fix: ruff lint&format

app.py

@@ -12,113 +12,117 @@ GEMINI_API_KEY = ""
 
 
 def update_api_keys(mistral_key, gemini_key):
-	"""
-	Updates the global MISTRAL_API_KEY and GEMINI_API_KEY variables.
+    """
+    Updates the global MISTRAL_API_KEY and GEMINI_API_KEY variables.
 
-	Args:
-		mistral_key: The Mistral API key.
-		gemini_key: The Gemini API key.
+    Args:
+            mistral_key: The Mistral API key.
+            gemini_key: The Gemini API key.
 
-	Returns:
-		A string confirming that the API keys have been saved.
-	"""
-	global MISTRAL_API_KEY, GEMINI_API_KEY
+    Returns:
+            A string confirming that the API keys have been saved.
+    """
+    global MISTRAL_API_KEY, GEMINI_API_KEY
 
-	MISTRAL_API_KEY = mistral_key
-	GEMINI_API_KEY = gemini_key
+    MISTRAL_API_KEY = mistral_key
+    GEMINI_API_KEY = gemini_key
 
-	return "API keys saved"
+    return "API keys saved"
 
 
 def ocr_workflow_wrapper(file: File, mistral_key: str):
-	"""
-	Manages the OCR workflow, processing an uploaded file to extract text.
-
-	Args:
-		file: The file object to process (image, PDF, or text).
-		mistral_key: The Mistral API key for OCR processing.
-
-	Yields:
-		Status messages and the extracted text or error messages.
-	"""
-	if not mistral_key:
-		error_msg = "Error: Mistral API Key not set."
-		yield error_msg, error_msg
-		return
-	if not file or file.name == "":
-		error_msg = "Error: File/Text not found."
-		yield error_msg, error_msg
-		return
-
-	try:
-		result = perform_raw_ocr(file, mistral_key)
-		yield result, f"\n{result}\n"
-	except Exception as e:
-		error_msg = f"An error occurred during processing: {str(e)}"
-		yield error_msg, error_msg
+    """
+    Manages the OCR workflow, processing an uploaded file to extract text.
+
+    Args:
+            file: The file object to process (image, PDF, or text).
+            mistral_key: The Mistral API key for OCR processing.
+
+    Yields:
+            Status messages and the extracted text or error messages.
+    """
+    if not mistral_key:
+        error_msg = "Error: Mistral API Key not set."
+        yield error_msg, error_msg
+        return
+    if not file or file.name == "":
+        error_msg = "Error: File/Text not found."
+        yield error_msg, error_msg
+        return
+
+    try:
+        result = perform_raw_ocr(file, mistral_key)
+        yield result, f"\n{result}\n"
+    except Exception as e:
+        error_msg = f"An error occurred during processing: {str(e)}"
+        yield error_msg, error_msg
 
 
 def ai_correct(current_text: str, mistral_key: str):
-	"""
-	Corrects the provided text using an AI model.
-
-	Args:
-		current_text: The text to be corrected.
-		mistral_key: The Mistral API key for AI correction.
-
-	Yields:
-		Status messages and the corrected text or error messages.
-	"""
-	if not mistral_key:
-		error_msg = "Error: Mistral API Key not set."
-		yield error_msg, error_msg
-		return
-	if not current_text or current_text.strip() == "":
-		error_msg = "*No text to correct. Upload a file, or paste text into 'Raw Text' box first*"
-		yield error_msg, error_msg
-		return
-
-	try:
-		result = correct_text_with_ai(current_text, mistral_key)
-		yield result, result
-	except Exception as e:
-		error_msg = f"Error : {e}"
-		yield error_msg, error_msg
-
-
-def interpretation_workflow(text: str, genre: str, learn_language: str, target_language: str, gemini_key: str):
-	"""
-	Generates an interpretation of the text based on genre and language settings.
-
-	Args:
-		text: The text to interpret.
-		genre: The genre of the text (e.g., "general", "news").
-		learn_language: The language being learned.
-		target_language: The language for the interpretation output.
-		gemini_key: The Gemini API key for interpretation.
-
-	Yields:
-		Status messages and the generated interpretation or error messages.
-	"""
-	if not gemini_key:
-		yield "Error: Gemini api key not found."
-		return
-	if not text or text.strip() == "":
-		yield "Error: Text is empty"
-		return
-	if not learn_language or not target_language:
-		yield "Error: Language not selected"
-		return
-
-	if genre.lower() in ["general", "news", "philosophy"]:
-		result = get_interpretation(genre.lower(), gemini_key, text, learn_language, target_language)
-		yield result
-	else:
-		yield "not implemented yet"
+    """
+    Corrects the provided text using an AI model.
+
+    Args:
+            current_text: The text to be corrected.
+            mistral_key: The Mistral API key for AI correction.
+
+    Yields:
+            Status messages and the corrected text or error messages.
+    """
+    if not mistral_key:
+        error_msg = "Error: Mistral API Key not set."
+        yield error_msg, error_msg
+        return
+    if not current_text or current_text.strip() == "":
+        error_msg = "*No text to correct. Upload a file, or paste text into 'Raw Text' box first*"
+        yield error_msg, error_msg
+        return
+
+    try:
+        result = correct_text_with_ai(current_text, mistral_key)
+        yield result, result
+    except Exception as e:
+        error_msg = f"Error : {e}"
+        yield error_msg, error_msg
+
+
+def interpretation_workflow(
+    text: str, genre: str, learn_language: str, target_language: str, gemini_key: str
+):
+    """
+    Generates an interpretation of the text based on genre and language settings.
+
+    Args:
+            text: The text to interpret.
+            genre: The genre of the text (e.g., "general", "news").
+            learn_language: The language being learned.
+            target_language: The language for the interpretation output.
+            gemini_key: The Gemini API key for interpretation.
+
+    Yields:
+            Status messages and the generated interpretation or error messages.
+    """
+    if not gemini_key:
+        yield "Error: Gemini api key not found."
+        return
+    if not text or text.strip() == "":
+        yield "Error: Text is empty"
+        return
+    if not learn_language or not target_language:
+        yield "Error: Language not selected"
+        return
+
+    if genre.lower() in ["general", "news", "philosophy"]:
+        result = get_interpretation(
+            genre.lower(), gemini_key, text, learn_language, target_language
+        )
+        yield result
+    else:
+        yield "not implemented yet"
 
 
 def translation_workflow(text: str, target_language: str, gemini_key):
-	"""
+    """
     Translates the provided text to the target language.
 
     Args:
@@ -129,21 +133,31 @@ def translation_workflow(text: str, target_language: str, gemini_key):
     Yields:
         Status messages and the translated text or error messages.
     """
-	if not gemini_key:
-		yield "Error: Gemini api key not found."
-		return
-	if not text or text.strip() == "":
-		yield "Error: Text is empty"
-		return
-	if not target_language:
-		yield "Error: Language not selected"
-	
-	existin_languages = ["العربية", "Deutsch", "Español", "English", "Français", "Italiano", "日本語", "Русский язык", "中文"]
-	if target_language in existin_languages:
-		result = get_translaton(text, gemini_key, target_language)
-		yield result
-	else:
-		yield "not implemented yet"
+    if not gemini_key:
+        yield "Error: Gemini api key not found."
+        return
+    if not text or text.strip() == "":
+        yield "Error: Text is empty"
+        return
+    if not target_language:
+        yield "Error: Language not selected"
+
+    existin_languages = [
+        "العربية",
+        "Deutsch",
+        "Español",
+        "English",
+        "Français",
+        "Italiano",
+        "日本語",
+        "Русский язык",
+        "中文",
+    ]
+    if target_language in existin_languages:
+        result = get_translaton(text, gemini_key, target_language)
+        yield result
+    else:
+        yield "not implemented yet"
 
 
 def agent_workflow(text: str, prof_language: str, mistral_key: str, gemini_key: str):
@@ -151,7 +165,7 @@ def agent_workflow(text: str, prof_language: str, mistral_key: str, gemini_key:
         return "Error: Both Mistral and Gemini API keys are required."
     if not text or not text.strip():
         return "Error: Input text is empty."
-    
+
     try:
         agent = AutomatedAnalysisAgent(mistral_key=mistral_key, gemini_key=gemini_key)
         result = agent.run(text, prof_language=prof_language)
@@ -161,153 +175,195 @@ def agent_workflow(text: str, prof_language: str, mistral_key: str, gemini_key:
 
 
 with gr.Blocks(theme=gr.themes.Monochrome(), css=CUSTOM_CSS) as demo:
-	gr.Markdown("# 📚 LogosAI - Intensive Reading in Any Language", elem_classes=["section-header"])
-
-	# --- API Key ---
-	with gr.Accordion("API Configuration", open=True):
-		with gr.Row():
-			with gr.Column(scale=2):
-				mistral_api = gr.Textbox(
-					label="Mistral API Key", 
-					type="password", 
-					placeholder="Enter your key",
-					info="OCR recognition & text processing"
-				)
-			with gr.Column(scale=2):
-				gemini_api = gr.Textbox(
-					label="Gemini API Key", 
-					type="password", 
-					placeholder="Enter your key",
-					info="text interpretation"
-				)
-			with gr.Column(scale=1):
-				update_keys_button = gr.Button("Save keys")
-
-	api_key_status_output = gr.Markdown()
-
-	update_keys_button.click(
-		fn=update_api_keys,
-		inputs=[mistral_api, gemini_api],
-		outputs=api_key_status_output
-	)
-
-	# --- Text Processing ---
-	gr.Markdown("---")
-	with gr.Tab("Text"):
-
-		with gr.Row():
-			with gr.Column(scale=1):
-				gr.Markdown("### Upload documents")
-				file_input = gr.File(
-					label="Upload Image/PDF/text",
-					file_types=["image", ".pdf", ".txt"]
-					)
-				process_button = gr.Button("1. File Process (OCR/Read)", variant="primary")
-				ai_correct_button = gr.Button("2. AI Correct", variant="primary")
-			with gr.Column(scale=2):
-				gr.Markdown("### Processed result")
-				with gr.Tabs():
-					with gr.Tab("Raw Text"):
-						text_display = gr.Textbox(
-							label="Raw Text(editable)",
-							lines=15,
-							max_lines=20,
-							show_copy_button=True,
-							value="",
-							interactive=True
-						)
-					with gr.Tab("Formatted Text"):
-						text_markdown = gr.Markdown(
-							value="*Processed text will appear here...*\n\n",
-							label="Formatted Text"
-						)
-
-	# Hook the ocr button to click event
-	process_button.click(
-		fn=ocr_workflow_wrapper,
-		inputs=[file_input, mistral_api],
-		outputs=[text_display, text_markdown]
-	)
-
-	# AI correction button to click event
-	ai_correct_button.click(
-		fn=ai_correct,
-		inputs=[text_display, mistral_api],
-		outputs=[text_display, text_markdown]
-	)
-
-	# --- Agent ---
-	with gr.Tab("Agent"):
-		gr.Markdown("### Automated Analysis")
-		with gr.Row():
-			with gr.Column(scale=1):
-				agent_prof_language_selector = gr.Dropdown(["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"], label="Prof's Language", value="EN")
-				agent_run_button = gr.Button("Run Automated Analysis", variant="primary")
-			with gr.Column(scale=2):
-				gr.Markdown("### Agent Result")
-				agent_output = gr.Markdown(
-					value="*Agent analysis will appear here...*\n\n",
-					label="Agent Result"
-				)
-		
-		agent_run_button.click(
-			fn=agent_workflow,
-			inputs=[text_display, agent_prof_language_selector, mistral_api, gemini_api],
-			outputs=agent_output
-		)
-
-
-	# --- Text Interpertation ---
-	with gr.Tab("🎓 Interpretation"):
-		gr.Markdown("### Configure Interpretation Settings")
-
-		with gr.Row():
-			with gr.Column(scale=1):
-				prof_language_seletor = gr.Dropdown(["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"], label="Prof's Language", value="EN")
-				learn_language_seletor = gr.Dropdown(["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"], label="Language to Learn", value="EN")
-				style_seletor = gr.Dropdown(["General", "News", "Philosophy", "Narrative", "Poem", "Paper"], label="Genre")
-				interpret_button = gr.Button("Generate Interpretation", variant="primary")
-
-			with gr.Column(scale=2):
-				gr.Markdown("### COURSE")
-				interpretation_output = gr.Markdown(
-					value="*Interpretation will appear here after processing...*\n\n",
-					label="Interpretation Result",
-					show_copy_button=True
-					)
-
-	interpret_button.click(
-		fn=interpretation_workflow,
-		inputs=[text_display, style_seletor, learn_language_seletor, prof_language_seletor, gemini_api],
-		outputs=interpretation_output
-	)
-
-	# --- Translation ---
-	with gr.Tab("Translation"):
-		gr.Markdown("### Configure Translation Settings")
-		with gr.Row():
-			with gr.Column(scale=1):
-				target_language_selector = gr.Dropdown(
-					["العربية", "Deutsch", "Español", "English", "Français", "Italiano", "日本語", "Русский язык", "中文"],
-					value="English",
-					label="Target Language",
-					interactive=True)
-				translation_button = gr.Button("Translate!", variant="primary")
-
-			with gr.Column(scale=2):
-				interpretation_output = gr.Markdown(
-					value="*Translation will appear here ...*\n\n",
-					label="Translation Result",
-					show_copy_button=True
-					)
-
-	translation_button.click(
-		fn=translation_workflow,
-		inputs=[text_display, target_language_selector, gemini_api],
-		outputs=interpretation_output
-	)
-
+    gr.Markdown(
+        "# 📚 LogosAI - Intensive Reading in Any Language",
+        elem_classes=["section-header"],
+    )
+
+    # --- API Key ---
+    with gr.Accordion("API Configuration", open=True):
+        with gr.Row():
+            with gr.Column(scale=2):
+                mistral_api = gr.Textbox(
+                    label="Mistral API Key",
+                    type="password",
+                    placeholder="Enter your key",
+                    info="OCR recognition & text processing",
+                )
+            with gr.Column(scale=2):
+                gemini_api = gr.Textbox(
+                    label="Gemini API Key",
+                    type="password",
+                    placeholder="Enter your key",
+                    info="text interpretation",
+                )
+            with gr.Column(scale=1):
+                update_keys_button = gr.Button("Save keys")
+
+    api_key_status_output = gr.Markdown()
+
+    update_keys_button.click(
+        fn=update_api_keys,
+        inputs=[mistral_api, gemini_api],
+        outputs=api_key_status_output,
+    )
+
+    # --- Text Processing ---
+    gr.Markdown("---")
+    with gr.Tab("Text"):
+        with gr.Row():
+            with gr.Column(scale=1):
+                gr.Markdown("### Upload documents")
+                file_input = gr.File(
+                    label="Upload Image/PDF/text", file_types=["image", ".pdf", ".txt"]
+                )
+                process_button = gr.Button(
+                    "1. File Process (OCR/Read)", variant="primary"
+                )
+                ai_correct_button = gr.Button("2. AI Correct", variant="primary")
+            with gr.Column(scale=2):
+                gr.Markdown("### Processed result")
+                with gr.Tabs():
+                    with gr.Tab("Raw Text"):
+                        text_display = gr.Textbox(
+                            label="Raw Text(editable)",
+                            lines=15,
+                            max_lines=20,
+                            show_copy_button=True,
+                            value="",
+                            interactive=True,
+                        )
+                    with gr.Tab("Formatted Text"):
+                        text_markdown = gr.Markdown(
+                            value="*Processed text will appear here...*\n\n",
+                            label="Formatted Text",
+                        )
+
+    # Hook the ocr button to click event
+    process_button.click(
+        fn=ocr_workflow_wrapper,
+        inputs=[file_input, mistral_api],
+        outputs=[text_display, text_markdown],
+    )
+
+    # AI correction button to click event
+    ai_correct_button.click(
+        fn=ai_correct,
+        inputs=[text_display, mistral_api],
+        outputs=[text_display, text_markdown],
+    )
+
+    # --- Agent ---
+    with gr.Tab("Agent"):
+        gr.Markdown("### Automated Analysis")
+        with gr.Row():
+            with gr.Column(scale=1):
+                agent_prof_language_selector = gr.Dropdown(
+                    ["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"],
+                    label="Prof's Language",
+                    value="EN",
+                )
+                agent_run_button = gr.Button(
+                    "Run Automated Analysis", variant="primary"
+                )
+            with gr.Column(scale=2):
+                gr.Markdown("### Agent Result")
+                agent_output = gr.Markdown(
+                    value="*Agent analysis will appear here...*\n\n",
+                    label="Agent Result",
+                )
+
+        agent_run_button.click(
+            fn=agent_workflow,
+            inputs=[
+                text_display,
+                agent_prof_language_selector,
+                mistral_api,
+                gemini_api,
+            ],
+            outputs=agent_output,
+        )
+
+    # --- Text Interpertation ---
+    with gr.Tab("🎓 Interpretation"):
+        gr.Markdown("### Configure Interpretation Settings")
+
+        with gr.Row():
+            with gr.Column(scale=1):
+                prof_language_seletor = gr.Dropdown(
+                    ["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"],
+                    label="Prof's Language",
+                    value="EN",
+                )
+                learn_language_seletor = gr.Dropdown(
+                    ["AR", "DE", "ES", "EN", "FR", "IT", "JA", "RU", "ZH"],
+                    label="Language to Learn",
+                    value="EN",
+                )
+                style_seletor = gr.Dropdown(
+                    ["General", "News", "Philosophy", "Narrative", "Poem", "Paper"],
+                    label="Genre",
+                )
+                interpret_button = gr.Button(
+                    "Generate Interpretation", variant="primary"
+                )
+
+            with gr.Column(scale=2):
+                gr.Markdown("### COURSE")
+                interpretation_output = gr.Markdown(
+                    value="*Interpretation will appear here after processing...*\n\n",
+                    label="Interpretation Result",
+                    show_copy_button=True,
+                )
+
+    interpret_button.click(
+        fn=interpretation_workflow,
+        inputs=[
+            text_display,
+            style_seletor,
+            learn_language_seletor,
+            prof_language_seletor,
+            gemini_api,
+        ],
+        outputs=interpretation_output,
+    )
+
+    # --- Translation ---
+    with gr.Tab("Translation"):
+        gr.Markdown("### Configure Translation Settings")
+        with gr.Row():
+            with gr.Column(scale=1):
+                target_language_selector = gr.Dropdown(
+                    [
+                        "العربية",
+                        "Deutsch",
+                        "Español",
+                        "English",
+                        "Français",
+                        "Italiano",
+                        "日本語",
+                        "Русский язык",
+                        "中文",
+                    ],
+                    value="English",
+                    label="Target Language",
+                    interactive=True,
+                )
+                translation_button = gr.Button("Translate!", variant="primary")
+
+            with gr.Column(scale=2):
+                interpretation_output = gr.Markdown(
+                    value="*Translation will appear here ...*\n\n",
+                    label="Translation Result",
+                    show_copy_button=True,
+                )
+
+    translation_button.click(
+        fn=translation_workflow,
+        inputs=[text_display, target_language_selector, gemini_api],
+        outputs=interpretation_output,
+    )
 
 
 if __name__ == "__main__":
-	demo.launch(mcp_server=True)
+    demo.launch(mcp_server=True)

process/agent.py

@@ -1,4 +1,3 @@
-
 import json
 from google import genai
 from google.genai import types
@@ -33,6 +32,7 @@ Example output:
 }
 """
 
+
 class AutomatedAnalysisAgent:
     def __init__(self, mistral_key: str, gemini_key: str):
         if not mistral_key or not gemini_key:
@@ -53,11 +53,15 @@ class AutomatedAnalysisAgent:
                     temperature=0.0,
                     response_mime_type="application/json",
                 ),
-                contents=[text]
+                contents=[text],
             )
             directives = json.loads(response.text)
             # Basic validation
-            if "language" not in directives or "genre" not in directives or "correction_needed" not in directives:
+            if (
+                "language" not in directives
+                or "genre" not in directives
+                or "correction_needed" not in directives
+            ):
                 raise ValueError("Invalid JSON structure from analysis model.")
             return directives
         except Exception as e:
@@ -75,7 +79,7 @@ class AutomatedAnalysisAgent:
 
         # 1. Get analysis directives from the agent's brain
         directives = self._get_analysis_directives(text)
-        
+
         processed_text = text
         # 2. Conditionally apply AI correction
         if directives.get("correction_needed", False):
@@ -93,10 +97,9 @@ class AutomatedAnalysisAgent:
                 api_key=self.gemini_key,
                 text=processed_text,
                 learn_language=directives.get("language", "EN"),
-                prof_language=prof_language
+                prof_language=prof_language,
             )
             return interpretation
         except Exception as e:
             print(f"Error during interpretation: {e}")
             return f"An error occurred during the final interpretation step: {e}"
-

process/gradio_css.py

@@ -15,4 +15,4 @@ rest = """
         max-width: 1200px !important;
         margin: auto !important;
     }
-"""
+"""

process/interpretation.py

@@ -7,42 +7,52 @@ NARRATIVE_PROMPT = ""
 POEM_PROMPT = ""
 
 
-def get_interpretation(genre: str,
-						api_key: str,
-						text: str,
-						learn_language: str,
-						prof_language: str) -> str:
-
-	if not api_key:
-		return "Error: Gemini API Key not found."
-	if not text:
-		return "Error: text not found."
-
-	try:
-		client = genai.Client(api_key=api_key)
-	except Exception as e:
-		return f"ERROR: {str(e)}"
-
-
-	lang_map ={"AR": "Arabic", "DE": "German", "ES": "Spanish", "EN": "English", "FR": "French", "IT": "Italian", "JA": "Japanese", "RU":"Russian", "ZH": "Chinese"}
-	learn_lang = lang_map.get(learn_language.upper(), "English")
-	prof_lang = lang_map.get(prof_language.upper(), "English")
-	genres = {
-		"general": GENERAL_PROMPT,
-		"news": NEWS_PROMPT, 
-		"narrative": NARRATIVE_PROMPT, 
-		"poem": POEM_PROMPT,
-		"philosophy": PHILO_PROMPT
-		}
-	if genre.lower() in ["general", "news", "philosophy"]:
-		sys_prompt = genres[genre.lower()].replace("[LEARN_LANGUAGE]", learn_lang).replace("[PROF_LANGUAGE]", prof_lang)
-
-	response = client.models.generate_content(
-		model="gemini-2.5-pro",
-		config=types.GenerateContentConfig(
-			system_instruction=sys_prompt,
-			temperature=0.3,
-			),
-		contents=[text]
-	)
-	return response.text
+def get_interpretation(
+    genre: str, api_key: str, text: str, learn_language: str, prof_language: str
+) -> str:
+    if not api_key:
+        return "Error: Gemini API Key not found."
+    if not text:
+        return "Error: text not found."
+
+    try:
+        client = genai.Client(api_key=api_key)
+    except Exception as e:
+        return f"ERROR: {str(e)}"
+
+    lang_map = {
+        "AR": "Arabic",
+        "DE": "German",
+        "ES": "Spanish",
+        "EN": "English",
+        "FR": "French",
+        "IT": "Italian",
+        "JA": "Japanese",
+        "RU": "Russian",
+        "ZH": "Chinese",
+    }
+    learn_lang = lang_map.get(learn_language.upper(), "English")
+    prof_lang = lang_map.get(prof_language.upper(), "English")
+    genres = {
+        "general": GENERAL_PROMPT,
+        "news": NEWS_PROMPT,
+        "narrative": NARRATIVE_PROMPT,
+        "poem": POEM_PROMPT,
+        "philosophy": PHILO_PROMPT,
+    }
+    if genre.lower() in ["general", "news", "philosophy"]:
+        sys_prompt = (
+            genres[genre.lower()]
+            .replace("[LEARN_LANGUAGE]", learn_lang)
+            .replace("[PROF_LANGUAGE]", prof_lang)
+        )
+
+    response = client.models.generate_content(
+        model="gemini-2.5-pro",
+        config=types.GenerateContentConfig(
+            system_instruction=sys_prompt,
+            temperature=0.3,
+        ),
+        contents=[text],
+    )
+    return response.text

process/ocr.py

@@ -7,72 +7,68 @@ CHAT_MODEL = "mistral-large-latest"
 
 
 def ocr_from_file(file_path, api_key: str, mode="image"):
-
-	if not api_key:
-		raise ValueError("Mistral API Key is required.")
-
-	try:
-		client = Mistral(api_key=api_key)
-	except Exception as e:
-		raise ValueError("API invalid.")
-
-	uploaded_image = client.files.upload(
-		file={
-			"file_name": file_path,
-			"content": open(file_path, "rb"),
-		},
-		purpose="ocr"
-	)
-	signed_url = client.files.get_signed_url(file_id=uploaded_image.id)
-
-	if mode == "image":
-		ocr_response = client.ocr.process(
-			model=OCR_MODEL,
-			document={
-				"type": "image_url",
-				"image_url": signed_url.url,
-			},
-			include_image_base64=True
-		)
-	elif mode == "pdf":
-		ocr_response = client.ocr.process(
-			model=OCR_MODEL,
-			document={
-				"type": "document_url",
-				"document_url": signed_url.url,
-			},
-			include_image_base64=True
-		)
-
-	return ocr_response
+    if not api_key:
+        raise ValueError("Mistral API Key is required.")
+
+    try:
+        client = Mistral(api_key=api_key)
+    except Exception:
+        raise ValueError("API invalid.")
+
+    uploaded_image = client.files.upload(
+        file={
+            "file_name": file_path,
+            "content": open(file_path, "rb"),
+        },
+        purpose="ocr",
+    )
+    signed_url = client.files.get_signed_url(file_id=uploaded_image.id)
+
+    if mode == "image":
+        ocr_response = client.ocr.process(
+            model=OCR_MODEL,
+            document={
+                "type": "image_url",
+                "image_url": signed_url.url,
+            },
+            include_image_base64=True,
+        )
+    elif mode == "pdf":
+        ocr_response = client.ocr.process(
+            model=OCR_MODEL,
+            document={
+                "type": "document_url",
+                "document_url": signed_url.url,
+            },
+            include_image_base64=True,
+        )
+
+    return ocr_response
 
 
 def get_combined_markdown(ocr_response: OCRResponse) -> str:
+    markdowns: list[str] = []
+    for page in ocr_response.pages:
+        markdowns.append(page.markdown)
 
-	markdowns: list[str] = []
-	for page in ocr_response.pages:
-		markdowns.append(page.markdown)
-
-	return "\n\n".join(markdowns)
+    return "\n\n".join(markdowns)
 
 
 def correct_text_with_ai(text: str, api_key: str) -> str:
-
-	if not api_key:
-		raise ValueError("Mistral API Key is required.")
-
-	try:
-		client = Mistral(api_key=api_key)
-	except Exception as e:
-		return f"ERROR: {str(e)}"
-
-	response = client.chat.complete(
-		model=CHAT_MODEL,
-		messages=[
-			{
-				"role": "system",
-				"content":
-					"""You are an expert proofreader specializing in Markdown formatting and OCR error correction. Your task is to meticulously review provided Markdown text that has been generated via OCR.
+    if not api_key:
+        raise ValueError("Mistral API Key is required.")
+
+    try:
+        client = Mistral(api_key=api_key)
+    except Exception as e:
+        return f"ERROR: {str(e)}"
+
+    response = client.chat.complete(
+        model=CHAT_MODEL,
+        messages=[
+            {
+                "role": "system",
+                "content": """You are an expert proofreader specializing in Markdown formatting and OCR error correction. Your task is to meticulously review provided Markdown text that has been generated via OCR.
 					Your primary goal is to identify and correct **typographical errors, spelling mistakes, and redundant symbols** that are clearly a result of the OCR process.
 					Additionally, you must correct any illogical or jumbled line breaks to ensure proper Markdown paragraph formatting.
 
@@ -82,31 +78,28 @@ def correct_text_with_ai(text: str, api_key: str) -> str:
 					* Markdown formatting errors
 					* Jumbled or incorrect line breaks for proper paragraphing
 
-					After your thorough review, output the carefully corrected Markdown text. JUST the text."""
-				},
-			{
-				"role": "user",
-				"content": text
-				},
-		],
-		temperature=0.1,
-	)
-	return(response.choices[0].message.content)
+					After your thorough review, output the carefully corrected Markdown text. JUST the text.""",
+            },
+            {"role": "user", "content": text},
+        ],
+        temperature=0.1,
+    )
+    return response.choices[0].message.content
 
 
 def perform_raw_ocr(input_file: File, api_key: str):
-	if input_file and input_file.name:
-		file_ext = input_file.name.split('.')[-1].lower()
-	else:
-		return "File/Text not found"
-
-	if file_ext == "txt":
-		with open(input_file, "r", encoding="utf-8") as f:
-			return f.read()
-	elif file_ext == "pdf":
-		file_type = "pdf"
-	else:
-		file_type = "image"
-	response = ocr_from_file(input_file, api_key, file_type)
-	res_text = get_combined_markdown(response)
-	return res_text
+    if input_file and input_file.name:
+        file_ext = input_file.name.split(".")[-1].lower()
+    else:
+        return "File/Text not found"
+
+    if file_ext == "txt":
+        with open(input_file, "r", encoding="utf-8") as f:
+            return f.read()
+    elif file_ext == "pdf":
+        file_type = "pdf"
+    else:
+        file_type = "image"
+    response = ocr_from_file(input_file, api_key, file_type)
+    res_text = get_combined_markdown(response)
+    return res_text

process/sys_prompt.py

@@ -1,4 +1,4 @@
-GENERAL_PROMPT ="""
+GENERAL_PROMPT = """
 ## Core Purpose and Goals:
 
 * To assist students with **intermediate to advanced `[LEARN_LANGUAGE]` proficiency** in mastering sophisticated aspects of the language through the deep analysis of complex, authentic texts.

process/translation.py

@@ -9,38 +9,37 @@ Do not add any extra information, explanations, or stylistic changes.
 Maintain the original meaning and tone as closely as possible.
 """
 
-def get_translaton(text: str, api_key: str, target_language: str) -> str:
 
-	if not api_key:
-		return "Error: Gemini API Key not found."
-	if not text:
-		return "Error: text not found."
+def get_translaton(text: str, api_key: str, target_language: str) -> str:
+    if not api_key:
+        return "Error: Gemini API Key not found."
+    if not text:
+        return "Error: text not found."
 
-	try:
-		client = genai.Client(api_key=api_key)
-	except Exception as e:
-		return f"ERROR: {str(e)}"
+    try:
+        client = genai.Client(api_key=api_key)
+    except Exception as e:
+        return f"ERROR: {str(e)}"
 
-	lang_map = {
-		"العربية": "Arabic",
-		"Deutsch": "German",
-		"Español": "Spanish",
-		"English": "English",
-		"Français": "French",
-		"Italiano": "Italian",
-		"日本語": "Japanese",
-		"Русский язык": "Russian",
-		"中文": "Chinese"
-		}
-	lang_map = {"Deutsch": "German", "English": "English", "Français": "French", "Русский язык": "Russain", "中文": "Chinese"}
-	tar_lang = lang_map.get(target_language, "English")
-	sys_prompt = SYS_PROMPT_TRANSLATION.replace("[TARGET_LANGUAGE]", tar_lang)
-	response = client.models.generate_content(
-		model="gemini-2.5-pro",
-		config=types.GenerateContentConfig(
-			system_instruction=sys_prompt,
-			temperature=0.1,
-			),
-		contents=[text]
-	)
-	return response.text
+    lang_map = {
+        "العربية": "Arabic",
+        "Deutsch": "German",
+        "Español": "Spanish",
+        "English": "English",
+        "Français": "French",
+        "Italiano": "Italian",
+        "日本語": "Japanese",
+        "Русский язык": "Russian",
+        "中文": "Chinese",
+    }
+    tar_lang = lang_map.get(target_language, "English")
+    sys_prompt = SYS_PROMPT_TRANSLATION.replace("[TARGET_LANGUAGE]", tar_lang)
+    response = client.models.generate_content(
+        model="gemini-2.5-pro",
+        config=types.GenerateContentConfig(
+            system_instruction=sys_prompt,
+            temperature=0.1,
+        ),
+        contents=[text],
+    )
+    return response.text