Update 2025-04-13_16:05:19

semantic_search.py

@@ -0,0 +1,79 @@
+#!/usr/bin/env python3
+# Script Version: 0.4
+# Description: Semantic search over local embeddings.json with content preview and optional file copy
+
+import json
+import torch
+import os
+import shutil
+import numpy as np
+from sentence_transformers import SentenceTransformer
+from sklearn.metrics.pairwise import cosine_similarity
+
+# Config
+EMBEDDING_FILE = "embeddings.json"
+CONTENT_DIR = "content"
+RESULTS_DIR = "results"
+MODEL_NAME = "all-mpnet-base-v2"
+PREVIEW_LINES = 5  # Number of lines to preview from the matching .txt files
+
+# Ensure results directory exists
+os.makedirs(RESULTS_DIR, exist_ok=True)
+
+# Load model
+model = SentenceTransformer(MODEL_NAME)
+if torch.cuda.is_available():
+    model = model.to("cuda")
+    print("[INFO] Running on GPU")
+
+# Load stored embeddings
+with open(EMBEDDING_FILE, "r") as f:
+    stored_embeddings = json.load(f)
+
+# Prompt user
+query = input("\U0001F50D Enter your search query: ").strip()
+
+# Embed query
+query_embedding = model.encode(query)
+
+# Compute cosine similarities
+results = []
+for filename, embedding in stored_embeddings.items():
+    score = cosine_similarity([query_embedding], [embedding])[0][0]
+    results.append((filename, score))
+
+# Sort and display top result(s)
+results.sort(key=lambda x: x[1], reverse=True)
+
+copied_files = []
+
+print("\n\U0001F4C2 Top matches:")
+for fname, score in results[:3]:
+    print(f"\n{fname} → score: {score:.4f}")
+    txt_path = os.path.join(CONTENT_DIR, fname)
+    if os.path.exists(txt_path):
+        print("Preview:")
+        with open(txt_path, "r", encoding="utf-8") as f:
+            for i, line in enumerate(f):
+                print("  " + line.strip())
+                if i + 1 >= PREVIEW_LINES:
+                    break
+
+        # Ask user if they want to copy the file
+        should_copy = input(f"📄 Copy '{fname}' to '{RESULTS_DIR}'? [y/N]: ").strip().lower()
+        if should_copy == "y":
+            dest_path = os.path.join(RESULTS_DIR, fname)
+            shutil.copyfile(txt_path, dest_path)
+            copied_files.append(fname)
+            print(f"[INFO] File copied to {dest_path}")
+    else:
+        print("[WARN] Source file not found for preview.")
+
+# Final summary
+if copied_files:
+    print("\n✅ Summary of copied files:")
+    for f in copied_files:
+        print(f" - {f}")
+else:
+    print("\nℹ️ No files were copied.")
+