = json.loads(query) # This could return any valid JSON (string, number, etc.) | |
| # Ensure the parsed query is either a JSON object (dict) or a list of JSON objects | |
| if not isinstance(query_json, (dict, list)): | |
| return { | |
| "error": "Invalid input. Only JSON objects, arrays of objects, or wildcard '*' are allowed."} | |
| # If it's a list, make sure it's a list of JSON objects | |
| if isinstance(query_json, list): | |
| if not all(isinstance(item, dict) for item in query_json): | |
| return {"error": "Invalid input. Arrays must contain only JSON objects."} | |
| except json.JSONDecodeError: | |
| return {"error": "Invalid JSON format in query input"} | |
| data = { | |
| 'group_by_rows': '', | |
| 'agent': 'sparrow-parse', | |
| 'keywords': '', | |
| 'sparrow_key': key, | |
| 'update_targets': '', | |
| 'debug': 'false', | |
| 'index_name': '', | |
| 'types': '', | |
| 'fields': query_json if query_json == "*" else json.dumps(query_json), # Use wildcard as-is, or JSON | |
| 'options': 'huggingface,katanaml/sparrow-qwen2-vl-7b' | |
| } | |
| # Perform the POST request | |
| response = requests.post(url, headers=headers, files=files, data=data) | |
| # Process the response and return the JSON data | |
| if response.status_code == 200: | |
| return response.json() | |
| else: | |
| return {"error": f"Request failed with status code {response.status_code}", "details": response.text} | |
| finally: | |
| # Clean up the temporary file | |
| if os.path.exists(file_path): | |
| os.remove(file_path) | |
| def handle_example(example_image): | |
| # Find the corresponding entry in the examples array | |
| for example in examples: | |
| if example[0] == example_image: | |
| # Return bonds_json if Bonds table is selected | |
| if example_image == "bonds_table.png": | |
| return example_image, bonds_json, example[2] | |
| # Return lab_results_json if Lab results is selected | |
| elif example_image == "lab_results.png": | |
| return example_image, lab_results_json, example[2] | |
| # Return bank_statement_json if Bank statement is selected | |
| elif example_image == "bank_statement.png": | |
| return example_image, bank_statement_json, example[2] | |
| # Default return if no match found | |
| return None, "No example selected.", "" | |
| # Define the UI | |
| with gr.Blocks(theme=gr.themes.Ocean()) as demo: | |
| with gr.Tab(label="Sparrow UI"): | |
| with gr.Row(): | |
| with gr.Column(): | |
| input_img = gr.Image(label="Input Document Image", type="filepath") | |
| query_input = gr.Textbox(label="Query", placeholder="Use * to query all data or JSON schema, e.g.: [{\"instrument_name\": \"example\"}]") | |
| key_input = gr.Textbox(label="Sparrow Key", type="password") | |
| submit_btn = gr.Button(value="Submit", variant="primary") | |
| # Radio button for selecting examples | |
| example_radio = gr.Radio(label="Select Example", choices=[ex[0] for ex in examples]) | |
| with gr.Column(): | |
| # JSON output for structured JSON display | |
| output_json = gr.JSON(label="Response (JSON)", height=900, min_height=900) | |
| # Function to handle example selection | |
| def on_example_select(selected_example): | |
| # Handle example selection and return the image, output (text or JSON), and query | |
| return handle_example(selected_example) | |
| # Update image, output JSON, and query when an example is selected | |
| example_radio.change(on_example_select, | |
| inputs=example_radio, | |
| outputs=[input_img, output_json, query_input]) | |
| # When submit is clicked | |
| submit_btn.click(run_inference, [input_img, query_input, key_input], [output_json]) | |
| gr.Markdown( | |
| """ | |
| --- | |
| <p style="text-align: center;"> | |
| Visit <a href="https://katanaml.io/" target="_blank">Katana ML</a> for more details. | |
| </p> | |
| """ | |
| ) | |
| # Launch the app | |
| demo.queue(api_open=False) | |
| demo.launch(debug=True) | |