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Update app.py
Browse files
app.py
CHANGED
@@ -7,28 +7,23 @@ from sentence_transformers import SentenceTransformer
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import requests
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from langchain_community.vectorstores import Chroma
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from langchain_community.embeddings import HuggingFaceEmbeddings
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load_dotenv()
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URL_APP_SCRIPT = os.getenv('URL_APP_SCRIPT')
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SYSTEM_PROMPT = ["Sei BonsiAI e mi aiuterai nelle mie richieste (Parla in ITALIANO)", "Esatto, sono BonsiAI. Di cosa hai bisogno?"]
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'systemStyle': '
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'instruction':
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'
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'systemStyle': 'Sii molto formale, sintetico e parla in ITALIANO',
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'instruction': '',
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'RAG': True}
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}
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st.set_page_config(page_title="BonsiAI", page_icon="🤖")
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def init_state() :
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if "messages" not in st.session_state:
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@@ -52,25 +47,48 @@ def init_state() :
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if 'loaded_data' not in st.session_state:
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st.session_state.loaded_data = False
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if not st.session_state.loaded_data:
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with st.
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st.session_state.loaded_data = True
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def sidebar():
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def retrieval_settings() :
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st.markdown("# Impostazioni Prompt")
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st.session_state.selected_option_key = st.selectbox('Azione', list(st.session_state.options.keys())
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st.session_state.selected_option = st.session_state.options.get(st.session_state.selected_option_key, {})
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st.session_state.systemRole = st.session_state.selected_option.get('systemRole', '')
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st.session_state.systemRole = st.text_area("Descrizione", st.session_state.systemRole, help='Ruolo del chatbot e descrizione dell\'azione che deve svolgere')
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st.session_state.systemStyle = st.session_state.selected_option.get('systemStyle', '')
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st.session_state.systemStyle = st.text_area("Stile", st.session_state.systemStyle, help='Descrizione dello stile utilizzato per generare il testo')
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st.session_state.instruction = st.session_state.selected_option.get('instruction', '')
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#st.session_state.instruction = st.text_area("Istruzioni", st.session_state.instruction, help='Testo di riferimento sul quale il modello si basa per generare il testo')
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st.session_state.rag_enabled = st.session_state.selected_option.get('tipo', '')=='RAG'
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if st.session_state.selected_option_key == 'Decreti':
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st.session_state.top_k = st.slider(label="Documenti da ricercare", min_value=1, max_value=20, value=4, disabled=not st.session_state.rag_enabled)
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st.session_state.decreti_escludere = st.multiselect(
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@@ -81,9 +99,11 @@ def sidebar():
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def model_settings() :
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st.markdown("# Impostazioni Modello")
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st.session_state.chat_bot = st.sidebar.radio('
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st.session_state.temp = st.slider(label="Creatività", min_value=0.0, max_value=1.0, step=0.1, value=0.9)
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st.session_state.max_tokens = st.slider(label="Lunghezza Output", min_value = 64, max_value=2048, step= 32, value=1024)
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with st.sidebar:
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retrieval_settings()
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@@ -102,6 +122,12 @@ def chat_box() :
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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def formattaPrompt(prompt, systemRole, systemStyle, instruction):
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input_text = f'''
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{{
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@@ -140,29 +166,24 @@ def gen_augmented_prompt(prompt, top_k) :
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links.append((reference, testo))
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generated_prompt = f"""
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A PARTIRE DAL SEGUENTE CONTESTO: {docs},
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----
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RISPONDI ALLA SEGUENTE RICHIESTA: {prompt}
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"""
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return context, links
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def generate_chat_stream(prompt) :
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links = []
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prompt_originale = prompt
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if st.session_state.rag_enabled :
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with st.spinner("Ricerca nei Decreti...."):
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time.sleep(1)
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st.session_state.instruction, links = gen_augmented_prompt(prompt=prompt_originale, top_k=st.session_state.top_k)
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prompt = formattaPrompt(prompt, st.session_state.systemRole, st.session_state.systemStyle, st.session_state.instruction)
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print(prompt)
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with st.spinner("Generazione in corso...") :
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time.sleep(1)
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chat_stream = chat(prompt, st.session_state.history,chat_client=CHAT_BOTS[st.session_state.chat_bot] ,
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temperature=st.session_state.temp, max_new_tokens=st.session_state.max_tokens)
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return chat_stream, links
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def stream_handler(chat_stream, placeholder) :
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start_time = time.time()
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full_response = ''
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for chunk in chat_stream :
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if chunk.token.text!='</s>' :
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@@ -177,24 +198,49 @@ def show_source(links) :
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reference, testo = link
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st.info('##### ' + reference.replace('_', ' ') + '\n\n'+ testo)
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chat_stream, links = generate_chat_stream(prompt)
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import requests
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from langchain_community.vectorstores import Chroma
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from langchain_community.embeddings import HuggingFaceEmbeddings
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import json
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load_dotenv()
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URL_APP_SCRIPT = os.getenv('URL_APP_SCRIPT')
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URL_PROMPT = URL_APP_SCRIPT + '?IdFoglio=1cLw9q70BsPmxMBj9PIzgXtq6sm3X-GVBVnOB5wE8jr8'
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URL_DOCUMENTI = URL_APP_SCRIPT + '?IdSecondoFoglio=1cLw9q70BsPmxMBj9PIzgXtq6sm3X-GVBVnOB5wE8jr8'
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SYSTEM_PROMPT = ["Sei BonsiAI e mi aiuterai nelle mie richieste (Parla in ITALIANO)", "Esatto, sono BonsiAI. Di cosa hai bisogno?"]
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CHAT_BOTS = {"Mixtral 8x7B v0.1" :"mistralai/Mixtral-8x7B-Instruct-v0.1"}
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option_personalizzata = {'Personalizzata': {'systemRole': 'Tu sei BONSI AI, il mio assistente personale della scuola superiore del Bonsignori. Aiutami in base alle mie esigenze',
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'systemStyle': 'Firmati sempre come BONSI AI. (scrivi in italiano)',
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'instruction': '',
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'tipo': '',
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'RAG': False}
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}
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# ----------------------------------------------------------- Interfaccia --------------------------------------------------------------------
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st.set_page_config(page_title="Bonsi AI", page_icon="🏫")
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def init_state() :
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if "messages" not in st.session_state:
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if 'loaded_data' not in st.session_state:
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st.session_state.loaded_data = False
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if "split" not in st.session_state:
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st.session_state.split = 30
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if "enable_history" not in st.session_state:
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st.session_state.enable_history = False
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if "numero_generazioni" not in st.session_state:
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st.session_state.numero_generazioni = 1
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if not st.session_state.loaded_data:
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with st.status("Caricamento in corso...", expanded=True) as status:
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st.write("Inizializzazione Ambiente")
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time.sleep(1)
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st.write("Inizializzazione Prompt")
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options = requests.get(URL_PROMPT).json()
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st.write("Inizializzazione Documenti")
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documenti = requests.get(URL_DOCUMENTI).json()
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st.session_state.options = {**option_personalizzata, **options}
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st.session_state.documenti = documenti
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st.session_state.loaded_data = True
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status.update(label="Caricamento Completato", state="complete", expanded=False)
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def sidebar():
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def retrieval_settings() :
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st.markdown("# Impostazioni Prompt")
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st.session_state.selected_option_key = st.selectbox('Azione', list(st.session_state.options.keys()))
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st.session_state.selected_option = st.session_state.options.get(st.session_state.selected_option_key, {})
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if st.session_state.options.get(st.session_state.selected_option_key, {})["tipo"]=='DOCUMENTO':
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st.session_state.selected_documento_key = st.selectbox('Documento', list(st.session_state.documenti.keys()))
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st.session_state.selected_documento = st.session_state.documenti.get(st.session_state.selected_documento_key, {})
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st.session_state.instruction = st.session_state.selected_documento.get('instruction', '')['Testo']
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st.session_state.split = st.slider(label="Pagine Suddivisione", min_value=1, max_value=30, value=30, help='Se il documento ha 100 pagine e suddivido per 20 pagine elaborerà la risposta 5 volte. Più alto è il numero e meno volte elaborerà ma la risposta sarà più imprecisa')
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else:
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st.session_state.instruction = st.session_state.selected_option.get('instruction', '')
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st.session_state.systemRole = st.session_state.selected_option.get('systemRole', '')
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st.session_state.systemRole = st.text_area("Descrizione", st.session_state.systemRole, help='Ruolo del chatbot e descrizione dell\'azione che deve svolgere')
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st.session_state.systemStyle = st.session_state.selected_option.get('systemStyle', '')
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st.session_state.systemStyle = st.text_area("Stile", st.session_state.systemStyle, help='Descrizione dello stile utilizzato per generare il testo')
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st.session_state.rag_enabled = st.session_state.selected_option.get('tipo', '')=='RAG'
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if st.session_state.selected_option_key == 'Decreti':
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st.session_state.top_k = st.slider(label="Documenti da ricercare", min_value=1, max_value=20, value=4, disabled=not st.session_state.rag_enabled)
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st.session_state.decreti_escludere = st.multiselect(
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def model_settings() :
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st.markdown("# Impostazioni Modello")
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st.session_state.chat_bot = st.sidebar.radio('Modello:', [key for key, value in CHAT_BOTS.items() ])
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st.session_state.numero_generazioni = st.slider(label="Generazioni", min_value = 1, max_value=10, value=1)
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st.session_state.temp = st.slider(label="Creatività", min_value=0.0, max_value=1.0, step=0.1, value=0.9)
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st.session_state.max_tokens = st.slider(label="Lunghezza Output", min_value = 64, max_value=2048, step= 32, value=1024)
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st.session_state.enable_history = st.toggle("Storico Messaggi", value=False)
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with st.sidebar:
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retrieval_settings()
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with st.chat_message(message["role"]):
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st.markdown(message["content"])
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init_state()
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sidebar()
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header()
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chat_box()
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# ----------------------------------------------------------- Funzioni Varie --------------------------------------------------------------------
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def formattaPrompt(prompt, systemRole, systemStyle, instruction):
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input_text = f'''
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{{
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links.append((reference, testo))
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generated_prompt = f"""
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A PARTIRE DAL SEGUENTE CONTESTO: {docs},
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----
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RISPONDI ALLA SEGUENTE RICHIESTA: {prompt}
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"""
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return context, links
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def generate_chat_stream(prompt, prompt_originale, inst) :
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links = []
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if st.session_state.rag_enabled :
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with st.spinner("Ricerca nei Decreti...."):
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time.sleep(1)
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st.session_state.instruction, links = gen_augmented_prompt(prompt=prompt_originale, top_k=st.session_state.top_k)
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with st.spinner("Generazione in corso...") :
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time.sleep(1)
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chat_stream = chat(prompt, st.session_state.history,chat_client=CHAT_BOTS[st.session_state.chat_bot] ,
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temperature=st.session_state.temp, max_new_tokens=st.session_state.max_tokens)
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return chat_stream, links, inst
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def stream_handler(chat_stream, placeholder) :
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full_response = ''
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for chunk in chat_stream :
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if chunk.token.text!='</s>' :
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reference, testo = link
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st.info('##### ' + reference.replace('_', ' ') + '\n\n'+ testo)
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def split_text(text, chunk_size):
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testo_suddiviso = []
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if text == '':
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text = ' '
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if chunk_size < 100:
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chunk_size = 60000
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for i in range(0, len(text), chunk_size):
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testo_suddiviso.append(text[i:i+chunk_size])
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return testo_suddiviso
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# -------------------------------------------------------------- Gestione Chat -----------------------------------------------------------------------
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if prompt := st.chat_input("Chatta con BonsiAI..."):
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instruction_suddivise = split_text(st.session_state.instruction, st.session_state.split*2000)
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prompt_originale = prompt
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ruolo_originale = st.session_state.systemRole
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ruoli_divisi = ruolo_originale.split("&&")
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parte = 1
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i = 1
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risposta_completa = ''
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for ruolo_singolo in ruoli_divisi:
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for instruction_singola in instruction_suddivise:
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for numgen in range(1, st.session_state.numero_generazioni+1):
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prompt = formattaPrompt(prompt_originale, ruolo_singolo, st.session_state.systemStyle, instruction_singola)
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if i==1:
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st.chat_message("user").markdown(prompt_originale + (': Parte ' + str(parte) if i > 1 else ''))
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i+=1
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st.session_state.messages.append({"role": "user", "content": prompt_originale})
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chat_stream, links, inst = generate_chat_stream(prompt, prompt_originale, instruction_singola)
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with st.chat_message("assistant"):
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placeholder = st.empty()
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full_response = stream_handler(chat_stream, placeholder)
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if st.session_state.rag_enabled:
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show_source(links)
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if st.session_state.options.get(st.session_state.selected_option_key, {})["tipo"]=='DOCUMENTO':
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with st.expander("Mostra Documento") :
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st.info('##### ' + st.session_state.selected_documento_key + ' (Parte ' + str(parte) +')'+ '\n\n\n' + inst)
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parte+=1
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st.session_state.messages.append({"role": "assistant", "content": full_response})
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risposta_completa = risposta_completa + '\n' + full_response
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if st.session_state.enable_history:
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st.session_state.history.append([prompt, full_response])
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st.success('Generazione Completata')
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payload = {"domanda": prompt_originale, "risposta": risposta_completa}
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json_payload = json.dumps(payload)
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response = requests.post(URL_APP_SCRIPT, data=json_payload)
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