parth parekh
commited on
Commit
·
dd174fa
1
Parent(s):
fa5ad45
added a process to remove punctuation to improve accuracy
Browse files
app.py
CHANGED
@@ -12,6 +12,9 @@ app = FastAPI(
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docs_url="/"
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)
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class TextInput(BaseModel):
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text: str
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@@ -36,8 +39,10 @@ def check_regex_patterns(text):
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@app.post("/detect_contact", summary="Detect contact information in text")
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async def detect_contact(input: TextInput):
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try:
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# First, check with regex patterns
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if check_regex_patterns(
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return {
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"text": input.text,
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"contact_probability": 1.0,
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@@ -45,9 +50,8 @@ async def detect_contact(input: TextInput):
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"method": "regex"
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}
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-
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is_contact = predict(input.text) # You can adjust this threshold as needed
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return {
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"text": input.text,
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"contact_probability": 0.98,
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docs_url="/"
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)
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def preprocess_text(text):
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# Remove all punctuation except for @ and . which are often used in email addresses
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return re.sub(r'[^\w\s@.]', '', text)
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class TextInput(BaseModel):
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text: str
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@app.post("/detect_contact", summary="Detect contact information in text")
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async def detect_contact(input: TextInput):
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try:
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preprocessed_text = preprocess_text(input.text)
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# First, check with regex patterns
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if check_regex_patterns(preprocessed_text):
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return {
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"text": input.text,
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"contact_probability": 1.0,
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"method": "regex"
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}
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# If no regex patterns match, use the model
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is_contact = predict(preprocessed_text)
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return {
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"text": input.text,
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"contact_probability": 0.98,
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test.py
CHANGED
@@ -1,46 +1,68 @@
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-
import
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import json
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test_texts = [
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"
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"
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"
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"Call me maybe? Area code is square root of 169, then 555-CHAT",
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]
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url = "https://vidhitmakvana1-contact-sharing-recognizer-api.hf.space/detect_contact"
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payload = {"text": text}
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headers = {"Content-Type": "application/json"}
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-
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print(f"Text: {result['text']}")
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print(f"Contact Probability: {result['contact_probability']:.4f}")
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print(f"Is Contact Info: {result['is_contact_info']}")
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print("---")
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else:
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print(f"Error for text: {text}")
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print(f"Status code: {response.status_code}")
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print(f"Response: {response.text}")
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print("---")
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import asyncio
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import aiohttp
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import json
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from tqdm.asyncio import tqdm
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test_texts = [
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"You can reach me at triple eight, then the square of 7, followed by 2^10",
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"Drop a line to first_name [underscore] last_name at that company with a fruit logo dot com",
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"Find me on the platform where professionals connect: J. Doe, Senior Developer at TechCorp",
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"Message me on that app with the ghost icon: @ShadowWhisperer2023",
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"Contact via carrier pigeon: coordinates 40.7128° N, 74.0060° W",
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"Ping me on the federated network: @[email protected]",
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"My contact is the reverse of moc.elpmaxe@eodnhoj",
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"Reach out using morse: -... -.-- -....- . -- .- .. .-..",
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"Find me on the platform with blue checkmarks: @RealJohnDoe (parody)",
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"Send a message to username 'l33tc0d3r' on that platform for developers",
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"You can locate me at the place where the streets have no name, in the city of angels",
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"My digits are the Fibonacci sequence up to 21, concatenated",
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"Contact: foxtrot oscar oscar at bravo alpha romeo dot charlie oscar mike",
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"Beep me at the number you get when you multiply 555 by 1.5, then add 867-5309",
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"I'm on that app where you share shortvideos: @Dancing2023",
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"Reach out via electronic mail to 'lastnamefirstinitial' at that search engine company dot com",
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"Call me at the number you get when you solve this equation: 2x + 5 = 13, then 555-MATH",
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"My handle on that photo-sharing app is @SunsetSnapper_42",
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"You can find me at the intersection of Binary Boulevard and Algorithm Avenue",
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"Contact info: romeo oscar charlie kilo echo tango mike alpha november at zulu uniform lima uniform dot india oscar",
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]
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url = "https://vidhitmakvana1-contact-sharing-recognizer-api.hf.space/detect_contact"
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async def process_text(session, text):
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payload = {"text": text}
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headers = {"Content-Type": "application/json"}
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async with session.post(url, data=json.dumps(payload), headers=headers) as response:
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if response.status == 200:
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result = await response.json()
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return result
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else:
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print(f"Error for text: {text}")
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print(f"Status code: {response.status}")
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print(f"Response: {await response.text()}")
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return None
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async def main():
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async with aiohttp.ClientSession() as session:
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tasks = [process_text(session, text) for text in test_texts]
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results = await tqdm.gather(*tasks)
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correct_predictions = 0
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total_predictions = len(results)
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for text, result in zip(test_texts, results):
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if result:
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print(f"Text: {result['text']}")
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print(f"Contact Probability: {result['contact_probability']:.4f}")
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print(f"Is Contact Info: {result['is_contact_info']}")
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print("---")
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# Assuming all texts in test_texts are actually contact information
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if result['is_contact_info']:
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correct_predictions += 1
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accuracy = correct_predictions / total_predictions
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print(f"Accuracy: {accuracy:.2f}")
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if __name__ == "__main__":
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asyncio.run(main())
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