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feat(ai): support PDF inputs

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This commit is contained in:
Aiden Cline
2026-07-22 00:12:00 -05:00
parent 69c05ae3fc
commit f7593836cd
6 changed files with 146 additions and 28 deletions
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packages/ai/src/protocols/anthropic-messages.ts
+43 -9
View File
@@ -56,6 +56,17 @@ const AnthropicImageBlock = Schema.Struct({
})
type AnthropicImageBlock = Schema.Schema.Type<typeof AnthropicImageBlock>
const AnthropicDocumentBlock = Schema.Struct({
type: Schema.tag("document"),
source: Schema.Struct({
type: Schema.tag("base64"),
media_type: Schema.Literal("application/pdf"),
data: Schema.String,
}),
cache_control: Schema.optional(AnthropicCacheControl),
})
type AnthropicDocumentBlock = Schema.Schema.Type<typeof AnthropicDocumentBlock>
const AnthropicThinkingBlock = Schema.Struct({
type: Schema.tag("thinking"),
thinking: Schema.String,
@@ -101,13 +112,13 @@ const AnthropicServerToolResultBlock = Schema.Struct({
})
type AnthropicServerToolResultBlock = Schema.Schema.Type<typeof AnthropicServerToolResultBlock>
// Anthropic accepts either a plain string or an ordered array of text/image
// blocks inside `tool_result.content`. The array form is required when a tool
// Anthropic accepts either a plain string or an ordered array of text, image, and
// document blocks inside `tool_result.content`. The array form is required when a tool
// returns image bytes (screenshot, image search, etc.) so they can be passed
// to the model as proper image inputs instead of being JSON-stringified into
// the prompt — which silently inflates context by megabytes and can push the
// conversation over the model's token limit.
const AnthropicToolResultContent = Schema.Union([AnthropicTextBlock, AnthropicImageBlock])
const AnthropicToolResultContent = Schema.Union([AnthropicTextBlock, AnthropicImageBlock, AnthropicDocumentBlock])
const AnthropicToolResultBlock = Schema.Struct({
type: Schema.tag("tool_result"),
@@ -117,7 +128,12 @@ const AnthropicToolResultBlock = Schema.Struct({
cache_control: Schema.optional(AnthropicCacheControl),
})
const AnthropicUserBlock = Schema.Union([AnthropicTextBlock, AnthropicImageBlock, AnthropicToolResultBlock])
const AnthropicUserBlock = Schema.Union([
AnthropicTextBlock,
AnthropicImageBlock,
AnthropicDocumentBlock,
AnthropicToolResultBlock,
])
type AnthropicUserBlock = Schema.Schema.Type<typeof AnthropicUserBlock>
const AnthropicAssistantBlock = Schema.Union([
AnthropicTextBlock,
@@ -319,12 +335,21 @@ const lowerServerToolResult = Effect.fn("AnthropicMessages.lowerServerToolResult
return { type: wireType, tool_use_id: part.id, content: part.result.value } satisfies AnthropicServerToolResultBlock
})
const lowerImage = Effect.fn("AnthropicMessages.lowerImage")(function* (part: MediaPart) {
const lowerMedia = Effect.fn("AnthropicMessages.lowerMedia")(function* (part: MediaPart) {
const media = yield* ProviderShared.validateMedia(
"Anthropic Messages",
part,
new Set<string>(ProviderShared.IMAGE_MIMES),
new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.DOCUMENT_MIMES]),
)
if (media.mime === "application/pdf")
return {
type: "document" as const,
source: {
type: "base64" as const,
media_type: "application/pdf" as const,
data: media.base64,
},
} satisfies AnthropicDocumentBlock
return {
type: "image" as const,
source: {
@@ -335,7 +360,7 @@ const lowerImage = Effect.fn("AnthropicMessages.lowerImage")(function* (part: Me
} satisfies AnthropicImageBlock
})
// Tool results may carry structured text/images. Keep media as provider-native
// Tool results may carry structured text, images, and documents. Keep media as provider-native
// content instead of JSON-stringifying base64 into a prompt string.
const lowerToolResultContentItem = Effect.fn("AnthropicMessages.lowerToolResultContentItem")(function* (
item: ToolContent,
@@ -344,8 +369,17 @@ const lowerToolResultContentItem = Effect.fn("AnthropicMessages.lowerToolResultC
const media = yield* ProviderShared.validateToolFile(
"Anthropic Messages",
item,
new Set<string>(ProviderShared.IMAGE_MIMES),
new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.DOCUMENT_MIMES]),
)
if (media.mime === "application/pdf")
return {
type: "document" as const,
source: {
type: "base64" as const,
media_type: "application/pdf" as const,
data: media.base64,
},
} satisfies AnthropicDocumentBlock
return {
type: "image" as const,
source: {
@@ -445,7 +479,7 @@ const lowerMessages = Effect.fn("AnthropicMessages.lowerMessages")(function* (
continue
}
if (part.type === "media") {
content.push(yield* lowerImage(part))
content.push(yield* lowerMedia(part))
continue
}
return yield* ProviderShared.unsupportedContent("Anthropic Messages", "user", ["text", "media"])
packages/ai/src/protocols/openai-responses.ts
+31 -6
View File
@@ -42,7 +42,16 @@ const OpenAIResponsesInputImage = Schema.Struct({
type: Schema.tag("input_image"),
image_url: Schema.String,
})
const OpenAIResponsesInputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])
const OpenAIResponsesInputFile = Schema.Struct({
type: Schema.tag("input_file"),
filename: Schema.String,
file_data: Schema.String,
})
const OpenAIResponsesInputContent = Schema.Union([
OpenAIResponsesInputText,
OpenAIResponsesInputImage,
OpenAIResponsesInputFile,
])
type OpenAIResponsesInputContent = Schema.Schema.Type<typeof OpenAIResponsesInputContent>
const OpenAIResponsesOutputText = Schema.Struct({
@@ -68,9 +77,13 @@ const OpenAIResponsesItemReference = Schema.Struct({
})
// `function_call_output.output` accepts either a plain string or an ordered
// array of content items so tools can return images in addition to text.
// array of content items so tools can return images and files in addition to text.
// https://platform.openai.com/docs/api-reference/responses/object
const OpenAIResponsesFunctionCallOutputContent = Schema.Union([OpenAIResponsesInputText, OpenAIResponsesInputImage])
const OpenAIResponsesFunctionCallOutputContent = Schema.Union([
OpenAIResponsesInputText,
OpenAIResponsesInputImage,
OpenAIResponsesInputFile,
])
const OpenAIResponsesFunctionCallOutput = Schema.Union([
Schema.String,
@@ -351,14 +364,20 @@ const lowerUserContent = Effect.fn("OpenAIResponses.lowerUserContent")(function*
const media = yield* ProviderShared.validateMedia(
"OpenAI Responses",
part,
new Set<string>(ProviderShared.IMAGE_MIMES),
new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.DOCUMENT_MIMES]),
)
if (media.mime === "application/pdf")
return {
type: "input_file" as const,
filename: part.filename ?? "document.pdf",
file_data: media.dataUrl,
}
return { type: "input_image" as const, image_url: media.dataUrl }
}
return yield* ProviderShared.unsupportedContent("OpenAI Responses", "user", ["text", "media"])
})
// Tool results may carry structured text/images. Keep media as provider-native
// Tool results may carry structured text, images, and files. Keep media as provider-native
// content instead of JSON-stringifying base64 into a prompt string.
const lowerToolResultContentItem = Effect.fn("OpenAIResponses.lowerToolResultContentItem")(function* (
item: ToolContent,
@@ -367,8 +386,14 @@ const lowerToolResultContentItem = Effect.fn("OpenAIResponses.lowerToolResultCon
const media = yield* ProviderShared.validateToolFile(
"OpenAI Responses",
item,
new Set<string>(ProviderShared.IMAGE_MIMES),
new Set<string>([...ProviderShared.IMAGE_MIMES, ...ProviderShared.DOCUMENT_MIMES]),
)
if (media.mime === "application/pdf")
return {
type: "input_file" as const,
filename: item.name ?? "document.pdf",
file_data: media.dataUrl,
}
return { type: "input_image" as const, image_url: media.dataUrl }
})
packages/ai/src/protocols/shared.ts
+2 -1
View File
@@ -158,7 +158,8 @@ export const parseToolInput = (route: string, name: string, raw: string) =>
export const IMAGE_MIMES = ["image/png", "image/jpeg", "image/gif", "image/webp"] as const
export const VIDEO_MIMES = ["video/mp4", "video/webm", "video/quicktime"] as const
export const AUDIO_MIMES = ["audio/wav", "audio/mp3", "audio/aiff", "audio/aac", "audio/ogg", "audio/flac"] as const
export const MEDIA_MIMES = [...IMAGE_MIMES, ...VIDEO_MIMES, ...AUDIO_MIMES] as const
export const DOCUMENT_MIMES = ["application/pdf"] as const
export const MEDIA_MIMES = [...IMAGE_MIMES, ...VIDEO_MIMES, ...AUDIO_MIMES, ...DOCUMENT_MIMES] as const
export const MAX_MEDIA_ENCODED_BYTES = 28 * 1024 * 1024
export const MAX_MEDIA_DECODED_BYTES = 20 * 1024 * 1024
packages/ai/test/provider/anthropic-messages.test.ts
+8 -4
View File
@@ -235,9 +235,9 @@ describe("Anthropic Messages route", () => {
}),
)
// Regression: screenshot/read tool results must stay structured so base64
// image data is not JSON-stringified into `tool_result.content`.
it.effect("lowers image tool-result content as structured image blocks", () =>
// Regression: read tool results must stay structured so base64 media data is
// not JSON-stringified into `tool_result.content`.
it.effect("lowers media tool-result content as structured blocks", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<AnthropicMessages.AnthropicMessagesBody>(
LLM.request({
@@ -253,6 +253,7 @@ describe("Anthropic Messages route", () => {
result: [
{ type: "text", text: "Image read successfully" },
{ type: "file", uri: "data:image/png;base64,AAECAw==", mime: "image/png" },
{ type: "file", uri: "data:application/pdf;base64,JVBERi0xLjQ=", mime: "application/pdf" },
],
}),
],
@@ -263,6 +264,7 @@ describe("Anthropic Messages route", () => {
expect(expectToolResult(prepared.body).content).toEqual([
{ type: "text", text: "Image read successfully" },
{ type: "image", source: { type: "base64", media_type: "image/png", data: "AAECAw==" } },
{ type: "document", source: { type: "base64", media_type: "application/pdf", data: "JVBERi0xLjQ=" } },
])
}),
)
@@ -756,7 +758,7 @@ describe("Anthropic Messages route", () => {
}),
)
it.effect("continues a conversation with user image content", () =>
it.effect("continues a conversation with user media content", () =>
Effect.gen(function* () {
const response = yield* LLMClient.generate(
LLM.request({
@@ -766,6 +768,7 @@ describe("Anthropic Messages route", () => {
Message.user([
{ type: "text", text: "What is in this image?" },
{ type: "media", mediaType: "image/png", data: "AAECAw==" },
{ type: "media", mediaType: "application/pdf", data: "JVBERi0xLjQ=", filename: "report.pdf" },
]),
],
}),
@@ -781,6 +784,7 @@ describe("Anthropic Messages route", () => {
content: [
{ type: "text", text: "What is in this image?" },
{ type: "image", source: { type: "base64", media_type: "image/png", data: "AAECAw==" } },
{ type: "document", source: { type: "base64", media_type: "application/pdf", data: "JVBERi0xLjQ=" } },
],
},
],
packages/ai/test/provider/gemini.test.ts
+9 -2
View File
@@ -70,6 +70,7 @@ describe("Gemini route", () => {
Message.user([
{ type: "text", text: "What is in this image?" },
{ type: "media", mediaType: "image/png", data: "AAECAw==" },
{ type: "media", mediaType: "application/pdf", data: "JVBERi0xLjQ=" },
]),
Message.assistant([ToolCallPart.make({ id: "call_1", name: "lookup", input: { query: "weather" } })]),
Message.tool({ id: "call_1", name: "lookup", result: { forecast: "sunny" } }),
@@ -81,7 +82,11 @@ describe("Gemini route", () => {
contents: [
{
role: "user",
parts: [{ text: "What is in this image?" }, { inlineData: { mimeType: "image/png", data: "AAECAw==" } }],
parts: [
{ text: "What is in this image?" },
{ inlineData: { mimeType: "image/png", data: "AAECAw==" } },
{ inlineData: { mimeType: "application/pdf", data: "JVBERi0xLjQ=" } },
],
},
{
role: "model",
@@ -110,7 +115,7 @@ describe("Gemini route", () => {
}),
)
it.effect("continues image tool results as inline vision input without base64 text", () =>
it.effect("continues media tool results as inline model input without base64 text", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<Gemini.GeminiBody>(
LLM.request({
@@ -125,6 +130,7 @@ describe("Gemini route", () => {
value: [
{ type: "text", text: "Image read successfully" },
{ type: "file", uri: "data:image/png;base64,AAECAw==", mime: "image/png", name: "pixel.png" },
{ type: "file", uri: "data:application/pdf;base64,JVBERi0xLjQ=", mime: "application/pdf" },
],
},
}),
@@ -144,6 +150,7 @@ describe("Gemini route", () => {
},
},
{ inlineData: { mimeType: "image/png", data: "AAECAw==" } },
{ inlineData: { mimeType: "application/pdf", data: "JVBERi0xLjQ=" } },
],
},
])
packages/ai/test/provider/openai-responses.test.ts
+53 -6
View File
@@ -524,7 +524,42 @@ describe("OpenAI Responses route", () => {
}),
)
it.effect("rejects non-image media in tool-result content with a clear error", () =>
it.effect("lowers PDF tool-result content as structured input_file array", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
LLM.request({
id: "req_tool_result_pdf",
model,
messages: [
Message.assistant([ToolCallPart.make({ id: "call_1", name: "read", input: {} })]),
Message.tool({
id: "call_1",
name: "read",
resultType: "content",
result: [
{
type: "file",
uri: "data:application/pdf;base64,JVBERi0xLjQ=",
mime: "application/pdf",
name: "report.pdf",
},
],
}),
],
}),
)
expect(expectToolOutput(prepared.body).output).toEqual([
{
type: "input_file",
filename: "report.pdf",
file_data: "data:application/pdf;base64,JVBERi0xLjQ=",
},
])
}),
)
it.effect("rejects unsupported media in tool-result content with a clear error", () =>
Effect.gen(function* () {
const error = yield* LLMClient.prepare(
LLM.request({
@@ -1526,20 +1561,32 @@ describe("OpenAI Responses route", () => {
}),
)
it.effect("lowers user image content", () =>
it.effect("lowers user image and PDF content", () =>
Effect.gen(function* () {
const prepared = yield* LLMClient.prepare<OpenAIResponses.OpenAIResponsesBody>(
LLM.request({
id: "req_media",
model,
messages: [Message.user({ type: "media", mediaType: "image/png", data: "AAECAw==" })],
messages: [
Message.user([
{ type: "media", mediaType: "image/png", data: "AAECAw==" },
{ type: "media", mediaType: "application/pdf", data: "JVBERi0xLjQ=", filename: "report.pdf" },
]),
],
}),
)
expect(prepared.body.input).toEqual([
{
role: "user",
content: [{ type: "input_image", image_url: "data:image/png;base64,AAECAw==" }],
content: [
{ type: "input_image", image_url: "data:image/png;base64,AAECAw==" },
{
type: "input_file",
filename: "report.pdf",
file_data: "data:application/pdf;base64,JVBERi0xLjQ=",
},
],
},
])
}),
@@ -1551,11 +1598,11 @@ describe("OpenAI Responses route", () => {
LLM.request({
id: "req_media",
model,
messages: [Message.user({ type: "media", mediaType: "application/pdf", data: "AAECAw==" })],
messages: [Message.user({ type: "media", mediaType: "application/x-tar", data: "AAECAw==" })],
}),
).pipe(Effect.flip)
expect(error.message).toContain("OpenAI Responses does not support media type application/pdf")
expect(error.message).toContain("OpenAI Responses does not support media type application/x-tar")
}),
)