mirror of
https://github.com/oobabooga/text-generation-webui.git
synced 2024-11-28 18:48:04 +01:00
124 lines
5.7 KiB
Python
124 lines
5.7 KiB
Python
import json
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import requests
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import re
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from urllib.request import urlopen
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from bs4 import BeautifulSoup
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from bs4.element import Comment
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import gradio as gr
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import modules.chat as chat
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import modules.shared as shared
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import requests
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import torch
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torch._C._jit_set_profiling_mode(False)
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params = { # These can all be set in the settings.yml file
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'enable_search': True,
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'include_first_result_content': True,
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'include_result_summary': False,
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'max_characters_per_page': 4096,
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'searx_instance': "",
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'max_total_characters': 8192,
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'extra_query_information': "",
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'removal_list': ['\t', '\n', '\\n', '\\t'],
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'number_of_results': 1,
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'console_log': True
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}
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html_element_blacklist = [
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'[document]',
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'noscript',
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'header',
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'meta',
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'head',
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'input',
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'script',
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'style'
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]
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def url_to_text(url):
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html = urlopen(url).read()
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soup = BeautifulSoup(html, "lxml")
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for tag in soup.find_all(html_element_blacklist):
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tag.decompose()
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text = soup.get_text(strip=True)
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for string in params['removal_list']:
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text.replace(string, " ")
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return text[0:params['max_characters_per_page']]
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def get_search_term(string): # This checks if you say "search ... about" something, and if the "Activate Searx integration" checkbox is ticked will search about that
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commands = ['search', 'tell me', 'give me a summary']
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marker = ['about']
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lowstr = string.lower()
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for s in ['\"', '\'']:
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lowstr = lowstr.replace(s, '')
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if any(command in lowstr for command in commands) and any(case in lowstr for case in marker):
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print("Found search term")
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subject = string.split('about',1)[1]
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return subject
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def search_string(search_term): # This is the main logic that sends the API request to Searx and returns the text to add to the context
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print("Searching about" + search_term + "...")
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query = f"{search_term} {params['extra_query_information']}"
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r = requests.get(params['searx_instance'], params={'q': query,'format': 'json','pageno': '1'})
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try:
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searchdata = r.json()
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searchdata = searchdata['results']
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except:
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new_context = "Tell me that you could not find the results I asked for."
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else:
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new_context = f"This is new information from after your knowledge cutoff date about {search_term} :\n"
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if params['include_first_result_content']:
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for i in range(params['number_of_results']):
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new_context += url_to_text(searchdata[i]['url']) + "\n"
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if params['include_result_summary']:
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for result in searchdata:
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if 'content' in result:
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new_context += result['content'] + "\n"
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new_context = new_context[0:params['max_total_characters']]
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finally:
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if params['console_log']:
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print(new_context)
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return new_context
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def input_modifier(string):
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if params['enable_search'] and params['searx_instance']:
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if get_search_term(string):
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search_result = search_string(string)
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if search_result == "Tell me that you could not find the results I asked for.": # If it failed to get a result, ask the LLM to tell user it did
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return search_result
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else:
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return f"{search_result} Using the information I just gave you, without adding any thing new, respond to this request: {string}"
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return string
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def ui():
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with gr.Accordion("Searx Integration", open=True):
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with gr.Row():
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with gr.Column():
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enable_search = gr.Checkbox(value=params['enable_search'], label='Activate Searx integration')
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console_log = gr.Checkbox(value=params['console_log'], label='Display search results on console')
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include_first_result_content = gr.Checkbox(value=params['include_first_result_content'], label='Include content from the first result')
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number_of_results = gr.Slider(1,10,value=params['number_of_results'],step=1,label='Number of results to fetch')
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with gr.Column():
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searx_instance = gr.Textbox(placeholder=params['searx_instance'], value=params['searx_instance'], label='Searx instance address')
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extra_query_information = gr.Textbox(placeholder=params['extra_query_information'], value=params['extra_query_information'], label='Extra info to pass in Searx query')
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include_result_summary = gr.Checkbox(value=params['include_result_summary'], label='Include summary from each search result')
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max_characters_per_page = gr.Slider(256,16384,value=params['max_characters_per_page'],step=64,label='Maximum characters per fetched pages')
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max_total_characters = gr.Slider(256,16384,value=params['max_total_characters'],step=64,label='Total max characters')
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enable_search.change(lambda x: params.update({"enable_search": x}), enable_search, None)
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console_log.change(lambda x: params.update({"console_display": x}), console_log, None)
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include_first_result_content.change(lambda x: params.update({"include_first_result_content": x}), include_first_result_content, None)
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include_result_summary.change(lambda x: params.update({"include_result_summary": x}), include_result_summary, None)
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number_of_results.change(lambda x: params.update({"number_of_results": x}), number_of_results, None)
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max_characters_per_page.change(lambda x: params.update({"max_characters_per_page": x}), max_characters_per_page, None)
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searx_instance.change(lambda x: params.update({"searx_instance": x}), searx_instance, None)
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extra_query_information.change(lambda x: params.update({"extra_query_information": x}), extra_query_information, None)
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max_total_characters.change(lambda x: params.update({"max_total_characters": x}), max_total_characters, None) |