upd docker prepare script
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Backend/arch.py
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122
Backend/arch.py
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from pptx import Presentation
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from pptx.util import Inches
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from pptx.enum.shapes import MSO_AUTO_SHAPE_TYPE, MSO_CONNECTOR
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# Vytvorenie novej prezentácie
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prs = Presentation()
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slide_layout = prs.slide_layouts[5] # Prázdny slide
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slide = prs.slides.add_slide(slide_layout)
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# Definícia základných rozmerov a pozícií
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left_margin = Inches(0.5)
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top_margin = Inches(0.5)
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block_width = Inches(3)
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block_height = Inches(0.7)
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vertical_gap = Inches(0.3)
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horizontal_gap = Inches(0.5)
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# Blok 1: Používateľský dotaz & Chat history
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box1 = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, top_margin, block_width, block_height)
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box1.text = "Používateľský dotaz\n& Chat history"
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# Blok 2: ConversationalAgent (pod box1)
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box2_top = top_margin + block_height + vertical_gap
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box2 = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, box2_top, block_width, block_height)
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box2.text = "ConversationalAgent"
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# Blok 3: Klasifikácia dotazu (pod box2)
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box3_top = box2_top + block_height + vertical_gap
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box3 = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, box3_top, block_width, block_height)
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box3.text = "Klasifikácia dotazu"
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# Vetvenie: Pozície pre dve vetvy
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branch_top = box3_top + block_height + vertical_gap
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# Ľavá vetva ("Vyhladavanie")
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left_branch_left = left_margin - Inches(0.2)
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box4A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, branch_top, block_width, block_height)
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box4A.text = "ElasticsearchStore\nvyhľadávanie"
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box5A_top = branch_top + block_height + vertical_gap
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box5A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, box5A_top, block_width, block_height)
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box5A.text = "Generovanie\ndynamického promptu"
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box6A_top = box5A_top + block_height + vertical_gap
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box6A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, box6A_top, block_width, block_height)
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box6A.text = "Generovanie\nodpovede"
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box7A_top = box6A_top + block_height + vertical_gap
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box7A = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_branch_left, box7A_top, block_width, block_height)
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box7A.text = "Finalizácia\nodpovede"
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# Pravá vetva ("Upresnenie")
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right_branch_left = left_margin + block_width + horizontal_gap
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box4B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, branch_top, block_width, block_height)
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box4B.text = "Kombinovanie\ndotazov"
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box5B_top = branch_top + block_height + vertical_gap
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box5B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box5B_top, block_width, block_height)
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box5B.text = "ElasticsearchStore\nvyhľadávanie"
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box6B_top = box5B_top + block_height + vertical_gap
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box6B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box6B_top, block_width, block_height)
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box6B.text = "Generovanie\ndynamického promptu"
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box7B_top = box6B_top + block_height + vertical_gap
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box7B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box7B_top, block_width, block_height)
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box7B.text = "Generovanie\nodpovedí (2 modely)"
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box8B_top = box7B_top + block_height + vertical_gap
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box8B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box8B_top, block_width, block_height)
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box8B.text = "Validácia a\nhodnotenie odpovedí"
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box9B_top = box8B_top + block_height + vertical_gap
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box9B = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, right_branch_left, box9B_top, block_width, block_height)
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box9B.text = "Finalizácia\nodpovede"
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# Finálny blok: Výstup (zlúčenie vetiev)
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final_box_top = max(box7A_top, box9B_top) + block_height + vertical_gap
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final_box = slide.shapes.add_shape(MSO_AUTO_SHAPE_TYPE.RECTANGLE, left_margin, final_box_top, block_width, block_height)
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final_box.text = "Výstup"
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# Funkcia na pridanie šípok medzi blokmi
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def add_connector(slide, start_shape, end_shape):
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start_x = start_shape.left + start_shape.width / 2
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start_y = start_shape.top + start_shape.height
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end_x = end_shape.left + end_shape.width / 2
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end_y = end_shape.top
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connector = slide.shapes.add_connector(MSO_CONNECTOR.STRAIGHT, start_x, start_y, end_x, end_y)
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# Aktuálna verzia python-pptx nepodporuje nastavenie šípky, preto tento riadok odstraňte alebo zakomentujte:
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# connector.line.end_arrowhead.style = 1
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return connector
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# Prepojenie blokov
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add_connector(slide, box1, box2)
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add_connector(slide, box2, box3)
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# Vetvenie z Box3 do oboch vetiev
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mid_point = box3.left + box3.width / 2
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branch_mid_y = box3.top + box3.height + vertical_gap/2
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# Do ľavej vetvy:
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connector_left = slide.shapes.add_connector(MSO_CONNECTOR.STRAIGHT, mid_point, box3.top + box3.height, left_branch_left + block_width/2, branch_mid_y)
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# Do pravej vetvy:
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connector_right = slide.shapes.add_connector(MSO_CONNECTOR.STRAIGHT, mid_point, box3.top + box3.height, right_branch_left + block_width/2, branch_mid_y)
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# Prepojenie blokov v ľavej vetve
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add_connector(slide, box4A, box5A)
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add_connector(slide, box5A, box6A)
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add_connector(slide, box6A, box7A)
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# Prepojenie blokov v pravej vetve
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add_connector(slide, box4B, box5B)
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add_connector(slide, box5B, box6B)
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add_connector(slide, box6B, box7B)
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add_connector(slide, box7B, box8B)
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add_connector(slide, box8B, box9B)
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# Spojenie oboch vetiev s finálnym blokom "Výstup"
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add_connector(slide, box7A, final_box)
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add_connector(slide, box9B, final_box)
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# Uloženie prezentácie
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prs.save("architecture_diagram.pptx")
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@ -14,7 +14,6 @@ from psycopg2.extras import RealDictCursor
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logging.basicConfig(level=logging.INFO)
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logger = logging.getLogger(__name__)
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config_file_path = "config.json"
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with open(config_file_path, 'r') as config_file:
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config = json.load(config_file)
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@ -23,15 +22,18 @@ mistral_api_key = "hXDC4RBJk1qy5pOlrgr01GtOlmyCBaNs"
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if not mistral_api_key:
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raise ValueError("Mistral API key not found in configuration.")
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###############################################################################
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# Simple functions for translation (stub)
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###############################################################################
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def translate_to_slovak(text: str) -> str:
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return text
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def translate_preserving_medicine_names(text: str) -> str:
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return text
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###############################################################################
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# Function for evaluating the completeness of the answer
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###############################################################################
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@ -53,6 +55,7 @@ def evaluate_complete_answer(query: str, answer: str) -> dict:
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score = 0.0
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return {"rating": round(score, 2), "explanation": "Evaluation based on required criteria."}
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###############################################################################
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# Function for validating the response logic
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###############################################################################
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@ -73,6 +76,7 @@ def validate_answer_logic(query: str, answer: str) -> str:
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logger.error(f"Error during answer validation: {e}")
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return answer
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###############################################################################
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# Function for creating a dynamic prompt with information from documents
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###############################################################################
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@ -91,6 +95,7 @@ def build_dynamic_prompt(query: str, documents: list) -> str:
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)
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return prompt
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###############################################################################
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# Function to get user data from the database via endpoint /api/get_user_data
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###############################################################################
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@ -106,6 +111,7 @@ def get_user_data_from_db(chat_id: str) -> str:
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logger.error(f"Error retrieving user_data from DB: {e}", exc_info=True)
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return ""
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###############################################################################
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# Class for calling Mistral LLM
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###############################################################################
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@ -147,6 +153,21 @@ class CustomMistralLLM:
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raise ex
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raise Exception("Reached maximum number of retries for API request")
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###############################################################################
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# Function for generating a detailed evaluation description
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###############################################################################
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# def detailed_evaluation_description(query: str, answer: str, rating: float) -> str:
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# prompt = (
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# f"Podrobne opíš, prečo odpoveď: '{answer}' na otázku: '{query}' dosiahla hodnotenie {rating} zo 10. "
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# "Uveď relevantné aspekty, ktoré ovplyvnili toto hodnotenie, vrátane úplnosti, presnosti a kvality vysvetlenia."
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# )
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# description = llm_small.generate_text(prompt=prompt, max_tokens=150, temperature=0.5)
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# return description.strip()
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#
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# Ak chcete vidieť podrobné hodnotenie, odkomentujte funkciu detailed_evaluation_description a príslušné časti kódu.
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###############################################################################
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# Initialisation of Embeddings and Elasticsearch
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###############################################################################
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@ -188,6 +209,7 @@ llm_large = CustomMistralLLM(
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model_name="mistral-large-latest"
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)
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###############################################################################
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# Request classification function: vyhladavanie vs. upresnenie
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###############################################################################
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@ -213,6 +235,7 @@ def classify_query(query: str, chat_history: str = "") -> str:
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return "upresnenie"
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return "vyhladavanie"
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###############################################################################
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# Template for upresnenie dopytu
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###############################################################################
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@ -237,6 +260,7 @@ Upresňujúca otázka od používateľa:
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"""
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return prompt
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###############################################################################
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# Function for retrieving the last vyhladavacieho dopytu z histórie
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###############################################################################
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@ -249,6 +273,7 @@ def extract_last_vyhladavacie_query(chat_history: str) -> str:
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break
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return last_query
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###############################################################################
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# Agent class for data storage: vek, anamneza, predpis, user_data, search_query
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###############################################################################
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@ -308,15 +333,16 @@ class ConversationalAgent:
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def ask_follow_up(self, missing_info: dict) -> str:
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return " ".join(missing_info.values())
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###############################################################################
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# Main function process_query_with_mistral with updated logic
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###############################################################################
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CHAT_HISTORY_ENDPOINT = "http://localhost:5000/api/chat_history_detail"
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def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10):
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logger.info("Processing query started.")
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chat_history = ""
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if chat_context:
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chat_history = chat_context
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@ -337,23 +363,18 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
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except Exception as e:
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logger.error(f"Chyba pri načítaní histórie: {e}")
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agent = ConversationalAgent()
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if chat_history:
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agent.load_memory_from_history(chat_history)
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existing_user_data = ""
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if chat_id:
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existing_user_data = get_user_data_from_db(chat_id)
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agent.parse_user_info(query)
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missing_info = agent.analyze_input(query)
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if not existing_user_data:
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if "Prosím, uveďte vek pacienta" in chat_history:
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if chat_id:
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update_payload = {"chatId": chat_id, "userData": query}
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@ -388,19 +409,16 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
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"patient_data": query
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}
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qtype = classify_query(query, chat_history)
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logger.info(f"Typ dopytu: {qtype}")
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logger.info(f"Chat context (snippet): {chat_history[:200]}...")
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if qtype == "vyhladavanie":
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user_data_db = get_user_data_from_db(chat_id)
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if user_data_db:
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query = query + " Udaje cloveka: " + user_data_db
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agent.long_term_memory["search_query"] = query
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if qtype == "upresnenie":
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original_search = agent.long_term_memory.get("search_query")
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if not original_search:
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@ -442,7 +460,8 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
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f"Otázka: {combined_query}\n\n"
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"Na základe týchto informácií:\n"
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f"{joined_docs}\n\n"
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"Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné."
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"Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné.\n"
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"Prosím, odpovedaj stručne a dostatočne, bez nadmernej dĺžky."
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)
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ans_small = llm_small.generate_text(final_prompt, max_tokens=1200, temperature=0.7)
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ans_large = llm_large.generate_text(final_prompt, max_tokens=1200, temperature=0.7)
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@ -454,8 +473,32 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
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{"summary": val_small, "eval": eval_small, "model": "Mistral Small"},
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{"summary": val_large, "eval": eval_large, "model": "Mistral Large"},
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]
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#
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# for candidate in candidates:
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# detailed_desc = detailed_evaluation_description(combined_query, candidate["summary"], candidate["eval"]["rating"])
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# candidate["eval"]["detailed_description"] = detailed_desc
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#
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best = max(candidates, key=lambda x: x["eval"]["rating"])
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logger.info(f"Odpoveď od modelu {best['model']} má rating: {best['eval']['rating']}/10")
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evaluation_table = "=== Výsledky hodnotenia odpovedí ===\n"
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evaluation_table += "{:<15} | {:<6} | {:<60}\n".format("Model", "Rating", "Evaluated Text")
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evaluation_table += "-" * 100 + "\n"
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for candidate in candidates:
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model_name = candidate["model"]
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rating = candidate["eval"]["rating"]
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evaluated_text = candidate["summary"].replace("\n", " ")
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evaluation_table += "{:<15} | {:<6} | {:<60}\n".format(model_name, rating, evaluated_text)
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evaluation_table += "=" * 100 + "\n"
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# with open("evaluation.txt", "w", encoding="utf-8") as f:
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# f.write(evaluation_table)
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# logger.info("Evaluation table записана в evaluation.txt")
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final_answer = translate_preserving_medicine_names(best["summary"])
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memory_json = json.dumps(agent.long_term_memory)
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memory_block = f"[MEMORY]{memory_json}[/MEMORY]"
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@ -467,7 +510,6 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
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"explanation": best["eval"]["explanation"]
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}
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vector_results = vectorstore.similarity_search(query, k=k)
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max_docs = 5
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max_len = 1000
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@ -484,7 +526,8 @@ def process_query_with_mistral(query: str, chat_id: str, chat_context: str, k=10
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f"Otázka: {query}\n\n"
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"Na základe týchto informácií:\n"
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f"{joined_docs}\n\n"
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"Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné."
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"Vygeneruj odporúčanie liekov alebo vysvetlenie, ak je to relevantné.\n"
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"Prosím, odpovedaj stručne a dostatočne, bez nadmernej dĺžky."
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)
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answer = llm_small.generate_text(final_prompt, max_tokens=1200, temperature=0.7)
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memory_json = json.dumps(agent.long_term_memory)
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56
Backend/tablepresent.py
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56
Backend/tablepresent.py
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from pptx import Presentation
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from pptx.util import Inches
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# Создание новой презентации
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prs = Presentation()
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# Добавляем пустой слайд (layout с индексом 5 обычно является пустым)
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slide_layout = prs.slide_layouts[5]
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slide = prs.slides.add_slide(slide_layout)
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# Определяем позицию и размер таблицы
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left = Inches(0.5)
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top = Inches(1.5)
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width = Inches(9)
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height = Inches(3)
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# Количество строк: 1 заголовок + 2 строки с данными
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rows = 3
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cols = 4
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# Добавляем таблицу на слайд
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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")
|
||||
@ -1,4 +1,5 @@
|
||||
#!/bin/bash
|
||||
echo "Подготовка окружения: сборка Docker образов..."
|
||||
docker-compose build
|
||||
echo "Подготовка завершена."
|
||||
echo "Prepearing Docker images..."
|
||||
docker-compose up --build
|
||||
|
||||
echo "Preparation ended."
|
||||
|
||||
Loading…
Reference in New Issue
Block a user