''' import requests import os # Function to load the pre-trained KNN model def load_knn_model_expected(): github_url = "https://raw.githubusercontent.com/PreethamGollapalli/QA-Test-steps-generation-project/main/knn_model_expected%20(2).joblib" response = requests.get(github_url) if response.status_code == 200: # Save the file locally with open("knn_model_expected.joblib", "wb") as f: f.write(response.content) # Load the model knn_model_expected = joblib.load("knn_model_expected.joblib") # Optionally, clean up the local file os.remove("knn_model_expected.joblib") return knn_model_expected else: raise Exception(f"Failed to download the file: {response.status_code}") def load_knn_model_steps (): github_url = "https://raw.githubusercontent.com/PreethamGollapalli/QA-Test-steps-generation-project/main/knn_model_steps%20(2).joblib" response = requests.get(github_url) if response.status_code == 200: # Save the file locally with open("knn_model_steps.joblib", "wb") as f: f.write(response.content) # Load the model knn_model_steps = joblib.load("knn_model_steps.joblib") # Optionally, clean up the local file os.remove("knn_model_steps.joblib") return knn_model_steps else: raise Exception(f"Failed to download the file: {response.status_code}") def load_tfidf_vectorizer(): github_url = "https://raw.githubusercontent.com/PreethamGollapalli/QA-Test-steps-generation-project/main/tfidf_vectorizer%20(3).pkl" response = requests.get(github_url) if response.status_code == 200: # Save the file locally with open("tfidf_vectorizer.pkl", "wb") as f: f.write(response.content) # Load the model vectorizer = joblib.load("tfidf_vectorizer.pkl") # Optionally, clean up the local file os.remove("tfidf_vectorizer.pkl") return vectorizer else: raise Exception(f"Failed to download the file: {response.status_code}") ''' # Load models (KNN model and embedding model) ''' knn_model_steps = load_knn_model_steps() knn_model_results = load_knn_model_expected() tfidf_vectorizer = load_tfidf_vectorizer() '''