Create personalized_interaction.py

src/interaction/personalized_interaction.py

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+# © 2025 Elena Marziali — Code released under Apache 2.0 license.
+# See LICENSE in the repository for details.
+# Removal of this copyright is prohibited.
+
+# This cell analyzes the user's question and adapts the response
+# based on subject, skill level, language, and preferences.
+
+# Analyze the question to extract intent and context
+def analyze_question(question):
+    question_lower = question.lower()
+    if re.search(r"\d+|equation|formula|calculate|solve", question_lower):
+        return "mathematical problem"
+    elif re.search(r"anatomy|biology|description|organ|function|system", question_lower):
+        return "descriptive-biological problem"
+    elif re.search(r"experiment|measurement|test|observation", question_lower):
+        return "experimental problem"
+    else:
+        return "theoretical problem"
+
+# Extract semantic and conceptual characteristics
+def extract_features(problem):
+    problem_lower = problem.lower()
+    if re.search(r"\d+|equation|formula|energy|speed", problem_lower):
+        return "Chart"
+    elif re.search(r"principle|theory|model|experiment", problem_lower):
+        return "Conceptual diagram"
+    elif re.search(r"pressure|volume|temperature|transformation", problem_lower):
+        return "State diagram"
+    else:
+        return "Plain text"
+
+# Reformulate the question to make it clearer for the model
+def reformulate_question(question):
+    prompt = f"""Reformulate this question in a technical and precise way for a scientific AI assistant.
+
+Question: "{question}"
+
+Return only the reformulated question, without explanations."""
+    response = generate_response(prompt, temperature=0.5).strip()
+
+    for prefix in [
+        "The generated response to the question",
+        "Return only the reformulated question",
+        "Question:"
+    ]:
+        if response.lower().startswith(prefix.lower()):
+            response = response[len(prefix):].strip(": .\"'\n")
+
+    if "\n" in response:
+        response = response.split("\n")[0].strip()
+
+    return response
+
+# === File upload ===
+try:
+    uploaded = files.upload()
+    file_name = list(uploaded.keys())[0]
+    file_text = extract_text(file_name)
+
+    if not file_text or file_text == "Empty or non-textual file.":
+        raise ValueError("The uploaded file does not contain valid text.")
+except Exception as e:
+    logging.error(f"File upload error: {e}")
+    file_text = input("Manually enter the problem: ").strip()
+
+# Save
+with open(INDEX_FILE, "wb") as f:
+    pickle.dump(index, f)
+
+# Load
+with open(INDEX_FILE, "rb") as f:
+    index = pickle.load(f)
+
+
+# Generate intelligent report
+async def example_search():
+    query = "quantum physics"
+    articles = await search_multi_database(query)
+    print(articles)
+
+# Execute the function directly with await
+await example_search()
+
+# === User input ===
+import asyncio
+
+# Validate that input is correct and coherent
+async def get_valid_input(message, valid_options=None):
+    """ Asynchronous function to handle validated input. """
+    while True:
+        value = await asyncio.to_thread(input, message.strip())
+        value = value.strip()
+
+        if not value:
+            print("Error! Please enter a valid value.")
+        elif valid_options and value.lower() not in valid_options:
+            print(f"Error! You must choose from: {', '.join(valid_options)}")
+        else:
+            return value
+
+example_problem = ""
+
+while not example_problem:
+    example_problem = file_text.strip() if file_text.strip() else await get_valid_input("Enter the problem manually:")
+
+subject = input("Enter the subject (e.g., physics, biology, etc.): ").strip().lower() or "general subject"
+level = input("Choose the level (basic/advanced/expert): ").strip().lower()
+while level not in ["basic", "advanced", "expert"]:
+    level = input("Error! Enter basic/advanced/expert: ").strip().lower()
+
+topic = input("Enter the scientific problem or topic: ").strip()
+
+chart_choice = input("Do you want a chart for the explanation? (yes/no): ").strip().lower()
+while chart_choice not in ["yes", "no"]:
+    chart_choice = input("Error! Please answer 'yes' or 'no': ").strip().lower()
+
+chart_requested = chart_choice == "yes"
+
+fig = None
+caption = ""
+
+if chart_requested:
+    try:
+        fig, caption = generate_interactive_chart(example_problem)
+        fig.show()
+        logging.info("Chart successfully generated.")
+    except Exception as e:
+        logging.error(f"Chart generation error: {e}")
+        fig = None
+else:
+    logging.info("Chart not requested by the user.")
+
+available_languages = ["en", "fr", "de", "es", "zh", "ja", "ar", "it"]
+
+target_language = input("Which language do you want the translation in? (" + ", ".join(available_languages) + "): ").strip().lower()
+while target_language not in available_languages:
+    target_language = input("Error! Choose a valid language from: " + ", ".join(available_languages) + ": ").strip().lower()
+
+#Secure Translation and Protected Embedding Storage
+save_multilingual_journal(
+    journal_text=example_problem,
+    journal_id=0,
+    target_language=target_language
+)
+
+#Secure Translation and Protected Embedding Retrieval
+similar_entries = search_similar_journals(
+    query=example_problem,
+    target_language=target_language
+)
+
+for s in similar_entries:
+    print("Similar journal:", s)