mirror of
https://github.com/supermemoryai/supermemory.git
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updated ai sdk object structure
This commit is contained in:
Sreeram Sreedhar
parent
7b99822ae3
commit
1da2ae0529
10 changed files with 377 additions and 371 deletions
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@ -35,8 +35,7 @@ import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/vercel"
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import { openai } from "@ai-sdk/openai"
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const modelWithMemory = withSupermemory({
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model: openai("gpt-4"),
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const modelWithMemory = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456"
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})
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@ -51,8 +50,7 @@ const result = await generateText({
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**Memory saving is enabled by default.** The middleware automatically saves conversations to memory. To disable memory saving:
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```typescript
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const modelWithMemory = withSupermemory({
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model: openai("gpt-4"),
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const modelWithMemory = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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addMemory: "never"
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@ -65,8 +63,7 @@ const result = await generateText({
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**Profile Mode (Default)** - Retrieves the user's complete profile:
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```typescript
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const model = withSupermemory({
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model: openai("gpt-4"),
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const model = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "profile"
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@ -76,8 +73,7 @@ const model = withSupermemory({
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**Query Mode** - Searches memories based on the user's message:
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```typescript
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const model = withSupermemory({
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model: openai("gpt-4"),
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const model = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "query"
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@ -87,8 +83,7 @@ const model = withSupermemory({
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**Full Mode** - Combines profile AND query-based search:
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```typescript
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const model = withSupermemory({
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model: openai("gpt-4"),
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const model = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "full"
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@ -113,8 +108,7 @@ const claudePrompt = (data: MemoryPromptData) => `
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</context>
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`.trim()
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const model = withSupermemory({
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model: anthropic("claude-3-sonnet"),
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const model = withSupermemory(anthropic("claude-3-sonnet"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "full",
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@ -125,8 +119,7 @@ const model = withSupermemory({
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### Verbose Logging
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```typescript
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const model = withSupermemory({
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model: openai("gpt-4"),
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const model = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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verbose: true
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@ -57,8 +57,8 @@ const addTool = addMemoryTool(process.env.SUPERMEMORY_API_KEY!, {
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#### AI SDK Middleware with Supermemory
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- `withSupermemory` will take advantage supermemory profile v4 endpoint personalized based on container tag
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- You can provide the Supermemory API key via the `apiKey` option to `withSupermemory` (recommended for browser usage), or fall back to `SUPERMEMORY_API_KEY` in the environment for server usage.
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- `withSupermemory` wraps any language model with supermemory capabilities using the v4 profile endpoint
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- You can provide the Supermemory API key via the `apiKey` option (recommended for browser usage), or fall back to `SUPERMEMORY_API_KEY` in the environment for server usage
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- **Per-turn caching**: Memory injection is cached for tool-call continuations within the same user turn. The middleware detects when the AI SDK is continuing a multi-step flow (e.g., after a tool call) and reuses the cached memories instead of making redundant API calls. A fresh fetch occurs on each new user message turn.
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```typescript
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@ -66,35 +66,36 @@ import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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const modelWithMemory = withSupermemory(openai("gpt-5"), "user_id_life")
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const modelWithMemory = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conversation-456",
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})
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const result = await generateText({
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model: modelWithMemory,
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messages: [{ role: "user", content: "where do i live?" }],
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model: modelWithMemory,
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messages: [{ role: "user", content: "where do i live?" }],
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})
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console.log(result.text)
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```
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#### Conversation Grouping
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#### Configuration Options
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Use the `conversationId` option to group messages into a single document for contextual memory generation:
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The `withSupermemory` function accepts a model and a configuration object:
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```typescript
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import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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const modelWithMemory = withSupermemory(openai("gpt-5"), "user_id_life", {
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conversationId: "conversation-456"
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withSupermemory(model, {
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containerTag: string, // Required: User/container identifier for memory scoping
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customId: string, // Required: Conversation ID for grouping messages
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mode?: "profile" | "query" | "full", // Memory retrieval mode (default: "profile")
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addMemory?: "always" | "never", // Auto-save conversations (default: "always")
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searchMode?: "memories" | "hybrid" | "documents", // Search mode (default: "memories")
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searchLimit?: number, // Max search results for hybrid/documents mode (default: 10)
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verbose?: boolean, // Enable detailed logging (default: false)
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apiKey?: string, // Supermemory API key (falls back to env var)
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baseUrl?: string, // Custom API base URL
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promptTemplate?: (data: MemoryPromptData) => string, // Custom memory formatting
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})
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const result = await generateText({
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model: modelWithMemory,
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messages: [{ role: "user", content: "where do i live?" }],
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})
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console.log(result.text)
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```
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#### Verbose Mode
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@ -106,13 +107,15 @@ import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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const modelWithMemory = withSupermemory(openai("gpt-5"), "user_id_life", {
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verbose: true
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const modelWithMemory = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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verbose: true,
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})
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const result = await generateText({
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model: modelWithMemory,
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messages: [{ role: "user", content: "where do i live?" }],
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model: modelWithMemory,
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messages: [{ role: "user", content: "where do i live?" }],
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})
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console.log(result.text)
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@ -120,7 +123,7 @@ console.log(result.text)
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When verbose mode is enabled, you'll see console output like:
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```
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[supermemory] Searching memories for container: user_id_life
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[supermemory] Searching memories for container: user-123
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[supermemory] User message: where do i live?
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[supermemory] System prompt exists: false
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[supermemory] Found 3 memories
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@ -139,11 +142,10 @@ import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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// Uses profile mode by default - gets all user profile memories
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const modelWithMemory = withSupermemory(openai("gpt-4"), "user-123")
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// Explicitly specify profile mode
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const modelWithProfile = withSupermemory(openai("gpt-4"), "user-123", {
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mode: "profile"
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const modelWithMemory = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "profile",
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})
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const result = await generateText({
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@ -158,8 +160,10 @@ import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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const modelWithQuery = withSupermemory(openai("gpt-4"), "user-123", {
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mode: "query"
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const modelWithQuery = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "query",
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})
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const result = await generateText({
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@ -174,8 +178,10 @@ import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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const modelWithFull = withSupermemory(openai("gpt-4"), "user-123", {
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mode: "full"
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const modelWithFull = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "full",
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})
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const result = await generateText({
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@ -184,38 +190,58 @@ const result = await generateText({
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})
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```
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#### Automatic Memory Capture
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#### RAG with Hybrid Search
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The middleware can automatically save user messages as memories:
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Use `searchMode: "hybrid"` to search both memories AND document chunks (recommended for RAG applications):
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**Always Save Memories** - Automatically stores every user message as a memory:
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```typescript
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import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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const modelWithAutoSave = withSupermemory(openai("gpt-4"), "user-123", {
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addMemory: "always"
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const ragModel = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "full",
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searchMode: "hybrid", // Search both memories and document chunks
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searchLimit: 15, // Return up to 15 results
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})
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const result = await generateText({
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model: ragModel,
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messages: [{ role: "user", content: "What's in my documents about quarterly goals?" }],
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})
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```
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#### Automatic Memory Capture
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The middleware can automatically save conversations as memories:
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**Always Save Memories (Default)** - Automatically stores conversations:
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```typescript
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import { generateText } from "ai"
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import { withSupermemory } from "@supermemory/tools/ai-sdk"
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import { openai } from "@ai-sdk/openai"
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const modelWithAutoSave = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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addMemory: "always",
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})
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const result = await generateText({
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model: modelWithAutoSave,
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messages: [{ role: "user", content: "I prefer React with TypeScript for my projects" }],
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})
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// This message will be automatically saved as a memory
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// This conversation will be automatically saved as a memory
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```
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**Never Save Memories (Default)** - Only retrieves memories without storing new ones:
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**Never Save Memories** - Only retrieves memories without storing new ones:
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```typescript
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const modelWithNoSave = withSupermemory(openai("gpt-4"), "user-123")
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```
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**Combined Options** - Use verbose logging with specific modes and memory storage:
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```typescript
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const modelWithOptions = withSupermemory(openai("gpt-4"), "user-123", {
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mode: "profile",
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addMemory: "always",
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verbose: true
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const modelWithNoSave = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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addMemory: "never",
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})
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```
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@ -239,7 +265,9 @@ ${data.generalSearchMemories}
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</user_memories>
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`.trim()
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const modelWithCustomPrompt = withSupermemory(openai("gpt-4"), "user-123", {
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const modelWithCustomPrompt = withSupermemory(openai("gpt-4"), {
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containerTag: "user-123",
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customId: "conv-456",
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mode: "full",
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promptTemplate: customPrompt,
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})
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@ -646,23 +674,30 @@ Without `strict: true`, optional fields like `includeFullDocs` and `limit` won't
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### withSupermemory Middleware Options
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The `withSupermemory` middleware accepts additional configuration options:
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The `withSupermemory` middleware accepts a model and a configuration object:
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```typescript
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interface WithSupermemoryOptions {
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conversationId?: string
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verbose?: boolean
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mode?: "profile" | "query" | "full"
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addMemory?: "always" | "never"
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/** Optional Supermemory API key. Use this in browser environments. */
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apiKey?: string
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interface WithSupermemoryConfig {
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containerTag: string // Required: User/container identifier for memory scoping
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customId: string // Required: Conversation ID for grouping messages
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verbose?: boolean // Enable detailed logging (default: false)
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mode?: "profile" | "query" | "full" // Memory retrieval mode (default: "profile")
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searchMode?: "memories" | "hybrid" | "documents" // Search mode (default: "memories")
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searchLimit?: number // Max search results for hybrid/documents mode (default: 10)
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addMemory?: "always" | "never" // Auto-save conversations (default: "always")
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apiKey?: string // Supermemory API key (falls back to SUPERMEMORY_API_KEY env var)
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baseUrl?: string // Custom API base URL
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promptTemplate?: (data: MemoryPromptData) => string // Custom memory formatting
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}
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```
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- **conversationId**: Optional conversation ID to group messages into a single document for contextual memory generation
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- **containerTag**: Required. The container tag/identifier for memory search (e.g., user ID, project ID)
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- **customId**: Required. Custom ID to group messages into a single document for contextual memory generation
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- **verbose**: Enable detailed logging of memory search and injection process (default: false)
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- **mode**: Memory search mode - "profile" (default), "query", or "full"
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- **addMemory**: Automatic memory storage mode - "always" or "never" (default: "never")
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- **searchMode**: Search mode - "memories" (default), "hybrid" (memories + chunks), or "documents" (chunks only)
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- **searchLimit**: Maximum number of search results when using hybrid/documents mode (default: 10)
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- **addMemory**: Automatic memory storage mode - "always" (default) or "never"
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## Available Tools
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@ -5,8 +5,12 @@ import type { MemoryMode } from "./types"
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* Generic memory cache for storing per-turn memories to avoid redundant API calls.
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* Used to cache memory retrieval results during tool-call loops within the same turn.
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*/
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export class MemoryCache<T = string> {
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private cache: LRUCache<string, T> = new LRUCache({ max: 100 })
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export class MemoryCache<T extends {} = string> {
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private cache: LRUCache<string, T>
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constructor() {
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this.cache = new LRUCache<string, T>({ max: 100 })
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}
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/**
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* Generates a cache key for the current turn based on context parameters.
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@ -3,6 +3,7 @@ export type {
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MemoryPromptData,
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PromptTemplate,
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MemoryMode,
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SearchMode,
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AddMemoryMode,
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Logger,
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ProfileStructure,
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@ -2,6 +2,7 @@ import { deduplicateMemories } from "../tools-shared"
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import type {
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Logger,
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MemoryMode,
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SearchMode,
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MemoryPromptData,
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ProfileStructure,
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PromptTemplate,
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@ -72,6 +73,15 @@ export interface BuildMemoriesTextOptions {
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apiKey: string
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logger: Logger
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promptTemplate?: PromptTemplate
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/**
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* Search mode for memory retrieval:
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* - "memories": Search only memory entries (default)
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* - "hybrid": Search both memories AND document chunks
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* - "documents": Search only document chunks
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*/
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searchMode?: SearchMode
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/** Maximum number of search results to return (default: 10) */
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searchLimit?: number
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}
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/**
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@ -47,6 +47,14 @@ export type PromptTemplate = (data: MemoryPromptData) => string
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*/
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export type MemoryMode = "profile" | "query" | "full"
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/**
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* Search mode for memory retrieval:
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* - "memories": Search only memory entries (default)
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* - "hybrid": Search both memories AND document chunks (recommended for RAG)
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* - "documents": Search only document chunks
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*/
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export type SearchMode = "memories" | "hybrid" | "documents"
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/**
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* Memory persistence mode:
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* - "always": Automatically save conversations as memories
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@ -12,9 +12,10 @@ import {
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} from "./middleware"
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import type { PromptTemplate, MemoryPromptData } from "./memory-prompt"
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interface WrapVercelLanguageModelOptions<T extends LanguageModel> {
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/** The language model to wrap with supermemory capabilities */
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model: T
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/**
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* Configuration options for Supermemory integration
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*/
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interface WithSupermemoryConfig {
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/** The container tag/identifier for memory search (e.g., user ID, project ID) */
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containerTag: string
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/** Custom ID to group messages into a single document. Required. */
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@ -76,17 +77,17 @@ interface WrapVercelLanguageModelOptions<T extends LanguageModel> {
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* Supports both Vercel AI SDK 5 (LanguageModelV2) and SDK 6 (LanguageModelV3) via runtime
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* detection of `model.specificationVersion`.
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*
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* @param options - Configuration object containing model and Supermemory options
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* @param options.model - The language model to wrap with supermemory capabilities (V2 or V3)
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* @param options.containerTag - Required. The container tag/identifier for memory search (e.g., user ID, project ID)
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* @param options.customId - Required. Custom ID to group messages into a single document
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* @param options.verbose - Optional flag to enable detailed logging of memory search and injection process (default: false)
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* @param options.mode - Optional mode for memory search: "profile", "query", or "full" (default: "profile")
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* @param options.searchMode - Optional search mode: "memories" (default), "hybrid" (memories + chunks), or "documents" (chunks only)
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* @param options.searchLimit - Optional maximum number of search results when using hybrid/documents mode (default: 10)
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* @param options.addMemory - Optional mode for memory persistence: "always" (default - saves conversations), "never" (read-only mode)
|
||||
* @param options.apiKey - Optional Supermemory API key to use instead of the environment variable
|
||||
* @param options.baseUrl - Optional base URL for the Supermemory API (default: "https://api.supermemory.ai")
|
||||
* @param model - The language model to wrap with supermemory capabilities (V2 or V3)
|
||||
* @param config - Configuration object for Supermemory integration
|
||||
* @param config.containerTag - Required. The container tag/identifier for memory search (e.g., user ID, project ID)
|
||||
* @param config.customId - Required. Custom ID to group messages into a single document
|
||||
* @param config.verbose - Optional flag to enable detailed logging of memory search and injection process (default: false)
|
||||
* @param config.mode - Optional mode for memory search: "profile", "query", or "full" (default: "profile")
|
||||
* @param config.searchMode - Optional search mode: "memories" (default), "hybrid" (memories + chunks), or "documents" (chunks only)
|
||||
* @param config.searchLimit - Optional maximum number of search results when using hybrid/documents mode (default: 10)
|
||||
* @param config.addMemory - Optional mode for memory persistence: "always" (default - saves conversations), "never" (read-only mode)
|
||||
* @param config.apiKey - Optional Supermemory API key to use instead of the environment variable
|
||||
* @param config.baseUrl - Optional base URL for the Supermemory API (default: "https://api.supermemory.ai")
|
||||
*
|
||||
* @returns A wrapped language model that automatically includes relevant memories in prompts
|
||||
*
|
||||
|
|
@ -97,23 +98,27 @@ interface WrapVercelLanguageModelOptions<T extends LanguageModel> {
|
|||
* import { generateText } from "ai"
|
||||
*
|
||||
* // Basic usage with profile memories
|
||||
* const modelWithMemory = withSupermemory({
|
||||
* model: openai("gpt-4"),
|
||||
* containerTag: "user-123",
|
||||
* customId: "conv-456",
|
||||
* mode: "full",
|
||||
* addMemory: "always"
|
||||
* })
|
||||
* const modelWithMemory = withSupermemory(
|
||||
* openai("gpt-4"),
|
||||
* {
|
||||
* containerTag: "user-123",
|
||||
* customId: "conv-456",
|
||||
* mode: "full",
|
||||
* addMemory: "always"
|
||||
* }
|
||||
* )
|
||||
*
|
||||
* // RAG usage with hybrid search (memories + document chunks)
|
||||
* const ragModel = withSupermemory({
|
||||
* model: openai("gpt-4"),
|
||||
* containerTag: "user-123",
|
||||
* customId: "conv-789",
|
||||
* mode: "full",
|
||||
* searchMode: "hybrid", // Search both memories and document chunks
|
||||
* searchLimit: 15,
|
||||
* })
|
||||
* const ragModel = withSupermemory(
|
||||
* openai("gpt-4"),
|
||||
* {
|
||||
* containerTag: "user-123",
|
||||
* customId: "conv-789",
|
||||
* mode: "full",
|
||||
* searchMode: "hybrid", // Search both memories and document chunks
|
||||
* searchLimit: 15,
|
||||
* }
|
||||
* )
|
||||
*
|
||||
* const result = await generateText({
|
||||
* model: ragModel,
|
||||
|
|
@ -121,13 +126,14 @@ interface WrapVercelLanguageModelOptions<T extends LanguageModel> {
|
|||
* })
|
||||
* ```
|
||||
*
|
||||
* @throws {Error} When neither `options.apiKey` nor `process.env.SUPERMEMORY_API_KEY` are set
|
||||
* @throws {Error} When neither `config.apiKey` nor `process.env.SUPERMEMORY_API_KEY` are set
|
||||
* @throws {Error} When supermemory API request fails
|
||||
*/
|
||||
const wrapVercelLanguageModel = <T extends LanguageModel>(
|
||||
options: WrapVercelLanguageModelOptions<T>,
|
||||
model: T,
|
||||
config: WithSupermemoryConfig,
|
||||
): T => {
|
||||
const { model, containerTag, customId, ...restOptions } = options
|
||||
const { containerTag, customId, ...restOptions } = config
|
||||
const providedApiKey = restOptions.apiKey ?? process.env.SUPERMEMORY_API_KEY
|
||||
|
||||
if (!providedApiKey) {
|
||||
|
|
@ -149,109 +155,113 @@ const wrapVercelLanguageModel = <T extends LanguageModel>(
|
|||
promptTemplate: restOptions.promptTemplate,
|
||||
})
|
||||
|
||||
const wrappedModel = {
|
||||
...model,
|
||||
// Use Object.create to preserve prototype chain, then copy own properties
|
||||
const wrappedModel = Object.create(
|
||||
Object.getPrototypeOf(model),
|
||||
Object.getOwnPropertyDescriptors(model),
|
||||
) as T
|
||||
|
||||
doGenerate: async (params: LanguageModelCallOptions) => {
|
||||
try {
|
||||
const transformedParams = await transformParamsWithMemory(params, ctx)
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3
|
||||
wrappedModel.doGenerate = async (params: LanguageModelCallOptions): Promise<any> => {
|
||||
try {
|
||||
const transformedParams = await transformParamsWithMemory(params, ctx)
|
||||
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3
|
||||
const result = await model.doGenerate(transformedParams as any)
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3
|
||||
const result = await model.doGenerate(transformedParams as any)
|
||||
|
||||
const userMessage = getLastUserMessage(params)
|
||||
if (
|
||||
ctx.addMemory === "always" &&
|
||||
ctx.customId &&
|
||||
userMessage &&
|
||||
userMessage.trim()
|
||||
) {
|
||||
const assistantResponseText = extractAssistantResponseText(
|
||||
result.content as unknown[],
|
||||
)
|
||||
saveMemoryAfterResponse(
|
||||
ctx.client,
|
||||
ctx.containerTag,
|
||||
ctx.customId,
|
||||
assistantResponseText,
|
||||
params,
|
||||
ctx.logger,
|
||||
ctx.apiKey,
|
||||
ctx.normalizedBaseUrl,
|
||||
)
|
||||
}
|
||||
|
||||
return result
|
||||
} catch (error) {
|
||||
ctx.logger.error("Error generating response", {
|
||||
error: error instanceof Error ? error.message : "Unknown error",
|
||||
})
|
||||
throw error
|
||||
}
|
||||
},
|
||||
|
||||
doStream: async (params: LanguageModelCallOptions) => {
|
||||
let generatedText = ""
|
||||
|
||||
try {
|
||||
const transformedParams = await transformParamsWithMemory(params, ctx)
|
||||
|
||||
const { stream, ...rest } = await model.doStream(
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3
|
||||
transformedParams as any,
|
||||
const userMessage = getLastUserMessage(params)
|
||||
if (
|
||||
ctx.addMemory === "always" &&
|
||||
ctx.customId &&
|
||||
userMessage &&
|
||||
userMessage.trim()
|
||||
) {
|
||||
const assistantResponseText = extractAssistantResponseText(
|
||||
result.content as unknown[],
|
||||
)
|
||||
saveMemoryAfterResponse(
|
||||
ctx.client,
|
||||
ctx.containerTag,
|
||||
ctx.customId,
|
||||
assistantResponseText,
|
||||
params,
|
||||
ctx.logger,
|
||||
ctx.apiKey,
|
||||
ctx.normalizedBaseUrl,
|
||||
)
|
||||
|
||||
const transformStream = new TransformStream<
|
||||
LanguageModelStreamPart,
|
||||
LanguageModelStreamPart
|
||||
>({
|
||||
transform(chunk, controller) {
|
||||
if (chunk.type === "text-delta") {
|
||||
generatedText += chunk.delta
|
||||
}
|
||||
controller.enqueue(chunk)
|
||||
},
|
||||
flush: async () => {
|
||||
const userMessage = getLastUserMessage(params)
|
||||
if (
|
||||
ctx.addMemory === "always" &&
|
||||
ctx.customId &&
|
||||
userMessage &&
|
||||
userMessage.trim()
|
||||
) {
|
||||
saveMemoryAfterResponse(
|
||||
ctx.client,
|
||||
ctx.containerTag,
|
||||
ctx.customId,
|
||||
generatedText,
|
||||
params,
|
||||
ctx.logger,
|
||||
ctx.apiKey,
|
||||
ctx.normalizedBaseUrl,
|
||||
)
|
||||
}
|
||||
},
|
||||
})
|
||||
|
||||
return {
|
||||
stream: stream.pipeThrough(transformStream),
|
||||
...rest,
|
||||
}
|
||||
} catch (error) {
|
||||
ctx.logger.error("Error streaming response", {
|
||||
error: error instanceof Error ? error.message : "Unknown error",
|
||||
})
|
||||
throw error
|
||||
}
|
||||
},
|
||||
} as T
|
||||
|
||||
return result
|
||||
} catch (error) {
|
||||
ctx.logger.error("Error generating response", {
|
||||
error: error instanceof Error ? error.message : "Unknown error",
|
||||
})
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3
|
||||
wrappedModel.doStream = async (params: LanguageModelCallOptions): Promise<any> => {
|
||||
let generatedText = ""
|
||||
|
||||
try {
|
||||
const transformedParams = await transformParamsWithMemory(params, ctx)
|
||||
|
||||
const { stream, ...rest } = await model.doStream(
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3
|
||||
transformedParams as any,
|
||||
)
|
||||
|
||||
const transformStream = new TransformStream<
|
||||
LanguageModelStreamPart,
|
||||
LanguageModelStreamPart
|
||||
>({
|
||||
transform(chunk, controller) {
|
||||
if (chunk.type === "text-delta") {
|
||||
generatedText += chunk.delta
|
||||
}
|
||||
controller.enqueue(chunk)
|
||||
},
|
||||
flush: async () => {
|
||||
const userMessage = getLastUserMessage(params)
|
||||
if (
|
||||
ctx.addMemory === "always" &&
|
||||
ctx.customId &&
|
||||
userMessage &&
|
||||
userMessage.trim()
|
||||
) {
|
||||
saveMemoryAfterResponse(
|
||||
ctx.client,
|
||||
ctx.containerTag,
|
||||
ctx.customId,
|
||||
generatedText,
|
||||
params,
|
||||
ctx.logger,
|
||||
ctx.apiKey,
|
||||
ctx.normalizedBaseUrl,
|
||||
)
|
||||
}
|
||||
},
|
||||
})
|
||||
|
||||
return {
|
||||
stream: stream.pipeThrough(transformStream),
|
||||
...rest,
|
||||
}
|
||||
} catch (error) {
|
||||
ctx.logger.error("Error streaming response", {
|
||||
error: error instanceof Error ? error.message : "Unknown error",
|
||||
})
|
||||
throw error
|
||||
}
|
||||
}
|
||||
|
||||
return wrappedModel
|
||||
}
|
||||
|
||||
export {
|
||||
wrapVercelLanguageModel as withSupermemory,
|
||||
type WrapVercelLanguageModelOptions as WithSupermemoryOptions,
|
||||
type WithSupermemoryConfig,
|
||||
type PromptTemplate,
|
||||
type MemoryPromptData,
|
||||
}
|
||||
|
|
|
|||
|
|
@ -1,144 +1,70 @@
|
|||
import { deduplicateMemories } from "../shared"
|
||||
import type { Logger } from "./logger"
|
||||
import {
|
||||
type LanguageModelCallOptions,
|
||||
convertProfileToMarkdown,
|
||||
type ProfileStructure,
|
||||
} from "./util"
|
||||
// Re-export shared types and functions
|
||||
export {
|
||||
type MemoryPromptData,
|
||||
type PromptTemplate,
|
||||
defaultPromptTemplate,
|
||||
normalizeBaseUrl,
|
||||
buildMemoriesText,
|
||||
type BuildMemoriesTextOptions,
|
||||
} from "../shared"
|
||||
|
||||
export const normalizeBaseUrl = (url?: string): string => {
|
||||
const defaultUrl = "https://api.supermemory.ai"
|
||||
if (!url) return defaultUrl
|
||||
return url.endsWith("/") ? url.slice(0, -1) : url
|
||||
}
|
||||
import type { Logger, MemoryPromptData } from "../shared"
|
||||
import type { LanguageModelCallOptions } from "./util"
|
||||
|
||||
const supermemoryProfileSearch = async (
|
||||
containerTag: string,
|
||||
queryText: string,
|
||||
baseUrl: string,
|
||||
): Promise<ProfileStructure> => {
|
||||
const payload = queryText
|
||||
? JSON.stringify({
|
||||
q: queryText,
|
||||
containerTag: containerTag,
|
||||
})
|
||||
: JSON.stringify({
|
||||
containerTag: containerTag,
|
||||
})
|
||||
|
||||
try {
|
||||
const response = await fetch(`${baseUrl}/v4/profile`, {
|
||||
method: "POST",
|
||||
headers: {
|
||||
"Content-Type": "application/json",
|
||||
Authorization: `Bearer ${process.env.SUPERMEMORY_API_KEY}`,
|
||||
},
|
||||
body: payload,
|
||||
})
|
||||
|
||||
if (!response.ok) {
|
||||
const errorText = await response.text().catch(() => "Unknown error")
|
||||
throw new Error(
|
||||
`Supermemory profile search failed: ${response.status} ${response.statusText}. ${errorText}`,
|
||||
)
|
||||
}
|
||||
|
||||
return await response.json()
|
||||
} catch (error) {
|
||||
if (error instanceof Error) {
|
||||
throw error
|
||||
}
|
||||
throw new Error(`Supermemory API request failed: ${error}`)
|
||||
}
|
||||
}
|
||||
|
||||
export const addSystemPrompt = async (
|
||||
/**
|
||||
* Extracts the query text from params based on mode.
|
||||
* For "profile" mode, returns empty string (no query needed).
|
||||
* For "query" or "full" mode, extracts the last user message text.
|
||||
*
|
||||
* @param params - The language model call options
|
||||
* @param mode - The memory retrieval mode
|
||||
* @returns The query text for memory search
|
||||
*/
|
||||
export const extractQueryText = (
|
||||
params: LanguageModelCallOptions,
|
||||
containerTag: string,
|
||||
logger: Logger,
|
||||
mode: "profile" | "query" | "full",
|
||||
baseUrl = "https://api.supermemory.ai",
|
||||
): Promise<LanguageModelCallOptions> => {
|
||||
): string => {
|
||||
if (mode === "profile") {
|
||||
return ""
|
||||
}
|
||||
|
||||
const userMessage = params.prompt
|
||||
.slice()
|
||||
.reverse()
|
||||
.find((prompt: { role: string }) => prompt.role === "user")
|
||||
|
||||
const content = userMessage?.content
|
||||
if (!content) return ""
|
||||
|
||||
if (typeof content === "string") {
|
||||
return content
|
||||
}
|
||||
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3
|
||||
return (content as any[])
|
||||
.filter((part) => part.type === "text")
|
||||
.map((part) => part.text || "")
|
||||
.join(" ")
|
||||
}
|
||||
|
||||
/**
|
||||
* Injects memories string into params by appending to existing system prompt
|
||||
* or creating a new one. Pure function - does not mutate the original params.
|
||||
*
|
||||
* @param params - The language model call options
|
||||
* @param memories - The formatted memories string to inject
|
||||
* @param logger - Logger for debug output
|
||||
* @returns New params with memories injected into the system prompt
|
||||
*/
|
||||
export const injectMemoriesIntoParams = (
|
||||
params: LanguageModelCallOptions,
|
||||
memories: string,
|
||||
logger: Logger,
|
||||
): LanguageModelCallOptions => {
|
||||
const systemPromptExists = params.prompt.some(
|
||||
(prompt) => prompt.role === "system",
|
||||
)
|
||||
|
||||
const queryText =
|
||||
mode !== "profile"
|
||||
? params.prompt
|
||||
.slice()
|
||||
.reverse()
|
||||
.find((prompt) => prompt.role === "user")
|
||||
?.content?.filter((content) => content.type === "text")
|
||||
?.map((content) => (content.type === "text" ? content.text : ""))
|
||||
?.join(" ") || ""
|
||||
: ""
|
||||
|
||||
const memoriesResponse = await supermemoryProfileSearch(
|
||||
containerTag,
|
||||
queryText,
|
||||
baseUrl,
|
||||
)
|
||||
|
||||
const memoryCountStatic = memoriesResponse.profile.static?.length || 0
|
||||
const memoryCountDynamic = memoriesResponse.profile.dynamic?.length || 0
|
||||
|
||||
logger.info("Memory search completed", {
|
||||
containerTag,
|
||||
memoryCountStatic,
|
||||
memoryCountDynamic,
|
||||
queryText:
|
||||
queryText.substring(0, 100) + (queryText.length > 100 ? "..." : ""),
|
||||
mode,
|
||||
})
|
||||
|
||||
const deduplicated = deduplicateMemories({
|
||||
static: memoriesResponse.profile.static,
|
||||
dynamic: memoriesResponse.profile.dynamic,
|
||||
searchResults: memoriesResponse.searchResults?.results,
|
||||
})
|
||||
|
||||
logger.debug("Memory deduplication completed", {
|
||||
static: {
|
||||
original: memoryCountStatic,
|
||||
deduplicated: deduplicated.static.length,
|
||||
},
|
||||
dynamic: {
|
||||
original: memoryCountDynamic,
|
||||
deduplicated: deduplicated.dynamic.length,
|
||||
},
|
||||
searchResults: {
|
||||
original: memoriesResponse.searchResults.results.length,
|
||||
deduplicated: deduplicated.searchResults?.length,
|
||||
},
|
||||
})
|
||||
|
||||
const profileData =
|
||||
mode !== "query"
|
||||
? convertProfileToMarkdown({
|
||||
profile: {
|
||||
static: deduplicated.static,
|
||||
dynamic: deduplicated.dynamic,
|
||||
},
|
||||
searchResults: { results: [] },
|
||||
})
|
||||
: ""
|
||||
const searchResultsMemories =
|
||||
mode !== "profile"
|
||||
? `Search results for user's recent message: \n${deduplicated.searchResults
|
||||
.map((memory) => `- ${memory}`)
|
||||
.join("\n")}`
|
||||
: ""
|
||||
|
||||
const memories =
|
||||
`User Supermemories: \n${profileData}\n${searchResultsMemories}`.trim()
|
||||
if (memories) {
|
||||
logger.debug("Memory content preview", {
|
||||
content: memories,
|
||||
fullLength: memories.length,
|
||||
})
|
||||
}
|
||||
|
||||
if (systemPromptExists) {
|
||||
logger.debug("Added memories to existing system prompt")
|
||||
// biome-ignore lint/suspicious/noExplicitAny: Union type compatibility between V2 and V3 prompt types
|
||||
|
|
@ -160,3 +86,35 @@ export const addSystemPrompt = async (
|
|||
] as any
|
||||
return { ...params, prompt: newPrompt } as LanguageModelCallOptions
|
||||
}
|
||||
|
||||
/**
|
||||
* Adds memories to the system prompt by fetching from API and injecting.
|
||||
* This is the original combined function, now implemented via helpers.
|
||||
*
|
||||
* @deprecated Prefer using buildMemoriesText + injectMemoriesIntoParams for caching support
|
||||
*/
|
||||
export const addSystemPrompt = async (
|
||||
params: LanguageModelCallOptions,
|
||||
containerTag: string,
|
||||
logger: Logger,
|
||||
mode: "profile" | "query" | "full",
|
||||
baseUrl: string,
|
||||
apiKey: string,
|
||||
promptTemplate?: (data: MemoryPromptData) => string,
|
||||
): Promise<LanguageModelCallOptions> => {
|
||||
const { buildMemoriesText } = await import("../shared")
|
||||
|
||||
const queryText = extractQueryText(params, mode)
|
||||
|
||||
const memories = await buildMemoriesText({
|
||||
containerTag,
|
||||
queryText,
|
||||
mode,
|
||||
baseUrl,
|
||||
apiKey,
|
||||
logger,
|
||||
promptTemplate,
|
||||
})
|
||||
|
||||
return injectMemoriesIntoParams(params, memories, logger)
|
||||
}
|
||||
|
|
|
|||
|
|
@ -82,8 +82,8 @@ const createIntegrationMockModel = () => {
|
|||
reset: () => {
|
||||
capturedGenerateParams = null
|
||||
capturedStreamParams = null
|
||||
vi.mocked(model.doGenerate).mockClear()
|
||||
vi.mocked(model.doStream).mockClear()
|
||||
;(model.doGenerate as any).mockClear()
|
||||
;(model.doStream as any).mockClear()
|
||||
},
|
||||
}
|
||||
}
|
||||
|
|
@ -96,8 +96,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
const { model, getCapturedGenerateParams } =
|
||||
createIntegrationMockModel()
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -126,8 +125,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
|
||||
const customId = `test-generate-${Date.now()}`
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -169,8 +167,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
|
||||
const customId = `test-conversation-${Date.now()}`
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -198,8 +195,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
it("should fetch memories and stream response", async () => {
|
||||
const { model, getCapturedStreamParams } = createIntegrationMockModel()
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-stream-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -236,8 +232,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
|
||||
const customId = `test-stream-${Date.now()}`
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -278,8 +273,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
it("should handle text-delta chunks correctly", async () => {
|
||||
const { model } = createIntegrationMockModel()
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-chunks-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -318,8 +312,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
const { model } = createIntegrationMockModel()
|
||||
const fetchSpy = vi.spyOn(globalThis, "fetch")
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-profile-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -358,8 +351,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
const { model } = createIntegrationMockModel()
|
||||
const fetchSpy = vi.spyOn(globalThis, "fetch")
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-query-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -398,8 +390,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
const { model } = createIntegrationMockModel()
|
||||
const fetchSpy = vi.spyOn(globalThis, "fetch")
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-full-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -444,8 +435,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
generalSearchMemories: string
|
||||
}) => `<custom-memories>${data.userMemories}</custom-memories>`
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-template-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -472,8 +462,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
const { model, getCapturedGenerateParams } =
|
||||
createIntegrationMockModel()
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-verbose-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -500,8 +489,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
const fetchSpy = vi.spyOn(globalThis, "fetch")
|
||||
|
||||
// Use the configured base URL (or default)
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-baseurl-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -537,12 +525,11 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
const { model } = createIntegrationMockModel()
|
||||
|
||||
// Override doGenerate to throw an error
|
||||
vi.mocked(model.doGenerate).mockRejectedValueOnce(
|
||||
;(model.doGenerate as any).mockRejectedValueOnce(
|
||||
new Error("Model error"),
|
||||
)
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-error-${Date.now()}`,
|
||||
apiKey: INTEGRATION_CONFIG.apiKey,
|
||||
|
|
@ -564,8 +551,7 @@ describe.skipIf(!shouldRunIntegration)(
|
|||
it("should handle invalid API key gracefully", async () => {
|
||||
const { model } = createIntegrationMockModel()
|
||||
|
||||
const wrapped = withSupermemory({
|
||||
model,
|
||||
const wrapped = withSupermemory(model, {
|
||||
containerTag: INTEGRATION_CONFIG.containerTag,
|
||||
customId: `test-invalid-key-${Date.now()}`,
|
||||
apiKey: "invalid-api-key-12345",
|
||||
|
|
|
|||
|
|
@ -73,8 +73,7 @@ describe("Unit: withSupermemory", () => {
|
|||
const mockModel = createMockLanguageModel()
|
||||
|
||||
expect(() => {
|
||||
withSupermemory({
|
||||
model: mockModel,
|
||||
withSupermemory(mockModel, {
|
||||
containerTag: TEST_CONFIG.containerTag,
|
||||
customId: "test-conv-123",
|
||||
})
|
||||
|
|
@ -85,8 +84,7 @@ describe("Unit: withSupermemory", () => {
|
|||
process.env.SUPERMEMORY_API_KEY = "test-key"
|
||||
|
||||
const mockModel = createMockLanguageModel()
|
||||
const wrappedModel = withSupermemory({
|
||||
model: mockModel,
|
||||
const wrappedModel = withSupermemory(mockModel, {
|
||||
containerTag: TEST_CONFIG.containerTag,
|
||||
customId: "test-conv-456",
|
||||
})
|
||||
|
|
@ -107,7 +105,10 @@ describe("Unit: withSupermemory", () => {
|
|||
doStream: vi.fn(),
|
||||
}
|
||||
const inner = Object.create(proto) as LanguageModelV2
|
||||
const wrappedModel = withSupermemory(inner, TEST_CONFIG.containerTag)
|
||||
const wrappedModel = withSupermemory(inner, {
|
||||
containerTag: TEST_CONFIG.containerTag,
|
||||
customId: "test-proto",
|
||||
})
|
||||
|
||||
expect(wrappedModel.specificationVersion).toBe("v2")
|
||||
expect(wrappedModel.provider).toBe("gateway")
|
||||
|
|
@ -149,7 +150,7 @@ describe("Unit: withSupermemory", () => {
|
|||
await transformParamsWithMemory(params, ctx)
|
||||
|
||||
expect(ctx.memoryCache).toBeDefined()
|
||||
const turnKey = `${TEST_CONFIG.containerTag}::profile:Hello`
|
||||
const turnKey = `${TEST_CONFIG.containerTag}:test-cache-123:profile:Hello`
|
||||
const cachedMemories = ctx.memoryCache.get(turnKey)
|
||||
expect(cachedMemories).toBeDefined()
|
||||
expect(cachedMemories).toContain("Cached memory")
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue