Advanced OCR Text Extraction and Translation App_Claude 3.5 Sonet
Description
This app utilizes advanced OCR technology to extract text from various file formats. It allows for quick and accurate conversion of images and documents into text. The text is then divided into smaller segments for tasks like translation or document review. This app also includes a translation algorithm that analyzes the context, identifies key terms and idioms, translates the text, and applies cultural adaptations. The final translation undergoes a quality check before being returned.
Workflow
Input
VAR_1-INPUT 0
1. Text Extractor for Images and Documents
Model: Text Extraction
Prompt:
This app leverages advanced OCR technology to extract text from a wide range of file formats including PDF, DOCX, PPTX, XLSX, TXT, JPEG, PNG, JPG, and HTML. Quickly and accurately convert your images and documents into text.
Output:
1: Text Extractor for Images and Documents2. Split TextLogic
Input:
1: Text Extractor for Images and DocumentsSplit Method:
token
Chunk Size:
4000 tokens
Output:
2: Split Text3. Loop / ReduceLoop
Input:
2: Split TextInternal Module:
Korean Text Translation Analysis Framework
Model: claude-sonnet-4-5@20250929
Analyze and translate the Korean text provided in the input variable. Follow this pseudo-code algorithm:
```pseudo
function analyze_and_translate(input):
// Step 1: Context Analysis
context = extract_context(input)
text_type = identify_text_type(input)
audience = identify_target_audience(input)
tone = determine_tone(input)
cultural_elements = identify_cultural_elements(input)
// Step 2: Preparatory Processing
preprocessed_text = preprocess(input)
terms = extract_key_terms(preprocessed_text)
idioms = identify_idioms(preprocessed_text)
// Step 3: Translation
translation = initialize_translation()
for sentence in preprocessed_text:
translated_sentence = translate_sentence(sentence, context, tone)
translation.append(translated_sentence)
// Step 4: Post-processing
refined_translation = refine_translation(translation, text_type, audience)
cultural_adaptations = adapt_cultural_elements(refined_translation, cultural_elements)
final_translation = apply_adaptations(refined_translation, cultural_adaptations)
// Step 5: Quality Check
if quality_check(final_translation, input):
return final_translation
else:
return revise_translation(final_translation, input)
// Main Execution
korean_text = input
english_translation = analyze_and_translate(korean_text)
// Output
print "Context Analysis:"
print context, text_type, audience, tone, cultural_elements
print "English Translation:"
print english_translation
print "Translation Notes:"
print explain_key_decisions(english_translation, korean_text)
```
Apply this algorithm to the following input:
input: Loop Item
Provide your analysis, translation, and explanatory notes based on the pseudo-code algorithm above.
output: [translated texts]
```pseudo
function analyze_and_translate(input):
// Step 1: Context Analysis
context = extract_context(input)
text_type = identify_text_type(input)
audience = identify_target_audience(input)
tone = determine_tone(input)
cultural_elements = identify_cultural_elements(input)
// Step 2: Preparatory Processing
preprocessed_text = preprocess(input)
terms = extract_key_terms(preprocessed_text)
idioms = identify_idioms(preprocessed_text)
// Step 3: Translation
translation = initialize_translation()
for sentence in preprocessed_text:
translated_sentence = translate_sentence(sentence, context, tone)
translation.append(translated_sentence)
// Step 4: Post-processing
refined_translation = refine_translation(translation, text_type, audience)
cultural_adaptations = adapt_cultural_elements(refined_translation, cultural_elements)
final_translation = apply_adaptations(refined_translation, cultural_adaptations)
// Step 5: Quality Check
if quality_check(final_translation, input):
return final_translation
else:
return revise_translation(final_translation, input)
// Main Execution
korean_text = input
english_translation = analyze_and_translate(korean_text)
// Output
print "Context Analysis:"
print context, text_type, audience, tone, cultural_elements
print "English Translation:"
print english_translation
print "Translation Notes:"
print explain_key_decisions(english_translation, korean_text)
```
Apply this algorithm to the following input:
input: Loop Item
Provide your analysis, translation, and explanatory notes based on the pseudo-code algorithm above.
output: [translated texts]
Output:
3: Loop / ReduceAdvanced OCR Text Extraction and Translation App_Claude 3.5 Sonet
Final Output Template
module_8890073119871_individual
Information
Creator: Sung Lee
5
Runs
1
Bookmarks
62650.00s
Avg. Time
$0.20
Avg. Cost
Examples (0)