Pierwsze wersje plików.
Browse files- app.py +55 -0
- praca.pkl +3 -0
- requirements.txt +3 -0
app.py
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import pickle
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import numpy as np
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from sentence_transformers import SentenceTransformer
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from scipy.spatial.distance import cosine
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import gradio as gr
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from openai import OpenAI
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client=OpenAI()
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model = SentenceTransformer("quanthome/paraphrase-multilingual-MiniLM-L12-v2")
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# Funkcja do znajdowania najbardziej podobnych tekstów
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def find_similar(text, vector_map, model, top_n=5):
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query_embedding = model.encode([text])[0]
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similarities = []
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for key, embedding in vector_map.items():
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similarity = 1 - cosine(query_embedding, embedding) # 1 - cosine distance gives similarity
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similarities.append((key, similarity))
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# Sortowanie po podobieństwie malejąco
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similarities = sorted(similarities, key=lambda x: x[1], reverse=True)
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return similarities[:top_n]
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# Odczytanie słownika z pliku
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with open('praca.pkl', 'rb') as f:
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vector_map = pickle.load(f)
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def szukaj(query_text, history):
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top_n_results = find_similar(query_text, vector_map, model, top_n=1)
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context=''
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for text, similarity in top_n_results:
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context=context+text
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agata=client.chat.completions.create(
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model='gpt-4o',
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temperature=0.1,
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max_tokens=1024,
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messages=[
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{'role': 'system',
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'content': 'Nazywasz się Agata Gawska i jesteś ekspertką do spraw zatrudniania i aktywizacji zawodowej osób z niepełnosprawnością. Odpowiadasz konkretnie na pytania.'+context},
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{'role': 'user',
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'content': query_text}
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]
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)
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return agata.choices[0].message.content
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demo=gr.ChatInterface(
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fn=szukaj,
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theme=gr.themes.Glass(font='OpenSans'),
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title='Agata',
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description='Twoja doradczyni w zatrudnianiu osób z niepełnosprawnościami.',
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submit_btn='Zapytaj',
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clear_btn='Wyczyść',
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retry_btn=None,
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undo_btn=None,
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show_progress='minimal',
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).launch(show_api=False, inbrowser=True)
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praca.pkl
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version https://git-lfs.github.com/spec/v1
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oid sha256:679412f31e5d37910fe973e45c965b88b804b5c047edce82a441307c14e1a75e
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size 166608
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requirements.txt
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sentence-transformers
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openai
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scipy
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