Spaces:
Runtime error
Runtime error
File size: 27,967 Bytes
b8ae371 a15fbb1 00572b2 bcbe1f2 00572b2 ea94315 b8ae371 a15fbb1 b8ae371 a15fbb1 281b59a a15fbb1 281b59a a15fbb1 98ed31f a15fbb1 5747ecd 28a124d 8980a48 5747ecd ea94315 724e446 5747ecd ea94315 e2eaf2f a15fbb1 e2eaf2f a15fbb1 00572b2 a15fbb1 4b2f203 a15fbb1 ead8a4a a15fbb1 ef09d22 a15fbb1 e2eaf2f a15fbb1 4b2f203 a15fbb1 059817f a15fbb1 e2eaf2f a15fbb1 e2eaf2f a15fbb1 e2eaf2f a15fbb1 e2eaf2f a15fbb1 34783b1 a15fbb1 4b2f203 a15fbb1 062b368 a15fbb1 e2eaf2f a15fbb1 e2eaf2f a15fbb1 30884e8 a15fbb1 dc2152e e2eaf2f cfc27ff e2eaf2f 6ea21bf e2eaf2f a88ab04 e2eaf2f 28a124d 98ed31f e2eaf2f 98ed31f e2eaf2f 30884e8 e2eaf2f a15fbb1 ea82e78 2f7a54a 86006ff a15fbb1 e751767 a15fbb1 5db5929 2d55fc9 b4e2f36 c4855d0 a15fbb1 8726db8 a15fbb1 5db5929 2d55fc9 b4e2f36 c4855d0 985d183 c4855d0 0a75d62 a15fbb1 c4855d0 a15fbb1 e751767 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d a3705d0 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 18e747d 00572b2 49cabbd 18e747d 30bcbc0 18e747d 30bcbc0 18e747d 55ea49d c4855d0 55ea49d a15fbb1 c4855d0 bd623ee c4855d0 bd623ee a15fbb1 c4855d0 a15fbb1 5db5929 2d55fc9 b4e2f36 c4855d0 b9fb0e1 c4855d0 a15fbb1 c4855d0 a15fbb1 724e446 3112302 e14a22a 2f7a54a e14a22a b3740a9 e2eaf2f dc2152e a15fbb1 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469 470 471 472 473 474 475 476 477 478 479 480 481 482 483 484 485 486 487 488 489 490 491 492 493 494 495 496 497 498 499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515 516 517 518 519 520 521 522 523 524 525 526 527 528 529 530 531 532 533 534 535 536 537 538 539 540 541 542 543 544 545 546 547 548 549 550 551 552 553 554 555 556 557 558 559 560 561 562 563 564 565 566 567 568 569 570 571 572 573 574 575 576 577 578 579 580 581 582 583 584 585 586 587 588 589 590 591 592 593 594 595 596 597 598 599 |
import gradio as gr
from llama_index.core import VectorStoreIndex,StorageContext
from llama_index.core.memory import ChatMemoryBuffer
import re
from llama_index.core import get_response_synthesizer
from llama_index.core.query_engine import RetrieverQueryEngine
# Retrievers
from llama_index.core.retrievers import (
VectorIndexRetriever,
)
from llama_index.core.chat_engine import ContextChatEngine
from llama_index.core.memory import ChatMemoryBuffer
from pinecone import Pinecone
from llama_index.vector_stores.pinecone import PineconeVectorStore
import time
from utils import *
import spaces
import threading
import sys
import torch
from llama_index.core.vector_stores import (
MetadataFilter,
MetadataFilters,
FilterOperator,
FilterCondition,
)
head = """
<link href="https://cdn.jsdelivr.net/npm/[email protected]/dist/css/bootstrap.min.css" rel="stylesheet" integrity="sha384-QWTKZyjpPEjISv5WaRU9OFeRpok6YctnYmDr5pNlyT2bRjXh0JMhjY6hW+ALEwIH" crossorigin="anonymous">
<script>
// JavaScript function to toggle text visibility
function toggleText(id){
console.log(id)
if(id=="span1"){
nodo_id = "nodo1"
}else if(id=="span2"){
nodo_id = "nodo2"
}else if(id=="span3"){
nodo_id = "nodo3"
}else{
nodo_id = "nodo4"
}
var text = document.getElementById(nodo_id);
if (text.style.display === "none") {
text.style.display = "block";
} else {
text.style.display = "none";
}
}
</script>
"""
css = """
#chatbot {
margin-top: 1%;
width: 75%;
position:relative;
height:70%;
}
#textBox{
width: 75%;
position:relative;
}
.wrapper.svelte-nab2ao p{
font-size: 14px;
}
#btnClear{
width: 75%;
}
#buttonChat{
width:50%;
position: relative;
}
#colonnaElementi{
position: absolute;
left: 77%;
top: 10%;
bottom: 10%; /* Adjust this value as necessary */
width: 10%;
height: auto; /* Let the height be determined by the top and bottom properties */
max-height: 80%; /* Ensure it does not exceed 80% of the parent container's height */
overflow-y: auto; /* Allow scrolling if content overflows vertically */
overflow-x: hidden; /* Hide horizontal overflow */
word-wrap: break-word; /* Ensure words break to fit within the width */
box-sizing: border-box; /* Include padding and border in the element's total width and height */
}
#responseMode{
width: 5%;
}
.message.user.svelte-gutj6d.message-bubble-border{
padding: 5px;
}
.message.bot.svelte-gutj6d.message-bubble-border{
padding: 5px;
}
.icon {
cursor: pointer;
}
/* Style for the hidden text */
.hidden-text {
display: none;
}
.wrap svelte-1sk0pyu{
width: 12%
}
"""
user_message=""
current_chat_mode=""
current_response_mode="tree_summarize"
current_collection="BANDI_SISTEMA_PUGLIA"
file_path=""
num_responses=0
current_chat_mode="STANDARD"
retriever=None
token_count_bandi=0
token_count_bandi_sistema_puglia=0
chat_engine_bandi=None
chat_engine_bandi_sistema_puglia=None
memory_bandi=None
memory_bandi_sistema_puglia=None
stream_response=None
divDocumenti=None
llm = None
def main():
global llm
setGPU()
llm = setLLM()
Settings.llm = llm
Settings.embed_model = "local:google-bert/bert-base-multilingual-cased"
embed_model = Settings.embed_model
text_qa_template, refine_template = setPromptTemplate()
def select_initial_collection():
global current_collection
global retriever
global index
pc = Pinecone(api_key="7e412663-a2dc-44a6-ab57-25dd0bdce226")
# connect to index
pinecone_index = pc.Index("indexbandisistemapuglia")
vector_store = PineconeVectorStore(
pinecone_index=pinecone_index,
add_sparse_vector=True,
)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_vector_store(
vector_store, storage_context=storage_context
)
retriever = VectorIndexRetriever(index=index, similarity_top_k=3, vector_store_query_mode="hybrid", embed_model=embed_model, alpha=0.5)
current_collection = "BANDI_SISTEMA_PUGLIA"
return "collezione settata"
select_initial_collection()
def select_collection(evt: gr.SelectData):
global current_collection
global retriever
global chat_engine_bandi
global chat_engine_bandi_sistema_puglia
global token_count_bandi
global token_count_bandi_sistema_puglia
global memory_bandi
global memory_bandi_sistema_puglia
selected_collection = evt.value
if(selected_collection != current_collection):
if(selected_collection == "BANDI_SISTEMA_PUGLIA"):
chat_engine_bandi.reset()
chat_engine_bandi_sistema_puglia.reset()
memory_bandi_sistema_puglia.reset()
memory_bandi.reset()
token_count_bandi = 0
token_count_bandi_sistema_puglia = 0
pc = Pinecone(api_key="7e412663-a2dc-44a6-ab57-25dd0bdce226")
# connect to index
pinecone_index = pc.Index("indexbandisistemapuglia")
vector_store = PineconeVectorStore(
pinecone_index=pinecone_index,
add_sparse_vector=True,
)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
# load your index from stored vectors
index = VectorStoreIndex.from_vector_store(
vector_store, storage_context=storage_context
)
retriever = VectorIndexRetriever(index=index, similarity_top_k=3, vector_store_query_mode="hybrid", embed_model=embed_model, alpha=0.5)
else:
chat_engine_bandi.reset()
chat_engine_bandi_sistema_puglia.reset()
memory_bandi_sistema_puglia.reset()
memory_bandi.reset()
token_count_bandi = 0
token_count_bandi_sistema_puglia = 0
pc = Pinecone(api_key="7e412663-a2dc-44a6-ab57-25dd0bdce226")
# connect to index
pinecone_index = pc.Index("indexbandi")
vector_store = PineconeVectorStore(
pinecone_index=pinecone_index,
add_sparse_vector=True,
)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
# load your index from stored vectors
index = VectorStoreIndex.from_vector_store(
vector_store, storage_context=storage_context
)
retriever = VectorIndexRetriever(index=index, similarity_top_k=3, vector_store_query_mode="hybrid", embed_model=embed_model, alpha=0.4)
current_collection = selected_collection
return "<div class='alert alert-success' role='alert'> Collezione "+selected_collection+" selezionata </div>"
def select_response_mode(evt: gr.SelectData):
global current_response_mode
current_response_mode = evt.value
return "<div class='alert alert-success' role='alert'>"+current_response_mode+" selezionato </div>"
def select_chat_mode():
global current_chat_mode
global memory_bandi
global memory_bandi_sistema_puglia
global chat_engine_bandi
global chat_engine_bandi_sistema_puglia
global token_count_bandi
global token_count_bandi_sistema_puglia
memory_bandi_sistema_puglia.reset()
memory_bandi.reset()
chat_engine_bandi.reset()
chat_engine_bandi_sistema_puglia.reset()
token_count_bandi = 0
token_count_bandi_sistema_puglia = 0
current_chat_mode = "CHAT"
return "<div class='alert alert-success' role='alert'>Hai selezionato la modalità "+current_chat_mode+" </div>"
def select_standard_mode():
global current_chat_mode
current_chat_mode = "STANDARD"
return "<div class='alert alert-success' role='alert'>Hai selezionato la modalità "+current_chat_mode+" </div>"
def set_chat_engine():
global chat_engine_bandi
global chat_engine_bandi_sistema_puglia
global memory_bandi
global memory_bandi_sistema_puglia
global token_count_bandi_sistema_puglia
global token_count_bandi
memory_bandi = ChatMemoryBuffer.from_defaults(token_limit=5000)
memory_bandi_sistema_puglia = ChatMemoryBuffer.from_defaults(token_limit=3000)
pc = Pinecone(api_key="7e412663-a2dc-44a6-ab57-25dd0bdce226")
pinecone_index = pc.Index("indexbandi")
vector_store = PineconeVectorStore(
pinecone_index=pinecone_index,
add_sparse_vector=True,
)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_vector_store(
vector_store, storage_context=storage_context
)
retriever_bandi = VectorIndexRetriever(index=index, similarity_top_k=3, vector_store_query_mode="hybrid", embed_model=embed_model, alpha=0.4)
chat_engine_bandi = ContextChatEngine(retriever=retriever_bandi,
context_template="Sei un chatbot in grado di rispondere alle domande su bandi regionali e avvisi della regione Puglia. Hai accesso ai bandi della regione Puglia. Qui sotto le informazioni di contesto recuperate. \n"
"---------------------\n"
"Informazioni di contesto: "+"{context_str}\n"
"---------------------\n"
"Usa le informazioni di contesto sopra fornite e non la tua conoscenza pregressa per rispondere, l'unica regione che conosci è la regione Puglia. "
"rispondi sempre alla seguente query sul bando regionale della Puglia usando le informazioni di contesto."
"\n", llm=llm, memory=memory_bandi, prefix_messages=[])
pinecone_index = pc.Index("indexbandisistemapuglia")
vector_store = PineconeVectorStore(
pinecone_index=pinecone_index,
add_sparse_vector=True,
)
storage_context = StorageContext.from_defaults(vector_store=vector_store)
index = VectorStoreIndex.from_vector_store(
vector_store, storage_context=storage_context
)
retriever_bandi_sistema_puglia = VectorIndexRetriever(index=index, similarity_top_k=3, vector_store_query_mode="hybrid", embed_model=embed_model, alpha=0.5)
chat_engine_bandi_sistema_puglia = ContextChatEngine(retriever=retriever_bandi_sistema_puglia,
context_template="Sei un chatbot in grado di rispondere alle domande su bandi regionali e avvisi della regione Puglia. Hai accesso ai bandi della regione Puglia. Qui sotto le informazioni di contesto recuperate. \n"
"---------------------\n"
"Informazioni di contesto: "+"{context_str}\n"
"---------------------\n"
"Usa le informazioni di contesto sopra fornite e non la tua conoscenza pregressa per rispondere, l'unica regione che conosci è la regione Puglia. "
"rispondi sempre alla seguente query sul bando regionale della Puglia usando le informazioni di contesto."
"\n", llm=llm, memory=memory_bandi_sistema_puglia, prefix_messages=[])
set_chat_engine()
def html_escape(text):
html_entities = {
'à': 'à',
'è': 'è',
'é': 'é',
'ì': 'ì',
'ò': 'ò',
'ù': 'ù',
'À': 'À',
'È': 'È',
'É': 'É',
'Ì': 'Ì',
'Ò': 'Ò',
'Ù': 'Ù',
'ç': 'ç',
'Ç': 'Ç',
'ä': 'ä',
'ö': 'ö',
'ü': 'ü',
'Ä': 'Ä',
'Ö': 'Ö',
'Ü': 'Ü',
'ß': 'ß',
'ñ': 'ñ',
'Ñ': 'Ñ',
'œ': 'œ',
'Œ': 'Œ',
'æ': 'æ',
'Æ': 'Æ',
'ø': 'ø',
'Ø': 'Ø',
'å': 'å',
'Å': 'Å',
'&': '&',
'<': '<',
'>': '>',
'"': '"',
"'": '''
}
return ''.join(html_entities.get(c, c) for c in text)
def reset():
global chat_engine_bandi
global chat_engine_bandi_sistema_puglia
global memory_bandi
global memory_bandi_sistema_puglia
global token_count_bandi
global token_count_bandi_sistema_puglia
chat_engine_bandi.reset()
chat_engine_bandi_sistema_puglia.reset()
memory_bandi_sistema_puglia.reset()
memory_bandi.reset()
token_count_bandi = 0
token_count_bandi_sistema_puglia = 0
return ""
with gr.Blocks(css=css, head=head) as demo:
with gr.Row():
output = gr.HTML()
with gr.Row(elem_id="buttonChat"):
gr.Button("STANDARD", size="sm").click(fn=select_standard_mode, outputs=output)
gr.Button("CHAT",size="sm").click(fn=select_chat_mode, outputs=output)
gr.Dropdown(
["BANDI_SISTEMA_PUGLIA","BANDI"], min_width= 185, label="Collezione di documenti", info="", container=False, interactive=True, value="BANDI_SISTEMA_PUGLIA", elem_id="dropdown"
).select(fn=select_collection, outputs=output)
chatbot = gr.Chatbot(elem_id="chatbot", container=False)
with gr.Column(elem_id="colonnaElementi"):
gr.Radio(["compact","tree_summarize"], label="Response mode", info="Influenzerà il modo in cui il chatbot risponde", interactive=True,container=False, value="tree_summarize",elem_id="responseMode").select(fn=select_response_mode, outputs=output),
divDocumenti = gr.HTML("<div id='divDocumenti'></div>")
msg = gr.Textbox(elem_id="textBox", container=False)
clear = gr.ClearButton([msg, chatbot], elem_id="btnClear")
clear.click(fn=reset, outputs=divDocumenti)
def user(userMessage, history):
global user_message
user_message = userMessage
if history is None:
history = []
return "", history + [[user_message, None]]
@spaces.GPU(duration=150)
def bot(history):
lenght = len(history)
userMessage = history[lenght-1][0]
global chat_engine_bandi
global chat_engine_bandi_sistema_puglia
global memory_bandi
global memory_bandi_sistema_puglia
global current_response_mode
global current_collection
global retriever
global file_path
global current_chat_mode
global token_count_bandi
global token_count_bandi_sistema_puglia
if(current_chat_mode=="CHAT"):
print("MODALITA CHAT")
if(current_collection=="BANDI"):
if(token_count_bandi >= 1000):
print("RESET!!!")
token_count_bandi = 0
memory_bandi.reset()
chat_engine_bandi.reset()
print(chat_engine_bandi.chat_history)
print(memory_bandi)
stream_response = None
print(userMessage)
stream_response = chat_engine_bandi.stream_chat(userMessage)
print("risposta con chat engine")
responseHTML = ""
for i, node in enumerate(stream_response.source_nodes):
responseHTML += "<p><b>"+node.metadata['nome_bando']+"</b><a href='"+node.metadata['file_path']+"' download> <svg xmlns='http://www.w3.org/2000/svg' width='16' height='16' fill='currentColor' class='bi bi-download' viewBox='0 0 16 16'><path d='M.5 9.9a.5.5 0 0 1 .5.5v2.5a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-2.5a.5.5 0 0 1 1 0v2.5a2 2 0 0 1-2 2H2a2 2 0 0 1-2-2v-2.5a.5.5 0 0 1 .5-.5'/><path d='M7.646 11.854a.5.5 0 0 0 .708 0l3-3a.5.5 0 0 0-.708-.708L8.5 10.293V1.5a.5.5 0 0 0-1 0v8.793L5.354 8.146a.5.5 0 1 0-.708.708z'/> </svg></a><br>Nodo <span id='span"+str(i+1)+"' class='icon' onclick='toggleText(this.id)'>🔍</span> <!-- Text to show/hide --><p class='hidden-text' id='nodo"+str(i+1)+"'>"+node.text+"</p>"
history[-1][1] = ""
for character in stream_response.response_gen:
tokens = character.split(" ")
num_tokens = len(tokens)
token_count_bandi = token_count_bandi + num_tokens
print(token_count_bandi)
history[-1][1] += html_escape(str(character))
time.sleep(0.05)
yield history, responseHTML
else:
if(token_count_bandi_sistema_puglia >= 1000):
print("RESET!!!")
token_count_bandi_sistema_puglia = 0
memory_bandi_sistema_puglia.reset()
chat_engine_bandi_sistema_puglia.reset()
print(chat_engine_bandi_sistema_puglia.chat_history)
print(memory_bandi_sistema_puglia)
stream_response = None
print(userMessage)
stream_response = chat_engine_bandi_sistema_puglia.stream_chat(userMessage)
print("risposta con chat engine")
responseHTML = ""
for i, node in enumerate(stream_response.source_nodes):
responseHTML += "<p><b>"+node.metadata['nome_bando']+"</b><a href='"+node.metadata['file_path']+"' download> <svg xmlns='http://www.w3.org/2000/svg' width='16' height='16' fill='currentColor' class='bi bi-download' viewBox='0 0 16 16'><path d='M.5 9.9a.5.5 0 0 1 .5.5v2.5a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-2.5a.5.5 0 0 1 1 0v2.5a2 2 0 0 1-2 2H2a2 2 0 0 1-2-2v-2.5a.5.5 0 0 1 .5-.5'/><path d='M7.646 11.854a.5.5 0 0 0 .708 0l3-3a.5.5 0 0 0-.708-.708L8.5 10.293V1.5a.5.5 0 0 0-1 0v8.793L5.354 8.146a.5.5 0 1 0-.708.708z'/> </svg></a><br>Nodo <span id='span"+str(i+1)+"' class='icon' onclick='toggleText(this.id)'>🔍</span> <!-- Text to show/hide --><p class='hidden-text' id='nodo"+str(i+1)+"'>"+node.text+"</p>"
history[-1][1] = ""
for character in stream_response.response_gen:
tokens = character.split(" ")
num_tokens = len(tokens)
token_count_bandi_sistema_puglia = token_count_bandi_sistema_puglia + num_tokens
print(token_count_bandi_sistema_puglia)
history[-1][1] += html_escape(str(character))
time.sleep(0.05)
yield history,responseHTML
else:
print("MODALITA STANDARD")
nome_bando = ""
userMessage = userMessage.lower()
if("diploma professionale" in userMessage):
nome_bando += "Scheda Avviso Pubblico Diploma Professionale 2022.pdf,"
if("red" in userMessage):
nome_bando += "Scheda RED 2020.pdf,"
if("ifts" in userMessage):
nome_bando += "Scheda Avviso Pubblico IFTS_2023.pdf,"
if(("impianti" in userMessage) or ("idrogeno" in userMessage)):
nome_bando += "Scheda Avviso PNRR - Impianti idrogeno rinnovabile.pdf,"
if("laureati" in userMessage):
nome_bando += "Scheda Pass Laureati 2023.pdf,"
if("nidi" in userMessage):
nome_bando += "Scheda NIDI - Nuove iniziative d'impresa_ Strumento di ingegneria finanziaria.pdf,"
if("microprestito" in userMessage):
nome_bando += "Scheda MicroPrestito della Regione Puglia - edizione 2021.pdf,"
if("gol" in userMessage):
nome_bando += "Scheda Garanzia di occupabilità dei lavoratori - GOL.pdf,"
if("edifici pubblici" in userMessage):
nome_bando += "Scheda Efficientamento Energetico Edifici Pubblici.pdf,"
if("innoaid" in userMessage):
nome_bando += "Scheda di sintesi Avviso _INNOAID - RIAPERTURA_.pdf,"
if("tecnonidi" in userMessage):
nome_bando += "Scheda Avviso Tecnonidi - Aiuti alle piccole imprese innovative.pdf,"
if(("bando of" in userMessage) or ("avviso of" in userMessage)):
nome_bando += "Scheda Avviso Pubblico OF a_f_ 2023_2024.pdf,"
if("giardin" in userMessage):
nome_bando += "Scheda Avviso Pubblico _Giardiniere d'arte per giardini e parchi storici_.pdf,"
if("punti cardinali" in userMessage):
nome_bando += "Scheda Avviso _Punti Cardinali_ punti di orientamento per la formazione e il lavoro.pdf,"
if("multimisura POC" in userMessage):
nome_bando += "Avviso Multimisura POC.pdf,"
if("garanzia giovani" in userMessage):
nome_bando += "Avviso Multimisura - Garanzia Giovani II Fase.pdf,"
if("apprendistato professionalizzante" in userMessage):
nome_bando += "Apprendistato Professionalizzante.pdf,"
if(nome_bando!=""):
# Rimuovi l'ultima virgola
if nome_bando.endswith(","):
nome_bando = nome_bando[:-1]
# Crea una lista di bandi separati dalla virgola
lista_bandi = nome_bando.split(",")
# Crea una lista di oggetti MetadataFilter
filter_list = []
for bando in lista_bandi:
filter_list.append(MetadataFilter(key="nome_bando", value=bando))
#crea una lista di MetadataFilter
filters = MetadataFilters(
filters=filter_list,
condition=FilterCondition.OR,
)
retriever = VectorIndexRetriever(index=index, similarity_top_k=3, vector_store_query_mode="hybrid", embed_model=embed_model, alpha=0.5, filters=filters)
else:
retriever = VectorIndexRetriever(index=index, similarity_top_k=3, vector_store_query_mode="hybrid", embed_model=embed_model, alpha=0.5)
if(str(current_response_mode)=="tree_summarize"):
# define response synthesizer
response_synthesizer = get_response_synthesizer(streaming=True,response_mode="tree_summarize",text_qa_template=text_qa_template)
query_engine = None
query_engine = RetrieverQueryEngine(retriever=retriever, response_synthesizer=response_synthesizer)
stream_response = None
print(userMessage)
stream_response = query_engine.query(userMessage)
print("risposta con query engine")
responseHTML = ""
for i, node in enumerate(stream_response.source_nodes):
responseHTML += "<p><b>"+node.metadata['nome_bando']+"</b><a href='"+node.metadata['file_path']+"' download> <svg xmlns='http://www.w3.org/2000/svg' width='16' height='16' fill='currentColor' class='bi bi-download' viewBox='0 0 16 16'><path d='M.5 9.9a.5.5 0 0 1 .5.5v2.5a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-2.5a.5.5 0 0 1 1 0v2.5a2 2 0 0 1-2 2H2a2 2 0 0 1-2-2v-2.5a.5.5 0 0 1 .5-.5'/><path d='M7.646 11.854a.5.5 0 0 0 .708 0l3-3a.5.5 0 0 0-.708-.708L8.5 10.293V1.5a.5.5 0 0 0-1 0v8.793L5.354 8.146a.5.5 0 1 0-.708.708z'/> </svg></a><br>Nodo <span id='span"+str(i+1)+"' class='icon' onclick='toggleText(this.id)'>🔍</span> <!-- Text to show/hide --><p class='hidden-text' id='nodo"+str(i+1)+"'>"+node.text+"</p>"
history[-1][1] = ""
# Misura il tempo di inizio
start_time = time.time()
for character in stream_response.response_gen:
history[-1][1] += html_escape(str(character))
time.sleep(0.05)
yield history, responseHTML
# Misura il tempo di fine
end_time = time.time()
# Calcola il tempo di esecuzione
execution_time = end_time - start_time
print(f"Tempo di esecuzione: {execution_time} secondi")
else:
# define response synthesizer
response_synthesizer = get_response_synthesizer(streaming=True,response_mode="compact",text_qa_template=text_qa_template, refine_template=refine_template)
query_engine = None
query_engine = RetrieverQueryEngine(retriever=retriever, response_synthesizer=response_synthesizer)
stream_response = None
print(userMessage)
stream_response = query_engine.query(userMessage)
print("risposta con query engine")
responseHTML = ""
for i, node in enumerate(stream_response.source_nodes):
responseHTML += "<p><b>"+node.metadata['nome_bando']+"</b><a href="+node.metadata['file_path']+" download> <svg xmlns='http://www.w3.org/2000/svg' width='16' height='16' fill='currentColor' class='bi bi-download' viewBox='0 0 16 16'><path d='M.5 9.9a.5.5 0 0 1 .5.5v2.5a1 1 0 0 0 1 1h12a1 1 0 0 0 1-1v-2.5a.5.5 0 0 1 1 0v2.5a2 2 0 0 1-2 2H2a2 2 0 0 1-2-2v-2.5a.5.5 0 0 1 .5-.5'/><path d='M7.646 11.854a.5.5 0 0 0 .708 0l3-3a.5.5 0 0 0-.708-.708L8.5 10.293V1.5a.5.5 0 0 0-1 0v8.793L5.354 8.146a.5.5 0 1 0-.708.708z'/> </svg></a><br>Nodo <span id='span"+str(i+1)+"' class='icon' onclick='toggleText(this.id)'>🔍</span> <!-- Text to show/hide --><p class='hidden-text' id='nodo"+str(i+1)+"'>"+node.text+"</p>"
history[-1][1] = ""
for character in stream_response.response_gen:
history[-1][1] += html_escape(str(character))
time.sleep(0.05)
yield history, responseHTML
torch.cuda.empty_cache()
torch.cuda.reset_max_memory_allocated()
torch.cuda.reset_max_memory_cached()
msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
bot, chatbot, [chatbot, divDocumenti]
)
demo.queue()
demo.launch(debug=True, share=True)
if __name__ == "__main__":
main() |