Carlos Rosas commited on
Commit
201543f
·
verified ·
1 Parent(s): cbf42f2

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +13 -11
app.py CHANGED
@@ -46,8 +46,8 @@ table = db.open_table("edunat19")
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  def hybrid_search(text):
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  results = table.search(text, query_type="hybrid").limit(5).to_pandas()
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- # Use a list to maintain order
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- seen_hashes = []
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  document = []
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  document_html = []
@@ -58,24 +58,22 @@ def hybrid_search(text):
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  if hash_id in seen_hashes:
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  continue
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- seen_hashes.append(hash_id) # append instead of add to maintain order
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  title = row['section']
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  content = row['text']
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  source_text = f"<|source_start|><|source_id_start|>{hash_id}<|source_id_end|>{title}\n{content}<|source_end|>"
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  document.append(source_text)
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  document_html.append(f'<div class="source" id="{hash_id}"><p><b>{hash_id}</b> : {title}<br>{content}</div>')
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-
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- # Print for debugging
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- print(f"Added source {hash_id}")
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- print(f"Length of source text: {len(source_text)}")
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  document = "\n".join(document)
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  document_html = '<div id="source_listing">' + "".join(document_html) + "</div>"
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- # Print total length for debugging
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- print(f"Total length of document: {len(document)}")
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-
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  return document, document_html
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  class pleiasBot:
@@ -86,9 +84,13 @@ class pleiasBot:
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  fiches, fiches_html = hybrid_search(user_message)
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  detailed_prompt = f"""<|query_start|>{user_message}<|query_end|>\n{fiches}\n<|source_analysis_start|>"""
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-
 
 
 
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  # Convert inputs to tensor
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  input_ids = tokenizer.encode(detailed_prompt, return_tensors="pt").to(device)
 
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  attention_mask = torch.ones_like(input_ids)
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  try:
 
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  def hybrid_search(text):
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  results = table.search(text, query_type="hybrid").limit(5).to_pandas()
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+ # Add a check for duplicate hashes
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+ seen_hashes = set()
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  document = []
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  document_html = []
 
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  if hash_id in seen_hashes:
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  continue
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+ seen_hashes.add(hash_id)
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  title = row['section']
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  content = row['text']
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  source_text = f"<|source_start|><|source_id_start|>{hash_id}<|source_id_end|>{title}\n{content}<|source_end|>"
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  document.append(source_text)
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  document_html.append(f'<div class="source" id="{hash_id}"><p><b>{hash_id}</b> : {title}<br>{content}</div>')
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+
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+ # Add debug print
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+ print(f"Source added: {hash_id}")
 
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  document = "\n".join(document)
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  document_html = '<div id="source_listing">' + "".join(document_html) + "</div>"
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+ # Add debug print
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+ print(f"Total sources: {len(seen_hashes)}")
 
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  return document, document_html
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  class pleiasBot:
 
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  fiches, fiches_html = hybrid_search(user_message)
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  detailed_prompt = f"""<|query_start|>{user_message}<|query_end|>\n{fiches}\n<|source_analysis_start|>"""
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+
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+ # Add debug print
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+ print("Model input length:", len(detailed_prompt))
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+
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  # Convert inputs to tensor
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  input_ids = tokenizer.encode(detailed_prompt, return_tensors="pt").to(device)
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+ print("Token count:", len(input_ids[0]))
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  attention_mask = torch.ones_like(input_ids)
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  try: