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https://github.com/Dispatcharr/Dispatcharr.git
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Switched logging match rest of application.
This commit is contained in:
SergeantPanda
parent
0843776b6b
commit
1508c2902e
1 changed files with 28 additions and 20 deletions
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@ -4,11 +4,15 @@ import sys
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import json
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import re
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import os
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import sys
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import logging
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from rapidfuzz import fuzz
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from sentence_transformers import util
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from sentence_transformers import SentenceTransformer as st
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# Set up logger
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logger = logging.getLogger(__name__)
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# Load the sentence-transformers model once at the module level
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SENTENCE_MODEL_NAME = "sentence-transformers/all-MiniLM-L6-v2"
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MODEL_PATH = os.path.join("/app", "models", "all-MiniLM-L6-v2")
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@ -18,18 +22,15 @@ BEST_FUZZY_THRESHOLD = 85
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LOWER_FUZZY_THRESHOLD = 40
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EMBED_SIM_THRESHOLD = 0.65
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def eprint(*args, **kwargs):
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print(*args, file=sys.stderr, **kwargs)
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def process_data(input_data):
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os.makedirs(MODEL_PATH, exist_ok=True)
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# If not present locally, download:
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if not os.path.exists(os.path.join(MODEL_PATH, "config.json")):
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eprint(f"Local model not found in {MODEL_PATH}; downloading from {SENTENCE_MODEL_NAME}...")
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logger.info(f"Local model not found in {MODEL_PATH}; downloading from {SENTENCE_MODEL_NAME}...")
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st_model = st(SENTENCE_MODEL_NAME, cache_folder=MODEL_PATH)
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else:
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eprint(f"Loading local model from {MODEL_PATH}")
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logger.info(f"Loading local model from {MODEL_PATH}")
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st_model = st(MODEL_PATH)
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channels = input_data["channels"]
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@ -59,7 +60,7 @@ def process_data(input_data):
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# Add to matched_channels list so it's counted in the total
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matched_channels.append((chan['id'], fallback_name, epg_by_tvg_id["tvg_id"]))
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eprint(f"Channel {chan['id']} '{fallback_name}' => EPG found by tvg_id={epg_by_tvg_id['tvg_id']}")
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logger.info(f"Channel {chan['id']} '{fallback_name}' => EPG found by tvg_id={epg_by_tvg_id['tvg_id']}")
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continue
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# If channel has a tvg_id that doesn't exist in EPGData, do direct check.
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@ -67,15 +68,14 @@ def process_data(input_data):
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if chan["tvg_id"]:
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epg_match = [epg["id"] for epg in epg_data if epg["tvg_id"] == chan["tvg_id"]]
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if epg_match:
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# Fix: Access the first element directly since epg_match contains the IDs themselves
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chan["epg_data_id"] = epg_match[0] # Directly use the integer ID
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eprint(f"Channel {chan['id']} '{chan['name']}' => EPG found by tvg_id={chan['tvg_id']}")
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chan["epg_data_id"] = epg_match[0]
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logger.info(f"Channel {chan['id']} '{chan['name']}' => EPG found by tvg_id={chan['tvg_id']}")
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channels_to_update.append(chan)
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continue
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# C) Perform name-based fuzzy matching
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if not chan["norm_chan"]:
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eprint(f"Channel {chan['id']} '{chan['name']}' => empty after normalization, skipping")
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logger.debug(f"Channel {chan['id']} '{chan['name']}' => empty after normalization, skipping")
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continue
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best_score = 0
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@ -99,7 +99,7 @@ def process_data(input_data):
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bonus = 15
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score = base_score + bonus
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eprint(
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logger.debug(
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f"Channel {chan['id']} '{fallback_name}' => EPG row {row['id']}: "
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f"name='{row['name']}', norm_name='{row['norm_name']}', "
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f"combined_text='{combined_text}', dot_regions={dot_regions}, "
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@ -112,7 +112,7 @@ def process_data(input_data):
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# If no best match was found, skip
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if not best_epg:
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eprint(f"Channel {chan['id']} '{fallback_name}' => no EPG match at all.")
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logger.debug(f"Channel {chan['id']} '{fallback_name}' => no EPG match at all.")
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continue
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# If best_score is above BEST_FUZZY_THRESHOLD => direct accept
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@ -121,7 +121,7 @@ def process_data(input_data):
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channels_to_update.append(chan)
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matched_channels.append((chan['id'], fallback_name, best_epg["tvg_id"]))
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eprint(
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logger.info(
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f"Channel {chan['id']} '{fallback_name}' => matched tvg_id={best_epg['tvg_id']} "
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f"(score={best_score})"
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)
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@ -138,27 +138,35 @@ def process_data(input_data):
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channels_to_update.append(chan)
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matched_channels.append((chan['id'], fallback_name, matched_epg["tvg_id"]))
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eprint(
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logger.info(
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f"Channel {chan['id']} '{fallback_name}' => matched EPG tvg_id={matched_epg['tvg_id']} "
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f"(fuzzy={best_score}, cos-sim={top_value:.2f})"
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)
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else:
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eprint(
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logger.info(
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f"Channel {chan['id']} '{fallback_name}' => fuzzy={best_score}, "
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f"cos-sim={top_value:.2f} < {EMBED_SIM_THRESHOLD}, skipping"
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)
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else:
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eprint(
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f"Channel {chan['id']} '{fallback_name}' => fuzzy={best_score} < "
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f"{LOWER_FUZZY_THRESHOLD}, skipping"
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# No good match found - fuzzy score is too low
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logger.info(
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f"Channel {chan['id']} '{fallback_name}' => best fuzzy match score={best_score} < {LOWER_FUZZY_THRESHOLD}, skipping"
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)
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return {
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"channels_to_update": channels_to_update,
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"matched_channels": matched_channels,
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"matched_channels": matched_channels
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}
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def main():
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# Configure logging
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logging_level = os.environ.get('DISPATCHARR_LOG_LEVEL', 'INFO')
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logging.basicConfig(
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level=getattr(logging, logging_level),
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format='%(asctime)s - %(name)s - %(levelname)s - %(message)s',
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stream=sys.stderr
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)
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# Read input data from a file
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input_file_path = sys.argv[1]
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with open(input_file_path, 'r') as f:
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