Spaces:
Sleeping
Sleeping
IZERE HIRWA Roger
commited on
Commit
·
dd5d745
1
Parent(s):
82e2f24
po
Browse files- Dockerfile +14 -11
- app.py +311 -267
- clip_cache/text.txt +0 -0
- data/text.txt +0 -0
- requirements.txt +5 -14
Dockerfile
CHANGED
@@ -2,26 +2,29 @@ FROM python:3.11
|
|
2 |
|
3 |
WORKDIR /app
|
4 |
|
|
|
|
|
|
|
|
|
|
|
|
|
5 |
COPY requirements.txt .
|
6 |
RUN pip install -r requirements.txt
|
7 |
|
8 |
COPY . .
|
9 |
|
10 |
-
# Create writable directories
|
11 |
-
RUN mkdir -p /app/instance && chmod -R 777 /app/instance
|
12 |
-
ENV HF_HOME=/app/transformers_cache
|
13 |
-
RUN mkdir -p /app/transformers_cache && chmod -R 777 /app/transformers_cache
|
14 |
-
|
15 |
-
# Create ../data directory for vector store
|
16 |
RUN mkdir -p /app/data && chmod -R 777 /app/data
|
17 |
-
RUN mkdir -p /
|
18 |
-
|
19 |
-
# Create uploads directory
|
20 |
RUN mkdir -p /app/uploads && chmod -R 777 /app/uploads
|
21 |
-
|
22 |
-
# Create logs directory
|
23 |
RUN mkdir -p /app/logs && chmod -R 777 /app/logs
|
24 |
|
|
|
|
|
|
|
|
|
|
|
25 |
EXPOSE 7860
|
26 |
|
27 |
CMD ["python", "app.py"]
|
|
|
2 |
|
3 |
WORKDIR /app
|
4 |
|
5 |
+
# Install system dependencies
|
6 |
+
RUN apt-get update && apt-get install -y \
|
7 |
+
tesseract-ocr \
|
8 |
+
poppler-utils \
|
9 |
+
&& rm -rf /var/lib/apt/lists/*
|
10 |
+
|
11 |
COPY requirements.txt .
|
12 |
RUN pip install -r requirements.txt
|
13 |
|
14 |
COPY . .
|
15 |
|
16 |
+
# Create writable directories with proper permissions
|
|
|
|
|
|
|
|
|
|
|
17 |
RUN mkdir -p /app/data && chmod -R 777 /app/data
|
18 |
+
RUN mkdir -p /app/static && chmod -R 777 /app/static
|
|
|
|
|
19 |
RUN mkdir -p /app/uploads && chmod -R 777 /app/uploads
|
20 |
+
RUN mkdir -p /app/clip_cache && chmod -R 777 /app/clip_cache
|
|
|
21 |
RUN mkdir -p /app/logs && chmod -R 777 /app/logs
|
22 |
|
23 |
+
# Set environment variables for cache directories
|
24 |
+
ENV CLIP_CACHE=/app/clip_cache
|
25 |
+
ENV HF_HOME=/app/clip_cache
|
26 |
+
ENV TORCH_HOME=/app/clip_cache
|
27 |
+
|
28 |
EXPOSE 7860
|
29 |
|
30 |
CMD ["python", "app.py"]
|
app.py
CHANGED
@@ -1,7 +1,6 @@
|
|
1 |
-
from
|
2 |
-
from
|
3 |
-
from
|
4 |
-
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
|
5 |
import pytesseract
|
6 |
from PIL import Image
|
7 |
import numpy as np
|
@@ -15,51 +14,76 @@ import io
|
|
15 |
import json
|
16 |
import uuid
|
17 |
from datetime import datetime, timedelta
|
18 |
-
from typing import List, Dict, Any, Optional
|
19 |
-
import base64
|
20 |
import jwt
|
21 |
-
|
|
|
22 |
|
23 |
-
app =
|
|
|
24 |
|
25 |
# Security configuration
|
26 |
SECRET_KEY = "your-secret-key-change-this-in-production"
|
27 |
ALGORITHM = "HS256"
|
28 |
ACCESS_TOKEN_EXPIRE_MINUTES = 30
|
29 |
|
30 |
-
|
31 |
-
|
32 |
-
|
33 |
-
# Default admin user (change in production)
|
34 |
-
USERS_DB = {
|
35 |
-
"admin": {
|
36 |
-
"username": "admin",
|
37 |
-
"hashed_password": pwd_context.hash("admin123"),
|
38 |
-
"is_active": True
|
39 |
-
}
|
40 |
-
}
|
41 |
-
|
42 |
-
# Mount static files
|
43 |
-
app.mount("/static", StaticFiles(directory="static"), name="static")
|
44 |
-
|
45 |
-
# --- Load or Initialize Model/Index ---
|
46 |
-
device = "cuda" if torch.cuda.is_available() else "cpu"
|
47 |
-
clip_model, preprocess = clip.load("ViT-B/32", device=device)
|
48 |
|
|
|
49 |
INDEX_PATH = "data/index.faiss"
|
50 |
LABELS_PATH = "data/labels.pkl"
|
51 |
-
|
52 |
UPLOADS_DIR = "data/uploads"
|
53 |
|
54 |
-
# Ensure directories exist
|
55 |
os.makedirs("data", exist_ok=True)
|
56 |
os.makedirs("static", exist_ok=True)
|
57 |
os.makedirs(UPLOADS_DIR, exist_ok=True)
|
58 |
|
59 |
-
# Initialize
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
60 |
index = faiss.IndexFlatL2(512)
|
61 |
labels = []
|
62 |
-
documents = []
|
63 |
|
64 |
if os.path.exists(INDEX_PATH) and os.path.exists(LABELS_PATH):
|
65 |
try:
|
@@ -67,80 +91,57 @@ if os.path.exists(INDEX_PATH) and os.path.exists(LABELS_PATH):
|
|
67 |
with open(LABELS_PATH, "rb") as f:
|
68 |
labels = pickle.load(f)
|
69 |
print(f"✅ Loaded existing index with {len(labels)} labels")
|
70 |
-
except
|
71 |
print(f"⚠️ Failed to load existing index: {e}")
|
72 |
-
print("🔄 Starting with fresh index")
|
73 |
if os.path.exists(INDEX_PATH):
|
74 |
os.remove(INDEX_PATH)
|
75 |
if os.path.exists(LABELS_PATH):
|
76 |
os.remove(LABELS_PATH)
|
77 |
|
78 |
-
#
|
79 |
-
if
|
80 |
-
|
81 |
-
|
82 |
-
|
83 |
-
|
84 |
-
|
85 |
-
|
86 |
-
|
87 |
-
|
88 |
-
|
89 |
-
|
90 |
-
def get_password_hash(password):
|
91 |
-
return pwd_context.hash(password)
|
92 |
-
|
93 |
-
def authenticate_user(username: str, password: str):
|
94 |
-
user = USERS_DB.get(username)
|
95 |
-
if not user or not verify_password(password, user["hashed_password"]):
|
96 |
-
return False
|
97 |
-
return user
|
98 |
-
|
99 |
-
def create_access_token(data: dict, expires_delta: Optional[timedelta] = None):
|
100 |
-
to_encode = data.copy()
|
101 |
-
if expires_delta:
|
102 |
-
expire = datetime.utcnow() + expires_delta
|
103 |
-
else:
|
104 |
-
expire = datetime.utcnow() + timedelta(minutes=15)
|
105 |
-
to_encode.update({"exp": expire})
|
106 |
-
encoded_jwt = jwt.encode(to_encode, SECRET_KEY, algorithm=ALGORITHM)
|
107 |
-
return encoded_jwt
|
108 |
-
|
109 |
-
async def get_current_user(credentials: HTTPAuthorizationCredentials = Depends(security)):
|
110 |
-
credentials_exception = HTTPException(
|
111 |
-
status_code=status.HTTP_401_UNAUTHORIZED,
|
112 |
-
detail="Could not validate credentials",
|
113 |
-
headers={"WWW-Authenticate": "Bearer"},
|
114 |
-
)
|
115 |
-
try:
|
116 |
-
payload = jwt.decode(credentials.credentials, SECRET_KEY, algorithms=[ALGORITHM])
|
117 |
-
username: str = payload.get("sub")
|
118 |
-
if username is None:
|
119 |
-
raise credentials_exception
|
120 |
-
except jwt.PyJWTError:
|
121 |
-
raise credentials_exception
|
122 |
-
|
123 |
-
user = USERS_DB.get(username)
|
124 |
-
if user is None:
|
125 |
-
raise credentials_exception
|
126 |
-
return user
|
127 |
-
|
128 |
-
# --- Utilities ---
|
129 |
def save_index():
|
130 |
try:
|
131 |
-
os.makedirs("data", exist_ok=True)
|
132 |
faiss.write_index(index, INDEX_PATH)
|
133 |
with open(LABELS_PATH, "wb") as f:
|
134 |
pickle.dump(labels, f)
|
135 |
except Exception as e:
|
136 |
print(f"❌ Failed to save index: {e}")
|
137 |
|
138 |
-
def
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
139 |
try:
|
140 |
-
|
141 |
-
|
142 |
-
|
143 |
-
|
|
|
144 |
|
145 |
def image_from_pdf(pdf_bytes):
|
146 |
try:
|
@@ -152,17 +153,8 @@ def image_from_pdf(pdf_bytes):
|
|
152 |
|
153 |
def extract_text(image):
|
154 |
try:
|
155 |
-
if image is None:
|
156 |
-
return "❌ No image provided"
|
157 |
-
|
158 |
-
if isinstance(image, bytes):
|
159 |
-
image = Image.open(io.BytesIO(image))
|
160 |
-
elif not isinstance(image, Image.Image):
|
161 |
-
image = Image.fromarray(image)
|
162 |
-
|
163 |
if image.mode != 'RGB':
|
164 |
image = image.convert('RGB')
|
165 |
-
|
166 |
custom_config = r'--oem 3 --psm 6'
|
167 |
text = pytesseract.image_to_string(image, config=custom_config)
|
168 |
return text.strip() if text.strip() else "❓ No text detected"
|
@@ -171,17 +163,10 @@ def extract_text(image):
|
|
171 |
|
172 |
def get_clip_embedding(image):
|
173 |
try:
|
174 |
-
if
|
175 |
return None
|
176 |
-
|
177 |
-
if isinstance(image, bytes):
|
178 |
-
image = Image.open(io.BytesIO(image))
|
179 |
-
elif not isinstance(image, Image.Image):
|
180 |
-
image = Image.fromarray(image)
|
181 |
-
|
182 |
if image.mode != 'RGB':
|
183 |
image = image.convert('RGB')
|
184 |
-
|
185 |
image_input = preprocess(image).unsqueeze(0).to(device)
|
186 |
with torch.no_grad():
|
187 |
image_features = clip_model.encode_image(image_input)
|
@@ -202,84 +187,205 @@ def save_uploaded_file(file_content: bytes, filename: str) -> str:
|
|
202 |
|
203 |
return saved_filename
|
204 |
|
205 |
-
#
|
206 |
-
|
207 |
-
|
208 |
-
|
209 |
-
|
210 |
-
|
211 |
-
|
212 |
-
|
213 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
214 |
user = authenticate_user(username, password)
|
215 |
if not user:
|
216 |
-
|
217 |
-
|
218 |
-
|
219 |
-
|
220 |
-
|
221 |
-
|
222 |
-
|
223 |
-
|
224 |
-
|
225 |
-
|
226 |
-
|
227 |
-
|
228 |
-
|
229 |
-
|
230 |
-
|
231 |
-
)
|
|
|
232 |
try:
|
233 |
-
|
234 |
-
|
235 |
-
|
236 |
-
|
237 |
-
|
238 |
-
|
239 |
if file.content_type and file.content_type.startswith('application/pdf'):
|
240 |
image = image_from_pdf(file_content)
|
241 |
else:
|
242 |
image = Image.open(io.BytesIO(file_content))
|
243 |
|
244 |
if image is None:
|
245 |
-
|
246 |
|
247 |
embedding = get_clip_embedding(image)
|
248 |
if embedding is None:
|
249 |
-
|
250 |
-
|
251 |
index.add(np.array([embedding]))
|
252 |
-
labels.append(label)
|
253 |
save_index()
|
254 |
|
255 |
-
return {"message": f"✅ Added category '{label}' (Total: {len(labels)} categories)", "status": "success"}
|
256 |
except Exception as e:
|
257 |
-
|
258 |
-
|
259 |
-
@app.
|
260 |
-
|
261 |
-
|
262 |
-
|
263 |
-
):
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
264 |
try:
|
265 |
if len(labels) == 0:
|
266 |
-
|
267 |
-
|
268 |
-
file_content = await file.read()
|
269 |
|
|
|
|
|
|
|
|
|
|
|
270 |
if file.content_type and file.content_type.startswith('application/pdf'):
|
271 |
image = image_from_pdf(file_content)
|
272 |
else:
|
273 |
image = Image.open(io.BytesIO(file_content))
|
274 |
|
275 |
if image is None:
|
276 |
-
|
277 |
|
278 |
embedding = get_clip_embedding(image)
|
279 |
if embedding is None:
|
280 |
-
|
281 |
-
|
282 |
-
# Search for top 3 matches
|
283 |
k = min(3, len(labels))
|
284 |
D, I = index.search(np.array([embedding]), k=k)
|
285 |
|
@@ -295,137 +401,75 @@ async def classify_document(
|
|
295 |
sim = 1 - D[0][i]
|
296 |
matches.append({"category": labels[I[0][i]], "similarity": round(sim, 3)})
|
297 |
|
298 |
-
# Save classified document
|
299 |
if similarity >= confidence_threshold:
|
300 |
saved_filename = save_uploaded_file(file_content, file.filename)
|
301 |
ocr_text = extract_text(image)
|
302 |
|
303 |
-
|
304 |
-
|
305 |
-
|
306 |
-
|
307 |
-
|
308 |
-
|
309 |
-
|
310 |
-
|
311 |
-
|
312 |
-
|
313 |
-
|
314 |
-
documents.append(document)
|
315 |
-
save_documents()
|
316 |
|
317 |
-
return {
|
318 |
"status": "success",
|
319 |
"category": best_match,
|
320 |
"similarity": round(similarity, 3),
|
321 |
-
"confidence": "high"
|
322 |
"matches": matches,
|
323 |
"document_saved": True,
|
324 |
-
"document_id":
|
325 |
-
}
|
326 |
else:
|
327 |
-
return {
|
328 |
"status": "low_confidence",
|
329 |
"category": best_match,
|
330 |
"similarity": round(similarity, 3),
|
331 |
"confidence": "low",
|
332 |
"matches": matches,
|
333 |
"document_saved": False
|
334 |
-
}
|
335 |
|
336 |
-
|
337 |
except Exception as e:
|
338 |
-
|
339 |
-
|
340 |
-
@app.
|
341 |
-
|
342 |
-
|
343 |
-
|
344 |
-
|
345 |
-
|
346 |
|
347 |
-
|
348 |
-
|
349 |
-
|
350 |
-
|
351 |
-
|
352 |
-
|
353 |
-
)
|
354 |
-
|
355 |
-
|
356 |
-
|
357 |
-
|
358 |
-
|
359 |
-
|
360 |
-
|
361 |
-
|
362 |
-
|
363 |
-
|
364 |
-
|
365 |
-
|
366 |
-
|
367 |
-
|
368 |
-
document_index = None
|
369 |
-
document_to_delete = None
|
370 |
-
|
371 |
-
for i, doc in enumerate(documents):
|
372 |
-
if doc["id"] == document_id:
|
373 |
-
document_index = i
|
374 |
-
document_to_delete = doc
|
375 |
-
break
|
376 |
-
|
377 |
-
if document_to_delete is None:
|
378 |
-
raise HTTPException(status_code=404, detail="Document not found")
|
379 |
-
|
380 |
-
# Delete physical file
|
381 |
-
file_path = document_to_delete.get("file_path")
|
382 |
-
if file_path and os.path.exists(file_path):
|
383 |
-
os.remove(file_path)
|
384 |
-
|
385 |
-
# Remove from documents list
|
386 |
-
documents.pop(document_index)
|
387 |
-
save_documents()
|
388 |
-
|
389 |
-
return {"message": "Document deleted successfully", "status": "success"}
|
390 |
-
except Exception as e:
|
391 |
-
raise HTTPException(status_code=500, detail=str(e))
|
392 |
-
|
393 |
-
@app.post("/api/ocr")
|
394 |
-
async def ocr_document(
|
395 |
-
file: UploadFile = File(...),
|
396 |
-
current_user: dict = Depends(get_current_user)
|
397 |
-
):
|
398 |
-
try:
|
399 |
-
file_content = await file.read()
|
400 |
-
|
401 |
-
if file.content_type and file.content_type.startswith('application/pdf'):
|
402 |
-
image = image_from_pdf(file_content)
|
403 |
-
else:
|
404 |
-
image = Image.open(io.BytesIO(file_content))
|
405 |
-
|
406 |
-
if image is None:
|
407 |
-
raise HTTPException(status_code=400, detail="Failed to process image")
|
408 |
-
|
409 |
-
text = extract_text(image)
|
410 |
-
return {"text": text, "status": "success"}
|
411 |
-
except Exception as e:
|
412 |
-
raise HTTPException(status_code=500, detail=str(e))
|
413 |
-
|
414 |
-
@app.get("/api/stats")
|
415 |
-
async def get_stats(current_user: dict = Depends(get_current_user)):
|
416 |
-
category_stats = {}
|
417 |
-
for doc in documents:
|
418 |
-
category = doc["category"]
|
419 |
-
if category not in category_stats:
|
420 |
-
category_stats[category] = 0
|
421 |
-
category_stats[category] += 1
|
422 |
|
423 |
-
return {
|
424 |
-
"total_categories": len(set(labels)),
|
425 |
-
"total_documents": len(documents),
|
426 |
-
"category_distribution": category_stats
|
427 |
-
}
|
428 |
|
429 |
if __name__ == "__main__":
|
430 |
-
|
431 |
-
uvicorn.run(app, host="0.0.0.0", port=7860)
|
|
|
1 |
+
from flask import Flask, request, jsonify, render_template_string, send_from_directory
|
2 |
+
from werkzeug.utils import secure_filename
|
3 |
+
from werkzeug.security import generate_password_hash, check_password_hash
|
|
|
4 |
import pytesseract
|
5 |
from PIL import Image
|
6 |
import numpy as np
|
|
|
14 |
import json
|
15 |
import uuid
|
16 |
from datetime import datetime, timedelta
|
|
|
|
|
17 |
import jwt
|
18 |
+
import sqlite3
|
19 |
+
import tempfile
|
20 |
|
21 |
+
app = Flask(__name__)
|
22 |
+
app.config['SECRET_KEY'] = 'your-secret-key-change-this-in-production'
|
23 |
|
24 |
# Security configuration
|
25 |
SECRET_KEY = "your-secret-key-change-this-in-production"
|
26 |
ALGORITHM = "HS256"
|
27 |
ACCESS_TOKEN_EXPIRE_MINUTES = 30
|
28 |
|
29 |
+
# Set CLIP cache to writable directory
|
30 |
+
os.environ['CLIP_CACHE'] = '/app/clip_cache'
|
31 |
+
os.makedirs('/app/clip_cache', exist_ok=True)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
32 |
|
33 |
+
# Directories
|
34 |
INDEX_PATH = "data/index.faiss"
|
35 |
LABELS_PATH = "data/labels.pkl"
|
36 |
+
DATABASE_PATH = "data/documents.db"
|
37 |
UPLOADS_DIR = "data/uploads"
|
38 |
|
|
|
39 |
os.makedirs("data", exist_ok=True)
|
40 |
os.makedirs("static", exist_ok=True)
|
41 |
os.makedirs(UPLOADS_DIR, exist_ok=True)
|
42 |
|
43 |
+
# Initialize database
|
44 |
+
def init_db():
|
45 |
+
conn = sqlite3.connect(DATABASE_PATH)
|
46 |
+
cursor = conn.cursor()
|
47 |
+
|
48 |
+
# Users table
|
49 |
+
cursor.execute('''
|
50 |
+
CREATE TABLE IF NOT EXISTS users (
|
51 |
+
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
52 |
+
username TEXT UNIQUE NOT NULL,
|
53 |
+
password_hash TEXT NOT NULL,
|
54 |
+
is_active BOOLEAN DEFAULT TRUE
|
55 |
+
)
|
56 |
+
''')
|
57 |
+
|
58 |
+
# Documents table
|
59 |
+
cursor.execute('''
|
60 |
+
CREATE TABLE IF NOT EXISTS documents (
|
61 |
+
id TEXT PRIMARY KEY,
|
62 |
+
filename TEXT NOT NULL,
|
63 |
+
original_filename TEXT NOT NULL,
|
64 |
+
category TEXT NOT NULL,
|
65 |
+
similarity REAL NOT NULL,
|
66 |
+
ocr_text TEXT,
|
67 |
+
upload_date TEXT NOT NULL,
|
68 |
+
file_path TEXT NOT NULL
|
69 |
+
)
|
70 |
+
''')
|
71 |
+
|
72 |
+
# Insert default admin user if not exists
|
73 |
+
cursor.execute('SELECT * FROM users WHERE username = ?', ('admin',))
|
74 |
+
if not cursor.fetchone():
|
75 |
+
admin_hash = generate_password_hash('admin123')
|
76 |
+
cursor.execute('INSERT INTO users (username, password_hash) VALUES (?, ?)',
|
77 |
+
('admin', admin_hash))
|
78 |
+
|
79 |
+
conn.commit()
|
80 |
+
conn.close()
|
81 |
+
|
82 |
+
init_db()
|
83 |
+
|
84 |
+
# Initialize index and labels
|
85 |
index = faiss.IndexFlatL2(512)
|
86 |
labels = []
|
|
|
87 |
|
88 |
if os.path.exists(INDEX_PATH) and os.path.exists(LABELS_PATH):
|
89 |
try:
|
|
|
91 |
with open(LABELS_PATH, "rb") as f:
|
92 |
labels = pickle.load(f)
|
93 |
print(f"✅ Loaded existing index with {len(labels)} labels")
|
94 |
+
except Exception as e:
|
95 |
print(f"⚠️ Failed to load existing index: {e}")
|
|
|
96 |
if os.path.exists(INDEX_PATH):
|
97 |
os.remove(INDEX_PATH)
|
98 |
if os.path.exists(LABELS_PATH):
|
99 |
os.remove(LABELS_PATH)
|
100 |
|
101 |
+
# Initialize CLIP model with custom cache
|
102 |
+
device = "cuda" if torch.cuda.is_available() else "cpu"
|
103 |
+
try:
|
104 |
+
clip_model, preprocess = clip.load("ViT-B/32", device=device, download_root='/app/clip_cache')
|
105 |
+
print("✅ CLIP model loaded successfully")
|
106 |
+
except Exception as e:
|
107 |
+
print(f"❌ Failed to load CLIP model: {e}")
|
108 |
+
# Fallback initialization
|
109 |
+
clip_model = None
|
110 |
+
preprocess = None
|
111 |
+
|
112 |
+
# Helper functions
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
113 |
def save_index():
|
114 |
try:
|
|
|
115 |
faiss.write_index(index, INDEX_PATH)
|
116 |
with open(LABELS_PATH, "wb") as f:
|
117 |
pickle.dump(labels, f)
|
118 |
except Exception as e:
|
119 |
print(f"❌ Failed to save index: {e}")
|
120 |
|
121 |
+
def authenticate_user(username: str, password: str):
|
122 |
+
conn = sqlite3.connect(DATABASE_PATH)
|
123 |
+
cursor = conn.cursor()
|
124 |
+
cursor.execute('SELECT password_hash FROM users WHERE username = ? AND is_active = TRUE', (username,))
|
125 |
+
result = cursor.fetchone()
|
126 |
+
conn.close()
|
127 |
+
|
128 |
+
if result and check_password_hash(result[0], password):
|
129 |
+
return {"username": username}
|
130 |
+
return None
|
131 |
+
|
132 |
+
def create_access_token(data: dict):
|
133 |
+
expire = datetime.utcnow() + timedelta(minutes=ACCESS_TOKEN_EXPIRE_MINUTES)
|
134 |
+
to_encode = data.copy()
|
135 |
+
to_encode.update({"exp": expire})
|
136 |
+
return jwt.encode(to_encode, SECRET_KEY, algorithm=ALGORITHM)
|
137 |
+
|
138 |
+
def verify_token(token: str):
|
139 |
try:
|
140 |
+
payload = jwt.decode(token, SECRET_KEY, algorithms=[ALGORITHM])
|
141 |
+
username = payload.get("sub")
|
142 |
+
return username if username else None
|
143 |
+
except jwt.PyJWTError:
|
144 |
+
return None
|
145 |
|
146 |
def image_from_pdf(pdf_bytes):
|
147 |
try:
|
|
|
153 |
|
154 |
def extract_text(image):
|
155 |
try:
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
156 |
if image.mode != 'RGB':
|
157 |
image = image.convert('RGB')
|
|
|
158 |
custom_config = r'--oem 3 --psm 6'
|
159 |
text = pytesseract.image_to_string(image, config=custom_config)
|
160 |
return text.strip() if text.strip() else "❓ No text detected"
|
|
|
163 |
|
164 |
def get_clip_embedding(image):
|
165 |
try:
|
166 |
+
if clip_model is None:
|
167 |
return None
|
|
|
|
|
|
|
|
|
|
|
|
|
168 |
if image.mode != 'RGB':
|
169 |
image = image.convert('RGB')
|
|
|
170 |
image_input = preprocess(image).unsqueeze(0).to(device)
|
171 |
with torch.no_grad():
|
172 |
image_features = clip_model.encode_image(image_input)
|
|
|
187 |
|
188 |
return saved_filename
|
189 |
|
190 |
+
# Routes
|
191 |
+
@app.route("/")
|
192 |
+
def dashboard():
|
193 |
+
return render_template_string('''
|
194 |
+
<!DOCTYPE html>
|
195 |
+
<html>
|
196 |
+
<head>
|
197 |
+
<title>Document Classification System</title>
|
198 |
+
<style>
|
199 |
+
body { font-family: Arial, sans-serif; margin: 40px; }
|
200 |
+
.container { max-width: 800px; margin: 0 auto; }
|
201 |
+
.form-group { margin: 20px 0; }
|
202 |
+
input, button { padding: 10px; margin: 5px; }
|
203 |
+
button { background: #007bff; color: white; border: none; cursor: pointer; }
|
204 |
+
.result { margin: 20px 0; padding: 10px; background: #f8f9fa; border: 1px solid #dee2e6; }
|
205 |
+
</style>
|
206 |
+
</head>
|
207 |
+
<body>
|
208 |
+
<div class="container">
|
209 |
+
<h1>Document Classification System</h1>
|
210 |
+
|
211 |
+
<div class="form-group">
|
212 |
+
<h3>Login</h3>
|
213 |
+
<form id="loginForm">
|
214 |
+
<input type="text" id="username" placeholder="Username" required>
|
215 |
+
<input type="password" id="password" placeholder="Password" required>
|
216 |
+
<button type="submit">Login</button>
|
217 |
+
</form>
|
218 |
+
</div>
|
219 |
+
|
220 |
+
<div id="mainContent" style="display:none;">
|
221 |
+
<div class="form-group">
|
222 |
+
<h3>Upload Category</h3>
|
223 |
+
<form id="categoryForm" enctype="multipart/form-data">
|
224 |
+
<input type="file" id="categoryFile" accept="image/*,.pdf" required>
|
225 |
+
<input type="text" id="categoryLabel" placeholder="Category Label" required>
|
226 |
+
<button type="submit">Add Category</button>
|
227 |
+
</form>
|
228 |
+
</div>
|
229 |
+
|
230 |
+
<div class="form-group">
|
231 |
+
<h3>Classify Document</h3>
|
232 |
+
<form id="classifyForm" enctype="multipart/form-data">
|
233 |
+
<input type="file" id="classifyFile" accept="image/*,.pdf" required>
|
234 |
+
<button type="submit">Classify</button>
|
235 |
+
</form>
|
236 |
+
</div>
|
237 |
+
|
238 |
+
<div id="result" class="result" style="display:none;"></div>
|
239 |
+
</div>
|
240 |
+
</div>
|
241 |
+
|
242 |
+
<script>
|
243 |
+
let token = null;
|
244 |
+
|
245 |
+
document.getElementById('loginForm').onsubmit = async (e) => {
|
246 |
+
e.preventDefault();
|
247 |
+
const formData = new FormData();
|
248 |
+
formData.append('username', document.getElementById('username').value);
|
249 |
+
formData.append('password', document.getElementById('password').value);
|
250 |
+
|
251 |
+
const response = await fetch('/api/login', {
|
252 |
+
method: 'POST',
|
253 |
+
body: formData
|
254 |
+
});
|
255 |
+
|
256 |
+
const result = await response.json();
|
257 |
+
if (response.ok) {
|
258 |
+
token = result.access_token;
|
259 |
+
document.getElementById('mainContent').style.display = 'block';
|
260 |
+
document.getElementById('result').innerHTML = 'Login successful!';
|
261 |
+
document.getElementById('result').style.display = 'block';
|
262 |
+
} else {
|
263 |
+
document.getElementById('result').innerHTML = 'Login failed: ' + result.detail;
|
264 |
+
document.getElementById('result').style.display = 'block';
|
265 |
+
}
|
266 |
+
};
|
267 |
+
|
268 |
+
document.getElementById('categoryForm').onsubmit = async (e) => {
|
269 |
+
e.preventDefault();
|
270 |
+
const formData = new FormData();
|
271 |
+
formData.append('file', document.getElementById('categoryFile').files[0]);
|
272 |
+
formData.append('label', document.getElementById('categoryLabel').value);
|
273 |
+
|
274 |
+
const response = await fetch('/api/upload-category', {
|
275 |
+
method: 'POST',
|
276 |
+
body: formData,
|
277 |
+
headers: {'Authorization': 'Bearer ' + token}
|
278 |
+
});
|
279 |
+
|
280 |
+
const result = await response.json();
|
281 |
+
document.getElementById('result').innerHTML = JSON.stringify(result, null, 2);
|
282 |
+
document.getElementById('result').style.display = 'block';
|
283 |
+
};
|
284 |
+
|
285 |
+
document.getElementById('classifyForm').onsubmit = async (e) => {
|
286 |
+
e.preventDefault();
|
287 |
+
const formData = new FormData();
|
288 |
+
formData.append('file', document.getElementById('classifyFile').files[0]);
|
289 |
+
|
290 |
+
const response = await fetch('/api/classify-document', {
|
291 |
+
method: 'POST',
|
292 |
+
body: formData,
|
293 |
+
headers: {'Authorization': 'Bearer ' + token}
|
294 |
+
});
|
295 |
+
|
296 |
+
const result = await response.json();
|
297 |
+
document.getElementById('result').innerHTML = JSON.stringify(result, null, 2);
|
298 |
+
document.getElementById('result').style.display = 'block';
|
299 |
+
};
|
300 |
+
</script>
|
301 |
+
</body>
|
302 |
+
</html>
|
303 |
+
''')
|
304 |
+
|
305 |
+
@app.route("/api/login", methods=["POST"])
|
306 |
+
def login():
|
307 |
+
username = request.form.get("username")
|
308 |
+
password = request.form.get("password")
|
309 |
+
|
310 |
user = authenticate_user(username, password)
|
311 |
if not user:
|
312 |
+
return jsonify({"detail": "Incorrect username or password"}), 401
|
313 |
+
|
314 |
+
access_token = create_access_token(data={"sub": user["username"]})
|
315 |
+
return jsonify({"access_token": access_token, "token_type": "bearer", "username": user["username"]})
|
316 |
+
|
317 |
+
@app.route("/api/upload-category", methods=["POST"])
|
318 |
+
def upload_category():
|
319 |
+
# Verify token
|
320 |
+
auth_header = request.headers.get('Authorization')
|
321 |
+
if not auth_header or not auth_header.startswith('Bearer '):
|
322 |
+
return jsonify({"error": "Missing or invalid token"}), 401
|
323 |
+
|
324 |
+
token = auth_header.split(' ')[1]
|
325 |
+
username = verify_token(token)
|
326 |
+
if not username:
|
327 |
+
return jsonify({"error": "Invalid token"}), 401
|
328 |
+
|
329 |
try:
|
330 |
+
label = request.form.get("label")
|
331 |
+
file = request.files.get("file")
|
332 |
+
if not label or not file:
|
333 |
+
return jsonify({"error": "Missing label or file"}), 400
|
334 |
+
|
335 |
+
file_content = file.read()
|
336 |
if file.content_type and file.content_type.startswith('application/pdf'):
|
337 |
image = image_from_pdf(file_content)
|
338 |
else:
|
339 |
image = Image.open(io.BytesIO(file_content))
|
340 |
|
341 |
if image is None:
|
342 |
+
return jsonify({"error": "Failed to process image"}), 400
|
343 |
|
344 |
embedding = get_clip_embedding(image)
|
345 |
if embedding is None:
|
346 |
+
return jsonify({"error": "Failed to generate embedding"}), 400
|
347 |
+
|
348 |
index.add(np.array([embedding]))
|
349 |
+
labels.append(label.strip())
|
350 |
save_index()
|
351 |
|
352 |
+
return jsonify({"message": f"✅ Added category '{label}' (Total: {len(labels)} categories)", "status": "success"})
|
353 |
except Exception as e:
|
354 |
+
return jsonify({"error": str(e)}), 500
|
355 |
+
|
356 |
+
@app.route("/api/classify-document", methods=["POST"])
|
357 |
+
def classify_document():
|
358 |
+
# Verify token
|
359 |
+
auth_header = request.headers.get('Authorization')
|
360 |
+
if not auth_header or not auth_header.startswith('Bearer '):
|
361 |
+
return jsonify({"error": "Missing or invalid token"}), 401
|
362 |
+
|
363 |
+
token = auth_header.split(' ')[1]
|
364 |
+
username = verify_token(token)
|
365 |
+
if not username:
|
366 |
+
return jsonify({"error": "Invalid token"}), 401
|
367 |
+
|
368 |
try:
|
369 |
if len(labels) == 0:
|
370 |
+
return jsonify({"error": "No categories in database. Please add some first."}), 400
|
|
|
|
|
371 |
|
372 |
+
file = request.files.get("file")
|
373 |
+
if not file:
|
374 |
+
return jsonify({"error": "Missing file"}), 400
|
375 |
+
|
376 |
+
file_content = file.read()
|
377 |
if file.content_type and file.content_type.startswith('application/pdf'):
|
378 |
image = image_from_pdf(file_content)
|
379 |
else:
|
380 |
image = Image.open(io.BytesIO(file_content))
|
381 |
|
382 |
if image is None:
|
383 |
+
return jsonify({"error": "Failed to process image"}), 400
|
384 |
|
385 |
embedding = get_clip_embedding(image)
|
386 |
if embedding is None:
|
387 |
+
return jsonify({"error": "Failed to generate embedding"}), 400
|
388 |
+
|
|
|
389 |
k = min(3, len(labels))
|
390 |
D, I = index.search(np.array([embedding]), k=k)
|
391 |
|
|
|
401 |
sim = 1 - D[0][i]
|
402 |
matches.append({"category": labels[I[0][i]], "similarity": round(sim, 3)})
|
403 |
|
404 |
+
# Save classified document to SQLite
|
405 |
if similarity >= confidence_threshold:
|
406 |
saved_filename = save_uploaded_file(file_content, file.filename)
|
407 |
ocr_text = extract_text(image)
|
408 |
|
409 |
+
document_id = str(uuid.uuid4())
|
410 |
+
conn = sqlite3.connect(DATABASE_PATH)
|
411 |
+
cursor = conn.cursor()
|
412 |
+
cursor.execute('''
|
413 |
+
INSERT INTO documents (id, filename, original_filename, category, similarity, ocr_text, upload_date, file_path)
|
414 |
+
VALUES (?, ?, ?, ?, ?, ?, ?, ?)
|
415 |
+
''', (document_id, saved_filename, file.filename, best_match, round(similarity, 3),
|
416 |
+
ocr_text, datetime.now().isoformat(), os.path.join(UPLOADS_DIR, saved_filename)))
|
417 |
+
conn.commit()
|
418 |
+
conn.close()
|
|
|
|
|
|
|
419 |
|
420 |
+
return jsonify({
|
421 |
"status": "success",
|
422 |
"category": best_match,
|
423 |
"similarity": round(similarity, 3),
|
424 |
+
"confidence": "high",
|
425 |
"matches": matches,
|
426 |
"document_saved": True,
|
427 |
+
"document_id": document_id
|
428 |
+
})
|
429 |
else:
|
430 |
+
return jsonify({
|
431 |
"status": "low_confidence",
|
432 |
"category": best_match,
|
433 |
"similarity": round(similarity, 3),
|
434 |
"confidence": "low",
|
435 |
"matches": matches,
|
436 |
"document_saved": False
|
437 |
+
})
|
438 |
|
439 |
+
return jsonify({"error": "Document not recognized"}), 400
|
440 |
except Exception as e:
|
441 |
+
return jsonify({"error": str(e)}), 500
|
442 |
+
|
443 |
+
@app.route("/api/documents", methods=["GET"])
|
444 |
+
def get_all_documents():
|
445 |
+
# Verify token
|
446 |
+
auth_header = request.headers.get('Authorization')
|
447 |
+
if not auth_header or not auth_header.startswith('Bearer '):
|
448 |
+
return jsonify({"error": "Missing or invalid token"}), 401
|
449 |
|
450 |
+
token = auth_header.split(' ')[1]
|
451 |
+
username = verify_token(token)
|
452 |
+
if not username:
|
453 |
+
return jsonify({"error": "Invalid token"}), 401
|
454 |
+
|
455 |
+
conn = sqlite3.connect(DATABASE_PATH)
|
456 |
+
cursor = conn.cursor()
|
457 |
+
cursor.execute('SELECT * FROM documents ORDER BY upload_date DESC')
|
458 |
+
documents = []
|
459 |
+
for row in cursor.fetchall():
|
460 |
+
documents.append({
|
461 |
+
"id": row[0],
|
462 |
+
"filename": row[1],
|
463 |
+
"original_filename": row[2],
|
464 |
+
"category": row[3],
|
465 |
+
"similarity": row[4],
|
466 |
+
"ocr_text": row[5],
|
467 |
+
"upload_date": row[6],
|
468 |
+
"file_path": row[7]
|
469 |
+
})
|
470 |
+
conn.close()
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
471 |
|
472 |
+
return jsonify({"documents": documents, "count": len(documents)})
|
|
|
|
|
|
|
|
|
473 |
|
474 |
if __name__ == "__main__":
|
475 |
+
app.run(host="0.0.0.0", port=7860, debug=True)
|
|
clip_cache/text.txt
ADDED
File without changes
|
data/text.txt
ADDED
File without changes
|
requirements.txt
CHANGED
@@ -1,20 +1,11 @@
|
|
1 |
-
|
2 |
-
|
3 |
-
python-multipart
|
4 |
-
python-jose[cryptography]
|
5 |
-
passlib[bcrypt]
|
6 |
-
bcrypt
|
7 |
-
gradio
|
8 |
-
faiss-cpu
|
9 |
pytesseract
|
10 |
pdf2image
|
11 |
-
|
12 |
torch
|
13 |
torchvision
|
14 |
Pillow
|
15 |
-
|
16 |
-
regex
|
17 |
-
tqdm
|
18 |
git+https://github.com/openai/CLIP.git
|
19 |
-
poppler-utils
|
20 |
-
jwt
|
|
|
1 |
+
flask
|
2 |
+
werkzeug
|
|
|
|
|
|
|
|
|
|
|
|
|
3 |
pytesseract
|
4 |
pdf2image
|
5 |
+
faiss-cpu
|
6 |
torch
|
7 |
torchvision
|
8 |
Pillow
|
9 |
+
PyJWT
|
|
|
|
|
10 |
git+https://github.com/openai/CLIP.git
|
11 |
+
poppler-utils
|
|