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Add new feature: Enable search engine integration in script.py
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@ -10,6 +10,9 @@ from modules.logging_colors import logger
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from .chromadb import add_chunks_to_collector, make_collector
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from .download_urls import download_urls
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import requests
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import json
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params = {
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'chunk_count': 5,
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'chunk_count_initial': 10,
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@ -57,6 +60,7 @@ def feed_file_into_collector(file, chunk_len, chunk_sep):
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def feed_url_into_collector(urls, chunk_len, chunk_sep, strong_cleanup, threads):
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print("feed_url_into_collector")
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all_text = ''
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cumulative = ''
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@ -83,6 +87,90 @@ def feed_url_into_collector(urls, chunk_len, chunk_sep, strong_cleanup, threads)
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for i in feed_data_into_collector(all_text, chunk_len, chunk_sep):
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yield i
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def feed_search_into_collector(query, chunk_len, chunk_sep, strong_cleanup, semantic_cleanup, semantic_requirement, threads):
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# Load parameters from the config file
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with open('custom_search_engine_keys.json') as key_file:
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key = json.load(key_file)
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print("=== Searching google ===")
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print("-- " + str(query))
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# Set up API endpoint and parameters
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url = "https://www.googleapis.com/customsearch/v1"
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# Retrieve the values from the config dictionary
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params = {
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"key": key.get("key", "default_key_value"),
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"cx": key.get("cx", "default_custom_engine_value"),
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"q": str(query),
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}
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if "default_key_value" in str(params):
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print("You need to provide an API key, by modifying the custom_search_engine_keys.json in oobabooga_windows \ text-generation-webui.\nSkipping search")
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return query
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if "default_custom_engine_value" in str(params):
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print("You need to provide an CSE ID, by modifying the script.py in oobabooga_windows \ text-generation-webui.\nSkipping search")
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return query
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# constructing the URL
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# doc: https://developers.google.com/custom-search/v1/using_rest
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# calculating start, (page=2) => (start=11), (page=3) => (start=21)
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page = 1
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start = (page - 1) * 10 + 1
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# Send API request
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response = requests.get(url, params=params)
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# Parse JSON response
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data = response.json()
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# get the result items
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search_items = data.get("items")
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# iterate over 10 results found
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search_urls = ""
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for i, search_item in enumerate(search_items, start=1):
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try:
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long_description = search_item["pagemap"]["metatags"][0]["og:description"]
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except KeyError:
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long_description = "N/A"
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# get the page title
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title = search_item.get("title")
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# page snippet
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snippet = search_item.get("snippet")
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# alternatively, you can get the HTML snippet (bolded keywords)
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html_snippet = search_item.get("htmlSnippet")
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# extract the page url
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link = search_item.get("link")
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search_urls += link + "\n"
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# TODO don't clone feed_url_into_collector
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all_text = ''
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cumulative = ''
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urls = search_urls.strip().split('\n')
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cumulative += f'Loading {len(urls)} URLs with {threads} threads...\n\n'
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yield cumulative
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for update, contents in download_urls(urls, threads=threads):
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yield cumulative + update
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cumulative += 'Processing the HTML sources...'
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yield cumulative
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for content in contents:
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soup = BeautifulSoup(content, features="html.parser")
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for script in soup(["script", "style"]):
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script.extract()
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strings = soup.stripped_strings
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if strong_cleanup:
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strings = [s for s in strings if re.search("[A-Za-z] ", s)]
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text = '\n'.join([s.strip() for s in strings])
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all_text += text
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for i in feed_data_into_collector(all_text, chunk_len, chunk_sep):
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yield i
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def apply_settings(chunk_count, chunk_count_initial, time_weight):
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global params
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@ -96,39 +184,38 @@ def apply_settings(chunk_count, chunk_count_initial, time_weight):
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def custom_generate_chat_prompt(user_input, state, **kwargs):
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global chat_collector
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history = state['history']
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if state['mode'] == 'instruct':
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results = collector.get_sorted(user_input, n_results=params['chunk_count'])
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additional_context = '\nYour reply should be based on the context below:\n\n' + '\n'.join(results)
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user_input += additional_context
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logger.info(f'\n\n=== === ===\nAdding the following new context:\n{additional_context}\n=== === ===\n')
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else:
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def make_single_exchange(id_):
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output = ''
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output += f"{state['name1']}: {history['internal'][id_][0]}\n"
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output += f"{state['name2']}: {history['internal'][id_][1]}\n"
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output += f"{state['name1']}: {shared.history['internal'][id_][0]}\n"
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output += f"{state['name2']}: {shared.history['internal'][id_][1]}\n"
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return output
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if len(history['internal']) > params['chunk_count'] and user_input != '':
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if len(shared.history['internal']) > params['chunk_count'] and user_input != '':
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chunks = []
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hist_size = len(history['internal'])
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hist_size = len(shared.history['internal'])
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for i in range(hist_size-1):
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chunks.append(make_single_exchange(i))
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add_chunks_to_collector(chunks, chat_collector)
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query = '\n'.join(history['internal'][-1] + [user_input])
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query = '\n'.join(shared.history['internal'][-1] + [user_input])
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try:
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best_ids = chat_collector.get_ids_sorted(query, n_results=params['chunk_count'], n_initial=params['chunk_count_initial'], time_weight=params['time_weight'])
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additional_context = '\n'
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for id_ in best_ids:
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if history['internal'][id_][0] != '<|BEGIN-VISIBLE-CHAT|>':
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if shared.history['internal'][id_][0] != '<|BEGIN-VISIBLE-CHAT|>':
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additional_context += make_single_exchange(id_)
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logger.warning(f'Adding the following new context:\n{additional_context}')
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state['context'] = state['context'].strip() + '\n' + additional_context
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kwargs['history'] = {
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'internal': [history['internal'][i] for i in range(hist_size) if i not in best_ids],
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'internal': [shared.history['internal'][i] for i in range(hist_size) if i not in best_ids],
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'visible': ''
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}
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except RuntimeError:
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@ -240,6 +327,36 @@ def ui():
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file_input = gr.File(label='Input file', type='binary')
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update_file = gr.Button('Load data')
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with gr.Tab("Search input"):
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search_term = gr.Textbox(lines=1, label='Search Input', info='Enter a google search, returned results will be fed into the DB')
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search_strong_cleanup = gr.Checkbox(value=params['strong_cleanup'], label='Strong cleanup', info='Only keeps html elements that look like long-form text.')
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semantic_cleanup = gr.Checkbox(value=params['strong_cleanup'], label='Require semantic similarity (not implemented)', info='Only download pages with similar titles/snippets to the search') # TODO cdg
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semantic_requirement = gr.Slider(0, 1, value=params['time_weight'], label='Semantic similarity requirement (not implemented)', info='Defines the requirement of the semantic search. 0 = no culling of dissimilar pages.') # TODO cdg
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search_threads = gr.Number(value=params['threads'], label='Threads', info='The number of threads to use while downloading the URLs.', precision=0)
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update_search = gr.Button('Load data')
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with gr.Accordion("Click for more information...", open=False):
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gr.Markdown(textwrap.dedent("""
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# installation/setup
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Please follow the instruction found here to setup a custom search engine with Google.
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https://www.thepythoncode.com/article/use-google-custom-search-engine-api-in-python
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create a file called "custom_search_engine_keys.json"
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Paste this text in it and replace with your values from the previous step:
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"
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{
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"key": "Custom search engine key",
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"cx": "Custom search engine cx number"
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}
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"
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# usage
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Enter a search query above. Press the load data button. This data will be added to the local chromaDB to be read into context at runtime.
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"""))
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with gr.Tab("Generation settings"):
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chunk_count = gr.Number(value=params['chunk_count'], label='Chunk count', info='The number of closest-matching chunks to include in the prompt.')
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gr.Markdown('Time weighting (optional, used in to make recently added chunks more likely to appear)')
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@ -256,4 +373,5 @@ def ui():
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update_data.click(feed_data_into_collector, [data_input, chunk_len, chunk_sep], last_updated, show_progress=False)
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update_url.click(feed_url_into_collector, [url_input, chunk_len, chunk_sep, strong_cleanup, threads], last_updated, show_progress=False)
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update_file.click(feed_file_into_collector, [file_input, chunk_len, chunk_sep], last_updated, show_progress=False)
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update_search.click(feed_search_into_collector, [search_term, chunk_len, chunk_sep, search_strong_cleanup, semantic_cleanup, semantic_requirement, search_threads], last_updated,show_progress=False)
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update_settings.click(apply_settings, [chunk_count, chunk_count_initial, time_weight], last_updated, show_progress=False)
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