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Convex File Storage

Community
waynesutton
convex-file-storage

Complete file handling including upload flows, serving files via URL, storing generated files from actions, deletion, and accessing file metadata from system tables

Overview

Publisherwaynesutton
Repositoryconvexskills
Skill nameconvex-file-storage
Stars
404
Forks
32
Bundled files
3
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by waynesutton on GitHub. Read the source before you install it.

Installation

Install the Convex File Storage AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/waynesutton/convexskills.git /tmp/convexskills
mkdir -p .claude/skills
cp -r /tmp/convexskills/skills/convex-file-storage .claude/skills/convex-file-storage
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Convex File Storage in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Convex File Storage on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Convex File Storage is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Convex File Storage

Handle file uploads, storage, serving, and management in Convex applications with proper patterns for images, documents, and generated files.

Documentation Sources

Before implementing, do not assume; fetch the latest documentation:

Instructions

File Storage Overview

Convex provides built-in file storage with:

  • Automatic URL generation for serving files
  • Support for any file type (images, PDFs, videos, etc.)
  • File metadata via the _storage system table
  • Integration with mutations and actions

Generating Upload URLs

typescript
// convex/files.ts
import { mutation } from "./_generated/server";
import { v } from "convex/values";

export const generateUploadUrl = mutation({
  args: {},
  returns: v.string(),
  handler: async (ctx) => {
    return await ctx.storage.generateUploadUrl();
  },
});

Client-Side Upload

typescript
// React component
import { useMutation } from "convex/react";
import { api } from "../convex/_generated/api";
import { useState } from "react";

function FileUploader() {
  const generateUploadUrl = useMutation(api.files.generateUploadUrl);
  const saveFile = useMutation(api.files.saveFile);
  const [uploading, setUploading] = useState(false);

  const handleUpload = async (e: React.ChangeEvent<HTMLInputElement>) => {
    const file = e.target.files?.[0];
    if (!file) return;

    setUploading(true);
    try {
      // Step 1: Get upload URL
      const uploadUrl = await generateUploadUrl();

      // Step 2: Upload file to storage
      const result = await fetch(uploadUrl, {
        method: "POST",
        headers: { "Content-Type": file.type },
        body: file,
      });

      const { storageId } = await result.json();

      // Step 3: Save file reference to database
      await saveFile({
        storageId,
        fileName: file.name,
        fileType: file.type,
        fileSize: file.size,
      });
    } finally {
      setUploading(false);
    }
  };

  return (
    <div>
      <input
        type="file"
        onChange={handleUpload}
        disabled={uploading}
      />
      {uploading && <p>Uploading...</p>}
    </div>
  );
}

Saving File References

typescript
// convex/files.ts
import { mutation, query } from "./_generated/server";
import { v } from "convex/values";

export const saveFile = mutation({
  args: {
    storageId: v.id("_storage"),
    fileName: v.string(),
    fileType: v.string(),
    fileSize: v.number(),
  },
  returns: v.id("files"),
  handler: async (ctx, args) => {
    return await ctx.db.insert("files", {
      storageId: args.storageId,
      fileName: args.fileName,
      fileType: args.fileType,
      fileSize: args.fileSize,
      uploadedAt: Date.now(),
    });
  },
});

Serving Files via URL

typescript
// convex/files.ts
export const getFileUrl = query({
  args: { storageId: v.id("_storage") },
  returns: v.union(v.string(), v.null()),
  handler: async (ctx, args) => {
    return await ctx.storage.getUrl(args.storageId);
  },
});

// Get file with URL
export const getFile = query({
  args: { fileId: v.id("files") },
  returns: v.union(
    v.object({
      _id: v.id("files"),
      fileName: v.string(),
      fileType: v.string(),
      fileSize: v.number(),
      url: v.union(v.string(), v.null()),
    }),
    v.null()
  ),
  handler: async (ctx, args) => {
    const file = await ctx.db.get(args.fileId);
    if (!file) return null;

    const url = await ctx.storage.getUrl(file.storageId);
    
    return {
      _id: file._id,
      fileName: file.fileName,
      fileType: file.fileType,
      fileSize: file.fileSize,
      url,
    };
  },
});

Displaying Files in React

typescript
import { useQuery } from "convex/react";
import { api } from "../convex/_generated/api";

function FileDisplay({ fileId }: { fileId: Id<"files"> }) {
  const file = useQuery(api.files.getFile, { fileId });

  if (!file) return <div>Loading...</div>;
  if (!file.url) return <div>File not found</div>;

  // Handle different file types
  if (file.fileType.startsWith("image/")) {
    return <img src={file.url} alt={file.fileName} />;
  }

  if (file.fileType === "application/pdf") {
    return (
      <iframe
        src={file.url}
        title={file.fileName}
        width="100%"
        height="600px"
      />
    );
  }

  return (
    <a href={file.url} download={file.fileName}>
      Download {file.fileName}
    </a>
  );
}

Storing Generated Files from Actions

typescript
// convex/generate.ts
"use node";

import { action } from "./_generated/server";
import { v } from "convex/values";
import { api } from "./_generated/api";

export const generatePDF = action({
  args: { content: v.string() },
  returns: v.id("_storage"),
  handler: async (ctx, args) => {
    // Generate PDF (example using a library)
    const pdfBuffer = await generatePDFFromContent(args.content);

    // Convert to Blob
    const blob = new Blob([pdfBuffer], { type: "application/pdf" });

    // Store in Convex
    const storageId = await ctx.storage.store(blob);

    return storageId;
  },
});

// Generate and save image
export const generateImage = action({
  args: { prompt: v.string() },
  returns: v.id("_storage"),
  handler: async (ctx, args) => {
    // Call external API to generate image
    const response = await fetch("https://api.example.com/generate", {
      method: "POST",
      body: JSON.stringify({ prompt: args.prompt }),
    });

    const imageBuffer = await response.arrayBuffer();
    const blob = new Blob([imageBuffer], { type: "image/png" });

    return await ctx.storage.store(blob);
  },
});

Accessing File Metadata

typescript
// convex/files.ts
import { query } from "./_generated/server";
import { v } from "convex/values";
import { Id } from "./_generated/dataModel";

type FileMetadata = {
  _id: Id<"_storage">;
  _creationTime: number;
  contentType?: string;
  sha256: string;
  size: number;
};

export const getFileMetadata = query({
  args: { storageId: v.id("_storage") },
  returns: v.union(
    v.object({
      _id: v.id("_storage"),
      _creationTime: v.number(),
      contentType: v.optional(v.string()),
      sha256: v.string(),
      size: v.number(),
    }),
    v.null()
  ),
  handler: async (ctx, args) => {
    const metadata = await ctx.db.system.get(args.storageId);
    return metadata as FileMetadata | null;
  },
});

Deleting Files

typescript
// convex/files.ts
import { mutation } from "./_generated/server";
import { v } from "convex/values";

export const deleteFile = mutation({
  args: { fileId: v.id("files") },
  returns: v.null(),
  handler: async (ctx, args) => {
    const file = await ctx.db.get(args.fileId);
    if (!file) return null;

    // Delete from storage
    await ctx.storage.delete(file.storageId);

    // Delete database record
    await ctx.db.delete(args.fileId);

    return null;
  },
});

Image Upload with Preview

typescript
import { useMutation } from "convex/react";
import { api } from "../convex/_generated/api";
import { useState, useRef } from "react";

function ImageUploader({ onUpload }: { onUpload: (id: Id<"files">) => void }) {
  const generateUploadUrl = useMutation(api.files.generateUploadUrl);
  const saveFile = useMutation(api.files.saveFile);
  const [preview, setPreview] = useState<string | null>(null);
  const [uploading, setUploading] = useState(false);
  const inputRef = useRef<HTMLInputElement>(null);

  const handleFileSelect = async (e: React.ChangeEvent<HTMLInputElement>) => {
    const file = e.target.files?.[0];
    if (!file) return;

    // Validate file type
    if (!file.type.startsWith("image/")) {
      alert("Please select an image file");
      return;
    }

    // Validate file size (max 10MB)
    if (file.size > 10 * 1024 * 1024) {
      alert("File size must be less than 10MB");
      return;
    }

    // Show preview
    const reader = new FileReader();
    reader.onload = (e) => setPreview(e.target?.result as string);
    reader.readAsDataURL(file);

    // Upload
    setUploading(true);
    try {
      const uploadUrl = await generateUploadUrl();
      const result = await fetch(uploadUrl, {
        method: "POST",
        headers: { "Content-Type": file.type },
        body: file,
      });

      const { storageId } = await result.json();
      const fileId = await saveFile({
        storageId,
        fileName: file.name,
        fileType: file.type,
        fileSize: file.size,
      });

      onUpload(fileId);
    } finally {
      setUploading(false);
    }
  };

  return (
    <div>
      <input
        ref={inputRef}
        type="file"
        accept="image/*"
        onChange={handleFileSelect}
        style={{ display: "none" }}
      />
      
      <button
        onClick={() => inputRef.current?.click()}
        disabled={uploading}
      >
        {uploading ? "Uploading..." : "Select Image"}
      </button>

      {preview && (
        <img
          src={preview}
          alt="Preview"
          style={{ maxWidth: 200, marginTop: 10 }}
        />
      )}
    </div>
  );
}

Examples

Schema for File Storage

typescript
// convex/schema.ts
import { defineSchema, defineTable } from "convex/server";
import { v } from "convex/values";

export default defineSchema({
  files: defineTable({
    storageId: v.id("_storage"),
    fileName: v.string(),
    fileType: v.string(),
    fileSize: v.number(),
    uploadedBy: v.id("users"),
    uploadedAt: v.number(),
  })
    .index("by_user", ["uploadedBy"])
    .index("by_type", ["fileType"]),

  // User avatars
  users: defineTable({
    name: v.string(),
    email: v.string(),
    avatarStorageId: v.optional(v.id("_storage")),
  }),

  // Posts with images
  posts: defineTable({
    authorId: v.id("users"),
    content: v.string(),
    imageStorageIds: v.array(v.id("_storage")),
    createdAt: v.number(),
  }).index("by_author", ["authorId"]),
});

Best Practices

  • Never run npx convex deploy unless explicitly instructed
  • Never run any git commands unless explicitly instructed
  • Validate file types and sizes on the client before uploading
  • Store file metadata (name, type, size) in your own table
  • Use the _storage system table only for Convex metadata
  • Delete storage files when deleting database references
  • Use appropriate Content-Type headers when uploading
  • Consider image optimization for large images

Common Pitfalls

  1. Not setting Content-Type header - Files may not serve correctly
  2. Forgetting to delete storage - Orphaned files waste storage
  3. Not validating file types - Security risk for malicious uploads
  4. Large file uploads without progress - Poor UX for users
  5. Using deprecated getMetadata - Use ctx.db.system.get instead

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Convex File Storage AI skill do?

Complete file handling including upload flows, serving files via URL, storing generated files from actions, deletion, and accessing file metadata from system tables

Why use Convex File Storage on TypingMind?

Because you install it once and use it with any model. Convex File Storage is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Convex File Storage in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/waynesutton/convexskills/tree/main/skills/convex-file-storage. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Convex File Storage?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Convex File Storage?

As many as you like. As long as a model supports skills, you can use Convex File Storage with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Convex File Storage AI skill free?

Yes. It is published on GitHub by waynesutton under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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