Multimodal Retrieval Augmented Generation (RAG) using the Gemini API in Agent Platform Reviews

Nariboina V. · Reviewed 1 hour ago

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Cleverson L. · Reviewed 19 hours ago

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GANGEDDULA P. · Reviewed 1 day ago

24EU04185 S. · Reviewed 2 days ago

fuck u

Venu Gopal D. · Reviewed 2 days ago

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PARA J. · Reviewed 2 days ago

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Ganesh C. · Reviewed 3 days ago

good

Jathin M. · Reviewed 3 days ago

GATE A. · Reviewed 3 days ago

K V S. · Reviewed 3 days ago

get_cosine_score function inside utils file didin't work. import numpy as np import pandas as pd import utils.intro_multimodal_rag_utils as utils # Define a corrected version of get_cosine_score def get_cosine_score_fixed(dataframe, column_name, input_text_embed): val = dataframe[column_name] # Handle None or empty values safely if val is None: return 0.0 # If it's a list or numpy array, check length safely without pd.isna() if isinstance(val, (list, np.ndarray)): if len(val) == 0: return 0.0 return float(np.dot(val, input_text_embed)) # Check for single scalar NA values if pd.isna(val): return 0.0 return float(np.dot(val, input_text_embed)) # Override the broken utility function with our fixed one utils.get_cosine_score = get_cosine_score_fixed. wasted two days to complete this lab.

Apsar M. · Reviewed 3 days ago