Vartex39 commited on
Commit
e724b91
·
1 Parent(s): c4e9c8e

Fix: Info bloğu sadece PDF özetlerinde gösteriliyor, token limiti 1000'e düşürüldü

Browse files
Files changed (2) hide show
  1. summarizer.py +1 -1
  2. ui.py +20 -11
summarizer.py CHANGED
@@ -68,7 +68,7 @@ def summarize_text(text, mode, model_name="anthropic/claude-3-haiku", lang_mode=
68
  "messages": [
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  {"role": "user", "content": build_prompt(text, mode, lang_mode, is_table)}
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  ],
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- "max_tokens": 1300
72
  }
73
 
74
  try:
 
68
  "messages": [
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  {"role": "user", "content": build_prompt(text, mode, lang_mode, is_table)}
70
  ],
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+ "max_tokens": 1000
72
  }
73
 
74
  try:
ui.py CHANGED
@@ -7,33 +7,41 @@ from utils import chunk_text_by_tokens
7
 
8
  def process_input(pdf, image, manual_text, mode, model_name, start_page, end_page, lang_mode, is_table):
9
  if is_table and model_name != "anthropic/claude-3-haiku":
10
- return "Tablo içeriği için yalnızca Claude önerilir.","",None
11
 
 
 
12
  if pdf is not None:
13
  text_chunks = extract_text_chunks_from_pdf(pdf, start=int(start_page), end=int(end_page))
14
  if any("[ERROR]" in chunk for chunk in text_chunks):
15
  return text_chunks[0], "", None
 
 
 
 
 
 
 
 
 
16
  elif image is not None:
17
  text = extract_text_from_image(image)
18
  if "[ERROR]" in text:
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  return text, "", None
20
  text_chunks = [text]
 
 
21
  elif manual_text.strip() != "":
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  text_chunks = [manual_text]
 
 
23
  else:
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  return "Lütfen bir giriş türü seçin.", "", None
25
 
26
- all_text = "\n\n".join(text_chunks)
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- chunk_count = len(chunk_text_by_tokens(all_text, max_tokens=1300))
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-
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- info_block = f"""
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- Sayfa Aralığı: {start_page}–{end_page}
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- Model: {model_name}
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- Chunk Sayısı: {chunk_count}
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- """.strip()
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-
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  full_summary = summarize_long_text(all_text, mode, model_name, lang_mode, is_table)
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- full_summary = f"{info_block}\n\n{full_summary}"
 
 
37
 
38
  temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".txt", mode='w', encoding='utf-8')
39
  temp_file.write(full_summary)
@@ -42,6 +50,7 @@ def process_input(pdf, image, manual_text, mode, model_name, start_page, end_pag
42
  return all_text, full_summary, temp_file.name
43
 
44
 
 
45
  with gr.Blocks() as demo:
46
  gr.Markdown("## VizSum")
47
 
 
7
 
8
  def process_input(pdf, image, manual_text, mode, model_name, start_page, end_page, lang_mode, is_table):
9
  if is_table and model_name != "anthropic/claude-3-haiku":
10
+ return "Tablo içeriği için yalnızca Claude önerilir.", "", None
11
 
12
+ info_block = ""
13
+
14
  if pdf is not None:
15
  text_chunks = extract_text_chunks_from_pdf(pdf, start=int(start_page), end=int(end_page))
16
  if any("[ERROR]" in chunk for chunk in text_chunks):
17
  return text_chunks[0], "", None
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+
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+ all_text = "\n\n".join(text_chunks)
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+ chunk_count = len(chunk_text_by_tokens(all_text, max_tokens=1000))
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+ info_block = f"""
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+ Sayfa Aralığı: {start_page}–{end_page}
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+ Model: {model_name}
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+ Chunk Sayısı: {chunk_count}
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+ """.strip()
26
+
27
  elif image is not None:
28
  text = extract_text_from_image(image)
29
  if "[ERROR]" in text:
30
  return text, "", None
31
  text_chunks = [text]
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+ all_text = text
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+
34
  elif manual_text.strip() != "":
35
  text_chunks = [manual_text]
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+ all_text = manual_text
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+
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  else:
39
  return "Lütfen bir giriş türü seçin.", "", None
40
 
 
 
 
 
 
 
 
 
 
41
  full_summary = summarize_long_text(all_text, mode, model_name, lang_mode, is_table)
42
+
43
+ if info_block:
44
+ full_summary = f"{info_block}\n\n{full_summary}"
45
 
46
  temp_file = tempfile.NamedTemporaryFile(delete=False, suffix=".txt", mode='w', encoding='utf-8')
47
  temp_file.write(full_summary)
 
50
  return all_text, full_summary, temp_file.name
51
 
52
 
53
+
54
  with gr.Blocks() as demo:
55
  gr.Markdown("## VizSum")
56