Update app.py

app.py

@@ -10,9 +10,9 @@ import nltk
 nltk.download('punkt')
 nltk.download('punkt_tab')
 
-# Define paths as variables
-manual_path = "ubuntu_manual.txt"
+# Paths
 faiss_path = "manual_chunked_faiss_index_500.bin"
+manual_path = "ubuntu_manual.txt"
 
 # Load the Ubuntu manual from a .txt file
 try:
@@ -22,7 +22,7 @@ except FileNotFoundError:
     raise FileNotFoundError(f"The file {manual_path} was not found.")
 
 # Function to chunk the text into smaller pieces
-def chunk_text(text, chunk_size=500):  # Larger chunks
+def chunk_text(text, chunk_size=500):
     sentences = sent_tokenize(text)
     chunks = []
     current_chunk = []
@@ -46,31 +46,31 @@ manual_chunks = chunk_text(full_text, chunk_size=500)
 try:
     index = faiss.read_index(faiss_path)
 except Exception as e:
-    raise RuntimeError(f"Failed to load FAISS index from {faiss_path}: {e}")
+    raise RuntimeError(f"Failed to load FAISS index: {e}")
 
 # Load your embedding model
-embedding_model = SentenceTransformer('FridayMaster/fine_tune_embedding')
+embedding_model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
 
 # OpenAI API key
-openai.api_key = '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'
+openai.api_key = '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'
 
 # Function to create embeddings
 def embed_text(text_list):
-    return np.array(embedding_model.encode(text_list), dtype=np.float32)
+    embeddings = embedding_model.encode(text_list)
+    print("Embedding shape:", embeddings.shape)  # Debugging: Print shape
+    return np.array(embeddings, dtype=np.float32)
 
 # Function to retrieve relevant chunks for a user query
 def retrieve_chunks(query, k=5):
     query_embedding = embed_text([query])
     
-    # Search the FAISS index
     try:
         distances, indices = index.search(query_embedding, k=k)
-        print("Indices:", indices)
-        print("Distances:", distances)
+        print("Indices:", indices)  # Debugging: Print indices
+        print("Distances:", distances)  # Debugging: Print distances
     except Exception as e:
         raise RuntimeError(f"FAISS search failed: {e}")
-    
-    # Check if indices are valid
+
     if len(indices[0]) == 0:
         return []
 
@@ -129,4 +129,3 @@ if __name__ == "__main__":
 
 
 
-