upd docker prepare script

Backend/arch.py

@@ -0,0 +1,122 @@
+from pptx import Presentation
+from pptx.util import Inches
+from pptx.enum.shapes import MSO_AUTO_SHAPE_TYPE, MSO_CONNECTOR
+
+# Vytvorenie novej prezentácie
+prs = Presentation()
+slide_layout = prs.slide_layouts[5]  # Prázdny slide
+slide = prs.slides.add_slide(slide_layout)
+
+# Definícia základných rozmerov a pozícií
+left_margin = Inches(0.5)
+top_margin = Inches(0.5)
+block_width = Inches(3)
+block_height = Inches(0.7)
+vertical_gap = Inches(0.3)
+horizontal_gap = Inches(0.5)
+
+# Blok 1: Používateľský dotaz & Chat history
+box1 = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, top_margin, block_width, block_height)
+box1.text = "Používateľský dotaz\n& Chat history"
+
+# Blok 2: ConversationalAgent (pod box1)
+box2_top = top_margin + block_height + vertical_gap
+box2 = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, box2_top, block_width, block_height)
+box2.text = "ConversationalAgent"
+
+# Blok 3: Klasifikácia dotazu (pod box2)
+box3_top = box2_top + block_height + vertical_gap
+box3 = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, box3_top, block_width, block_height)
+box3.text = "Klasifikácia dotazu"
+
+# Vetvenie: Pozície pre dve vetvy
+branch_top = box3_top + block_height + vertical_gap
+
+# Ľavá vetva ("Vyhladavanie")
+left_branch_left = left_margin - Inches(0.2)
+box4A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, branch_top, block_width, block_height)
+box4A.text = "ElasticsearchStore\nvyhľadávanie"
+
+box5A_top = branch_top + block_height + vertical_gap
+box5A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, box5A_top, block_width, block_height)
+box5A.text = "Generovanie\ndynamického promptu"
+
+box6A_top = box5A_top + block_height + vertical_gap
+box6A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, box6A_top, block_width, block_height)
+box6A.text = "Generovanie\nodpovede"
+
+box7A_top = box6A_top + block_height + vertical_gap
+box7A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, box7A_top, block_width, block_height)
+box7A.text = "Finalizácia\nodpovede"
+
+# Pravá vetva ("Upresnenie")
+right_branch_left = left_margin + block_width + horizontal_gap
+box4B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, branch_top, block_width, block_height)
+box4B.text = "Kombinovanie\ndotazov"
+
+box5B_top = branch_top + block_height + vertical_gap
+box5B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box5B_top, block_width, block_height)
+box5B.text = "ElasticsearchStore\nvyhľadávanie"
+
+box6B_top = box5B_top + block_height + vertical_gap
+box6B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box6B_top, block_width, block_height)
+box6B.text = "Generovanie\ndynamického promptu"
+
+box7B_top = box6B_top + block_height + vertical_gap
+box7B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box7B_top, block_width, block_height)
+box7B.text = "Generovanie\nodpovedí (2 modely)"
+
+box8B_top = box7B_top + block_height + vertical_gap
+box8B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box8B_top, block_width, block_height)
+box8B.text = "Validácia a\nhodnotenie odpovedí"
+
+box9B_top = box8B_top + block_height + vertical_gap
+box9B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box9B_top, block_width, block_height)
+box9B.text = "Finalizácia\nodpovede"
+
+# Finálny blok: Výstup (zlúčenie vetiev)
+final_box_top = max(box7A_top, box9B_top) + block_height + vertical_gap
+final_box = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, final_box_top, block_width, block_height)
+final_box.text = "Výstup"
+
+# Funkcia na pridanie šípok medzi blokmi
+def add_connector(slide, start_shape, end_shape):
+    start_x = start_shape.left + start_shape.width / 2
+    start_y = start_shape.top + start_shape.height
+    end_x = end_shape.left + end_shape.width / 2
+    end_y = end_shape.top
+    connector = slide.shapes.add_connector(MSO_CONNECTOR.STRAIGHT, start_x, start_y, end_x, end_y)
+    # Aktuálna verzia python-pptx nepodporuje nastavenie šípky, preto tento riadok odstraňte alebo zakomentujte:
+    # connector.line.end_arrowhead.style = 1
+    return connector
+
+# Prepojenie blokov
+add_connector(slide, box1, box2)
+add_connector(slide, box2, box3)
+
+# Vetvenie z Box3 do oboch vetiev
+mid_point = box3.left + box3.width / 2
+branch_mid_y = box3.top + box3.height + vertical_gap/2
+# Do ľavej vetvy:
+connector_left = slide.shapes.add_connector(MSO_CONNECTOR.STRAIGHT, mid_point, box3.top + box3.height, left_branch_left + block_width/2, branch_mid_y)
+# Do pravej vetvy:
+connector_right = slide.shapes.add_connector(MSO_CONNECTOR.STRAIGHT, mid_point, box3.top + box3.height, right_branch_left + block_width/2, branch_mid_y)
+
+# Prepojenie blokov v ľavej vetve
+add_connector(slide, box4A, box5A)
+add_connector(slide, box5A, box6A)
+add_connector(slide, box6A, box7A)
+
+# Prepojenie blokov v pravej vetve
+add_connector(slide, box4B, box5B)
+add_connector(slide, box5B, box6B)
+add_connector(slide, box6B, box7B)
+add_connector(slide, box7B, box8B)
+add_connector(slide, box8B, box9B)
+
+# Spojenie oboch vetiev s finálnym blokom "Výstup"
+add_connector(slide, box7A, final_box)
+add_connector(slide, box9B, final_box)
+
+# Uloženie prezentácie
+prs.save("architecture_diagram.pptx")

Backend/model.py

@@ -14,7 +14,6 @@ from psycopg2.extras import RealDictCursor
 logging.basicConfig(level=logging.INFO)
 logger = logging.getLogger(__name__)
 
-
 config_file_path = "config.json"
 with open(config_file_path, 'r') as config_file:
     config = json.load(config_file)
@@ -23,15 +22,18 @@ mistral_api_key = "hXDC4RBJk1qy5pOlrgr01GtOlmyCBaNs"
 if not mistral_api_key:
     raise ValueError("Mistral API key not found in configuration.")
 
+
 ###############################################################################
 # Simple functions for translation (stub)
 ###############################################################################
 def translate_to_slovak(text: str) -> str:
     return text
 
+
 def translate_preserving_medicine_names(text: str) -> str:
     return text
 
+
 ###############################################################################
 # Function for evaluating the completeness of the answer
 ###############################################################################
@@ -53,6 +55,7 @@ def evaluate_complete_answer(query: str, answer: str) -> dict:
         score = 0.0
     return {"rating": round(score, 2), "explanation": "Evaluation based on required criteria."}
 
+
 ###############################################################################
 # Function for validating the response logic
 ###############################################################################
@@ -73,6 +76,7 @@ def validate_answer_logic(query: str, answer: str) -> str:
         logger.error(f"Error during answer validation: {e}")
         return answer
 
+
 ###############################################################################
 # Function for creating a dynamic prompt with information from documents
 ###############################################################################
@@ -91,6 +95,7 @@ def build_dynamic_prompt(query: str, documents: list) -> str:
     )
     return prompt
 
+
 ###############################################################################
 #  Function to get user data from the database via endpoint /api/get_user_data
 ###############################################################################
@@ -106,6 +111,7 @@ def get_user_data_from_db(chat_id: str) -> str:
         logger.error(f"Error retrieving user_data from DB: {e}", exc_info=True)
     return ""
 
+
 ###############################################################################
 #  Class for calling Mistral LLM
 ###############################################################################
@@ -147,6 +153,21 @@ class CustomMistralLLM:
                 raise ex
         raise Exception("Reached maximum number of retries for API request")
 
+
+###############################################################################
+# Function for generating a detailed evaluation description
+###############################################################################
+# def detailed_evaluation_description(query: str, answer: str, rating: float) -> str:
+#     prompt = (
+#         f"Podrobne opíš, prečo odpoveď: '{answer}' na otázku: '{query}' dosiahla hodnotenie {rating} zo 10. "
+#         "Uveď relevantné aspekty, ktoré ovplyvnili toto hodnotenie, vrátane úplnosti, presnosti a kvality vysvetlenia."
+#     )
+#     description = llm_small.generate_text(prompt=prompt, max_tokens=150, temperature=0.5)
+#     return description.strip()
+#
+# Ak chcete vidieť podrobné hodnotenie, odkomentujte funkciu detailed_evaluation_description a príslušné časti kódu.
+
+
 ###############################################################################
 # Initialisation of Embeddings and Elasticsearch
 ###############################################################################
@@ -188,6 +209,7 @@ llm_large = CustomMistralLLM(
     model_name="mistral-large-latest"
 )
 
+
 ###############################################################################
 # Request classification function: vyhladavanie vs. upresnenie
 ###############################################################################
@@ -213,6 +235,7 @@ def classify_query(query: str, chat_history: str = "") -> str:
         return "upresnenie"
     return "vyhladavanie"
 
+
 ###############################################################################
 # Template for upresnenie dopytu
 ###############################################################################
@@ -237,6 +260,7 @@ Upresňujúca otázka od používateľa:
 """
     return prompt
 
+
 ###############################################################################
 # Function for retrieving the last vyhladavacieho dopytu z histórie
 ###############################################################################
@@ -249,6 +273,7 @@ def extract_last_vyhladavacie_query(chat_history: str) -> str:
             break
     return last_query
 
+
 ###############################################################################
 # Agent class for data storage: vek, anamneza, predpis, user_data, search_query
 ###############################################################################
@@ -308,15 +333,16 @@ class ConversationalAgent:
     def ask_follow_up(self, missing_info: dict) -> str:
         return " ".join(missing_info.values())
 
+
 ###############################################################################
 # Main function process_query_with_mistral with updated logic
 ###############################################################################
 CHAT_HISTORY_ENDPOINT = "http://localhost:5000/api/chat_history_detail"
 
+
 def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10):
     logger.info("Processing query started.")
 
-
     chat_history = ""
     if chat_context:
         chat_history = chat_context
@@ -337,23 +363,18 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
         except Exception as e:
             logger.error(f"Chyba pri načítaní histórie: {e}")
 
-
     agent = ConversationalAgent()
     if chat_history:
         agent.load_memory_from_history(chat_history)
 
-
     existing_user_data = ""
     if chat_id:
         existing_user_data = get_user_data_from_db(chat_id)
 
-
     agent.parse_user_info(query)
     missing_info = agent.analyze_input(query)
 
-
     if not existing_user_data:
-
         if "Prosím, uveďte vek pacienta" in chat_history:
             if chat_id:
                 update_payload = {"chatId": chat_id, "userData": query}
@@ -388,19 +409,16 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
                 "patient_data": query
             }
 
-
     qtype = classify_query(query, chat_history)
     logger.info(f"Typ dopytu: {qtype}")
     logger.info(f"Chat context (snippet): {chat_history[:200]}...")
 
-
     if qtype == "vyhladavanie":
         user_data_db = get_user_data_from_db(chat_id)
         if user_data_db:
             query = query + " Udaje cloveka: " + user_data_db
         agent.long_term_memory["search_query"] = query
 
-
     if qtype == "upresnenie":
         original_search = agent.long_term_memory.get("search_query")
         if not original_search:
@@ -442,7 +460,8 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
             f"Otázka: {combined_query}\n\n"
             "Na základe týchto informácií:\n"
             f"{joined_docs}\n\n"
-            "Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné."
+            "Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné.\n"
+            "Prosím, odpovedaj stručne a dostatočne, bez nadmernej dĺžky."
         )
         ans_small = llm_small.generate_text(final_prompt, max_tokens=1200, temperature=0.7)
         ans_large = llm_large.generate_text(final_prompt, max_tokens=1200, temperature=0.7)
@@ -454,8 +473,32 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
             {"summary": val_small, "eval": eval_small, "model": "Mistral Small"},
             {"summary": val_large, "eval": eval_large, "model": "Mistral Large"},
         ]
+
+        #
+        # for candidate in candidates:
+        #     detailed_desc = detailed_evaluation_description(combined_query, candidate["summary"], candidate["eval"]["rating"])
+        #     candidate["eval"]["detailed_description"] = detailed_desc
+        #
+
+
         best = max(candidates, key=lambda x: x["eval"]["rating"])
         logger.info(f"Odpoveď od modelu {best['model']} má rating: {best['eval']['rating']}/10")
+
+
+        evaluation_table = "=== Výsledky hodnotenia odpovedí ===\n"
+        evaluation_table += "{:<15} | {:<6} | {:<60}\n".format("Model", "Rating", "Evaluated Text")
+        evaluation_table += "-" * 100 + "\n"
+        for candidate in candidates:
+            model_name = candidate["model"]
+            rating = candidate["eval"]["rating"]
+            evaluated_text = candidate["summary"].replace("\n", " ")
+            evaluation_table += "{:<15} | {:<6} | {:<60}\n".format(model_name, rating, evaluated_text)
+        evaluation_table += "=" * 100 + "\n"
+
+        # with open("evaluation.txt", "w", encoding="utf-8") as f:
+        #     f.write(evaluation_table)
+        # logger.info("Evaluation table записана в evaluation.txt")
+
         final_answer = translate_preserving_medicine_names(best["summary"])
         memory_json = json.dumps(agent.long_term_memory)
         memory_block = f"[MEMORY]{memory_json}[/MEMORY]"
@@ -467,7 +510,6 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
             "explanation": best["eval"]["explanation"]
         }
 
-
     vector_results = vectorstore.similarity_search(query, k=k)
     max_docs = 5
     max_len = 1000
@@ -484,7 +526,8 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
         f"Otázka: {query}\n\n"
         "Na základe týchto informácií:\n"
         f"{joined_docs}\n\n"
-        "Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné."
+        "Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné.\n"
+        "Prosím, odpovedaj stručne a dostatočne, bez nadmernej dĺžky."
     )
     answer = llm_small.generate_text(final_prompt, max_tokens=1200, temperature=0.7)
     memory_json = json.dumps(agent.long_term_memory)

Backend/tablepresent.py

@@ -0,0 +1,56 @@
+from pptx import Presentation
+from pptx.util import Inches
+
+# Создание новой презентации
+prs = Presentation()
+
+# Добавляем пустой слайд (layout с индексом 5 обычно является пустым)
+slide_layout = prs.slide_layouts[5]
+slide = prs.slides.add_slide(slide_layout)
+
+# Определяем позицию и размер таблицы
+left = Inches(0.5)
+top = Inches(1.5)
+width = Inches(9)
+height = Inches(3)
+
+# Количество строк: 1 заголовок + 2 строки с данными
+rows = 3
+cols = 4
+
+# Добавляем таблицу на слайд
+table = slide.shapes.add_table(rows, cols, left, top, width, height).table
+
+# Устанавливаем ширину столбцов (при необходимости можно настроить отдельно)
+table.columns[0].width = Inches(1.5)  # Модель
+table.columns[1].width = Inches(1)    # Оценка
+table.columns[2].width = Inches(4)    # Текст
+table.columns[3].width = Inches(2.5)  # Описание
+
+# Заполняем заголовки
+table.cell(0, 0).text = "Модель"
+table.cell(0, 1).text = "Оценка"
+table.cell(0, 2).text = "Текст"
+table.cell(0, 3).text = "Описание"
+
+# Данные для первого кандидата
+table.cell(1, 0).text = "Mistral Small"
+table.cell(1, 1).text = "9.0"
+table.cell(1, 2).text = (
+    "Nevolnosť môže byť spôsobená rôznymi príčinami, ako sú napríklad gastrointestinálne problémy, infekcie, alebo vedľajšie účinky liekov. "
+    "Pre ľudí, ktorí hľadajú voľnopredajný liek na nevolnosť, sú dostupné niekoľko možností: 1. Dimedrol (Dramin) – Antihistaminikum; "
+    "2. Bismut subsalicylát (Pepto-Bismol); 3. Ginger (Zázvor); 4. Meclizin (Bonine). Pred použitím lieku je dôležité konzultovať s lekárom."
+)
+table.cell(1, 3).text = "Evaluation based on required criteria."
+
+# Данные для второго кандидата
+table.cell(2, 0).text = "Mistral Large"
+table.cell(2, 1).text = "8.0"
+table.cell(2, 2).text = (
+    "Pre nevolnosť sa dajú použiť niektoré voľne predávané lieky, ale dôležité je poradiť sa s lekárom, najmä ak má pacient 20 rokov. "
+    "Medzi bežné voľne predávané lieky patria: 1. Dimenhydrinát; 2. Meclozín. Tieto lieky môžu spôsobiť spánkovosť a dávkovanie je nutné konzultovať."
+)
+table.cell(2, 3).text = "Evaluation based on required criteria."
+
+# Сохраняем презентацию в файл
+prs.save("evaluation_table.pptx")

prepare.sh

@@ -1,4 +1,5 @@
 #!/bin/bash
-echo "Подготовка окружения: сборка Docker образов..."
+echo "Prepearing Docker images..."
-docker-compose build
+docker-compose up --build
-echo "Подготовка завершена."
+
+echo "Preparation ended."