tri.ai.cli.DocumentChunker.kt Maven / Gradle / Ivy
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/*-
* #%L
* tri.promptfx:promptkt
* %%
* Copyright (C) 2023 - 2024 Johns Hopkins University Applied Physics Laboratory
* %%
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
* #L%
*/
package tri.ai.cli
import tri.ai.text.chunks.process.LocalTextDocIndex
import tri.ai.text.chunks.process.SmartTextChunker
import tri.util.ANSI_CYAN
import tri.util.ANSI_GREEN
import tri.util.ANSI_RESET
import java.io.File
import kotlin.system.exitProcess
/** Runnable for extracting text from documents, and chunking documents into smaller pieces. */
object DocumentChunker {
@JvmStatic
fun main(args: Array) {
// val args = arrayOf("D:\\data\\chatgpt\\doc-insight-test", "--reindex-all", "--max-chunk-size=5000")
println(
"""
$ANSI_GREEN
Arguments expected:
Options:
--reindex-all
--reindex-new (default)
--max-chunk-size= (default 1000)
--index-file= (default docs.json)
$ANSI_RESET
""".trimIndent()
)
if (args.isEmpty())
exitProcess(0)
val path = args[0]
val reindexAll = args.contains("--reindex-all")
val maxChunkSize = args.find { it.startsWith("--max-chunk-size") }
?.substringAfter("=", "")
?.toIntOrNull() ?: 1000
val rootFolder = File(path)
val indexFile = File(rootFolder, args.find { it.startsWith("--index-file") }
?.substringAfter("=", "")
?: "docs.json")
println("${ANSI_CYAN}Refreshing file text in $rootFolder...$ANSI_RESET")
val docs = LocalTextDocIndex(rootFolder, indexFile)
docs.loadIndex()
docs.processDocuments(reindexAll)
println("${ANSI_CYAN}Chunking documents with max-chunk-size=$maxChunkSize...$ANSI_RESET")
val chunker = SmartTextChunker(maxChunkSize)
docs.processChunks(chunker, reindexAll)
println("${ANSI_CYAN}Saving document set info...$ANSI_RESET")
docs.saveIndex()
println("${ANSI_CYAN}Processing complete.$ANSI_RESET")
exitProcess(0)
}
}