New google gemini examples with pdf files

Author: peterbanda

anthropic-client/src/main/scala/io/cequence/openaiscala/anthropic/domain/Content.scala

@@ -87,6 +87,13 @@ object Content {
       val `type`: String = "web_search_tool_result"
     }
 
+    case class WebFetchToolResultBlock(
+      content: WebFetchToolResultContent,
+      toolUseId: String
+    ) extends ContentBlock {
+      val `type`: String = "web_fetch_tool_result"
+    }
+
     case class McpToolUseBlock(
       id: String,
       name: String,
@@ -335,6 +342,64 @@ object WebSearchToolResultContent {
   }
 }
 
+sealed trait WebFetchToolResultContent
+
+object WebFetchToolResultContent {
+
+  case class Success(
+    document: Document,
+    url: String,
+    retrievedAt: String
+  ) extends WebFetchToolResultContent
+
+  case class Error(
+    errorCode: WebFetchErrorCode
+  ) extends WebFetchToolResultContent
+      with HasType {
+    val `type`: String = "web_fetch_tool_result_error"
+  }
+
+  case class Document(
+    citations: Citations,
+    source: Source,
+    title: String
+  )
+
+  case class Citations(
+    enabled: Boolean
+  )
+
+  case class Source(
+    data: String,
+    mediaType: String,
+    `type`: String
+  )
+
+  sealed trait WebFetchErrorCode extends EnumValue
+
+  object WebFetchErrorCode {
+    case object invalid_tool_input extends WebFetchErrorCode
+    case object url_too_long extends WebFetchErrorCode
+    case object url_not_allowed extends WebFetchErrorCode
+    case object url_not_accessible extends WebFetchErrorCode
+    case object unsupported_content_type extends WebFetchErrorCode
+    case object too_many_requests extends WebFetchErrorCode
+    case object max_uses_exceeded extends WebFetchErrorCode
+    case object unavailable extends WebFetchErrorCode
+
+    def values: Seq[WebFetchErrorCode] = Seq(
+      invalid_tool_input,
+      url_too_long,
+      url_not_allowed,
+      url_not_accessible,
+      unsupported_content_type,
+      too_many_requests,
+      max_uses_exceeded,
+      unavailable
+    )
+  }
+}
+
 sealed trait McpToolResultContent
 
 case class McpToolResultString(

openai-examples/src/main/scala/io/cequence/openaiscala/examples/googlegemini/GoogleGeminiCreateChatCompletionPDFWithOpenAIAdapter.scala

@@ -0,0 +1,52 @@
+package io.cequence.openaiscala.examples.googlegemini
+
+import io.cequence.openaiscala.domain._
+import io.cequence.openaiscala.domain.settings.CreateChatCompletionSettings
+import io.cequence.openaiscala.examples.ExampleBase
+import io.cequence.openaiscala.gemini.service.GeminiServiceFactory
+import io.cequence.openaiscala.service.OpenAIChatCompletionService
+
+import scala.concurrent.Future
+import io.cequence.openaiscala.examples.BufferedImageHelper
+import java.util.Base64
+import java.nio.file.Files
+
+/**
+ * Requires `GOOGLE_API_KEY` environment variable to be set.
+ */
+object GoogleGeminiCreateChatCompletionPDFWithOpenAIAdapter
+    extends ExampleBase[OpenAIChatCompletionService]
+    with BufferedImageHelper {
+
+  override val service: OpenAIChatCompletionService = GeminiServiceFactory.asOpenAI()
+
+  // provide a local jpeg here
+  private lazy val localImagePath = sys.env("EXAMPLE_PDF_PATH")
+
+  private val pdfBase64Source =
+    Base64.getEncoder.encodeToString(
+      Files.readAllBytes(new java.io.File(localImagePath).toPath)
+    )
+
+  val messages: Seq[BaseMessage] = Seq(
+    SystemMessage("You are a helpful assistant."),
+    UserSeqMessage(
+      Seq(
+        TextContent("What is in this picture?"),
+        ImageURLContent(s"data:application/pdf;base64,${pdfBase64Source}")
+      )
+    )
+  )
+
+  private val modelId = NonOpenAIModelId.gemini_2_5_pro
+
+  override protected def run: Future[_] =
+    service
+      .createChatCompletion(
+        messages = messages,
+        settings = CreateChatCompletionSettings(
+          model = modelId
+        )
+      )
+      .map(printMessageContent)
+}

openai-examples/src/main/scala/io/cequence/openaiscala/examples/googlegemini/GoogleGeminiCreateChatCompletionPdfJSONWithOpenAIAdapter.scala

@@ -0,0 +1,73 @@
+package io.cequence.openaiscala.examples.googlegemini
+
+import io.cequence.openaiscala.domain._
+import io.cequence.openaiscala.domain.settings.CreateChatCompletionSettings
+import io.cequence.openaiscala.examples.ExampleBase
+import io.cequence.openaiscala.gemini.service.GeminiServiceFactory
+import io.cequence.openaiscala.service.OpenAIChatCompletionService
+
+import scala.concurrent.Future
+import io.cequence.openaiscala.examples.BufferedImageHelper
+import java.util.Base64
+import java.nio.file.Files
+import io.cequence.openaiscala.domain.settings.JsonSchemaDef
+import io.cequence.openaiscala.domain.settings.ChatCompletionResponseFormatType
+
+/**
+ * Requires `GOOGLE_API_KEY` environment variable to be set.
+ */
+object GoogleGeminiCreateChatCompletionPdfJSONWithOpenAIAdapter
+    extends ExampleBase[OpenAIChatCompletionService]
+    with BufferedImageHelper {
+
+  override val service: OpenAIChatCompletionService = GeminiServiceFactory.asOpenAI()
+
+  // provide a local jpeg here
+  private lazy val localImagePath = sys.env("EXAMPLE_PDF_PATH")
+
+  private val pdfBase64Source =
+    Base64.getEncoder.encodeToString(
+      Files.readAllBytes(new java.io.File(localImagePath).toPath)
+    )
+
+  val messages: Seq[BaseMessage] = Seq(
+    SystemMessage("You are a helpful assistant."),
+    UserSeqMessage(
+      Seq(
+        TextContent("What is in this pdf?"),
+        ImageURLContent(s"data:application/pdf;base64,${pdfBase64Source}")
+      )
+    )
+  )
+
+  private val jsonSchema =
+    JsonSchema.Array(
+      items = JsonSchema.Object(
+        properties = Map(
+          "itemName" -> JsonSchema.String(),
+          "value" -> JsonSchema.String(),
+          "comment" -> JsonSchema.String()
+        )
+      )
+    )
+
+  private val modelId = NonOpenAIModelId.gemini_2_5_pro
+
+  override protected def run: Future[_] =
+    service
+      .createChatCompletion(
+        messages = messages,
+        settings = CreateChatCompletionSettings(
+          model = modelId,
+          response_format_type = Some(ChatCompletionResponseFormatType.json_schema),
+          jsonSchema = Some(
+            JsonSchemaDef(
+              name = "extraction_response",
+              strict = false,
+              structure = jsonSchema
+            )
+          )
+        )
+      )
+      .map(printMessageContent)
+}