OpenAIImageEmbeddingParser.java
/*
* Licensed to the Apache Software Foundation (ASF) under one or more
* contributor license agreements. See the NOTICE file distributed with
* this work for additional information regarding copyright ownership.
* The ASF licenses this file to You 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.
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package org.apache.tika.inference;
import java.io.Closeable;
import java.io.IOException;
import java.util.Arrays;
import java.util.Base64;
import java.util.Collections;
import java.util.HashMap;
import java.util.HashSet;
import java.util.List;
import java.util.Map;
import java.util.Set;
import com.fasterxml.jackson.databind.JsonNode;
import com.fasterxml.jackson.databind.ObjectMapper;
import com.fasterxml.jackson.databind.node.ArrayNode;
import com.fasterxml.jackson.databind.node.ObjectNode;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.xml.sax.ContentHandler;
import org.xml.sax.SAXException;
import org.apache.tika.config.ConfigDeserializer;
import org.apache.tika.config.Initializable;
import org.apache.tika.config.JsonConfig;
import org.apache.tika.config.ParseContextConfig;
import org.apache.tika.config.TikaComponent;
import org.apache.tika.config.TikaProgressTracker;
import org.apache.tika.config.TimeoutLimits;
import org.apache.tika.exception.TikaConfigException;
import org.apache.tika.exception.TikaException;
import org.apache.tika.http.TikaHttpClient;
import org.apache.tika.inference.locator.Locators;
import org.apache.tika.inference.locator.PaginatedLocator;
import org.apache.tika.io.TikaInputStream;
import org.apache.tika.metadata.Metadata;
import org.apache.tika.metadata.TikaPagedText;
import org.apache.tika.mime.MediaType;
import org.apache.tika.parser.ParseContext;
import org.apache.tika.parser.Parser;
import org.apache.tika.sax.XHTMLContentHandler;
import org.apache.tika.utils.StringUtils;
/**
* Parser that sends images to a CLIP-like embedding endpoint
* (OpenAI-compatible {@code /v1/embeddings} with image input) and
* stores the resulting vector in metadata.
* <p>
* This parser registers for the same {@code image/ocr-*} media types
* used by the PDF renderer's OCR pipeline, so it slots into the
* existing {@code ocrStrategy} mechanism. When configured, each
* rendered page image is sent to the embedding endpoint and the
* vector is stored as a serialized {@link Chunk} with a
* {@link PaginatedLocator} (when page number metadata is available).
* <p>
* The image is sent in the Jina CLIP format:
* {@code {"input": [{"image": "data:image/png;base64,..."}]}}.
* <p>
* Configuration key: {@code "openai-image-embedding-parser"}
* <p>
* Thread safety: instances are safe for concurrent {@link #parse} calls once
* fully constructed. Setters must not be called concurrently with
* {@link #parse}.
*
* @since Apache Tika 4.0
*/
@TikaComponent(name = "openai-image-embedding-parser", spi = false)
public class OpenAIImageEmbeddingParser implements Parser, Initializable, Closeable {
private static final long serialVersionUID = 1L;
private static final Logger LOG = LoggerFactory.getLogger(
OpenAIImageEmbeddingParser.class);
private static final String OCR = "ocr-";
private static final Set<MediaType> SUPPORTED_TYPES =
Collections.unmodifiableSet(new HashSet<>(Arrays.asList(
MediaType.image(OCR + "png"),
MediaType.image(OCR + "jpeg"),
MediaType.image(OCR + "tiff"),
MediaType.image(OCR + "bmp"),
MediaType.image(OCR + "gif"),
MediaType.image("jp2"),
MediaType.image("jpx"),
MediaType.image("x-portable-pixmap"),
MediaType.image(OCR + "jp2"),
MediaType.image(OCR + "jpx"),
MediaType.image(OCR + "x-portable-pixmap"),
MediaType.image("webp"),
MediaType.image(OCR + "webp")
)));
private static final ObjectMapper MAPPER = new ObjectMapper();
private ImageEmbeddingConfig defaultConfig;
private transient TikaHttpClient httpClient;
/** URL path for embeddings requests. Default: {@code /v1/embeddings}. */
private String embeddingsPath = "/v1/embeddings";
/** HTTP header name for API key auth. Default: {@code Authorization}. */
private String apiKeyHeaderName = "Authorization";
/** Prefix before API key value. Default: {@code "Bearer "}. */
private String apiKeyPrefix = "Bearer ";
public OpenAIImageEmbeddingParser() {
this(new ImageEmbeddingConfig());
}
public OpenAIImageEmbeddingParser(ImageEmbeddingConfig config) {
this.defaultConfig = config;
this.httpClient = TikaHttpClient.build(30);
}
public OpenAIImageEmbeddingParser(JsonConfig jsonConfig) {
this(ConfigDeserializer.buildConfig(jsonConfig, ImageEmbeddingConfig.class));
}
// ---- Parser interface -------------------------------------------------
@Override
public Set<MediaType> getSupportedTypes(ParseContext context) {
if (defaultConfig.isSkipEmbedding()) {
return Collections.emptySet();
}
return SUPPORTED_TYPES;
}
@Override
public void parse(TikaInputStream tis, ContentHandler handler,
Metadata metadata, ParseContext parseContext)
throws IOException, SAXException, TikaException {
ImageEmbeddingConfig config = getConfig(parseContext);
if (config.isSkipEmbedding()) {
return;
}
long size = tis.getLength();
if (size >= 0
&& (size < config.getMinFileSizeToEmbed()
|| size > config.getMaxFileSizeToEmbed())) {
return;
}
byte[] imageBytes = tis.readAllBytes();
String mimeType = detectMimeType(metadata);
String base64Data = Base64.getEncoder().encodeToString(imageBytes);
long timeoutMillis = TimeoutLimits.getProcessTimeoutMillis(
parseContext, config.getTimeoutSeconds() * 1000L);
int timeoutSeconds = (int) (timeoutMillis / 1000L);
float[] vector = callEmbeddingEndpoint(config, mimeType, base64Data, timeoutSeconds);
TikaProgressTracker.update(parseContext);
Locators locators = buildLocators(metadata);
Chunk chunk = new Chunk(null, locators);
chunk.setVector(vector);
ChunkSerializer.mergeInto(metadata, List.of(chunk));
XHTMLContentHandler xhtml = new XHTMLContentHandler(
handler, metadata, parseContext);
xhtml.startDocument();
xhtml.endDocument();
}
// ---- Initializable ----------------------------------------------------
@Override
public void initialize() throws TikaConfigException {
this.httpClient = TikaHttpClient.build(30);
}
// ---- internals --------------------------------------------------------
float[] callEmbeddingEndpoint(ImageEmbeddingConfig config,
String mimeType, String base64Data,
int timeoutSeconds)
throws IOException, TikaException {
String requestJson = buildRequest(config, mimeType, base64Data);
String url = config.getBaseUrl().replaceAll("/+$", "") + embeddingsPath;
Map<String, String> headers = new HashMap<>();
if (!StringUtils.isBlank(config.getApiKey())) {
headers.put(apiKeyHeaderName, apiKeyPrefix + config.getApiKey());
}
String responseBody = httpClient.postJson(url, requestJson, headers, timeoutSeconds);
return parseResponse(responseBody);
}
String buildRequest(ImageEmbeddingConfig config, String mimeType,
String base64Data) {
ObjectNode root = MAPPER.createObjectNode();
if (!StringUtils.isBlank(config.getModel())) {
root.put("model", config.getModel());
}
ArrayNode input = root.putArray("input");
ObjectNode imageEntry = input.addObject();
imageEntry.put("image", "data:" + mimeType + ";base64," + base64Data);
return root.toString();
}
float[] parseResponse(String responseBody) throws TikaException {
try {
JsonNode root = MAPPER.readTree(responseBody);
JsonNode data = root.get("data");
if (data == null || !data.isArray() || data.isEmpty()) {
throw new TikaException(
"Embedding response has no data array: " + responseBody);
}
JsonNode embedding = data.get(0).get("embedding");
if (embedding == null || !embedding.isArray()) {
throw new TikaException(
"Embedding response has no embedding array: "
+ responseBody);
}
float[] vector = new float[embedding.size()];
for (int i = 0; i < embedding.size(); i++) {
float v = (float) embedding.get(i).asDouble();
if (Float.isNaN(v) || Float.isInfinite(v)) {
throw new TikaException(
"Embedding response contains invalid float at dim [" + i
+ "]: " + v + " ��� image may be in an unsupported format");
}
vector[i] = v;
}
return vector;
} catch (IOException e) {
throw new TikaException(
"Failed to parse embedding response: " + e.getMessage(), e);
}
}
Locators buildLocators(Metadata metadata) {
Locators locators = new Locators();
String pageStr = metadata.get(TikaPagedText.PAGE_NUMBER);
if (pageStr != null) {
try {
int page = Integer.parseInt(pageStr);
locators.addPaginated(new PaginatedLocator(page));
} catch (NumberFormatException e) {
// skip
}
}
return locators;
}
private String detectMimeType(Metadata metadata) {
String contentType = metadata.get(Metadata.CONTENT_TYPE);
if (contentType != null) {
contentType = contentType.replace("ocr-", "");
if (contentType.startsWith("image/")) {
return contentType;
}
}
return "image/png";
}
private ImageEmbeddingConfig getConfig(ParseContext parseContext)
throws TikaConfigException, IOException {
String key = "openai-image-embedding-parser";
if (parseContext.hasJsonConfig(key)) {
ImageEmbeddingConfig.RuntimeConfig runtimeConfig =
ParseContextConfig.getConfig(
parseContext, key,
ImageEmbeddingConfig.RuntimeConfig.class,
new ImageEmbeddingConfig.RuntimeConfig());
if (runtimeConfig.isSkipEmbedding()) {
return runtimeConfig;
}
return ParseContextConfig.getConfig(
parseContext, key, ImageEmbeddingConfig.class,
defaultConfig);
}
return defaultConfig;
}
@Override
public void close() throws IOException {
if (httpClient != null) {
httpClient.close();
}
}
// ---- delegating config getters/setters --------------------------------
public String getBaseUrl() {
return defaultConfig.getBaseUrl();
}
public void setBaseUrl(String baseUrl) throws TikaConfigException {
defaultConfig.setBaseUrl(baseUrl);
}
public String getModel() {
return defaultConfig.getModel();
}
public void setModel(String model) {
defaultConfig.setModel(model);
}
public String getApiKey() {
return defaultConfig.getApiKey();
}
public void setApiKey(String apiKey) throws TikaConfigException {
defaultConfig.setApiKey(apiKey);
}
public int getTimeoutSeconds() {
return defaultConfig.getTimeoutSeconds();
}
public void setTimeoutSeconds(int timeoutSeconds) {
defaultConfig.setTimeoutSeconds(timeoutSeconds);
}
public boolean isSkipEmbedding() {
return defaultConfig.isSkipEmbedding();
}
public void setSkipEmbedding(boolean skipEmbedding) {
defaultConfig.setSkipEmbedding(skipEmbedding);
}
public long getMinFileSizeToEmbed() {
return defaultConfig.getMinFileSizeToEmbed();
}
public void setMinFileSizeToEmbed(long minFileSizeToEmbed) {
defaultConfig.setMinFileSizeToEmbed(minFileSizeToEmbed);
}
public long getMaxFileSizeToEmbed() {
return defaultConfig.getMaxFileSizeToEmbed();
}
public void setMaxFileSizeToEmbed(long maxFileSizeToEmbed) {
defaultConfig.setMaxFileSizeToEmbed(maxFileSizeToEmbed);
}
// ---- Azure / endpoint config getters/setters ----------------------------
public String getEmbeddingsPath() {
return embeddingsPath;
}
/**
* Set the URL path for embeddings requests.
* Default is {@code /v1/embeddings}.
* For Azure OpenAI, use
* {@code /openai/deployments/{deployment}/embeddings?api-version=2024-02-01}.
*/
public void setEmbeddingsPath(String embeddingsPath) {
this.embeddingsPath = embeddingsPath;
}
public String getApiKeyHeaderName() {
return apiKeyHeaderName;
}
/**
* Set the HTTP header name for API key authentication.
* Default is {@code Authorization}. For Azure OpenAI, set to {@code api-key}.
*/
public void setApiKeyHeaderName(String apiKeyHeaderName) {
this.apiKeyHeaderName = apiKeyHeaderName;
}
public String getApiKeyPrefix() {
return apiKeyPrefix;
}
/**
* Set the prefix prepended to the API key in the auth header.
* Default is {@code "Bearer "} (with trailing space).
* For Azure OpenAI, set to {@code ""} (empty string).
*/
public void setApiKeyPrefix(String apiKeyPrefix) {
this.apiKeyPrefix = apiKeyPrefix;
}
}