php semantic search
1.0.0
Essas classes contêm interfaces para pesquisa e implementações semânticas usando o ROPHERTA como Pesquisa de Vector ROPHERTA e SQLITE3 como banco de dados vetorial. Uma pesquisa de palavras -chave usando SQLITE3 FTS4 e BM25 também é fornecida.
Para preencher o banco de dados vetorial, a classe Ingester contém um pedaço recursivo semelhante ao disponível em Langchain, mas com algumas velocidades, além da capacidade de consultar as compensações no documento de origem.
Os usos mais avançados incluem o uso de pesquisa vetorial como re -reranker e o uso do HYDE para obter incorporações simétricas.
Um documentos de origem de demonstração e indexa mais de 35.000 documentos do Stackoverflow e a documentação do PHP está disponível para download.
O componente de ingestão leva documentos no formato JSONL , com um documento JSON bem formado por linha.
O texto deve ser o UTF-8 de texto simples codificado (por JSON Spec). O sistema o dividirá em pedaços na ingestão.
{ "url": "...", "title": "...", "text": "...", "section": "...", "license": "..." }
Você precisa de SQLite-VSS instalado (Vector0 e VSS0.so)
Definir
[sqlite3]
; Directory pointing to SQLite3 extensions
; https://php.net/sqlite3.extension-dir
sqlite3.extension_dir = /path/to/the/sqlite3-vss-dllsapt install libgomp1 libblas3 liblapack3Instale a estrutura ONNX:
composer exec -- php -r "require 'vendor/autoload.php'; OnnxRuntimeVendor::check();"
Se você deseja usar o modelo multilíngue, não faça o download deste modelo e siga as instruções na próxima seção. Para o modelo em inglês, faça o download da frase Roberta Onnx Model (isso leva um tempo, o modelo tem 362 MB de tamanho):
composer exec -- php -r "require 'vendor/autoload.php'; TextualizationSentenceTransphormersVendor::check();"
Faça o download da biblioteca de peças de sentença:
composer exec -- php -r "require 'vendor/autoload.php'; TextualizationSentencePieceVendor::check();"
Faça o download do modelo BPE do XLM Tokenizer Sentenizer:
composer exec -- php -r "require 'vendor/autoload.php'; TextualizationRophertaTokenizerVendor::check();"
Faça o download do modelo multilíngue-E5-small (471MB de tamanho):
composer exec -- php -r "require 'vendor/autoload.php'; TextualizationSentenceTransphormersVendor::check(true);"
Observação: se você baixou o modelo em inglês, precisará excluí -lo primeiro. Atualmente, apenas um modelo é possível, essa limitação será levantada em versões futuras.
Instale a extensão SQLITE3 e o ROPHERTA de acordo com as instruções acima.
Faça o download dos dados e índices em http://textualization.com/download/phpsemsearch_0.1.tar.bz2 (192MB).
Descompacte e mova os arquivos vector.db e keyword.db para a pasta raiz.
Os principais documentos parecem bastante adequados.
$ composer run-script query keyword " composer produce time-out on script execution "
> Composer C onfig::disableProcessTimeout
> @php scripts/query.php ' keyword ' ' composer produce time-out on script execution '
Search query: compos OR produc OR time OR out OR on OR script OR execut
0. SearchResult[16.874319996013,https://www.php.net/manual/en/function.set-time-limit.php 0, ' function set-time-limit ' ]
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30. SearchResult[12.457255454068,https://stackoverflow.com/q/4869611 0, ' Fatal error: Maximum execution time of 0 seconds exceeded ' ]
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45. SearchResult[11.812067390316,https://www.php.net/manual/en/function.getlastmod.php 0, ' function getlastmod ' ]
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49. SearchResult[11.603155219238,https://stackoverflow.com/q/35681947 0, ' How to get PHP max_execution_time from the command line? ' ]Não é tão bom quanto a palavra -chave, mas os resultados são realmente diferentes. A pesquisa de vetores usando uma incorporação simétrica (como a sentença Roberta) funciona melhor ao pesquisar documentos semelhantes e não consultas contra documentos. Para tais casos, o Hyde (apresentado abaixo) é melhor. Incorporadores alternativos e assimétricos (como instrutor) podem ser portados para PHP através do ONNX.
$ composer run-script query vector " How to stop composer giving a time-out on a script execution "
> Composer C onfig::disableProcessTimeout
> @php scripts/query.php ' vector ' ' How to stop composer giving a time-out on a script execution '
0. SearchResult[-0.51090812683105,https://www.php.net/manual/en/function.oci-bind-by-name.php 14, ' function oci-bind-by-name ' ]
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49. SearchResult[-0.61479258537292,https://stackoverflow.com/q/10520390 0, ' Stop script execution upon notice/warning ' ]Combinando palavras -chave e vetor. Deve ser mais preciso.
$ composer run-script query reranked " How to stop composer giving a time-out on a script execution "
> Composer C onfig::disableProcessTimeout
> @php scripts/query.php ' reranked ' ' How to stop composer giving a time-out on a script execution '
Search query: how OR to OR stop OR compos OR give OR a OR time OR out OR on OR script OR execut
0. SearchResult[-0.61479258537292,https://stackoverflow.com/q/10520390 0, ' Stop script execution upon notice/warning ' ]O uso dessa funcionalidade precisa de uma chave de API do OpenAI. Ele pode ser passado através de um arquivo, uma variável de ambiente ou diretamente no construtor. Observe que o chamado OpenAI é muito lento . Neste exemplo, o texto ChatGPT lança a pesquisa de vetor em algumas direções que não são necessariamente ideais. Um texto mais curto poderia ter sido melhor.
$ composer run-script query ' {"class": "\Textualization\SemanticSearch\VectorHydeIndex", "completion":{"open_ai_key":"/path/to/key"}} ' " How to stop composer giving a time-out on a script execution "
> Composer C onfig::disableProcessTimeout
> @php scripts/query.php ' {"class": "\Textualization\SemanticSearch\VectorHydeIndex", "completion":{"open_ai_key":"/path/to/key"}} ' ' How to stop composer giving a time-out on a script execution '
Hdydrated query: There are several ways to prevent Composer from timing out during script execution:
1. Increase the timeout limit: By default, Composer has a timeout limit of 300 seconds (5 minutes). You can increase this limit by modifying the ` max_execution_time ` directive in your PHP configuration file (php.ini). Set it to a higher value, such as 600 (10 minutes) or more, depending on your script ' s requirements.
2. Optimize your script: If your script is taking too long to execute, consider optimizing it to reduce the execution time. Analyze your code and identify any bottlenecks or areas that can be improved. Use efficient algorithms, avoid unnecessary loops or recursive calls, and optimize database queries if applicable.
3. Split your script into smaller tasks: If your script performs multiple tasks, consider breaking it down into smaller tasks and executing them separately. This way, you can avoid hitting the timeout limit by completing each task within the allowed time frame.
4. Use command-line execution: Instead of running the script through a web server, you can execute it via the command line. Command-line execution typically has a longer timeout limit compared to web server execution. You can run the script using the `php` command followed by the script ' s file path.
5. Increase memory limit: If your script requires more memory to execute, you can increase the memory limit in your PHP configuration file (php.ini). Modify the ` memory_limit ` directive and set it to a higher value, such as 256M or more, depending on your script ' s memory requirements.
6. Use caching: If your script performs repetitive or resource-intensive tasks, consider implementing caching mechanisms. Caching can help reduce the execution time by storing and retrieving precomputed or frequently accessed data instead of recalculating it every time.
7. Use asynchronous processing: If your script involves time-consuming operations, consider using asynchronous processing techniques. Instead of waiting for each operation to complete before moving to the next, you can execute them concurrently or in the background using tools like queues, workers, or event-driven architectures.
Remember to restart your web server or PHP service after making changes to the PHP configuration file for the changes to take effect.
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49. SearchResult[-0.69992303848267,https://stackoverflow.com/q/19249159 0, ' Best practice multi language website ' ]Dado um número de URL e bloco, o script busca o truque:
$ composer run-script fetch vector https://stackoverflow.com/q/2077576 2
> @php scripts/fetch.php ' vector ' ' https://stackoverflow.com/q/2077576 ' ' 2 '
URL: https://stackoverflow.com/q/2077576
Chunk: 2
Title: PHP & mySQL: When exactly to use htmlentities ?
Offset-start: 2169
Offset-end: 3238
Section: StackOverlow
License: CC-BY-SA-3.0
Text:
<p>I thought it might help to add some more specific details of a specific situation here. Consider that there is a 'Preview' page. Now when I submit the input from a textarea, the Preview page receives the input and shows it html and at the same time, a hidden input collects this input. When the submit button on the Preview button is hit, then the data from the hidden input is POST'ed to a new page and that page inserts the data contained in the hidden input, into the DB. If I do not apply htmlentities when the form is initially submitted (but apply only strip_tags and mysql_real_escape_string) and there's a malicious input in the textarea, the hidden input is broken and the last few characters of the hidden input visibly seen as <code>" /></code> on the page, which is undesirable. So keeping this in mind, I need to do something to preserve the integrity of the hidden input properly on the Preview page and yet collect the data in the hidden input so that it does not break it. How do I go about this? Apologize for the delay in posting this info.</p>Observe que o índice de palavras -chave não está escondido (todos os números de chunk são 0).
Os documentos são fornecidos como um arquivo JSONL no formato descrito na parte superior deste documento.
Um arquivo de amostra está disponível para download.
$ composer run-script index keyword sophp.jsonl$ composer run-script index vector sophp.jsonlPara usar um índice re -classificado, crie um vetor e os índices de palavras -chave separadamente.
A indexação vetorial leva cerca de um dia e consome uma quantidade significativa de RAM no momento.
O pedaço recursivo pode ser usado independente:
$ composer run-script chunk ropherta null 1024 tests/sornd1000.jsonl output.jsonl Os documentos JSONL de saída têm chaves:
title )text )url )chunk_num )offset_start )offset_end )license ) Outros tokenizadores são possíveis, consulte o código na pasta scripts . O uso da string null (null) define o tamanho para os caracteres em vez de tokens.
$ composer run-script embed /path/to/model.onnx " actual text to compute embeddings " Para expandir as respostas usando um serviço de conclusão (como o Open AI ChatGPT), use:
$ composer run-script hydrate /path/to/open-ai-key 1024 tests/sornd1000.jsonl output.jsonl Ele preenche a completion do campo do title no objeto JSON .
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