V1.1.0

.github/workflows/ci.yml

@@ -31,7 +31,7 @@ jobs:
         working-directory: sdks/python
     strategy:
       matrix:
-        python-version: ['3.8', '3.9', '3.10', '3.11', '3.12']
+        python-version: ['3.9', '3.10', '3.11', '3.12']
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5

.github/workflows/release.yml

@@ -0,0 +1,52 @@
+name: Release SDKs
+
+on:
+  release:
+    types: [published]
+
+jobs:
+  publish-js:
+    name: Publish JavaScript SDK
+    runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags/js-v')
+    defaults:
+      run:
+        working-directory: sdks/js
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-node@v4
+        with:
+          node-version: '20'
+          registry-url: 'https://registry.npmjs.org'
+      - run: npm ci
+      - run: npm test
+      - run: npm run build
+      - run: npm publish --access public
+        env:
+          NODE_AUTH_TOKEN: ${{ secrets.NPM_TOKEN }}
+
+  publish-python:
+    name: Publish Python SDK
+    runs-on: ubuntu-latest
+    if: startsWith(github.ref, 'refs/tags/py-v')
+    defaults:
+      run:
+        working-directory: sdks/python
+    steps:
+      - uses: actions/checkout@v4
+      - uses: actions/setup-python@v5
+        with:
+          python-version: '3.11'
+      - name: Install build tools
+        run: pip install build twine
+      - name: Run tests
+        run: |
+          pip install -e ".[dev]"
+          pytest
+      - name: Build package
+        run: python -m build
+      - name: Publish to PyPI
+        env:
+          TWINE_USERNAME: __token__
+          TWINE_PASSWORD: ${{ secrets.PYPI }}
+        run: twine upload dist/*

sdks/js/src/index.test.ts

@@ -1,5 +1,13 @@
 import { describe, it, expect, beforeEach, vi } from 'vitest';
-import { PLPClient, PLPError } from './index';
+import {
+  PLPClient,
+  PLPError,
+  isMultiModal,
+  normalizeContent,
+  getTextContent,
+  type ContentPart,
+  type PromptEnvelope,
+} from './index';
 
 // Mock fetch
 global.fetch = vi.fn();
@@ -156,4 +164,140 @@ describe('PLPClient', () => {
       );
     });
   });
+
+  describe('multi-modal content', () => {
+    it('should handle multi-modal prompt in get()', async () => {
+      const mockPrompt: PromptEnvelope = {
+        id: 'vision/test',
+        content: [
+          { type: 'text', text: 'Analyze this image:' },
+          { type: 'image_url', image_url: { url: 'https://example.com/img.png', detail: 'high' } },
+        ],
+        meta: { version: '1.0.0' },
+      };
+
+      (global.fetch as any).mockResolvedValueOnce({
+        ok: true,
+        status: 200,
+        json: async () => mockPrompt,
+      });
+
+      const result = await client.get('vision/test');
+
+      expect(result.content).toEqual(mockPrompt.content);
+      expect(Array.isArray(result.content)).toBe(true);
+    });
+
+    it('should handle multi-modal prompt in put()', async () => {
+      const input = {
+        content: [
+          { type: 'text' as const, text: 'Describe this:' },
+          { type: 'image_url' as const, image_url: { url: 'https://example.com/img.png' } },
+        ],
+        meta: { version: '1.0.0' },
+      };
+
+      const mockResponse = {
+        id: 'vision/new',
+        ...input,
+      };
+
+      (global.fetch as any).mockResolvedValueOnce({
+        ok: true,
+        status: 201,
+        json: async () => mockResponse,
+      });
+
+      const result = await client.put('vision/new', input);
+
+      expect(global.fetch).toHaveBeenCalledWith(
+        expect.any(String),
+        expect.objectContaining({
+          body: JSON.stringify(input),
+        })
+      );
+      expect(result.content).toEqual(input.content);
+    });
+  });
+});
+
+describe('Helper Functions', () => {
+  describe('isMultiModal()', () => {
+    it('should return false for string content', () => {
+      expect(isMultiModal('Hello {{name}}')).toBe(false);
+    });
+
+    it('should return false for text-only array content', () => {
+      const content: ContentPart[] = [
+        { type: 'text', text: 'First part' },
+        { type: 'text', text: 'Second part' },
+      ];
+      expect(isMultiModal(content)).toBe(false);
+    });
+
+    it('should return true for content with images', () => {
+      const content: ContentPart[] = [
+        { type: 'text', text: 'Look at this:' },
+        { type: 'image_url', image_url: { url: 'https://example.com/img.png' } },
+      ];
+      expect(isMultiModal(content)).toBe(true);
+    });
+
+    it('should work with PromptEnvelope', () => {
+      const textPrompt: PromptEnvelope = {
+        id: 'test',
+        content: 'Simple text',
+        meta: {},
+      };
+      expect(isMultiModal(textPrompt)).toBe(false);
+
+      const multiModalPrompt: PromptEnvelope = {
+        id: 'test',
+        content: [
+          { type: 'text', text: 'With image' },
+          { type: 'image_url', image_url: { url: 'https://example.com/img.png' } },
+        ],
+        meta: {},
+      };
+      expect(isMultiModal(multiModalPrompt)).toBe(true);
+    });
+  });
+
+  describe('normalizeContent()', () => {
+    it('should wrap string in TextContent array', () => {
+      const result = normalizeContent('Hello {{name}}');
+      expect(result).toEqual([{ type: 'text', text: 'Hello {{name}}' }]);
+    });
+
+    it('should return array content as-is', () => {
+      const content: ContentPart[] = [
+        { type: 'text', text: 'Part 1' },
+        { type: 'image_url', image_url: { url: 'https://example.com/img.png' } },
+      ];
+      const result = normalizeContent(content);
+      expect(result).toBe(content); // Same reference
+    });
+  });
+
+  describe('getTextContent()', () => {
+    it('should return string content as-is', () => {
+      expect(getTextContent('Hello {{name}}')).toBe('Hello {{name}}');
+    });
+
+    it('should extract and join text from ContentPart array', () => {
+      const content: ContentPart[] = [
+        { type: 'text', text: 'First' },
+        { type: 'image_url', image_url: { url: 'https://example.com/img.png' } },
+        { type: 'text', text: 'Second' },
+      ];
+      expect(getTextContent(content)).toBe('First\nSecond');
+    });
+
+    it('should handle array with no text parts', () => {
+      const content: ContentPart[] = [
+        { type: 'image_url', image_url: { url: 'https://example.com/img.png' } },
+      ];
+      expect(getTextContent(content)).toBe('');
+    });
+  });
 });

sdks/js/src/index.ts

@@ -3,9 +3,40 @@
  * @license MIT
  */
 
+// =============================================================================
+// Multi-modal Content Types
+// =============================================================================
+
+export interface TextContent {
+  type: 'text';
+  text: string;
+}
+
+export interface ImageUrl {
+  url: string;
+  detail?: 'auto' | 'low' | 'high';
+}
+
+export interface ImageContent {
+  type: 'image_url';
+  image_url: ImageUrl;
+}
+
+export type ContentPart = TextContent | ImageContent;
+
+/**
+ * Prompt content - either a simple string (backwards compatible)
+ * or an array of content parts for multi-modal prompts.
+ */
+export type PromptContent = string | ContentPart[];
+
+// =============================================================================
+// Prompt Envelope Types
+// =============================================================================
+
 export interface PromptEnvelope {
   id: string;
-  content: string;
+  content: PromptContent;
   meta: {
     version?: string;
     author?: string;
@@ -16,10 +47,14 @@ export interface PromptEnvelope {
 }
 
 export interface PromptInput {
-  content: string;
+  content: PromptContent;
   meta?: Record<string, unknown>;
 }
 
+// =============================================================================
+// Client Configuration
+// =============================================================================
+
 export interface PLPClientOptions {
   apiKey?: string;
   headers?: Record<string, string>;
@@ -37,6 +72,59 @@ export class PLPError extends Error {
   }
 }
 
+// =============================================================================
+// Helper Functions
+// =============================================================================
+
+/**
+ * Check if a prompt has multi-modal content (images)
+ * @param prompt - The prompt envelope or content
+ * @returns true if content contains image parts
+ */
+export function isMultiModal(prompt: PromptEnvelope | PromptContent): boolean {
+  const content = typeof prompt === 'object' && prompt !== null && 'content' in prompt
+    ? (prompt as PromptEnvelope).content
+    : prompt;
+
+  if (typeof content === 'string') {
+    return false;
+  }
+
+  return content.some((part) => part.type === 'image_url');
+}
+
+/**
+ * Normalize content to ContentPart[] format
+ * @param content - String or ContentPart array
+ * @returns ContentPart[] (string is wrapped as single TextContent)
+ */
+export function normalizeContent(content: PromptContent): ContentPart[] {
+  if (typeof content === 'string') {
+    return [{ type: 'text', text: content }];
+  }
+  return content;
+}
+
+/**
+ * Get text-only content from a prompt (useful for token counting)
+ * @param content - String or ContentPart array
+ * @returns Combined text from all text parts
+ */
+export function getTextContent(content: PromptContent): string {
+  if (typeof content === 'string') {
+    return content;
+  }
+
+  return content
+    .filter((part): part is TextContent => part.type === 'text')
+    .map((part) => part.text)
+    .join('\n');
+}
+
+// =============================================================================
+// PLP Client
+// =============================================================================
+
 export class PLPClient {
   private baseUrl: string;
   private apiKey?: string;

sdks/python/pyproject.toml

@@ -7,7 +7,7 @@ name = "plp-client"
 version = "1.0.0"
 description = "Official Python client for PLP (Prompt Library Protocol)"
 readme = "README.md"
-requires-python = ">=3.8"
+requires-python = ">=3.9"
 license = "MIT"
 keywords = ["plp", "prompt", "library", "protocol", "ai", "llm", "openai", "anthropic"]
 authors = [
@@ -18,7 +18,6 @@ classifiers = [
   "Intended Audience :: Developers",
   "License :: OSI Approved :: MIT License",
   "Programming Language :: Python",
-  "Programming Language :: Python :: 3.8",
   "Programming Language :: Python :: 3.9",
   "Programming Language :: Python :: 3.10",
   "Programming Language :: Python :: 3.11",
@@ -36,6 +35,7 @@ dev = [
   "black>=23.0.0",
   "mypy>=1.0.0",
   "ruff>=0.1.0",
+  "types-requests>=2.28.0",
 ]
 
 [project.urls]
@@ -55,7 +55,7 @@ line-length = 88
 target-version = "py38"
 
 [tool.mypy]
-python_version = "3.8"
+python_version = "3.9"
 warn_return_any = true
 warn_unused_configs = true
 disallow_untyped_defs = true