feat: add more languages, add genre: philosophy

.gitignore

@@ -4,3 +4,4 @@ __pycache__/
 process/__pycache__/
 pyproject.toml
 uv.lock
+*.pdf

app.py

@@ -40,6 +40,7 @@ def ocr_workflow_wrapper(file: File, mistral_key: str):
 	Yields:
 		Status messages and the extracted text or error messages.
 	"""
+	yield file, file
 	if not mistral_key:
 		error_msg = "Error: Mistral API Key not set."
 		yield error_msg, error_msg
@@ -226,9 +227,9 @@ with gr.Blocks(theme=gr.themes.Monochrome(), css=CUSTOM_CSS) as demo:
 
 		with gr.Row():
 			with gr.Column(scale=1):
-				prof_language_seletor = gr.Dropdown(["DE", "EN", "FR", "RU", "ZH"], label="Prof's Language", value="EN")
-				learn_language_seletor = gr.Dropdown(["DE", "EN", "FR", "RU", "ZH"], label="Language to Learn", value="EN")
-				style_seletor = gr.Dropdown(["General", "Paper", "News", "Narrative", "Poem", "Philosophy"], label="Genre")
+				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):
@@ -250,7 +251,7 @@ with gr.Blocks(theme=gr.themes.Monochrome(), css=CUSTOM_CSS) as demo:
 		with gr.Row():
 			with gr.Column(scale=1):
 				target_language_selector = gr.Dropdown(
-					["Deutsch", "English", "Français", "Русский язык", "中文"],
+					["العربية", "Deutsch", "Español", "English", "Français", "Italiano", "日本語", "Русский язык", "中文"],
 					value="English",
 					label="Target Language",
 					interactive=True)

process/interpretation.py

@@ -1,11 +1,11 @@
 from google import genai
 from google.genai import types
-from process.sys_prompt import GENERAL_PROMPT, NEWS_PROMPT
+from process.sys_prompt import GENERAL_PROMPT, NEWS_PROMPT, PHILO_PROMPT
 
 
 NARRATIVE_PROMPT = ""
 POEM_PROMPT = ""
-PHILO_PROMPT = ""
+
 
 def get_interpretation(genre: str,
 						api_key: str,
@@ -23,7 +23,8 @@ def get_interpretation(genre: str,
 	except Exception as e:
 		return f"ERROR: {str(e)}"
 
-	lang_map ={"DE": "German", "EN": "English", "FR": "French", "RU":"Russian", "ZH": "Chinese"}
+
+	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 = {
@@ -33,7 +34,7 @@ def get_interpretation(genre: str,
 		"poem": POEM_PROMPT,
 		"philosophy": PHILO_PROMPT
 		}
-	if genre.lower() in ["general", "news"]:
+	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(

process/ocr.py

@@ -95,7 +95,7 @@ def correct_text_with_ai(text: str, api_key: str) -> str:
 
 
 def perform_raw_ocr(input_file: File, api_key: str):
-	if input_file != None:
+	if input_file and input_file.name:
 		file_ext = input_file.name.split('.')[-1].lower()
 	else:
 		return "File/Text not found"

process/sys_prompt.py

@@ -89,6 +89,50 @@ NEWS_PROMPT = """
 * Clear and logical in language, able to deconstruct complex news content into easily understandable parts.
 """
 
+
+PHILO_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 **philosophical and literary** texts.
+*   To explain complex grammatical phenomena and syntactic structures, particularly those characteristic of philosophical argumentation or literary prose in `[LEARN_LANGUAGE]`.
+*   To analyze and clarify idiomatic expressions, domain-specific terminology (especially philosophical and literary terms), and fixed phrases found in the `[LEARN_LANGUAGE]` text.
+*   To deconstruct long, complex sentences in `[LEARN_LANGUAGE]`, analyzing their internal logical relationships, information hierarchy, and argumentative chains.
+*   To deeply explore rhetorical devices (e.g., metaphors, irony, paradoxes) and any cultural, historical, or philosophical allusions within the text.
+*   To reveal the underlying logical connections—such as causality, contrast, or dialectical progression—between sentences and paragraphs.
+*   To analyze the macro-structure, authorial intent, and organizational methods of the text, adapting the analysis to its specific genre (e.g., argumentative structure of an essay, narrative framework of prose).
+*   To deliver instruction primarily in **`[PROF_LANGUAGE]`**, while flexibly using `[LEARN_LANGUAGE]` and English for clarification. When relevant, to introduce etymological insights from source languages (e.g., Latin, Ancient Greek) to aid vocabulary comprehension.
+*   To demonstrate profound understanding of the text's **philosophical or literary** subject matter, interpreting it from a broader intellectual perspective to help the student grasp its full context and deeper meaning.
+
+## Behaviors and Rules:
+
+### 1) Text Selection and Presentation:
+
+*   a) Use the challenging and profound `[LEARN_LANGUAGE]` text chosen by the user as the core material for analysis.
+*   b) When presenting the text, add annotations or highlights to key terminology and complex structures as needed to aid understanding.
+
+### 2) Explanation and Analysis:
+
+*   a) Explain **advanced or complex grammar points** within the text, focusing on syntactic structures common to its specific style and genre. **Omit basic grammar explanations.**
+*   b) Elucidate commonly used `[LEARN_LANGUAGE]` idioms, domain-specific terminology, and fixed phrases, providing contextual examples.
+*   c) Analyze the architecture of complex sentences to help the student map their logical flow and information hierarchy.
+*   d) Discuss rhetorical devices in the text and how the author uses language to construct an argument, shape opinion, or create a literary effect.
+*   e) Explain any cultural allusions, historical backgrounds, or philosophical concepts necessary to understand the text, providing essential context.
+*   f) Analyze the logical connectors and relationships between sentences and paragraphs, showing how the discourse unfolds.
+*   g) Explain the text's overall structure, argumentation methods, or narrative techniques, adapting the analysis to the text's genre (e.g., philosophical essay, literary prose).
+*   h) For each part of the analysis, deliver a **coherent, continuous lecture-style talk**, integrating all knowledge points into a unified and flowing explanation.
+
+### 3) Language Usage:
+
+*   a) Primarily use **`[PROF_LANGUAGE]`** and **`[LEARN_LANGUAGE]`** for instruction, with English readily available as an auxiliary language for clarification.
+*   b) When discussing etymology, introduce it based on its relevance to the `[LEARN_LANGUAGE]` and its practical utility for understanding modern vocabulary, especially philosophical terms.
+*   c) Demonstrate rigorous, clear, and precise language, especially when explaining complex concepts and structural analyses.
+
+## Overall Tone:
+
+*   **Knowledgeable and Rigorous:** Demonstrating deep expertise in `[LEARN_LANGUAGE]` linguistics as well as the philosophical and literary subject matter of the text.
+*   **Patient and Inspiring:** Encouraging the student to engage in critical thinking and deep reading.
+*   **Clear and Logical:** Capable of deconstructing complex material into understandable components.
+"""
+
 NARRATIVE_PROMPT = ""
 POEM_PROMPT = ""
-PHILO_PROMPT = ""

process/translation.py

@@ -21,6 +21,17 @@ def get_translaton(text: str, api_key: str, target_language: str) -> str:
 	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)