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doc:beam/da4252ac-f0c3-49f6-811c-eecc297b7339decrypted_data = decrypt_data(key, encrypted_data) print(f"Decrypted data: {decrypted_data.decode()}") # Example with Hugging Face Transformers from transformers import AutoTokenizer # Initialize tokenizer tokenizer = AutoTokenizer.from_p…
doc:beam/ec399a32-c43b-4ab2-8bdf-1fc9a85ae033print(normalized_embeddings) ``` I've tried to implement the other methods, but I'm not sure if I'm doing it correctly. Can you review my code and suggest improvements? ->-> 3,12 [Turn 6463] Assistant: Certainly! Normalization techniques a…
doc:beam/8ff3dcf0-3ff8-4a60-8be2-3a05f95cffabdocument_paths = ["example1.pdf", "example2.docx", "example3.txt", "example4.html"] process_documents(document_paths) ``` ### Summary By extending the modular document processing system to support additional document formats, you can hand…
doc:beam/b42660f2-ce37-40df-b19e-abefd2b5c069- The `calculate_query_complexity` method calculates the query complexity by summing the `attention_mask` along the sequence dimension. ### Testing - The `input_ids` and `attention_mask` tensors are defined to simulate a batch of two s…
doc:beam/fcabe094-b676-4899-9d0c-92df470d5018param1 *= feedback_params.get("param1_factor", 1.0) param2 *= feedback_params.get("param2_factor", 1.0) refined_projection = { "name": projection["name"], "parameters": {"param1": param1, "param2": p…
doc:beam/aecfc98e-8fd4-42fe-813a-f35940e06f50expected_scores = np.random.rand(25000) # Example expected scores # Compute hybrid scores hybrid_scores = hybrid_ranking(sparse_scores, dense_scores, alpha=0.6) # Log mismatches for i in range(len(expected_scores)): log_mismatch(i, […
doc:beam/0dc58a34-901b-4417-92ed-97ac9c740f5c1. **Install Dependencies**: Ensure you have `flask`, `flask_caching`, and `redis` installed. 2. **Configure Cache Settings**: Set the cache type to `RedisCache` and specify the Redis URL. 3. **Implement Caching Logic**: Use the `@cache.cac…
doc:beam/755bfc56-0b96-455e-b5dd-19ff06b89c79# Define a regex pattern to match sensitive data in specific contexts pattern = r"(?i)(\bpassword\b|\bapi_key\b|\bsecret\b|\btoken\b|\bkey\b|\bauth\b|\bcredentials\b)" # Search for matches in the config matches = re.findall…
doc:beam/36547d87-ffdc-491b-9d91-41b797091448data = "Sample data for security check" if check_security(data): print("Security check passed") # Encrypt and decrypt data encrypted_data = encrypt_data(data, key, iv) print(f"Encrypted data: {encrypted_data}") decrypted_data = decryp…
doc:beam/3d99a976-3d6b-40c8-88d3-7549dd47cac5### 2. Check Data Types and Shapes Verify that the data types and shapes of the vectors are consistent and compatible with FAISS expectations. ### 3. Normalize Vectors Ensure that the vectors are properly normalized before adding them to t…
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