Update app.py

app.py

@@ -30,7 +30,7 @@ class VirusClassifier(nn.Module):
     def forward(self, x):
         return self.network(x)
 
-def sequence_to_kmer_vector(sequence: str, k: int = 4) -> np.ndarray:
+def sequence_to_kmer_vector(sequence: str, k: int = 6) -> np.ndarray:
     """Convert sequence to k-mer frequency vector"""
     try:
         kmers = [''.join(p) for p in product("ACGT", repeat=k)]
@@ -46,11 +46,9 @@ def sequence_to_kmer_vector(sequence: str, k: int = 4) -> np.ndarray:
         logger.error(f"Error in sequence_to_kmer_vector: {str(e)}")
         raise
 
-def parse_fasta(file_obj) -> list:
-    """Parse FASTA format from file object"""
+def parse_fasta(content: str) -> list:
+    """Parse FASTA format from string content"""
     try:
-        # Read the content from the file object
-        content = file_obj.decode('utf-8')
         logger.info(f"Received file content length: {len(content)}")
         
         sequences = []
@@ -86,6 +84,9 @@ def predict_sequence(file_obj) -> str:
         if file_obj is None:
             return "Please upload a FASTA file"
             
+        # Read the file content
+        content = file_obj.read().decode('utf-8')
+        
         device = 'cuda' if torch.cuda.is_available() else 'cpu'
         logger.info(f"Using device: {device}")
         k = 4
@@ -103,7 +104,7 @@ def predict_sequence(file_obj) -> str:
         
         # Process sequences
         try:
-            sequences = parse_fasta(file_obj)
+            sequences = parse_fasta(content)
         except Exception as e:
             logger.error(f"Error parsing FASTA file: {str(e)}")
             return f"Error parsing FASTA file: {str(e)}"