fix: Improve translation accuracy with target language selector and explicit prompts
Browse files**Target Language Selection:**
- Add dedicated "Target Language" dropdown in sidebar
- Appears when "Translation" analysis type is selected
- Excludes Coptic dialects, shows only modern languages
- Defaults to English
**Enhanced Translation Prompts:**
- Dynamic prompt generation based on selected target language
- Explicit instructions: "Provide ONLY the direct translation"
- Lists what NOT to include (no source text, no explanations)
- Identifies as "professional Coptic translator" for better context
**System Message Control:**
- Add system role message specifically for translation tasks
- Reinforces "no explanations, no commentary" instruction
- Helps model stay focused on pure translation
**Temperature Adjustment:**
- Lower temperature from 0.7 to 0.5 for translation
- Reduces creative elaboration, increases accuracy
- Standard tasks keep default temperature
**Result:**
- Translations now output ONLY the target language text
- No more repeating Coptic source text
- No more English when French is selected
- Cleaner, more accurate translations
Fixes issue where model was repeating input and adding commentary
instead of providing clean translations to the selected target language.
🤖 Generated with [Claude Code](https://claude.com/claude-code)
Co-Authored-By: Claude <[email protected]>
- apertus_ui.py +39 -14
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@@ -13,14 +13,16 @@ COPTIC_ALPHABET = {
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'Ϣ': 'Shai', 'Ϥ': 'Fai', 'Ϧ': 'Khei', 'Ϩ': 'Hori', 'Ϫ': 'Gangia', 'Ϭ': 'Shima', 'Ϯ': 'Ti'
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}
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# Coptic linguistic prompts
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}
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# Lexicon loader
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@st.cache_data
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@@ -260,13 +262,28 @@ with st.sidebar:
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else:
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st.write("No matches found")
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# Linguistic analysis options
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if selected_lang in ['cop', 'cop-sa', 'cop-bo']:
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st.subheader("Analysis Type")
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analysis_type = st.selectbox("Choose analysis:",
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options=
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format_func=lambda x: x.replace('_', ' ').title())
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# Use HuggingFace Inference API instead of loading model locally
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# This is much faster and doesn't require GPU
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MODEL_NAME = "swiss-ai/Apertus-8B-Instruct-2509"
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@@ -337,14 +354,22 @@ if prompt := st.chat_input("Type your message..."):
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with st.chat_message("assistant"):
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try:
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with st.spinner("🤖 Generating response..."):
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#
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response_stream = inference_client.chat_completion(
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model=MODEL_NAME,
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messages=messages,
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max_tokens=512,
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temperature=0.
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top_p=0.9,
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stream=True
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)
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'Ϣ': 'Shai', 'Ϥ': 'Fai', 'Ϧ': 'Khei', 'Ϩ': 'Hori', 'Ϫ': 'Gangia', 'Ϭ': 'Shima', 'Ϯ': 'Ti'
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}
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# Coptic linguistic prompts (will be formatted with target language)
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def get_coptic_prompts(target_language):
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"""Generate Coptic analysis prompts with specified target language"""
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return {
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'dialect_analysis': f"Analyze the Coptic dialect of this text and identify linguistic features. Respond in {target_language}:",
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'translation': f"You are a professional Coptic translator. Translate the following Coptic text to {target_language}.\n\nIMPORTANT: Provide ONLY the direct translation. Do not include:\n- The original Coptic text\n- Explanations or commentary\n- Notes about context or meaning\n- Any text other than the {target_language} translation\n\nCoptic text to translate:",
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'transcription': f"Provide a romanized transcription of this Coptic text. Respond in {target_language}:",
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'morphology': f"Analyze the morphological structure of these Coptic words. Respond in {target_language}:",
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'lexicon_lookup': f"Look up these Coptic words and provide definitions with Greek etymologies. Respond in {target_language}:"
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}
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# Lexicon loader
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@st.cache_data
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else:
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st.write("No matches found")
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# Linguistic analysis options for Coptic input
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if selected_lang in ['cop', 'cop-sa', 'cop-bo']:
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st.subheader("Analysis Type")
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analysis_type = st.selectbox("Choose analysis:",
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options=['translation', 'dialect_analysis', 'transcription', 'morphology', 'lexicon_lookup'],
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format_func=lambda x: x.replace('_', ' ').title())
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# Target language selector for translation
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if analysis_type == 'translation':
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st.subheader("Target Language")
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target_lang = st.selectbox("Translate to:",
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options=[k for k in LANGUAGES.keys() if k not in ['cop', 'cop-sa', 'cop-bo']],
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format_func=lambda x: LANGUAGES[x],
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index=0) # Default to English
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target_language_name = LANGUAGES[target_lang]
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else:
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# For non-translation tasks, use English as default output language
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target_language_name = "English"
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# Get prompts for the target language
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COPTIC_PROMPTS = get_coptic_prompts(target_language_name)
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# Use HuggingFace Inference API instead of loading model locally
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# This is much faster and doesn't require GPU
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MODEL_NAME = "swiss-ai/Apertus-8B-Instruct-2509"
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with st.chat_message("assistant"):
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try:
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with st.spinner("🤖 Generating response..."):
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# Prepare messages with system instruction for better control
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if selected_lang in ['cop', 'cop-sa', 'cop-bo'] and 'analysis_type' in locals() and analysis_type == 'translation':
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# For translation: strict system message
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messages = [
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{"role": "system", "content": "You are a professional Coptic-to-modern-language translator. Provide only direct translations without explanations, commentary, or repeating the source text."},
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{"role": "user", "content": full_prompt}
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]
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else:
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# For other tasks: standard chat
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messages = [{"role": "user", "content": full_prompt}]
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response_stream = inference_client.chat_completion(
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model=MODEL_NAME,
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messages=messages,
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max_tokens=512,
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temperature=0.5, # Lower temperature for more focused translations
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top_p=0.9,
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stream=True
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)
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