File size: 3,254 Bytes
0117df3 88da32f 0117df3 88da32f 0117df3 88da32f 0117df3 88da32f 0117df3 88da32f 0117df3 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 | from .inferencer import classify_text
import asyncio
from fastapi import HTTPException, UploadFile
from .preprocess import parse_docx, parse_pdf, parse_txt
from nltk.tokenize import sent_tokenize
from io import BytesIO
import logging
async def handle_text_analysis(text: str):
text = text.strip()
if not text or len(text.split()) < 2:
raise HTTPException(
status_code=400, detail="Text must contain at least two words"
)
label, perplexity,ai_likelihood = await asyncio.to_thread(classify_text, text)
return {"result": label, "perplexity": round(int(perplexity), 2),"ai_likelihood":ai_likelihood}
async def handle_file_sentance(file: UploadFile):
try:
file_contents = await extract_file_contents(file)
if len(file_contents) > 10000:
return {"message": "File contains more than 10,000 characters."}
cleaned_text = file_contents.replace("\n", "").replace("\t", "")
result = await handle_sentence_level_analysis(cleaned_text)
return {"content": file_contents, **result}
except Exception as e:
logging.error(f"Error processing file: {str(e)}")
raise HTTPException(status_code=500, detail="Error processing the file")
async def handle_file_upload(file: UploadFile):
try:
file_contents = await extract_file_contents(file)
if len(file_contents) > 10000:
return {"message": "File contains more than 10,000 characters."}
cleaned_text = file_contents.replace("\n", "").replace("\t", "")
label, perplexity,ai_likelihood = await asyncio.to_thread(classify_text, cleaned_text)
return {"content":file_contents,"result": label, "perplexity": round(int(perplexity), 2),"ai_likelihood":ai_likelihood}
except Exception as e:
logging.error(f"Error processing file: {str(e)}")
raise HTTPException(status_code=500, detail="Error processing the file")
async def extract_file_contents(file: UploadFile):
content = await file.read()
file_stream = BytesIO(content)
if (
file.content_type
== "application/vnd.openxmlformats-officedocument.wordprocessingml.document"
):
return parse_docx(file_stream)
elif file.content_type == "application/pdf":
return parse_pdf(file_stream)
elif file.content_type == "text/plain":
return parse_txt(file_stream)
else:
raise HTTPException(
status_code=400,
detail="Invalid file type. Only .docx, .pdf, and .txt are allowed.",
)
async def handle_sentence_level_analysis(text: str):
text = text.strip()
if not text or len(text.split()) < 2:
raise HTTPException(
status_code=400, detail="Text must contain at least two words"
)
sentences = sent_tokenize(text,language="english")
results = []
for sentence in sentences:
label, perplexity, likelihood = await asyncio.to_thread(classify_text, sentence)
results.append({
"sentence": sentence,
"label": label,
"perplexity": round(perplexity, 2),
"ai_likelihood": likelihood
})
return {"analysis": results}
def classify(text: str):
return classify_text(text)
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