convex agents files
12
总安装量
0
周安装量
#25886
全站排名
安装命令
npx skills add https://github.com/sstobo/convex-skills --skill Convex Agents Files
Skill 文档
Purpose
Files and images let agents understand and generate visual content. Covers uploading, storing, attaching to messages, and managing file lifecycle.
When to Use This Skill
- Users upload images for agent analysis
- Agents need to process documents or files
- Agents generate images with DALL-E
- Building file-based workflows
- Implementing file cleanup and tracking
Upload and Store a File
import { storeFile } from "@convex-dev/agent";
export const uploadFile = action({
args: { fileData: v.string(), filename: v.string(), mimeType: v.string() },
handler: async (ctx, { fileData, filename, mimeType }) => {
const bytes = Buffer.from(fileData, "base64");
const { file } = await storeFile(
ctx,
components.agent,
new Blob([bytes], { type: mimeType }),
{ filename, sha256: "hash" }
);
return {
fileId: file.fileId,
url: file.url,
storageId: file.storageId,
};
},
});
Send File with Message (2-Step)
Upload first, then send message with attachment:
import { saveMessage, getFile } from "@convex-dev/agent";
// Step 1: Save message with file
export const submitFileQuestion = mutation({
args: { threadId: v.string(), fileId: v.string(), question: v.string() },
handler: async (ctx, { threadId, fileId, question }) => {
const { imagePart, filePart } = await getFile(ctx, components.agent, fileId);
const { messageId } = await saveMessage(ctx, components.agent, {
threadId,
message: {
role: "user",
content: [
imagePart ?? filePart,
{ type: "text", text: question },
],
},
metadata: { fileIds: [fileId] },
});
return { messageId };
},
});
// Step 2: Generate response
export const generateFileResponse = action({
args: { threadId: v.string(), promptMessageId: v.string() },
handler: async (ctx, { threadId, promptMessageId }) => {
const { thread } = await myAgent.continueThread(ctx, { threadId });
await thread.generateText({ promptMessageId });
},
});
Inline File Saving (Action Only)
Pass file directly in generation:
export const analyzeImageInline = action({
args: { threadId: v.string(), imageData: v.string(), question: v.string() },
handler: async (ctx, { threadId, imageData, question }) => {
const { thread } = await myAgent.continueThread(ctx, { threadId });
await thread.generateText({
message: {
role: "user",
content: [
{
type: "image",
image: Buffer.from(imageData, "base64"),
mimeType: "image/png",
},
{ type: "text", text: question },
],
},
});
},
});
Generate and Save Images
export const generateAndSaveImage = action({
args: { threadId: v.string(), prompt: v.string() },
handler: async (ctx, { threadId, prompt }) => {
const { image } = await generateImage({
model: openai.image("dall-e-2"),
prompt,
});
const { file } = await storeFile(ctx, components.agent, image, {
filename: `generated-${Date.now()}.png`,
});
return { fileId: file.fileId };
},
});
Key Principles
- Automatic storage: Files > 64KB stored automatically
- File tracking: Metadata tracks which messages reference files
- URL generation: Signed URLs prevent unauthorized access
- MIME type inference: Auto-detected if not provided
- Cleanup: Files tracked for garbage collection
Next Steps
- See messages for message management
- See streaming for streamed file processing
- See fundamentals for agent setup