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import asyncio # on va en avoir besoin :)
import string
import random
from datetime import datetime
from src.tools.semantic_db import get_or_create_collection, reset_collection
from src.tools.wiki import Wiki
from src.model.document import InputDoc, WikiPage
from src.tools.llm_tools import get_wikilist, get_public_paragraph, get_private_paragraph
from src.tools.semantic_db import add_texts_to_collection, query_collection
"""
Tools
"""
def get_long_id(id_):
if id_ != -1:
return id_
else:
now = datetime.now().strftime("%m%d%H%M")
letters = string.ascii_lowercase + string.digits
long_id = now+'-'+''.join(random.choice(letters) for _ in range(10))
return long_id
"""
Input control
"""
"""
Source Control
"""
def wiki_fetch(input_text: str) -> [str]:
"""
returns the title of the wikipages corresponding to the tasks described in the input text
"""
tasks = InputDoc(input_text).tasks
wiki_lists = [get_wikilist(t) for t in tasks]
flatten_wiki_list = list(set().union(*[set(w) for w in wiki_lists]))
return flatten_wiki_list
async def wiki_upload_and_store(wiki_title: str, collection_name: str):
"""
uploads one wikipage and stores them into the right collection
"""
wikipage = Wiki().fetch(wiki_title)
wiki_title = wiki_title
if type(wikipage) != str:
texts = WikiPage(wikipage.page_content).get_paragraphs()
add_texts_to_collection(coll_name=collection_name, texts=texts, file=wiki_title, source='wiki')
else:
print(wikipage)
async def my_files_upload_and_store(title: str, collection_name: str):
doc = title
title = title
texts = InputDoc(doc).get_paragraphs()
add_texts_to_collection(coll_name=collection_name, texts=texts, file=title, source='my_files')
"""
Generate Control
"""
def generate_doc_from_gpt(input_txt: str) -> str:
input_doc = InputDoc(input_txt)
tasks = input_doc.tasks
task_resolutions = [get_public_paragraph(t) for t in tasks]
# task_resolutions = ["ça c'est de la réso"]
generated_doc = input_doc.replace_tasks(task_resolutions)
return generated_doc
def generate_doc_from_db(input_txt: str, collection_name: str, from_files: [str]) -> str:
def query_from_task(task):
return get_public_paragraph(task)
input_doc = InputDoc(input_txt)
tasks = input_doc.tasks
queries = [query_from_task(t) for t in tasks]
texts_list = [query_collection(coll_name=collection_name, query=q, from_files=from_files) for q in queries]
task_resolutions = [get_private_paragraph(task=task, texts=texts) for task, texts in zip(tasks, texts_list)]
generated_doc = input_doc.replace_tasks(task_resolutions)
return generated_doc
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