Standardize loggin
Browse files- climateqa/logging.py +31 -3
 
    	
        climateqa/logging.py
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         @@ -4,13 +4,38 @@ import json 
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            from huggingface_hub import HfApi
         
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            import gradio as gr
         
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            import csv
         
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            def serialize_docs(docs:list)->list:
         
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                new_docs = []
         
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                for doc in docs:
         
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                    new_doc = {}
         
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                    new_doc["page_content"] = doc.page_content
         
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                    new_doc["metadata"] =  
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                    new_docs.append(new_doc)
         
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                return new_docs
         
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         @@ -108,7 +133,7 @@ def log_on_huggingface(log_filename, logs): 
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                        return
         
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                    # Get repository name from environment or use default
         
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                    repo_id = os.getenv("HF_DATASET_REPO", " 
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                    # Initialize HfApi
         
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                    api = HfApi(token=hf_token)
         
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         @@ -159,9 +184,12 @@ def log_interaction_to_huggingface(history, output_query, sources, docs, share_c 
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                        }
         
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                        # Log to Hugging Face
         
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                        log_on_huggingface(f"chat/{timestamp}.json", logs)
         
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                except Exception as e:
         
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                    print(f"Error logging to Hugging Face: {e}")
         
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                    error_msg = f"ClimateQ&A Error: {str(e)[:100]} 
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                    raise gr.Error(error_msg)
         
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            def log_drias_interaction_to_huggingface(query, sql_query, user_id):
         
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            from huggingface_hub import HfApi
         
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            import gradio as gr
         
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            import csv
         
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            import pandas as pd
         
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            import io
         
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            from typing import TypedDict, List
         
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            from constants import DOCUMENT_METADATA_DEFAULT_VALUES
         
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            def serialize_docs(docs:list)->list:
         
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                """Convert document objects to a simplified format compatible with Hugging Face datasets.
         
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                This function processes document objects by extracting their page content and metadata,
         
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                normalizing the metadata structure to ensure consistency. It applies default values 
         
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                from DOCUMENT_METADATA_DEFAULT_VALUES for any missing metadata fields.
         
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                Args:
         
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                    docs (list): List of document objects, each with page_content and metadata attributes
         
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                Returns:
         
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                    list: List of dictionaries with standardized "page_content" and "metadata" fields
         
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                """
         
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                new_docs = []
         
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                for doc in docs:
         
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                    new_doc = {}
         
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                    new_doc["page_content"] = doc.page_content
         
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                    new_doc["metadata"] = {}
         
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                    # Define default empty values by field type
         
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                    # Copy each metadata field, using default if missing
         
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                    for field, default_value in DOCUMENT_METADATA_DEFAULT_VALUES.items():
         
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                        new_doc["metadata"][field] = doc.metadata.get(field, default_value)
         
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                    new_docs.append(new_doc)
         
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                return new_docs
         
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                        return
         
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                    # Get repository name from environment or use default
         
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                    repo_id = os.getenv("HF_DATASET_REPO", "Ekimetrics/climateqa_logs")
         
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                    # Initialize HfApi
         
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                    api = HfApi(token=hf_token)
         
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                        }
         
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                        # Log to Hugging Face
         
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                        log_on_huggingface(f"chat/{timestamp}.json", logs)
         
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                        print(f"Logged interaction to Hugging Face")
         
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                    else:
         
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                        print("Did not log to Hugging Face because GRADIO_ENV is local")
         
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                except Exception as e:
         
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                    print(f"Error logging to Hugging Face: {e}")
         
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                    error_msg = f"ClimateQ&A Error: {str(e)[:100]})"
         
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                    raise gr.Error(error_msg)
         
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            def log_drias_interaction_to_huggingface(query, sql_query, user_id):
         
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