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refactor(server): drop stale prompt text, duplicated routes and dead options

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- lib/system-prompts.ts: delete the extended prompt kept only to reach
  the 4096-token cache threshold of two old Claude models; describe the
  current canvas-first UI in the App Features section
- app/api/chat/route.ts: remove the server-side example cache (the
  browser answers examples itself), the ENABLE_HISTORY_XML_REPLACE
  option and its helper, the unread messageMetadata fields; the
  DEBUG_LLM_PAYLOAD blocks become one describeMessages summary
- app/api/log-feedback and log-save share scoreLatestTrace in
  lib/langfuse.ts
- app/api/admin/test-model and validate-model call a shared
  testModelConnection() instead of one route faking a request to the
  other and passing trust through the body
- lib/dynamo-quota-manager.ts reads the failing item from the
  conditional update instead of a second GetItem
- lib/ai-providers.ts: geminiThinkingOptions helper for the google and
  vertexai cases, drop the unused fourth resolveBaseURL parameter
- edge-functions: always stream, shrink messageSchema, drop model
  aliases nothing sends
- delete app/api/chat/xml_guide.md, parseOutputTokenLimit, unused type
  exports and export keywords on file-internal symbols
- env.example: drop variables nothing reads, document the quota,
  validation and analytics variables, mention the apiKeyEnv array form
  (also in docs/*/ai-providers.md)
This commit is contained in:
dayuan.jiang
2026-10-12 08:15:15 +09:00
parent 610ba6872d
commit 8ca2d03e7f
36 changed files with 694 additions and 1505 deletions
Download Patch File Download Diff File Expand all files Collapse all files
app/api/admin/test-model/route.ts
+19 -32
View File
@@ -1,4 +1,3 @@
import { POST as validateModel } from "@/app/api/validate-model/route"
import { checkAdminAuth } from "@/lib/admin/auth" import { checkAdminAuth } from "@/lib/admin/auth"
import { import {
AdminProviderSchema, AdminProviderSchema,
@@ -6,6 +5,7 @@ import {
mergeSecrets, mergeSecrets,
} from "@/lib/admin/providers" } from "@/lib/admin/providers"
import { globalBaseUrl } from "@/lib/ai-providers" import { globalBaseUrl } from "@/lib/ai-providers"
import { testModelConnection } from "@/lib/test-model-connection"
export const runtime = "nodejs" export const runtime = "nodejs"
export const dynamic = "force-dynamic" export const dynamic = "force-dynamic"
@@ -48,37 +48,24 @@ export async function POST(req: Request) {
sameEndpoint && stored ? [stored] : [], sameEndpoint && stored ? [stored] : [],
) )
// Without a URL of its own, chat sends the entry's key to the server's
// <P>_BASE_URL: test that endpoint, not another one. It is the server's
// own, which chat uses without the checks for a URL a user typed.
// The admin's own request supplies the EdgeOne endpoint, cookies and
// access code, as a chat request would.
const serverUrl = globalBaseUrl(resolved.provider) const serverUrl = globalBaseUrl(resolved.provider)
return validateModel( return testModelConnection(
new Request(new URL("/api/validate-model", req.url), { req,
method: "POST", {
headers: { provider: resolved.provider,
"Content-Type": "application/json", apiKey: resolved.apiKey,
// Checked again there, in place of an access code baseUrl: resolved.baseUrl || serverUrl,
"x-admin-password": req.headers.get("x-admin-password") || "", modelId: body.modelId,
// The EdgeOne function checks the access code and Pages awsAccessKeyId: resolved.awsAccessKeyId,
// cookies, and its URL is built from the page's origin awsSecretAccessKey: resolved.awsSecretAccessKey,
"x-access-code": req.headers.get("x-access-code") || "", awsRegion: resolved.awsRegion,
cookie: req.headers.get("cookie") || "", vertexApiKey: resolved.vertexApiKey,
...(req.headers.get("origin") && { },
origin: req.headers.get("origin") as string, !resolved.baseUrl && !!serverUrl,
}),
},
body: JSON.stringify({
provider: resolved.provider,
apiKey: resolved.apiKey,
// Without a URL of its own, chat sends the entry's key to
// the server's <P>_BASE_URL: test that endpoint, not
// another one. It is the server's own, which chat uses
// without the checks for a URL a user typed.
baseUrl: resolved.baseUrl || serverUrl,
...(!resolved.baseUrl && serverUrl && { serverBaseUrl: true }),
modelId: body.modelId,
awsAccessKeyId: resolved.awsAccessKeyId,
awsSecretAccessKey: resolved.awsSecretAccessKey,
awsRegion: resolved.awsRegion,
vertexApiKey: resolved.vertexApiKey,
}),
}),
) )
} }
app/api/chat/route.ts
+26 -132
View File
@@ -1,8 +1,6 @@
import { import {
APICallError, APICallError,
convertToModelMessages, convertToModelMessages,
createUIMessageStream,
createUIMessageStreamResponse,
InvalidToolInputError, InvalidToolInputError,
stepCountIs, stepCountIs,
streamText, streamText,
@@ -21,12 +19,10 @@ import {
usesServerCredentials, usesServerCredentials,
usesServerEndpoint, usesServerEndpoint,
} from "@/lib/ai-providers" } from "@/lib/ai-providers"
import { findCachedResponse } from "@/lib/cached-responses"
import { import {
dropInvalidToolCalls, dropInvalidToolCalls,
fixToolInputJson, fixToolInputJson,
formatSelectionContext, formatSelectionContext,
replaceHistoricalToolInputs,
validateFileParts, validateFileParts,
} from "@/lib/chat-helpers" } from "@/lib/chat-helpers"
import { withDeprecatedParamsFallback } from "@/lib/deprecated-params" import { withDeprecatedParamsFallback } from "@/lib/deprecated-params"
@@ -56,7 +52,6 @@ import { getSystemPrompt } from "@/lib/system-prompts"
import { normalizeBaseUrl } from "@/lib/types/model-config" import { normalizeBaseUrl } from "@/lib/types/model-config"
import { getUserIdFromRequest } from "@/lib/user-id" import { getUserIdFromRequest } from "@/lib/user-id"
import { foldCells } from "@/packages/mcp-server/src/compact-cells.ts" import { foldCells } from "@/packages/mcp-server/src/compact-cells.ts"
import { hasCells } from "@/packages/mcp-server/src/pages.ts"
import { import {
getShapeLibrary, getShapeLibrary,
SHAPE_LIBRARY_LIST, SHAPE_LIBRARY_LIST,
@@ -70,36 +65,6 @@ import {
// the tool call, so take whatever the host allows. Vercel's own default is 300s, // the tool call, so take whatever the host allows. Vercel's own default is 300s,
// which is also where Node's response-body timeout on the upstream stream lands. // which is also where Node's response-body timeout on the upstream stream lands.
// Helper function to create cached stream response
function createCachedStreamResponse(xml: string): Response {
const toolCallId = `cached-${Date.now()}`
const stream = createUIMessageStream({
execute: async ({ writer }) => {
writer.write({ type: "start" })
writer.write({
type: "tool-input-start",
toolCallId,
toolName: "display_diagram",
})
writer.write({
type: "tool-input-delta",
toolCallId,
inputTextDelta: xml,
})
writer.write({
type: "tool-input-available",
toolCallId,
toolName: "display_diagram",
input: { xml },
})
writer.write({ type: "finish" })
},
})
return createUIMessageStreamResponse({ stream })
}
// Responses streamed from the model, whose trace streamText's callbacks end // Responses streamed from the model, whose trace streamText's callbacks end
const modelStreamResponses = new WeakSet<Response>() const modelStreamResponses = new WeakSet<Response>()
// A Request's signal follows the client's disconnect only while the Request // A Request's signal follows the client's disconnect only while the Request
@@ -111,6 +76,21 @@ const requestOfResponse = new WeakMap<Response, Request>()
// Inner handler function // Inner handler function
const DEBUG_LLM_PAYLOAD = process.env.DEBUG_LLM_PAYLOAD === "true" const DEBUG_LLM_PAYLOAD = process.env.DEBUG_LLM_PAYLOAD === "true"
// Message structure for DEBUG_LLM_PAYLOAD logs: roles, part types, tool names
// and input keys, without the diagram XML or image data
const describeMessages = (msgs: any[]) =>
msgs.map((m) => ({
role: m.role,
parts: (m.parts ?? m.content ?? []).map(
(p: any) =>
p.type +
(p.toolName ? `:${p.toolName}` : "") +
(p.input && typeof p.input === "object"
? `(${Object.keys(p.input).join(",")})`
: ""),
),
}))
async function handleChatRequest(req: Request): Promise<Response> { async function handleChatRequest(req: Request): Promise<Response> {
const crossSite = rejectCrossSite(req) const crossSite = rejectCrossSite(req)
if (crossSite) return crossSite if (crossSite) return crossSite
@@ -156,23 +136,6 @@ async function handleChatRequest(req: Request): Promise<Response> {
} }
// === FILE VALIDATION END === // === FILE VALIDATION END ===
// === CACHE CHECK START ===
const isFirstMessage = messages.length === 1
const isEmptyDiagram = !xml || !hasCells(xml)
if (isFirstMessage && isEmptyDiagram) {
const lastMessage = messages[0]
const textPart = lastMessage.parts?.find((p: any) => p.type === "text")
const filePart = lastMessage.parts?.find((p: any) => p.type === "file")
const cached = findCachedResponse(textPart?.text || "", !!filePart)
if (cached) {
return createCachedStreamResponse(cached.xml)
}
}
// === CACHE CHECK END ===
// Read client AI provider overrides from headers // Read client AI provider overrides from headers
const provider = req.headers.get("x-ai-provider") const provider = req.headers.get("x-ai-provider")
let baseUrl = req.headers.get("x-ai-base-url") let baseUrl = req.headers.get("x-ai-base-url")
@@ -348,7 +311,7 @@ async function handleChatRequest(req: Request): Promise<Response> {
`[Prompt Caching] ${shouldCache ? "ENABLED" : "DISABLED"} for model: ${modelId}`, `[Prompt Caching] ${shouldCache ? "ENABLED" : "DISABLED"} for model: ${modelId}`,
) )
// Get the appropriate system prompt based on model (extended for Opus/Haiku 4.5) // System prompt, with the model name filled in and the style section chosen
const systemMessage = getSystemPrompt(modelId, minimalStyle) const systemMessage = getSystemPrompt(modelId, minimalStyle)
const finalSystemMessage = customSystemMessage const finalSystemMessage = customSystemMessage
? `${systemMessage}\n\n## Custom Instructions\n${customSystemMessage}` ? `${systemMessage}\n\n## Custom Instructions\n${customSystemMessage}`
@@ -380,47 +343,15 @@ ${userInputText}
// DEBUG_LLM_PAYLOAD=true logs the incoming message structure // DEBUG_LLM_PAYLOAD=true logs the incoming message structure
if (DEBUG_LLM_PAYLOAD) { if (DEBUG_LLM_PAYLOAD) {
console.log("[route.ts] Incoming messages count:", messages.length) console.log(
messages.forEach((msg: any, idx: number) => { "[route.ts] incoming",
console.log( JSON.stringify(describeMessages(messages)),
`[route.ts] Message ${idx} role:`, )
msg.role,
"parts count:",
msg.parts?.length,
)
if (msg.parts) {
msg.parts.forEach((part: any, partIdx: number) => {
if (
part.type === "tool-invocation" ||
part.type === "tool-result"
) {
console.log(`[route.ts] Part ${partIdx}:`, {
type: part.type,
toolName: part.toolName,
hasInput: !!part.input,
inputType: typeof part.input,
inputKeys:
part.input && typeof part.input === "object"
? Object.keys(part.input)
: null,
})
}
})
}
})
} }
// Replace historical tool call XML with placeholders to reduce tokens
// Disabled by default - some models (e.g. minimax) copy placeholders instead of generating XML
const enableHistoryReplace =
process.env.ENABLE_HISTORY_XML_REPLACE === "true"
const placeholderMessages = enableHistoryReplace
? replaceHistoricalToolInputs(modelMessages)
: modelMessages
// Filter out messages with empty content arrays (Bedrock API rejects these) // Filter out messages with empty content arrays (Bedrock API rejects these)
// This is a safety measure - ideally convertToModelMessages should handle all cases // This is a safety measure - ideally convertToModelMessages should handle all cases
let enhancedMessages = placeholderMessages.filter( let enhancedMessages = modelMessages.filter(
(msg: any) => (msg: any) =>
msg.content && Array.isArray(msg.content) && msg.content.length > 0, msg.content && Array.isArray(msg.content) && msg.content.length > 0,
) )
@@ -432,36 +363,10 @@ ${userInputText}
// DEBUG_LLM_PAYLOAD=true logs what is sent to the model // DEBUG_LLM_PAYLOAD=true logs what is sent to the model
if (DEBUG_LLM_PAYLOAD) { if (DEBUG_LLM_PAYLOAD) {
console.log("[route.ts] Model messages count:", enhancedMessages.length) console.log(
enhancedMessages.forEach((msg: any, idx: number) => { "[route.ts] to model",
console.log( JSON.stringify(describeMessages(enhancedMessages)),
`[route.ts] ModelMsg ${idx} role:`, )
msg.role,
"content count:",
msg.content?.length,
)
if (msg.content) {
msg.content.forEach((part: any, partIdx: number) => {
if (
part.type === "tool-call" ||
part.type === "tool-result"
) {
console.log(`[route.ts] Content ${partIdx}:`, {
type: part.type,
toolName: part.toolName,
hasInput: !!part.input,
inputType: typeof part.input,
inputValue:
part.input === undefined
? "undefined"
: part.input === null
? "null"
: "object",
})
}
})
}
})
} }
// Update the last message with user input only (XML moved to separate cached system message) // Update the last message with user input only (XML moved to separate cached system message)
@@ -790,17 +695,6 @@ Call this tool to get shape names and usage syntax for a specific library.`,
// Keyless endpoints keep theirs: the desktop app's Ollama is the // Keyless endpoints keep theirs: the desktop app's Ollama is the
// user's own, and EdgeOne's text is our function's explanation. // user's own, and EdgeOne's text is our function's explanation.
onError: (error) => streamErrorText(error, onServerCredentials), onError: (error) => streamErrorText(error, onServerCredentials),
messageMetadata: ({ part }) => {
if (part.type === "finish") {
const usage = (part as any).totalUsage
// AI SDK 6 provides totalTokens directly
return {
totalTokens: usage?.totalTokens ?? 0,
finishReason: (part as any).finishReason,
}
}
return undefined
},
}) })
modelStreamResponses.add(response) modelStreamResponses.add(response)
requestOfResponse.set(response, req) requestOfResponse.set(response, req)
@@ -840,7 +734,7 @@ async function safeHandler(req: Request): Promise<Response> {
} catch (error) { } catch (error) {
response = handleError(error) response = handleError(error)
} }
// Early returns, cache hits and errors never reach streamText's callbacks, // Early returns and errors never reach streamText's callbacks,
// so their Langfuse trace has to be ended here // so their Langfuse trace has to be ended here
if (!modelStreamResponses.has(response)) endTrace() if (!modelStreamResponses.has(response)) endTrace()
return response return response
app/api/chat/xml_guide.md
-321
View File
@@ -1,321 +0,0 @@
# Draw.io XML Schema Guide
This guide explains the structure of draw.io (diagrams.net) XML files to help you understand and create diagrams programmatically.
## Basic Structure
A draw.io XML file has the following hierarchy:
```xml
<mxfile>
<diagram>
<mxGraphModel>
<root>
<mxCell /> <!-- Cells that make up the diagram -->
</root>
</mxGraphModel>
</diagram>
</mxfile>
```
## Root Element: `<mxfile>`
The root element of a draw.io file.
**Attributes:**
- `host`: The application that created the file (e.g., "app.diagrams.net")
- `modified`: Last modification timestamp
- `agent`: Browser / user agent information
- `version`: Version of the application
- `type`: File type (usually "device" or "google")
**Example:**
```xml
<mxfile host="app.diagrams.net" modified="2023-07-14T10:20:30.123Z" agent="Mozilla/5.0" version="21.5.2" type="device">
```
## Diagram Element: `<diagram>`
Each page in your draw.io document is represented by a `<diagram>` element.
**Attributes:**
- `id`: Unique identifier for the diagram
- `name`: The name of the diagram / page
**Example:**
```xml
<diagram id="pWHN0msd4Ud1ZK5cD-Hr" name="Page-1">
```
## Graph Model: `<mxGraphModel>`
Contains the actual diagram data.
**Attributes:**
- `dx`: Grid size in x-direction (usually 1)
- `dy`: Grid size in y-direction (usually 1)
- `grid`: Whether grid is enabled (0 or 1)
- `gridSize`: Grid cell size (usually 10)
- `guides`: Whether guides are enabled (0 or 1)
- `tooltips`: Whether tooltips are enabled (0 or 1)
- `connect`: Whether connections are enabled (0 or 1)
- `arrows`: Whether arrows are enabled (0 or 1)
- `fold`: Whether folding is enabled (0 or 1)
- `page`: Whether page view is enabled (0 or 1)
- `pageScale`: Scale of the page (usually 1)
- `pageWidth`: Width of the page (e.g., 850)
- `pageHeight`: Height of the page (e.g., 1100)
- `math`: Whether math typesetting is enabled (0 or 1)
- `shadow`: Whether shadows are enabled (0 or 1)
**Example:**
```xml
<mxGraphModel dx="1" dy="1" grid="1" gridSize="10" guides="1" tooltips="1" connect="1" arrows="1" fold="1" page="1" pageScale="1" pageWidth="850" pageHeight="1100" math="0" shadow="0">
```
## Root Cell Container: `<root>`
Contains all the cells in the diagram. **Note:** When generating diagrams, you only need to provide the mxCell elements - the root container and root cells (id="0", id="1") are added automatically.
**Internal structure (auto-generated):**
```xml
<root>
<mxCell id="0"/> <!-- Auto-added -->
<mxCell id="1" parent="0"/> <!-- Auto-added -->
<!-- Your mxCell elements go here (start from id="2") -->
</root>
```
## Cell Elements: `<mxCell>`
The basic building block of diagrams. Cells represent shapes, connectors, text, etc.
**Attributes for all cells:**
- `id`: Unique identifier for the cell
- `parent`: ID of the parent cell (typically "1" for most cells)
- `value`: Text content of the cell
- `style`: Styling information (see Style section below)
**Attributes for shapes (vertices):**
- `vertex`: Set to "1" for shapes
- `connectable`: Whether the shape can be connected (0 or 1)
**Attributes for connectors (edges):**
- `edge`: Set to "1" for connectors
- `source`: ID of the source cell
- `target`: ID of the target cell
**Example (Rectangle shape):**
```xml
<mxCell id="2" value="Hello World" style="rounded=0;whiteSpace=wrap;html=1;" vertex="1" parent="1">
<mxGeometry x="350" y="190" width="120" height="60" as="geometry"/>
</mxCell>
```
**Example (Connector):**
```xml
<mxCell id="3" value="" style="endArrow=classic;html=1;rounded=0;" edge="1" parent="1" source="2" target="4">
<mxGeometry width="50" height="50" relative="1" as="geometry">
<mxPoint x="400" y="430" as="sourcePoint"/>
<mxPoint x="450" y="380" as="targetPoint"/>
</mxGeometry>
</mxCell>
```
## Geometry: `<mxGeometry>`
Defines the position and dimensions of cells.
**Attributes for shapes:**
- `x`: The x-coordinate of the **top-left** point of the shape.
- `y`: The y-coordinate of the **top-left** point of the shape.
- `width`: The width of the shape.
- `height`: The height of the shape.
- `as`: Specifies the role of this geometry within its parent cell. Typically set to `"geometry"` for the main shape definition.
**Attributes for connectors:**
- `relative`: Set to "1" for relative geometry
- `as`: Set to "geometry"
**Example for shapes:**
```xml
<mxGeometry x="350" y="190" width="120" height="60" as="geometry"/>
```
**Example for connectors:**
```xml
<mxGeometry width="50" height="50" relative="1" as="geometry">
<mxPoint x="400" y="430" as="sourcePoint"/>
<mxPoint x="450" y="380" as="targetPoint"/>
</mxGeometry>
```
## Cell Style Reference
Styles are specified as semicolon-separated `key=value` pairs in the `style` attribute of `<mxCell>` elements.
### Shape-specific Styles
- Rectangle: `shape=rectangle`
- Ellipse: `shape=ellipse`
- Triangle: `shape=triangle`
- Rhombus: `shape=rhombus`
- Hexagon: `shape=hexagon`
- Cloud: `shape=cloud`
- Actor: `shape=actor`
- Cylinder: `shape=cylinder`
- Document: `shape=document`
- Note: `shape=note`
- Card: `shape=card`
- Parallelogram: `shape=parallelogram`
### Connector Styles
- `endArrow=classic`: Arrow type at the end (classic, open, oval, diamond, block)
- `startArrow=none`: Arrow type at the start (none, classic, open, oval, diamond)
- `curved=1`: Curved connector (0 or 1)
- `edgeStyle=orthogonalEdgeStyle`: Connector routing style
- `elbow=vertical`: Elbow direction (vertical, horizontal)
- `jumpStyle=arc`: Jump style for line crossing (arc, gap)
- `jumpSize=10`: Size of the jump
## Special Cells
Draw.io files contain two special cells that are always present:
1. **Root Cell** (id = "0"): The parent of all cells
2. **Default Parent Cell** (id = "1", parent = "0"): The default layer and parent for most cells
## Tips for Creating Draw.io XML
1. **Generate ONLY mxCell elements** - wrapper tags and root cells (id="0", id="1") are added automatically
2. Start IDs from "2" (id="0" and id="1" are reserved for root cells)
3. Assign unique and sequential IDs to all cells
4. Define parent relationships correctly (use parent="1" for top-level shapes)
5. Use `mxGeometry` elements to position shapes
6. For connectors, specify `source` and `target` attributes
7. **CRITICAL: All mxCell elements must be siblings. NEVER nest mxCell inside another mxCell.**
## Common Patterns
### Grouping Elements
To group elements, create a parent cell and set other cells' `parent` attribute to its ID:
```xml
<!-- Group container -->
<mxCell id="10" value="Group" style="group" vertex="1" connectable="0" parent="1">
<mxGeometry x="200" y="200" width="200" height="100" as="geometry" />
</mxCell>
<!-- Elements inside the group -->
<mxCell id="11" value="Element 1" style="rounded=0;whiteSpace=wrap;html=1;" vertex="1" parent="10">
<mxGeometry width="90" height="40" as="geometry" />
</mxCell>
<mxCell id="12" value="Element 2" style="rounded=0;whiteSpace=wrap;html=1;" vertex="1" parent="10">
<mxGeometry x="110" width="90" height="40" as="geometry" />
</mxCell>
```
### Swimlanes
Swimlanes use the `swimlane` shape style. **IMPORTANT: All mxCell elements (swimlanes, steps, and edges) must be siblings under `<root>`. Edges are NOT nested inside swimlanes or steps.**
```xml
<root>
<mxCell id="0"/>
<mxCell id="1" parent="0"/>
<!-- Swimlane 1 -->
<mxCell id="lane1" value="Frontend" style="swimlane;startSize=30;" vertex="1" parent="1">
<mxGeometry x="40" y="40" width="200" height="300" as="geometry"/>
</mxCell>
<!-- Swimlane 2 -->
<mxCell id="lane2" value="Backend" style="swimlane;startSize=30;" vertex="1" parent="1">
<mxGeometry x="280" y="40" width="200" height="300" as="geometry"/>
</mxCell>
<!-- Step inside lane1 (parent="lane1") -->
<mxCell id="step1" value="Send Request" style="rounded=1;" vertex="1" parent="lane1">
<mxGeometry x="20" y="60" width="160" height="40" as="geometry"/>
</mxCell>
<!-- Step inside lane2 (parent="lane2") -->
<mxCell id="step2" value="Process" style="rounded=1;" vertex="1" parent="lane2">
<mxGeometry x="20" y="60" width="160" height="40" as="geometry"/>
</mxCell>
<!-- Edge connecting step1 to step2 (sibling element, NOT nested inside steps) -->
<mxCell id="edge1" style="edgeStyle=orthogonalEdgeStyle;endArrow=classic;" edge="1" parent="1" source="step1" target="step2">
<mxGeometry relative="1" as="geometry"/>
</mxCell>
</root>
```
### Tables
Tables use multiple cells with parent-child relationships:
```xml
<mxCell id="30" value="Table" style="shape=table;startSize=30;container=1;collapsible=1;childLayout=tableLayout;fixedRows=1;rowLines=0;fontStyle=1;align=center;resizeLast=1;html=1;" vertex="1" parent="1">
<mxGeometry x="200" y="200" width="180" height="120" as="geometry" />
</mxCell>
<mxCell id="31" value="" style="shape=tableRow;horizontal=0;startSize=0;swimlaneHead=0;swimlaneBody=0;fillColor=none;collapsible=0;dropTarget=0;points=[0,0.5,1,0.5];portConstraint=eastwest;top=0;left=0;right=0;bottom=1;" vertex="1" parent="30">
<mxGeometry y="30" width="180" height="30" as="geometry" />
</mxCell>
```
## Advanced Features
### Custom Attributes
Draw.io allows adding custom attributes to cells:
```xml
<mxCell id="40" value="Custom Element" style="rounded=0;whiteSpace=wrap;html=1;" vertex="1" parent="1">
<mxGeometry x="200" y="200" width="120" height="60" as="geometry"/>
<Object label="Custom Label" customAttr="value" />
</mxCell>
```
These custom attributes can store additional metadata or be used by plugins and custom behaviors.
### User-defined Styles
You can define custom styles for cells by combining various style attributes:
```xml
<mxCell id="50" value="Custom Styled Cell"
style="shape=hexagon;perimeter=hexagonPerimeter2;whiteSpace=wrap;html=1;fixedSize=1;fillColor=#f8cecc;strokeColor=#b85450;strokeWidth=2;fontSize=14;fontStyle=1"
vertex="1" parent="1">
<mxGeometry x="300" y="200" width="120" height="80" as="geometry"/>
</mxCell>
```
### Layers
You can create multiple layers in a diagram to organize complex diagrams:
```xml
<!-- Default layer (always present) -->
<mxCell id="1" parent="0"/>
<!-- Additional custom layer -->
<mxCell id="60" value="Layer 2" style="locked=0;group=" parent="0"/>
<!-- Elements in Layer 2 -->
<mxCell id="61" value="Element in Layer 2" style="rounded=0;whiteSpace=wrap;html=1;" vertex="1" parent="60">
<mxGeometry x="200" y="300" width="120" height="60" as="geometry"/>
</mxCell>
```
app/api/log-feedback/route.ts
+16 -68
View File
@@ -1,6 +1,5 @@
import { randomUUID } from "crypto"
import { z } from "zod" import { z } from "zod"
import { getLangfuseClient } from "@/lib/langfuse" import { getLangfuseClient, scoreLatestTrace } from "@/lib/langfuse"
import { getUserIdFromRequest } from "@/lib/user-id" import { getUserIdFromRequest } from "@/lib/user-id"
const feedbackSchema = z.object({ const feedbackSchema = z.object({
@@ -37,75 +36,24 @@ export async function POST(req: Request) {
const userId = getUserIdFromRequest(req) const userId = getUserIdFromRequest(req)
try { try {
// Find the most recent chat trace for this session to attach the score to // Score the session's latest chat trace; without one, a standalone
const tracesResponse = await langfuse.api.trace.list({ // feedback trace carries the score
await scoreLatestTrace(langfuse, {
sessionId, sessionId,
limit: 1, name: "user-feedback",
value: feedback === "good" ? 1 : 0,
comment: `User gave ${feedback} feedback`,
fallbackTrace: {
name: "user-feedback",
userId,
input: { messageId, feedback },
metadata: {
source: "feedback-button",
note: "standalone - no chat trace found",
},
},
}) })
const traces = tracesResponse.data || []
const latestTrace = traces[0]
if (!latestTrace) {
// No trace found for this session - create a standalone feedback trace
const traceId = randomUUID()
const timestamp = new Date().toISOString()
await langfuse.api.ingestion.batch({
batch: [
{
type: "trace-create",
id: randomUUID(),
timestamp,
body: {
id: traceId,
name: "user-feedback",
sessionId,
userId,
input: { messageId, feedback },
metadata: {
source: "feedback-button",
note: "standalone - no chat trace found",
},
timestamp,
},
},
{
type: "score-create",
id: randomUUID(),
timestamp,
body: {
id: randomUUID(),
traceId,
name: "user-feedback",
value: feedback === "good" ? 1 : 0,
comment: `User gave ${feedback} feedback`,
},
},
],
})
} else {
// Attach score to the existing chat trace
const timestamp = new Date().toISOString()
await langfuse.api.ingestion.batch({
batch: [
{
type: "score-create",
id: randomUUID(),
timestamp,
body: {
id: randomUUID(),
traceId: latestTrace.id,
name: "user-feedback",
value: feedback === "good" ? 1 : 0,
comment: `User gave ${feedback} feedback`,
},
},
],
})
}
return Response.json({ success: true, logged: true }) return Response.json({ success: true, logged: true })
} catch (error) { } catch (error) {
console.error("Langfuse feedback error:", error) console.error("Langfuse feedback error:", error)
app/api/log-save/route.ts
+8 -32
View File
@@ -1,6 +1,5 @@
import { randomUUID } from "crypto"
import { z } from "zod" import { z } from "zod"
import { getLangfuseClient } from "@/lib/langfuse" import { getLangfuseClient, scoreLatestTrace } from "@/lib/langfuse"
const saveSchema = z.object({ const saveSchema = z.object({
filename: z.string().min(1).max(255), filename: z.string().min(1).max(255),
@@ -33,39 +32,16 @@ export async function POST(req: Request) {
} }
try { try {
const timestamp = new Date().toISOString() // Flag the session's latest chat trace as saved; a session without a
// trace (no chat yet) is skipped
// Find the most recent chat trace for this session to attach the save flag const logged = await scoreLatestTrace(langfuse, {
const tracesResponse = await langfuse.api.trace.list({
sessionId, sessionId,
limit: 1, name: "diagram-saved",
value: 1,
comment: `User saved diagram as ${filename}.${format}`,
}) })
const traces = tracesResponse.data || [] return Response.json({ success: true, logged })
const latestTrace = traces[0]
if (latestTrace) {
// Add a score to the existing trace to flag that user saved
await langfuse.api.ingestion.batch({
batch: [
{
type: "score-create",
id: randomUUID(),
timestamp,
body: {
id: randomUUID(),
traceId: latestTrace.id,
name: "diagram-saved",
value: 1,
comment: `User saved diagram as ${filename}.${format}`,
},
},
],
})
}
// If no trace found, skip logging (user hasn't chatted yet)
return Response.json({ success: true, logged: !!latestTrace })
} catch (error) { } catch (error) {
console.error("Langfuse save error:", error) console.error("Langfuse save error:", error)
return Response.json( return Response.json(
app/api/server-models/route.ts
+1 -4
View File
@@ -7,8 +7,5 @@ export const dynamic = "force-dynamic"
export async function GET() { export async function GET() {
const models = await loadFlattenedServerModels() const models = await loadFlattenedServerModels()
return NextResponse.json({ return NextResponse.json({ models })
models,
hasConfig: models.length > 0,
})
} }
app/api/validate-model/route.ts
+13 -233
View File
@@ -1,249 +1,29 @@
import { streamText, tool } from "ai"
import { NextResponse } from "next/server" import { NextResponse } from "next/server"
import { z } from "zod"
import { checkAccessCode, rejectCrossSite } from "@/lib/access-code" import { checkAccessCode, rejectCrossSite } from "@/lib/access-code"
import { checkAdminAuth } from "@/lib/admin/auth"
import { import {
edgeOneEndpoint, type TestModelRequest,
getAIModel, testModelConnection,
globalBaseUrl, } from "@/lib/test-model-connection"
usesServerCredentials,
usesServerEndpoint,
} from "@/lib/ai-providers"
import {
checkAndIncrementRequest,
isQuotaEnabled,
} from "@/lib/dynamo-quota-manager"
import { classifyLLMError } from "@/lib/llm-errors"
import { allowPrivateUrls, isPrivateUrl } from "@/lib/ssrf-protection"
import { normalizeBaseUrl, type ProviderName } from "@/lib/types/model-config"
import { getUserIdFromRequest } from "@/lib/user-id"
export const runtime = "nodejs" export const runtime = "nodejs"
interface ValidateRequest { // The Settings dialog's Test button: a model on the user's own credentials
provider: ProviderName
apiKey: string
baseUrl?: string
modelId: string
// AWS Bedrock specific
awsAccessKeyId?: string
awsSecretAccessKey?: string
awsRegion?: string
awsSessionToken?: string
// Vertex AI specific
vertexApiKey?: string // Express Mode API key
// Set by the admin panel's Test: baseUrl is the server's <P>_BASE_URL
serverBaseUrl?: boolean
}
const TEST_TIMEOUT_MS = 15_000
// Drawing works through tool calls, so the test asks for one
const PING_TOOL = tool({
description: "Report that the connection works.",
inputSchema: z.object({}),
})
const NO_TOOL_CALL_WARNING =
"Connected, but the model answered without calling a tool. It may not support tool calls, which drawing needs."
export async function POST(req: Request) { export async function POST(req: Request) {
const crossSite = rejectCrossSite(req) const crossSite = rejectCrossSite(req)
if (crossSite) return crossSite if (crossSite) return crossSite
// Lets the server send requests to arbitrary URLs, so require the access // Lets the server send requests to arbitrary URLs, so require the access code
// code, or the admin password (the admin panel's Test button)
const accessError = checkAccessCode(req) const accessError = checkAccessCode(req)
if (accessError && checkAdminAuth(req)) return accessError if (accessError) return accessError
let body: TestModelRequest
try { try {
const body: ValidateRequest = await req.json() body = await req.json()
const { } catch {
provider,
apiKey,
modelId,
awsAccessKeyId,
awsSecretAccessKey,
awsRegion,
awsSessionToken,
// Note: Express Mode only needs vertexApiKey
vertexApiKey,
} = body
if (!provider || !modelId) {
return NextResponse.json(
{ valid: false, error: "Provider and model ID are required" },
{ status: 400 },
)
}
// EdgeOne is this site's own function, as in the chat; the admin
// panel's Test sends no URL, and a relative one cannot be fetched
const baseUrl =
provider === "edgeone" ? edgeOneEndpoint(req) : body.baseUrl
// The admin panel's Test of an entry without a URL sends the
// server's own <P>_BASE_URL, which chat uses as it is: not a URL a
// user chose, so no private-address or redirect rules
const serverUrl =
body.serverBaseUrl === true &&
!!baseUrl &&
baseUrl === globalBaseUrl(provider) &&
!checkAdminAuth(req)
// SECURITY: Block SSRF attacks via custom baseUrl
if (
baseUrl &&
!serverUrl &&
!allowPrivateUrls() &&
(await isPrivateUrl(baseUrl))
) {
return NextResponse.json(
{ valid: false, error: "Invalid base URL" },
{ status: 400 },
)
}
// Validate credentials based on provider
if (provider === "bedrock") {
if (
!(apiKey || (awsAccessKeyId && awsSecretAccessKey)) ||
!awsRegion
) {
return NextResponse.json(
{
valid: false,
error: "AWS credentials (a Bedrock API key, or an Access Key ID and Secret Access Key, and a Region) are required",
},
{ status: 400 },
)
}
} else if (provider === "vertexai") {
if (!vertexApiKey) {
return NextResponse.json(
{
valid: false,
error: "Vertex AI API key is required for Express Mode",
},
{ status: 400 },
)
}
} else if (provider !== "ollama" && provider !== "edgeone" && !apiKey) {
return NextResponse.json(
{ valid: false, error: "API key is required" },
{ status: 400 },
)
}
// The Test button checks the user's own provider. On the server's
// keys (Ollama Cloud without a key or URL) anyone could run any model.
if (
usesServerCredentials(provider, {
apiKey,
baseUrl,
awsAccessKeyId,
awsSecretAccessKey,
vertexApiKey,
})
) {
return NextResponse.json(
{ valid: false, error: "API key is required" },
{ status: 400 },
)
}
// On the deployment's own endpoints a Test runs a model as a chat
// does, so with the quota on it counts as a chat request (an
// admin's Test of the server's URL does not)
const userId = getUserIdFromRequest(req)
if (
isQuotaEnabled() &&
!serverUrl &&
userId !== "anonymous" &&
(await usesServerEndpoint(
provider,
normalizeBaseUrl(body.baseUrl ?? ""),
apiKey,
))
) {
const quotaCheck = await checkAndIncrementRequest(userId, {
requests: Number(process.env.DAILY_REQUEST_LIMIT) || 10,
tokens: Number(process.env.DAILY_TOKEN_LIMIT) || 200000,
tpm: Number(process.env.TPM_LIMIT) || 20000,
})
if (!quotaCheck.allowed) {
return NextResponse.json(
{ valid: false, error: quotaCheck.error },
{ status: 429 },
)
}
}
// The same model the chat would use. A client base URL makes it
// refuse redirects to internal hosts.
const { model } = getAIModel({
provider,
modelId,
apiKey,
baseUrl,
trustedBaseUrl: serverUrl,
awsAccessKeyId,
awsSecretAccessKey,
awsRegion,
// Temporary AWS credentials need it, as in the chat
awsSessionToken,
vertexApiKey,
// EdgeOne checks the Pages cookies and the access code
...(provider === "edgeone" && {
headers: {
cookie: req.headers.get("cookie") || "",
"x-access-code": req.headers.get("x-access-code") || "",
},
}),
})
// Streaming, like the chat (some models only stream). Stop at the
// first tool call; a reasoning model that runs out of tokens first
// proves the connection but not tool support.
const startTime = Date.now()
const result = streamText({
model,
prompt: "Call the ping tool.",
tools: { ping: PING_TOOL },
maxOutputTokens: 1024,
maxRetries: 0,
abortSignal: AbortSignal.timeout(TEST_TIMEOUT_MS),
})
let calledTool = false
let finishReason: string | undefined
for await (const part of result.fullStream) {
if (part.type === "error") throw part.error
// The timeout ends the stream with an abort part, not an error
if (part.type === "abort") {
const timeout = new Error(
`The model did not answer within ${TEST_TIMEOUT_MS / 1000} s.`,
)
timeout.name = "TimeoutError"
throw timeout
}
if (part.type === "tool-call") {
calledTool = true
break
}
if (part.type === "finish") finishReason = part.finishReason
}
const responseTime = Date.now() - startTime
return NextResponse.json({
valid: true,
responseTime,
...(!calledTool &&
finishReason !== "length" && { warning: NO_TOOL_CALL_WARNING }),
})
} catch (error) {
console.error("[validate-model] Error:", error)
const { code, message } = classifyLLMError(error)
return NextResponse.json( return NextResponse.json(
{ valid: false, code, error: message }, { valid: false, error: "Invalid JSON body" },
{ status: 200 }, // Return 200 so client can read error message { status: 400 },
) )
} }
// A URL in the request is one the user typed, never the server's own
return testModelConnection(req, body, false)
} }
docs/cn/ai-providers.md
+1 -1
View File
@@ -392,7 +392,7 @@ AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro
| `provider` | 是 | 提供商类型（`openai`, `anthropic`, `google`, `bedrock` 等） | | `provider` | 是 | 提供商类型（`openai`, `anthropic`, `google`, `bedrock` 等） |
| `models` | 是 | 模型 ID 列表 | | `models` | 是 | 模型 ID 列表 |
| `default` | 否 | 设为 `true` 表示默认选中该提供商的第一个模型 | | `default` | 否 | 设为 `true` 表示默认选中该提供商的第一个模型 |
| `apiKeyEnv` | 否 | 自定义 API Key 环境变量名（默认使用提供商标准变量如 `OPENAI_API_KEY`） | | `apiKeyEnv` | 否 | 自定义 API Key 环境变量名（默认使用提供商标准变量如 `OPENAI_API_KEY`）。也可以写成环境变量名数组，每次请求从有值的变量中随机选一个，把负载分摊到多个 Key 上 |
| `baseUrlEnv` | 否 | 自定义 Base URL 环境变量名 | | `baseUrlEnv` | 否 | 自定义 Base URL 环境变量名 |
### 说明 ### 说明
docs/en/ai-providers.md
+1 -1
View File
@@ -407,7 +407,7 @@ This is shorthand for the equivalent `ai-models.json`. For multiple providers or
| `provider` | Yes | Provider type (`openai`, `anthropic`, `google`, `bedrock`, etc.) | | `provider` | Yes | Provider type (`openai`, `anthropic`, `google`, `bedrock`, etc.) |
| `models` | Yes | List of model IDs | | `models` | Yes | List of model IDs |
| `default` | No | Set to `true` to auto-select this provider's first model as default | | `default` | No | Set to `true` to auto-select this provider's first model as default |
| `apiKeyEnv` | No | Custom API key env var name (defaults to provider's standard var like `OPENAI_API_KEY`) | | `apiKeyEnv` | No | Custom API key env var name (defaults to provider's standard var like `OPENAI_API_KEY`). May also be an array of env var names: each request picks one that has a value at random, spreading load over several keys |
| `baseUrlEnv` | No | Custom base URL env var name | | `baseUrlEnv` | No | Custom base URL env var name |
### Notes ### Notes
docs/ja/ai-providers.md
+1 -1
View File
@@ -392,7 +392,7 @@ AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro
| `provider` | はい | プロバイダータイプ（`openai`, `anthropic`, `google`, `bedrock` など） | | `provider` | はい | プロバイダータイプ（`openai`, `anthropic`, `google`, `bedrock` など） |
| `models` | はい | モデルIDのリスト | | `models` | はい | モデルIDのリスト |
| `default` | いいえ | `true` に設定すると、そのプロバイダーの最初のモデルがデフォルトで選択されます | | `default` | いいえ | `true` に設定すると、そのプロバイダーの最初のモデルがデフォルトで選択されます |
| `apiKeyEnv` | いいえ | カスタムAPIキー環境変数名（デフォルトは `OPENAI_API_KEY` などの標準変数） | | `apiKeyEnv` | いいえ | カスタムAPIキー環境変数名（デフォルトは `OPENAI_API_KEY` などの標準変数）。環境変数名の配列も指定でき、リクエストごとに値のある変数から1つがランダムに選ばれます（複数キーへの負荷分散） |
| `baseUrlEnv` | いいえ | カスタムBase URL環境変数名 | | `baseUrlEnv` | いいえ | カスタムBase URL環境変数名 |
### 備考 ### 備考
edge-functions/api/edgeai/chat/completions.ts
+14 -56
View File
@@ -29,6 +29,7 @@ const messageItemSchema = z
}) })
.passthrough() .passthrough()
// The fields read here; every other field is passed on to AI.chatCompletions
const messageSchema = z const messageSchema = z
.object({ .object({
messages: z.array(messageItemSchema), messages: z.array(messageItemSchema),
@@ -36,21 +37,6 @@ const messageSchema = z
stream: z.boolean().optional(), stream: z.boolean().optional(),
tools: z.any().optional(), tools: z.any().optional(),
tool_choice: z.any().optional(), tool_choice: z.any().optional(),
functions: z.any().optional(),
function_call: z.any().optional(),
temperature: z.number().optional(),
top_p: z.number().optional(),
max_tokens: z.number().optional(),
presence_penalty: z.number().optional(),
frequency_penalty: z.number().optional(),
stop: z.union([z.string(), z.array(z.string())]).optional(),
response_format: z.any().optional(),
seed: z.number().optional(),
user: z.string().optional(),
n: z.number().int().optional(),
logit_bias: z.record(z.string(), z.number()).optional(),
parallel_tool_calls: z.boolean().optional(),
stream_options: z.any().optional(),
}) })
.passthrough() .passthrough()
@@ -61,12 +47,6 @@ const ALLOWED_MODELS = [
"@tx/deepseek-ai/deepseek-v3-0324", "@tx/deepseek-ai/deepseek-v3-0324",
] ]
const MODEL_ALIASES: Record<string, string> = {
"deepseek-v3.2": "@tx/deepseek-ai/deepseek-v32",
"deepseek-r1-0528": "@tx/deepseek-ai/deepseek-r1-0528",
"deepseek-v3-0324": "@tx/deepseek-ai/deepseek-v3-0324",
}
/** /**
* Create standardized JSON response * Create standardized JSON response
*/ */
@@ -145,8 +125,16 @@ export async function onRequest({ request, env }: any) {
) )
} }
const { messages, model, stream, tools, tool_choice, ...extraParams } = // stream is taken out so it is not passed on: AI.chatCompletions
parseResult.data // only streams, and every caller reads a stream
const {
messages,
model,
stream: _,
tools,
tool_choice,
...extraParams
} = parseResult.data
// Validate messages // Validate messages
const userMessages = messages.filter( const userMessages = messages.filter(
@@ -165,14 +153,13 @@ export async function onRequest({ request, env }: any) {
} }
// Resolve model // Resolve model
const requestedModel = model || ALLOWED_MODELS[0] const selectedModel = model || ALLOWED_MODELS[0]
const selectedModel = MODEL_ALIASES[requestedModel] || requestedModel
if (!ALLOWED_MODELS.includes(selectedModel)) { if (!ALLOWED_MODELS.includes(selectedModel)) {
return createResponse( return createResponse(
{ {
error: { error: {
message: `Invalid model: ${requestedModel}.`, message: `Invalid model: ${selectedModel}.`,
type: "invalid_request_error", type: "invalid_request_error",
}, },
}, },
@@ -181,39 +168,10 @@ export async function onRequest({ request, env }: any) {
} }
console.log( console.log(
`[EdgeOne] Model: ${selectedModel}, Tools: ${tools?.length || 0}, Stream: ${stream ?? true}`, `[EdgeOne] Model: ${selectedModel}, Tools: ${tools?.length || 0}`,
) )
try { try {
const isStream = !!stream
// Non-streaming: return mock response for validation
// AI.chatCompletions doesn't support non-streaming mode
if (!isStream) {
const mockResponse = {
id: `chatcmpl-${Date.now()}`,
object: "chat.completion",
created: Math.floor(Date.now() / 1000),
model: selectedModel,
choices: [
{
index: 0,
message: {
role: "assistant",
content: "OK",
},
finish_reason: "stop",
},
],
usage: {
prompt_tokens: 10,
completion_tokens: 1,
total_tokens: 11,
},
}
return createResponse(mockResponse)
}
// Build AI.chatCompletions options for streaming // Build AI.chatCompletions options for streaming
const aiOptions: any = { const aiOptions: any = {
...extraParams, ...extraParams,
env.example
+18 -5
View File
@@ -8,6 +8,7 @@ AI_PROVIDER=bedrock
# Tip: For a single-provider quick multi-model setup, list comma-separated model IDs. # Tip: For a single-provider quick multi-model setup, list comma-separated model IDs.
# The first one becomes the default and the rest appear in the model picker. # The first one becomes the default and the rest appear in the model picker.
# For multiple providers or custom apiKeyEnv/baseUrlEnv, use AI_MODELS_CONFIG / ai-models.json instead. # For multiple providers or custom apiKeyEnv/baseUrlEnv, use AI_MODELS_CONFIG / ai-models.json instead.
# There, apiKeyEnv may also be an array of env var names: each request picks one that has a value at random.
# Example: AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro # Example: AI_MODEL=doubao-seed-1-8-251215,doubao-seed-1-6-flash,doubao-seed-1-6-pro
AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0 AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0
@@ -28,8 +29,6 @@ AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0
# OpenAI Configuration # OpenAI Configuration
# OPENAI_API_KEY=sk-... # OPENAI_API_KEY=sk-...
# OPENAI_BASE_URL=https://api.openai.com/v1 # Optional: Custom OpenAI-compatible endpoint # OPENAI_BASE_URL=https://api.openai.com/v1 # Optional: Custom OpenAI-compatible endpoint
# OPENAI_ORGANIZATION=org-... # Optional
# OPENAI_PROJECT=proj_... # Optional
# Note: o1/o3/gpt-5 models automatically enable reasoning summary (default: detailed) # Note: o1/o3/gpt-5 models automatically enable reasoning summary (default: detailed)
# OPENAI_REASONING_EFFORT=low # Optional: Reasoning effort (minimal/low/medium/high) - for o1/o3/gpt-5 # OPENAI_REASONING_EFFORT=low # Optional: Reasoning effort (minimal/low/medium/high) - for o1/o3/gpt-5
# OPENAI_REASONING_SUMMARY=detailed # Optional: Override reasoning summary (none/brief/detailed) # OPENAI_REASONING_SUMMARY=detailed # Optional: Override reasoning summary (none/brief/detailed)
@@ -142,6 +141,18 @@ AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0
# ADMIN_PASSWORD=your-admin-password # ADMIN_PASSWORD=your-admin-password
# SETTINGS_FILE=./data/settings.json # Optional: custom settings file location # SETTINGS_FILE=./data/settings.json # Optional: custom settings file location
# Quota & Validation (Optional, also editable in the admin panel)
# Quota enforcement is disabled unless DYNAMODB_QUOTA_TABLE is set.
# DYNAMODB_QUOTA_TABLE=next-ai-draw-io-quota # DynamoDB table that stores the per-IP counters
# DYNAMODB_REGION=ap-northeast-1 # Region of the table
# QUOTA_TIMEZONE=UTC # Timezone for the daily reset boundary
# DAILY_REQUEST_LIMIT=10 # Requests per IP per day
# DAILY_TOKEN_LIMIT=200000 # Tokens per IP per day
# TPM_LIMIT=20000 # Tokens per minute
# ENABLE_VLM_VALIDATION=true # Visually validate generated diagrams with a vision model
# VALIDATION_MODEL= # Falls back to the default AI model when empty
# VALIDATION_TIMEOUT=30000 # Validation timeout in ms
# Draw.io Configuration (Optional) # Draw.io Configuration (Optional)
# By default the app serves its own copy of draw.io from /drawio (downloaded into # By default the app serves its own copy of draw.io from /drawio (downloaded into
# public/drawio by `npm run dev` / `npm run build`). Same origin is required for # public/drawio by `npm run dev` / `npm run build`). Same origin is required for
@@ -156,9 +167,7 @@ AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0
# NEXT_PUBLIC_BASE_PATH=/nextaidrawio # NEXT_PUBLIC_BASE_PATH=/nextaidrawio
# PDF Input Feature (Optional) # PDF Input Feature (Optional)
# Enable PDF file upload to extract text and generate diagrams # PDF file upload to extract text and generate diagrams
# Enabled by default. Set to "false" to disable.
# ENABLE_PDF_INPUT=true
# NEXT_PUBLIC_MAX_EXTRACTED_CHARS=150000 # Max characters for PDF/text extraction (default: 150000) # NEXT_PUBLIC_MAX_EXTRACTED_CHARS=150000 # Max characters for PDF/text extraction (default: 150000)
# Security Settings (Optional) # Security Settings (Optional)
@@ -184,6 +193,10 @@ AI_MODEL=global.anthropic.claude-sonnet-4-5-20250929-v1:0
# It also turns off the MCP server advertisement in Settings > About. # It also turns off the MCP server advertisement in Settings > About.
# NEXT_PUBLIC_SELFHOSTED=true # NEXT_PUBLIC_SELFHOSTED=true
# Analytics (Optional)
# Google Analytics measurement ID; nothing is loaded when unset
# NEXT_PUBLIC_GA_ID=G-XXXXXXXXXX
# Minimax Configuration (Optional) # Minimax Configuration (Optional)
# Get your API key from: https://platform.minimaxi.com/docs/guides/models-intro # Get your API key from: https://platform.minimaxi.com/docs/guides/models-intro
# MINIMAX_API_KEY=your_minimax_api_key # MINIMAX_API_KEY=your_minimax_api_key
lib/admin/providers.ts
+4 -10
View File
@@ -56,7 +56,7 @@ const StoredAdminProviderSchema = AdminProviderSchema.extend({
vertexApiKey: z.string().optional(), vertexApiKey: z.string().optional(),
}) })
export type AdminProviderInput = z.infer<typeof AdminProviderSchema> type AdminProviderInput = z.infer<typeof AdminProviderSchema>
// Stored form: secrets are plain strings // Stored form: secrets are plain strings
export interface StoredAdminProvider { export interface StoredAdminProvider {
@@ -115,7 +115,7 @@ export function loadAdminProviders(): StoredAdminProvider[] {
} }
} }
export type MaskedAdminProvider = Omit< type MaskedAdminProvider = Omit<
StoredAdminProvider, StoredAdminProvider,
(typeof SECRET_FIELDS)[number] (typeof SECRET_FIELDS)[number]
> & { > & {
@@ -278,15 +278,9 @@ export function deriveEnvUpdates(
return updates return updates
} }
// Every settings key the panel may have written for a given list. // Every settings key the panel may have written for a given list
// AI_MODELS_CONFIG is included to clean up values written by older
// versions of the panel (it is no longer written).
function derivedEnvKeys(list: StoredAdminProvider[]): string[] { function derivedEnvKeys(list: StoredAdminProvider[]): string[] {
const keys = new Set<string>([ const keys = new Set<string>(["AI_PROVIDER", "AI_MODEL"])
"AI_MODELS_CONFIG",
"AI_PROVIDER",
"AI_MODEL",
])
const indexByProvider = new Map<ProviderName, number>() const indexByProvider = new Map<ProviderName, number>()
for (const p of list) { for (const p of list) {
const index = indexByProvider.get(p.provider) ?? 0 const index = indexByProvider.get(p.provider) ?? 0
lib/ai-providers.ts
+66 -115
View File
@@ -30,9 +30,7 @@ import {
type ProviderName, type ProviderName,
} from "@/lib/types/model-config" } from "@/lib/types/model-config"
export type { ProviderName } const AIHUBMIX_APP_CODE = "MSBS9675"
export const AIHUBMIX_APP_CODE = "MSBS9675"
interface ModelConfig { interface ModelConfig {
model: any model: any
@@ -56,7 +54,7 @@ export const SINGLE_SYSTEM_PROVIDERS = new Set<ProviderName>([
* Normalize MiniMax base URL for AI SDK compatibility. * Normalize MiniMax base URL for AI SDK compatibility.
* MiniMax supports Anthropic-compatible and OpenAI-compatible endpoints. * MiniMax supports Anthropic-compatible and OpenAI-compatible endpoints.
*/ */
export function normalizeMiniMaxBaseURL(rawUrl: string): { function normalizeMiniMaxBaseURL(rawUrl: string): {
baseURL: string baseURL: string
isAnthropicCompatible: boolean isAnthropicCompatible: boolean
} { } {
@@ -129,21 +127,19 @@ const BEDROCK_ANTHROPIC_BETA = {
* @param userApiKey - User-provided API key (if any) * @param userApiKey - User-provided API key (if any)
* @param userBaseUrl - User-provided base URL (if any) * @param userBaseUrl - User-provided base URL (if any)
* @param serverBaseUrl - Server's base URL from environment variable * @param serverBaseUrl - Server's base URL from environment variable
* @param defaultBaseUrl - Provider's official/default base URL (optional)
* @returns The resolved base URL to use * @returns The resolved base URL to use
*/ */
export function resolveBaseURL( export function resolveBaseURL(
userApiKey: string | null | undefined, userApiKey: string | null | undefined,
userBaseUrl: string | null | undefined, userBaseUrl: string | null | undefined,
serverBaseUrl: string | undefined, serverBaseUrl: string | undefined,
defaultBaseUrl?: string,
): string | undefined { ): string | undefined {
if (userApiKey) { if (userApiKey) {
// User provides their own API key - only use user's baseUrl or default // User provides their own API key - only use user's baseUrl
return userBaseUrl || defaultBaseUrl || undefined return userBaseUrl || undefined
} }
// No user API key - fall back to server config // No user API key - fall back to server config
return userBaseUrl || serverBaseUrl || defaultBaseUrl || undefined return userBaseUrl || serverBaseUrl || undefined
} }
/** /**
@@ -244,6 +240,39 @@ function googleSamplingSettings(): { topK?: number; topP?: number } {
return settings return settings
} }
/**
* Gemini 2.5/3 models think by default, but need includeThoughts: true to
* return the reasoning. The budget applies to Gemini 2.5, the level to
* Gemini 3. Shared by Google AI and Vertex AI, which read different variables.
*/
function geminiThinkingOptions(
modelId: string | undefined,
budgetEnvName: string,
levelEnvName: string,
): { thinkingConfig: Record<string, any> } | undefined {
if (!modelId || !/gemini-?[23]/.test(modelId)) return undefined
const thinkingConfig: Record<string, any> = { includeThoughts: true }
const budget = parseIntSafe(
process.env[budgetEnvName],
budgetEnvName,
1024,
100000,
)
const level = process.env[levelEnvName] as
| "minimal"
| "low"
| "medium"
| "high"
| undefined
if (budget && (modelId.includes("2.5") || modelId.includes("2-5"))) {
thinkingConfig.thinkingBudget = budget
} else if (level && /gemini-?3/.test(modelId)) {
thinkingConfig.thinkingLevel = level
}
return { thinkingConfig }
}
/** /**
* Build provider-specific options from environment variables * Build provider-specific options from environment variables
* Supports various AI SDK providers with their unique configuration options * Supports various AI SDK providers with their unique configuration options
@@ -271,41 +300,27 @@ function buildProviderOptions(
switch (provider) { switch (provider) {
case "openai": { case "openai": {
const reasoningEffort = process.env.OPENAI_REASONING_EFFORT const reasoningEffort = process.env.OPENAI_REASONING_EFFORT as
const reasoningSummary = process.env.OPENAI_REASONING_SUMMARY | "minimal"
| "low"
| "medium"
| "high"
| undefined
// Reasoning models (the o-series, gpt-5 and later) need // Reasoning models (the o-series, gpt-5 and later) need
// reasoningSummary to return thoughts // reasoningSummary to return thoughts; 'auto' as the default
if (modelId && /^(o\d|gpt-([5-9]|[1-9]\d))/.test(modelId)) { // since not all models support 'detailed'
options.openai = { const isReasoning =
// Auto-enable reasoning summary for reasoning models !!modelId && /^(o\d|gpt-([5-9]|[1-9]\d))/.test(modelId)
// Use 'auto' as default since not all models support 'detailed' const reasoningSummary =
reasoningSummary: (process.env.OPENAI_REASONING_SUMMARY as
(reasoningSummary as "auto" | "detailed") || "auto", | "auto"
} | "detailed"
| undefined) || (isReasoning ? "auto" : undefined)
// Optionally configure reasoning effort if (reasoningSummary || reasoningEffort) {
if (reasoningEffort) { options.openai = {
options.openai.reasoningEffort = reasoningEffort as ...(reasoningSummary && { reasoningSummary }),
| "minimal" ...(reasoningEffort && { reasoningEffort }),
| "low"
| "medium"
| "high"
}
} else if (reasoningEffort || reasoningSummary) {
// Non-reasoning models: only apply if explicitly configured
options.openai = {}
if (reasoningEffort) {
options.openai.reasoningEffort = reasoningEffort as
| "minimal"
| "low"
| "medium"
| "high"
}
if (reasoningSummary) {
options.openai.reasoningSummary = reasoningSummary as
| "auto"
| "detailed"
} }
} }
break break
@@ -333,85 +348,21 @@ function buildProviderOptions(
} }
case "google": { case "google": {
const thinkingBudgetVal = parseIntSafe( const google = geminiThinkingOptions(
process.env.GOOGLE_THINKING_BUDGET, modelId,
"GOOGLE_THINKING_BUDGET", "GOOGLE_THINKING_BUDGET",
1024, "GOOGLE_THINKING_LEVEL",
100000,
) )
const thinkingLevel = process.env.GOOGLE_THINKING_LEVEL if (google) options.google = google
// Google Gemini 2.5/3 models think by default, but need includeThoughts: true
// to return the reasoning in the response
if (
modelId &&
(modelId.includes("gemini-2") ||
modelId.includes("gemini-3") ||
modelId.includes("gemini2") ||
modelId.includes("gemini3"))
) {
const thinkingConfig: Record<string, any> = {
includeThoughts: true,
}
// Optionally configure thinking budget or level
if (
thinkingBudgetVal &&
(modelId.includes("2.5") || modelId.includes("2-5"))
) {
thinkingConfig.thinkingBudget = thinkingBudgetVal
} else if (
thinkingLevel &&
(modelId.includes("gemini-3") ||
modelId.includes("gemini3"))
) {
thinkingConfig.thinkingLevel = thinkingLevel as
| "low"
| "high"
}
options.google = { thinkingConfig }
}
break break
} }
case "vertexai": { case "vertexai": {
const thinkingBudget = parseIntSafe( const google = geminiThinkingOptions(
process.env.GOOGLE_VERTEX_THINKING_BUDGET, modelId,
"GOOGLE_VERTEX_THINKING_BUDGET", "GOOGLE_VERTEX_THINKING_BUDGET",
1024, "GOOGLE_VERTEX_THINKING_LEVEL",
100000,
) )
const thinkingLevel = process.env.GOOGLE_VERTEX_THINKING_LEVEL if (google) options.google = google
if (
modelId &&
(modelId.includes("gemini-2") ||
modelId.includes("gemini-3") ||
modelId.includes("gemini2") ||
modelId.includes("gemini3"))
) {
const thinkingConfig: Record<string, any> = {
includeThoughts: true,
}
const isGemini3 =
modelId?.includes("gemini-3") ||
modelId?.includes("gemini3")
const isGemini25 =
modelId?.includes("2.5") || modelId?.includes("2-5")
if (isGemini3 && thinkingLevel) {
// Vertex AI provider in AI SDK supports more granular levels (minimal/low/medium/high)
thinkingConfig.thinkingLevel = thinkingLevel as
| "minimal"
| "low"
| "medium"
| "high"
} else if (isGemini25 && thinkingBudget) {
thinkingConfig.thinkingBudget = thinkingBudget
}
options.google = { thinkingConfig }
}
break break
} }
case "azure": { case "azure": {
@@ -498,7 +449,7 @@ function buildProviderOptions(
} }
// Map of provider to required environment variable // Map of provider to required environment variable
export const PROVIDER_ENV_VARS: Record<ProviderName, string | null> = { const PROVIDER_ENV_VARS: Record<ProviderName, string | null> = {
bedrock: null, // AWS SDK auto-uses IAM role on AWS, or env vars locally bedrock: null, // AWS SDK auto-uses IAM role on AWS, or env vars locally
openai: "OPENAI_API_KEY", openai: "OPENAI_API_KEY",
anthropic: "ANTHROPIC_API_KEY", anthropic: "ANTHROPIC_API_KEY",
lib/cached-responses.ts
+2 -3
View File
@@ -892,9 +892,9 @@ export const CACHED_EXAMPLE_RESPONSES: CachedResponse[] = [
}, },
] ]
// The chat panel answers a built-in example from here, without a request.
// Examples that come with a file only match when that exact example file is // Examples that come with a file only match when that exact example file is
// attached, so a user's own file with the same prompt still goes to the model. // attached, so a user's own file with the same prompt still goes to the model.
// Callers that can't tell file names (the server) only get text-only examples.
export function findCachedResponse( export function findCachedResponse(
promptText: string, promptText: string,
hasImage: boolean, hasImage: boolean,
@@ -904,7 +904,6 @@ export function findCachedResponse(
(c) => (c) =>
c.promptText === promptText && c.promptText === promptText &&
c.hasImage === hasImage && c.hasImage === hasImage &&
(!c.fileName || c.fileName === fileName) && (!c.fileName || c.fileName === fileName),
c.xml !== "",
) )
} }
lib/chat-helpers.ts
-29
View File
@@ -58,35 +58,6 @@ function isValidToolInput(input: unknown): boolean {
return !!input && typeof input === "object" && Object.keys(input).length > 0 return !!input && typeof input === "object" && Object.keys(input).length > 0
} }
// Helper function to replace historical tool call XML with placeholders
// This reduces token usage and forces LLM to rely on the current diagram XML (source of truth)
// Tool calls with invalid inputs are left for dropInvalidToolCalls to remove
export function replaceHistoricalToolInputs(messages: any[]): any[] {
return messages.map((msg) => {
if (msg.role !== "assistant" || !Array.isArray(msg.content)) {
return msg
}
const replacedContent = msg.content.map((part: any) => {
if (
part.type === "tool-call" &&
isValidToolInput(part.input) &&
(part.toolName === "display_diagram" ||
part.toolName === "edit_diagram")
) {
return {
...part,
input: {
placeholder:
"[XML content replaced - see current diagram XML in system context]",
},
}
}
return part
})
return { ...msg, content: replacedContent }
})
}
// Remove tool-calls with invalid inputs (from failed repair or interrupted streaming), // Remove tool-calls with invalid inputs (from failed repair or interrupted streaming),
// together with their tool-results: providers reject a result whose call is missing. // together with their tool-results: providers reject a result whose call is missing.
// Messages left empty are removed too (Bedrock rejects empty content arrays). // Messages left empty are removed too (Bedrock rejects empty content arrays).
lib/diagram-validator.ts
+1 -1
View File
@@ -4,7 +4,7 @@
*/ */
// Re-export types from the schema file (single source of truth) // Re-export types from the schema file (single source of truth)
export type { ValidationIssue, ValidationResult } from "./validation-schema" export type { ValidationResult } from "./validation-schema"
import type { ValidationResult } from "./validation-schema" import type { ValidationResult } from "./validation-schema"
lib/dynamo-quota-manager.ts
+45 -61
View File
@@ -1,7 +1,6 @@
import { import {
ConditionalCheckFailedException, ConditionalCheckFailedException,
DynamoDBClient, DynamoDBClient,
GetItemCommand,
UpdateItemCommand, UpdateItemCommand,
} from "@aws-sdk/client-dynamodb" } from "@aws-sdk/client-dynamodb"
@@ -108,76 +107,61 @@ export async function checkAndIncrementRequest(
":tokenLimit": { N: String(limits.tokens || 999999) }, ":tokenLimit": { N: String(limits.tokens || 999999) },
":tpmLimit": { N: String(limits.tpm || 999999) }, ":tpmLimit": { N: String(limits.tpm || 999999) },
}, },
// On a failed condition the exception carries the item as it
// was, so no second read is needed to tell which limit was hit
ReturnValuesOnConditionCheckFailure: "ALL_OLD",
}), }),
) )
return { allowed: true } return { allowed: true }
} catch (e: any) { } catch (e: any) {
// Condition failed - need to determine which limit was exceeded // Condition failed - the exception's Item holds the current counts
if (e instanceof ConditionalCheckFailedException) { if (e instanceof ConditionalCheckFailedException) {
// Get current counts to determine which limit was hit const item = e.Item
try { const storedMinute = item?.lastMinute?.S
const getResult = await client.send(
new GetItemCommand({
TableName: TABLE,
Key: {
PK: { S: pk },
SK: { S: sk },
},
}),
)
const item = getResult.Item const reqCount = Number(item?.reqCount?.N || 0)
const storedMinute = item?.lastMinute?.S const tokenCount = Number(item?.tokenCount?.N || 0)
const tpmCount =
storedMinute !== currentMinute
? 0
: Number(item?.tpmCount?.N || 0)
const reqCount = Number(item?.reqCount?.N || 0) // Determine which limit was exceeded
const tokenCount = Number(item?.tokenCount?.N || 0) if (limits.requests > 0 && reqCount >= limits.requests) {
const tpmCount = return {
storedMinute !== currentMinute allowed: false,
? 0 type: "request",
: Number(item?.tpmCount?.N || 0) error: "Daily request limit exceeded",
used: reqCount,
// Determine which limit was exceeded limit: limits.requests,
if (limits.requests > 0 && reqCount >= limits.requests) {
return {
allowed: false,
type: "request",
error: "Daily request limit exceeded",
used: reqCount,
limit: limits.requests,
}
} }
if (limits.tokens > 0 && tokenCount >= limits.tokens) {
return {
allowed: false,
type: "token",
error: "Daily token limit exceeded",
used: tokenCount,
limit: limits.tokens,
}
}
if (limits.tpm > 0 && tpmCount >= limits.tpm) {
return {
allowed: false,
type: "tpm",
error: "Rate limit exceeded (tokens per minute)",
used: tpmCount,
limit: limits.tpm,
}
}
// Condition failed but no limit clearly exceeded - race condition edge case
// Fail safe by allowing (could be a TPM reset race)
console.warn(
`[quota] Condition failed but no limit exceeded for IP prefix: ${ip.slice(0, 8)}...`,
)
return { allowed: true }
} catch (getError: any) {
console.error(
`[quota] Failed to get quota details after condition failure, IP prefix: ${ip.slice(0, 8)}..., error: ${getError.message}`,
)
return { allowed: true } // Fail open
} }
if (limits.tokens > 0 && tokenCount >= limits.tokens) {
return {
allowed: false,
type: "token",
error: "Daily token limit exceeded",
used: tokenCount,
limit: limits.tokens,
}
}
if (limits.tpm > 0 && tpmCount >= limits.tpm) {
return {
allowed: false,
type: "tpm",
error: "Rate limit exceeded (tokens per minute)",
used: tpmCount,
limit: limits.tpm,
}
}
// Condition failed but no limit clearly exceeded - race condition edge case
// Fail safe by allowing (could be a TPM reset race)
console.warn(
`[quota] Condition failed but no limit exceeded for IP prefix: ${ip.slice(0, 8)}...`,
)
return { allowed: true }
} }
// Other DynamoDB errors - fail open // Other DynamoDB errors - fail open
lib/langfuse.ts
+50 -1
View File
@@ -1,10 +1,59 @@
import { LangfuseClient } from "@langfuse/client" import { LangfuseClient } from "@langfuse/client"
import { observe, updateActiveTrace } from "@langfuse/tracing" import { observe, updateActiveTrace } from "@langfuse/tracing"
import * as api from "@opentelemetry/api" import * as api from "@opentelemetry/api"
import { randomUUID } from "crypto"
// Singleton LangfuseClient instance for direct API calls // Singleton LangfuseClient instance for direct API calls
let langfuseClient: LangfuseClient | null = null let langfuseClient: LangfuseClient | null = null
type IngestionBatch = Parameters<
LangfuseClient["api"]["ingestion"]["batch"]
>[0]["batch"]
// Attach a score to the session's most recent chat trace. When the session
// has no trace yet, a fallbackTrace creates a standalone trace to carry the
// score; without one the score is skipped. Returns whether a score was written.
export async function scoreLatestTrace(
langfuse: LangfuseClient,
opts: {
sessionId: string
name: string
value: number
comment: string
fallbackTrace?: {
name: string
userId: string
input: unknown
metadata: Record<string, unknown>
}
},
): Promise<boolean> {
const { sessionId, name, value, comment, fallbackTrace } = opts
const traces = await langfuse.api.trace.list({ sessionId, limit: 1 })
let traceId = traces.data?.[0]?.id
const timestamp = new Date().toISOString()
const batch: IngestionBatch = []
if (!traceId) {
if (!fallbackTrace) return false
traceId = randomUUID()
batch.push({
type: "trace-create",
id: randomUUID(),
timestamp,
body: { id: traceId, sessionId, ...fallbackTrace, timestamp },
})
}
batch.push({
type: "score-create",
id: randomUUID(),
timestamp,
body: { id: randomUUID(), traceId, name, value, comment },
})
await langfuse.api.ingestion.batch({ batch })
return true
}
export function getLangfuseClient(): LangfuseClient | null { export function getLangfuseClient(): LangfuseClient | null {
if (!process.env.LANGFUSE_PUBLIC_KEY || !process.env.LANGFUSE_SECRET_KEY) { if (!process.env.LANGFUSE_PUBLIC_KEY || !process.env.LANGFUSE_SECRET_KEY) {
return null return null
@@ -22,7 +71,7 @@ export function getLangfuseClient(): LangfuseClient | null {
} }
// Check if Langfuse is configured (both keys required) // Check if Langfuse is configured (both keys required)
export function isLangfuseEnabled(): boolean { function isLangfuseEnabled(): boolean {
return !!( return !!(
process.env.LANGFUSE_PUBLIC_KEY && process.env.LANGFUSE_SECRET_KEY process.env.LANGFUSE_PUBLIC_KEY && process.env.LANGFUSE_SECRET_KEY
) )
lib/llm-errors.ts
+2 -2
View File
@@ -11,7 +11,7 @@ import {
* What went wrong with a model call, for a hint the user can act on. The * What went wrong with a model call, for a hint the user can act on. The
* provider's own message always goes along, because a guess can be wrong. * provider's own message always goes along, because a guess can be wrong.
*/ */
export type LLMErrorCode = type LLMErrorCode =
| "invalid_api_key" | "invalid_api_key"
| "forbidden" | "forbidden"
| "model_not_found" | "model_not_found"
@@ -28,7 +28,7 @@ export type LLMErrorCode =
| "server_key_forbidden" | "server_key_forbidden"
| "unknown" | "unknown"
export interface LLMError { interface LLMError {
type: "provider" type: "provider"
code: LLMErrorCode code: LLMErrorCode
message: string message: string
lib/model-catalog.ts
+1 -1
View File
@@ -6,7 +6,7 @@ import type { ProviderName } from "@/lib/types/model-config"
* Only used for hints: requests are sent the same way either way, since * Only used for hints: requests are sent the same way either way, since
* the data can be wrong or out of date. * the data can be wrong or out of date.
*/ */
export interface ModelInfo { interface ModelInfo {
tools: boolean tools: boolean
images: boolean images: boolean
reasoning: boolean reasoning: boolean
lib/output-token-limit.ts
+2 -9
View File
@@ -14,7 +14,7 @@ type WrappedModel = ReturnType<typeof wrapLanguageModel>
export const DEFAULT_MAX_OUTPUT_TOKENS = 64000 export const DEFAULT_MAX_OUTPUT_TOKENS = 64000
/** Ceiling for the user-supplied override, to catch typos like an extra zero. */ /** Ceiling for the user-supplied override, to catch typos like an extra zero. */
export const MAX_OUTPUT_TOKENS_LIMIT = 200000 const MAX_OUTPUT_TOKENS_LIMIT = 200000
/** /**
* Below this a diagram cannot come out whole, so a retry would just produce * Below this a diagram cannot come out whole, so a retry would just produce
@@ -81,7 +81,7 @@ export function rejectionText(error: unknown): string | null {
* "lower than N") would reinterpret unrelated failures, and retrying on a bogus * "lower than N") would reinterpret unrelated failures, and retrying on a bogus
* number turns a readable error into an empty diagram. * number turns a readable error into an empty diagram.
*/ */
function readCeiling(text: string): number | null { export function readCeiling(text: string): number | null {
// Combined input+output ceiling: subtract the input the provider counted, // Combined input+output ceiling: subtract the input the provider counted,
// plus a small margin because its estimate is approximate. // plus a small margin because its estimate is approximate.
const context = text.match(/maximum context length (?:is|of) (\d+)/i) const context = text.match(/maximum context length (?:is|of) (\d+)/i)
@@ -104,13 +104,6 @@ function readCeiling(text: string): number | null {
return output ? Number(output[1]) : null return output ? Number(output[1]) : null
} }
/** The usable output ceiling named in a rejection, or null. */
export function parseOutputTokenLimit(error: unknown): number | null {
const text = rejectionText(error)
const ceiling = text ? readCeiling(text) : null
return ceiling === null ? null : usableLimit(ceiling)
}
/** /**
* Thinking budget the provider adds on top of maxOutputTokens. Bedrock and * Thinking budget the provider adds on top of maxOutputTokens. Bedrock and
* Anthropic send maxOutputTokens + budgetTokens as max_tokens, so a ceiling in * Anthropic send maxOutputTokens + budgetTokens as max_tokens, so a ceiling in
lib/provider-models.ts
+1 -1
View File
@@ -14,7 +14,7 @@ export interface ListedModel {
tools?: boolean tools?: boolean
} }
export const AIHUBMIX_MODELS_ENDPOINT = "https://aihubmix.com/api/v1/models" const AIHUBMIX_MODELS_ENDPOINT = "https://aihubmix.com/api/v1/models"
export function canListModels(provider: ProviderName): boolean { export function canListModels(provider: ProviderName): boolean {
return ( return (
lib/server-model-config.ts
+1 -2
View File
@@ -10,7 +10,7 @@ export const ProviderNameSchema: z.ZodType<ProviderName> = z
message: "Invalid provider name", message: "Invalid provider name",
}) })
export const ServerProviderSchema = z.object({ const ServerProviderSchema = z.object({
name: z.string().min(1), name: z.string().min(1),
provider: ProviderNameSchema, provider: ProviderNameSchema,
models: z.array(z.string().min(1)), models: z.array(z.string().min(1)),
@@ -30,7 +30,6 @@ export const ServerModelsConfigSchema = z.object({
providers: z.array(ServerProviderSchema), providers: z.array(ServerProviderSchema),
}) })
export type ServerProviderConfig = z.infer<typeof ServerProviderSchema>
export type ServerModelsConfig = z.infer<typeof ServerModelsConfigSchema> export type ServerModelsConfig = z.infer<typeof ServerModelsConfigSchema>
export interface FlattenedServerModel { export interface FlattenedServerModel {
lib/system-prompts.ts
+12 -158
View File
@@ -1,17 +1,10 @@
/** /**
* System prompts for different AI models * System prompt for the chat route
* Extended prompt is used for models with higher cache token minimums (Opus 4.5, Haiku 4.5)
*/ */
import { import { STYLE_CLASS_EXAMPLE } from "@/packages/mcp-server/src/xml-examples.ts"
STYLE_CLASS_EXAMPLE,
SWIMLANE_EXAMPLE,
TWO_EDGES_EXAMPLE,
WAYPOINT_EXAMPLE,
} from "@/packages/mcp-server/src/xml-examples.ts"
// Default system prompt (~1900 tokens) - works with all models const DEFAULT_SYSTEM_PROMPT = `
export const DEFAULT_SYSTEM_PROMPT = `
You are an expert diagram creation assistant specializing in draw.io XML generation. You are an expert diagram creation assistant specializing in draw.io XML generation.
Your primary function is chat with user and crafting clear, well-organized visual diagrams through precise XML specifications. Your primary function is chat with user and crafting clear, well-organized visual diagrams through precise XML specifications.
You can see images that users upload, and you can read the text content extracted from PDF documents they upload. You can see images that users upload, and you can read the text content extracted from PDF documents they upload.
@@ -21,18 +14,14 @@ When you are asked to create a diagram, briefly describe your plan about the lay
After generating or editing a diagram, you don't need to say anything. The user can see the diagram - no need to describe it. After generating or editing a diagram, you don't need to say anything. The user can see the diagram - no need to describe it.
## App Context ## App Context
You are an AI agent (powered by {{MODEL_NAME}}) inside a web app. The interface has: You are an AI agent (powered by {{MODEL_NAME}}) inside a web app. The draw.io canvas fills the window, and the chat panel where you talk with the user floats on the right; users can open and close it.
- **Left panel**: Draw.io diagram editor where diagrams are rendered
- **Right panel**: Chat interface where you communicate with the user
You can read and modify diagrams by generating draw.io XML code through tool calls. You can read and modify diagrams by generating draw.io XML code through tool calls.
## App Features ## App Features
1. **Diagram History** (clock icon, bottom-left of chat input): The app automatically saves a snapshot before each AI edit. Users can view the history panel and restore any previous version. Feel free to make changes - nothing is permanently lost. 1. **Version history**: The app automatically saves a version before each AI edit. Users can go back to any earlier version with the "Restore version" button shown next to a message. Feel free to make changes: nothing is permanently lost.
2. **Theme Toggle** (palette icon, bottom-left of chat input): Users can switch between minimal UI and sketch-style UI for the draw.io editor. 2. **Image/PDF Upload** (the + menu of the chat input): Users can upload images or PDF documents for you to analyze and generate diagrams from.
3. **Image/PDF Upload** (paperclip icon, bottom-left of chat input): Users can upload images or PDF documents for you to analyze and generate diagrams from. 3. **Export** (via draw.io toolbar): Users can save diagrams as .drawio, .svg, or .png files.
4. **Export** (via draw.io toolbar): Users can save diagrams as .drawio, .svg, or .png files.
5. **Clear Chat** (trash icon, bottom-right of chat input): Clears the conversation and resets the diagram.
You utilize the following tools: You utilize the following tools:
---Tool1--- ---Tool1---
@@ -224,126 +213,9 @@ Since we skip styling, STRICTLY follow the "Edge Routing Rules" section below:
` `
// Extended additions (~2600 tokens) - appended for models with 4000 token cache minimum
// Total EXTENDED_SYSTEM_PROMPT = ~4400 tokens
const EXTENDED_ADDITIONS = `
## Extended Tool Reference
### display_diagram Details
**VALIDATION RULES** (XML will be rejected if violated):
1. Generate ONLY mxStyle definitions and mxCell elements - wrapper tags and root cells are added automatically
2. All mxCell elements must be siblings - never nested inside other mxCell elements
3. Every mxCell needs a unique id attribute (start from "2")
4. parent defaults to "1"; write it only for a shape inside a container (the container's id)
5. Edge source/target attributes must reference existing cell IDs
6. Escape special characters in values: &lt; for <, &gt; for >, &amp; for &, &quot; for "
**Example with swimlanes and edges** (generate ONLY this - no wrapper tags):
\`\`\`xml
${SWIMLANE_EXAMPLE}
\`\`\`
### append_diagram Details
**WHEN TO USE:** Only call this tool when display_diagram output was truncated (you'll see an error message about truncation).
**CRITICAL RULES:**
1. Do NOT include any wrapper tags - just continue the mxCell elements
2. Continue from EXACTLY where your previous output stopped
3. Complete the remaining mxCell elements
4. If still truncated, call append_diagram again with the next fragment
**Example:** If previous output ended with \`<mxCell id="x" style="rounded=1\`, continue with \`;" x="40" y="40" w="120" h="60"/>\` and complete the remaining elements.
### edit_diagram Details
edit_diagram uses ID-based operations to modify cells directly by their id attribute.
**Operations:**
- **update**: Replace an existing cell. Provide cell_id and new_xml.
- **add**: Add a new cell. Provide cell_id (new unique id) and new_xml.
- **delete**: Remove a cell. **Cascade is automatic**: children AND edges (source/target) are auto-deleted. Only specify ONE cell_id.
**Input Format:**
\`\`\`json
{
"operations": [
{"operation": "update", "cell_id": "3", "new_xml": "<mxCell ...complete element...>"},
{"operation": "add", "cell_id": "new1", "new_xml": "<mxCell ...new element...>"},
{"operation": "delete", "cell_id": "5"}
]
}
\`\`\`
**Examples:**
Change label:
\`\`\`json
{"operations": [{"operation": "update", "cell_id": "3", "new_xml": "<mxCell id=\\"3\\" value=\\"New Label\\" style=\\"rounded=1;\\" x=\\"100\\" y=\\"100\\" w=\\"120\\" h=\\"60\\"/>"}]}
\`\`\`
Add new shape:
\`\`\`json
{"operations": [{"operation": "add", "cell_id": "new1", "new_xml": "<mxCell id=\\"new1\\" value=\\"New Box\\" style=\\"rounded=1;fillColor=#dae8fc;\\" x=\\"400\\" y=\\"200\\" w=\\"120\\" h=\\"60\\"/>"}]}
\`\`\`
Delete container (children & edges auto-deleted):
\`\`\`json
{"operations": [{"operation": "delete", "cell_id": "2"}]}
\`\`\`
**Error Recovery:**
If cell_id not found, check "Current diagram XML" for correct IDs. Use display_diagram if major restructuring is needed
## Edge Examples
### Two edges between same nodes (CORRECT - no overlap):
\`\`\`xml
${TWO_EDGES_EXAMPLE}
\`\`\`
### Edge with single waypoint (simple detour):
\`\`\`xml
<mxCell id="edge1" style="edgeStyle=orthogonalEdgeStyle;exitX=0.5;exitY=1;entryX=0.5;entryY=0;" edge="1" parent="1" source="a" target="b">
<mxGeometry relative="1" as="geometry">
<Array as="points">
<mxPoint x="300" y="150"/>
</Array>
</mxGeometry>
</mxCell>
\`\`\`
### Edge with waypoints (routing AROUND obstacles) - CRITICAL PATTERN:
**Scenario:** Hotfix(right,bottom) → Main(center,top), but Develop(center,middle) is in between.
**WRONG:** Direct diagonal line crosses over Develop
**CORRECT:** Route around the OUTSIDE (go right first, then up)
\`\`\`xml
${WAYPOINT_EXAMPLE}
\`\`\`
This routes the edge to the RIGHT of all shapes (x=750), then enters Main from the right side.
**Key principle:** When connecting distant nodes diagonally, route along the PERIMETER of the diagram, not through the middle where other shapes exist.`
// Extended system prompt = DEFAULT + EXTENDED_ADDITIONS
export const EXTENDED_SYSTEM_PROMPT = DEFAULT_SYSTEM_PROMPT + EXTENDED_ADDITIONS
// Model patterns that require extended prompt (4000 token cache minimum)
// These patterns match Opus 4.5 and Haiku 4.5 model IDs
const EXTENDED_PROMPT_MODEL_PATTERNS = [
"claude-opus-4-5", // Matches any Opus 4.5 variant
"claude-haiku-4-5", // Matches any Haiku 4.5 variant
]
/** /**
* Get the appropriate system prompt based on the model ID and style preference * Build the system prompt for a model and style preference
* Uses extended prompt for Opus 4.5 and Haiku 4.5 which have 4000 token cache minimum * @param modelId - The AI model ID, shown to the model as its name
* @param modelId - The AI model ID from environment
* @param minimalStyle - If true, removes style instructions to save tokens * @param minimalStyle - If true, removes style instructions to save tokens
* @returns The system prompt string * @returns The system prompt string
*/ */
@@ -353,32 +225,14 @@ export function getSystemPrompt(
): string { ): string {
const modelName = modelId || "AI" const modelName = modelId || "AI"
let prompt: string
if (
modelId &&
EXTENDED_PROMPT_MODEL_PATTERNS.some((pattern) =>
modelId.includes(pattern),
)
) {
console.log(
`[System Prompt] Using EXTENDED prompt for model: ${modelId}`,
)
prompt = EXTENDED_SYSTEM_PROMPT
} else {
console.log(
`[System Prompt] Using DEFAULT prompt for model: ${modelId || "unknown"}`,
)
prompt = DEFAULT_SYSTEM_PROMPT
}
// Add style instructions based on preference
// Minimal style: prepend instruction at START (more prominent) // Minimal style: prepend instruction at START (more prominent)
// Normal style: append at end // Normal style: append at end
let prompt: string
if (minimalStyle) { if (minimalStyle) {
console.log(`[System Prompt] Minimal style mode ENABLED`) console.log(`[System Prompt] Minimal style mode ENABLED`)
prompt = MINIMAL_STYLE_INSTRUCTION + prompt prompt = MINIMAL_STYLE_INSTRUCTION + DEFAULT_SYSTEM_PROMPT
} else { } else {
prompt += STYLE_INSTRUCTIONS prompt = DEFAULT_SYSTEM_PROMPT + STYLE_INSTRUCTIONS
} }
return prompt.replace("{{MODEL_NAME}}", modelName) return prompt.replace("{{MODEL_NAME}}", modelName)
lib/test-model-connection.ts
+239
View File
@@ -0,0 +1,239 @@
import { streamText, tool } from "ai"
import { NextResponse } from "next/server"
import { z } from "zod"
import {
edgeOneEndpoint,
getAIModel,
usesServerCredentials,
usesServerEndpoint,
} from "@/lib/ai-providers"
import {
checkAndIncrementRequest,
isQuotaEnabled,
} from "@/lib/dynamo-quota-manager"
import { classifyLLMError } from "@/lib/llm-errors"
import { allowPrivateUrls, isPrivateUrl } from "@/lib/ssrf-protection"
import { normalizeBaseUrl, type ProviderName } from "@/lib/types/model-config"
import { getUserIdFromRequest } from "@/lib/user-id"
export interface TestModelRequest {
provider: ProviderName
apiKey?: string
baseUrl?: string
modelId: string
// AWS Bedrock specific
awsAccessKeyId?: string
awsSecretAccessKey?: string
awsRegion?: string
awsSessionToken?: string
// Vertex AI specific
vertexApiKey?: string // Express Mode API key
}
const TEST_TIMEOUT_MS = 15_000
// Drawing works through tool calls, so the test asks for one
const PING_TOOL = tool({
description: "Report that the connection works.",
inputSchema: z.object({}),
})
const NO_TOOL_CALL_WARNING =
"Connected, but the model answered without calling a tool. It may not support tool calls, which drawing needs."
/**
* Run one tool call on a model, as the chat would, and report the result.
* Shared by the Settings dialog's Test (/api/validate-model) and the admin
* panel's Test (/api/admin/test-model). req supplies the EdgeOne endpoint,
* cookies, access code and the user id for the quota. trustedBaseUrl marks
* body.baseUrl as the server's own <P>_BASE_URL (the admin panel's Test of
* an entry without a URL), not one a user typed: chat uses it as it is, so
* no private-address or redirect rules, and no quota.
*/
export async function testModelConnection(
req: Request,
body: TestModelRequest,
trustedBaseUrl: boolean,
): Promise<NextResponse> {
try {
const {
provider,
apiKey,
modelId,
awsAccessKeyId,
awsSecretAccessKey,
awsRegion,
awsSessionToken,
// Note: Express Mode only needs vertexApiKey
vertexApiKey,
} = body
if (!provider || !modelId) {
return NextResponse.json(
{ valid: false, error: "Provider and model ID are required" },
{ status: 400 },
)
}
// EdgeOne is this site's own function, as in the chat; the admin
// panel's Test sends no URL, and a relative one cannot be fetched
const baseUrl =
provider === "edgeone" ? edgeOneEndpoint(req) : body.baseUrl
// SECURITY: Block SSRF attacks via custom baseUrl
if (
baseUrl &&
!trustedBaseUrl &&
!allowPrivateUrls() &&
(await isPrivateUrl(baseUrl))
) {
return NextResponse.json(
{ valid: false, error: "Invalid base URL" },
{ status: 400 },
)
}
// Validate credentials based on provider
if (provider === "bedrock") {
if (
!(apiKey || (awsAccessKeyId && awsSecretAccessKey)) ||
!awsRegion
) {
return NextResponse.json(
{
valid: false,
error: "AWS credentials (a Bedrock API key, or an Access Key ID and Secret Access Key, and a Region) are required",
},
{ status: 400 },
)
}
} else if (provider === "vertexai") {
if (!vertexApiKey) {
return NextResponse.json(
{
valid: false,
error: "Vertex AI API key is required for Express Mode",
},
{ status: 400 },
)
}
} else if (provider !== "ollama" && provider !== "edgeone" && !apiKey) {
return NextResponse.json(
{ valid: false, error: "API key is required" },
{ status: 400 },
)
}
// The Test button checks the user's own provider. On the server's
// keys (Ollama Cloud without a key or URL) anyone could run any model.
if (
usesServerCredentials(provider, {
apiKey,
baseUrl,
awsAccessKeyId,
awsSecretAccessKey,
vertexApiKey,
})
) {
return NextResponse.json(
{ valid: false, error: "API key is required" },
{ status: 400 },
)
}
// On the deployment's own endpoints a Test runs a model as a chat
// does, so with the quota on it counts as a chat request (an
// admin's Test of the server's URL does not)
const userId = getUserIdFromRequest(req)
if (
isQuotaEnabled() &&
!trustedBaseUrl &&
userId !== "anonymous" &&
(await usesServerEndpoint(
provider,
normalizeBaseUrl(body.baseUrl ?? ""),
apiKey,
))
) {
const quotaCheck = await checkAndIncrementRequest(userId, {
requests: Number(process.env.DAILY_REQUEST_LIMIT) || 10,
tokens: Number(process.env.DAILY_TOKEN_LIMIT) || 200000,
tpm: Number(process.env.TPM_LIMIT) || 20000,
})
if (!quotaCheck.allowed) {
return NextResponse.json(
{ valid: false, error: quotaCheck.error },
{ status: 429 },
)
}
}
// The same model the chat would use. A client base URL makes it
// refuse redirects to internal hosts.
const { model } = getAIModel({
provider,
modelId,
apiKey,
baseUrl,
trustedBaseUrl,
awsAccessKeyId,
awsSecretAccessKey,
awsRegion,
// Temporary AWS credentials need it, as in the chat
awsSessionToken,
vertexApiKey,
// EdgeOne checks the Pages cookies and the access code
...(provider === "edgeone" && {
headers: {
cookie: req.headers.get("cookie") || "",
"x-access-code": req.headers.get("x-access-code") || "",
},
}),
})
// Streaming, like the chat (some models only stream). Stop at the
// first tool call; a reasoning model that runs out of tokens first
// proves the connection but not tool support.
const startTime = Date.now()
const result = streamText({
model,
prompt: "Call the ping tool.",
tools: { ping: PING_TOOL },
maxOutputTokens: 1024,
maxRetries: 0,
abortSignal: AbortSignal.timeout(TEST_TIMEOUT_MS),
})
let calledTool = false
let finishReason: string | undefined
for await (const part of result.fullStream) {
if (part.type === "error") throw part.error
// The timeout ends the stream with an abort part, not an error
if (part.type === "abort") {
const timeout = new Error(
`The model did not answer within ${TEST_TIMEOUT_MS / 1000} s.`,
)
timeout.name = "TimeoutError"
throw timeout
}
if (part.type === "tool-call") {
calledTool = true
break
}
if (part.type === "finish") finishReason = part.finishReason
}
const responseTime = Date.now() - startTime
return NextResponse.json({
valid: true,
responseTime,
...(!calledTool &&
finishReason !== "length" && { warning: NO_TOOL_CALL_WARNING }),
})
} catch (error) {
console.error("[validate-model] Error:", error)
const { code, message } = classifyLLMError(error)
return NextResponse.json(
{ valid: false, code, error: message },
{ status: 200 }, // Return 200 so client can read error message
)
}
}
lib/validation-schema.ts
-1
View File
@@ -35,4 +35,3 @@ export const ValidationResultSchema = z.object({
}) })
export type ValidationResult = z.infer<typeof ValidationResultSchema> export type ValidationResult = z.infer<typeof ValidationResultSchema>
export type ValidationIssue = ValidationResult["issues"][number]
tests/unit/admin-providers.test.ts
-3
View File
@@ -48,8 +48,6 @@ describe("deriveEnvUpdates", () => {
expect(updates.ADMIN_OPENAI_API_KEY).toBe("sk-test") expect(updates.ADMIN_OPENAI_API_KEY).toBe("sk-test")
expect(updates.OPENAI_API_KEY).toBeUndefined() expect(updates.OPENAI_API_KEY).toBeUndefined()
expect(JSON.parse(updates.ADMIN_PROVIDERS as string)).toHaveLength(1) expect(JSON.parse(updates.ADMIN_PROVIDERS as string)).toHaveLength(1)
// AI_MODELS_CONFIG is no longer written (merged at read time)
expect(updates.AI_MODELS_CONFIG).toBeNull()
}) })
it("suffixes env vars for a second instance of the same provider", () => { it("suffixes env vars for a second instance of the same provider", () => {
@@ -137,7 +135,6 @@ describe("deriveEnvUpdates", () => {
const prev = [provider()] const prev = [provider()]
const updates = deriveEnvUpdates([], prev) const updates = deriveEnvUpdates([], prev)
expect(updates.ADMIN_OPENAI_API_KEY).toBeNull() expect(updates.ADMIN_OPENAI_API_KEY).toBeNull()
expect(updates.AI_MODELS_CONFIG).toBeNull()
expect(updates.ADMIN_PROVIDERS).toBeNull() expect(updates.ADMIN_PROVIDERS).toBeNull()
}) })
tests/unit/admin-test-model.test.ts
+10 -10
View File
@@ -1,12 +1,12 @@
// @vitest-environment node // @vitest-environment node
import { afterEach, beforeEach, describe, expect, it, vi } from "vitest" import { afterEach, beforeEach, describe, expect, it, vi } from "vitest"
// The request the admin Test hands to validate-model // What the admin Test hands to testModelConnection
const sent = vi.hoisted(() => ({ body: null as any, headers: null as any })) const sent = vi.hoisted(() => ({ body: null as any, trusted: null as any }))
vi.mock("@/app/api/validate-model/route", () => ({ vi.mock("@/lib/test-model-connection", () => ({
POST: async (req: Request) => { testModelConnection: async (_req: Request, body: any, trusted: boolean) => {
sent.body = await req.json() sent.body = body
sent.headers = Object.fromEntries(req.headers) sent.trusted = trusted
return Response.json({ valid: true }) return Response.json({ valid: true })
}, },
})) }))
@@ -61,7 +61,7 @@ describe("admin Test of an entry without a URL", () => {
await test({ provider: "openai", apiKey: "panel-key" }) await test({ provider: "openai", apiKey: "panel-key" })
expect(sent.body.baseUrl).toBe("https://operator-proxy.example.com/v1") expect(sent.body.baseUrl).toBe("https://operator-proxy.example.com/v1")
// The server's own URL, tested without the rules for typed URLs // The server's own URL, tested without the rules for typed URLs
expect(sent.body.serverBaseUrl).toBe(true) expect(sent.trusted).toBe(true)
process.env.AI_GATEWAY_BASE_URL = "https://gateway.example.com/v3/ai" process.env.AI_GATEWAY_BASE_URL = "https://gateway.example.com/v3/ai"
await test({ provider: "gateway", apiKey: "k" }) await test({ provider: "gateway", apiKey: "k" })
@@ -91,7 +91,7 @@ describe("admin Test of an entry without a URL", () => {
"https://vertex-proxy.example.com" "https://vertex-proxy.example.com"
await test({ provider: "vertexai", vertexApiKey: "new-key" }) await test({ provider: "vertexai", vertexApiKey: "new-key" })
expect(sent.body.baseUrl).toBe("https://vertex-proxy.example.com") expect(sent.body.baseUrl).toBe("https://vertex-proxy.example.com")
expect(sent.body.serverBaseUrl).toBe(true) expect(sent.trusted).toBe(true)
} finally { } finally {
delete process.env.GOOGLE_VERTEX_BASE_URL delete process.env.GOOGLE_VERTEX_BASE_URL
} }
@@ -103,7 +103,7 @@ describe("admin Test of an entry without a URL", () => {
expect(sent.body.baseUrl).toBe( expect(sent.body.baseUrl).toBe(
"https://team-openai.openai.azure.com/openai", "https://team-openai.openai.azure.com/openai",
) )
expect(sent.body.serverBaseUrl).toBe(true) expect(sent.trusted).toBe(true)
}) })
it("tests Ollama where chat sends the entry's key", async () => { it("tests Ollama where chat sends the entry's key", async () => {
@@ -111,7 +111,7 @@ describe("admin Test of an entry without a URL", () => {
// the SDK's local default (the Test used to go to Ollama Cloud) // the SDK's local default (the Test used to go to Ollama Cloud)
await test({ provider: "ollama", apiKey: "k" }) await test({ provider: "ollama", apiKey: "k" })
expect(sent.body.baseUrl).toBe("http://127.0.0.1:11434/api") expect(sent.body.baseUrl).toBe("http://127.0.0.1:11434/api")
expect(sent.body.serverBaseUrl).toBe(true) expect(sent.trusted).toBe(true)
envFallback.values.OLLAMA_BASE_URL = "http://gpu:11434/api" envFallback.values.OLLAMA_BASE_URL = "http://gpu:11434/api"
await test({ provider: "ollama", apiKey: "k" }) await test({ provider: "ollama", apiKey: "k" })
expect(sent.body.baseUrl).toBe("http://gpu:11434/api") expect(sent.body.baseUrl).toBe("http://gpu:11434/api")
tests/unit/ai-providers-google.test.ts
+41 -5
View File
@@ -3,7 +3,13 @@ import { generateText } from "ai"
import { afterEach, describe, expect, it, vi } from "vitest" import { afterEach, describe, expect, it, vi } from "vitest"
import { getAIModel } from "@/lib/ai-providers" import { getAIModel } from "@/lib/ai-providers"
const ENV = ["GOOGLE_GENERATIVE_AI_API_KEY", "GOOGLE_TOP_K", "GOOGLE_TOP_P"] const ENV = [
"GOOGLE_GENERATIVE_AI_API_KEY",
"GOOGLE_TOP_K",
"GOOGLE_TOP_P",
"GOOGLE_THINKING_BUDGET",
"GOOGLE_THINKING_LEVEL",
]
const saved = Object.fromEntries(ENV.map((k) => [k, process.env[k]])) const saved = Object.fromEntries(ENV.map((k) => [k, process.env[k]]))
afterEach(() => { afterEach(() => {
@@ -15,7 +21,7 @@ afterEach(() => {
}) })
/** Send one request through the real Google provider and return its body */ /** Send one request through the real Google provider and return its body */
async function googleRequestBody() { async function googleRequestBody(modelId = "gemini-2.5-flash") {
let body: any let body: any
vi.stubGlobal( vi.stubGlobal(
"fetch", "fetch",
@@ -34,11 +40,17 @@ async function googleRequestBody() {
) )
}), }),
) )
const { model } = getAIModel({ // providerOptions carry the thinking settings, as the chat route passes them
const { model, providerOptions } = getAIModel({
provider: "google", provider: "google",
modelId: "gemini-2.5-flash", modelId,
})
await generateText({
model,
prompt: "hi",
maxRetries: 0,
...(providerOptions && { providerOptions }),
}) })
await generateText({ model, prompt: "hi", maxRetries: 0 })
return body return body
} }
@@ -60,3 +72,27 @@ describe("Google sampling settings", () => {
expect(body.generationConfig?.topP).toBeUndefined() expect(body.generationConfig?.topP).toBeUndefined()
}) })
}) })
describe("Gemini thinking settings", () => {
it("sends GOOGLE_THINKING_BUDGET as the Gemini 2.5 thinking budget", async () => {
process.env.GOOGLE_GENERATIVE_AI_API_KEY = "test-key"
process.env.GOOGLE_THINKING_BUDGET = "8192"
delete process.env.GOOGLE_THINKING_LEVEL
const body = await googleRequestBody("gemini-2.5-flash")
expect(body.generationConfig.thinkingConfig).toEqual({
includeThoughts: true,
thinkingBudget: 8192,
})
})
it("sends GOOGLE_THINKING_LEVEL as the Gemini 3 thinking level", async () => {
process.env.GOOGLE_GENERATIVE_AI_API_KEY = "test-key"
process.env.GOOGLE_THINKING_LEVEL = "high"
delete process.env.GOOGLE_THINKING_BUDGET
const body = await googleRequestBody("gemini-3-pro-preview")
expect(body.generationConfig.thinkingConfig).toEqual({
includeThoughts: true,
thinkingLevel: "high",
})
})
})
tests/unit/ai-providers.test.ts
+11 -73
View File
@@ -9,7 +9,6 @@ import {
describe("resolveBaseURL", () => { describe("resolveBaseURL", () => {
const SERVER_BASE_URL = "https://server-proxy.example.com" const SERVER_BASE_URL = "https://server-proxy.example.com"
const USER_BASE_URL = "https://user-proxy.example.com" const USER_BASE_URL = "https://user-proxy.example.com"
const DEFAULT_BASE_URL = "https://api.provider.com/v1"
const USER_API_KEY = "user-api-key-123" const USER_API_KEY = "user-api-key-123"
describe("when user provides their own API key", () => { describe("when user provides their own API key", () => {
@@ -18,28 +17,12 @@ describe("resolveBaseURL", () => {
USER_API_KEY, USER_API_KEY,
USER_BASE_URL, USER_BASE_URL,
SERVER_BASE_URL, SERVER_BASE_URL,
DEFAULT_BASE_URL,
) )
expect(result).toBe(USER_BASE_URL) expect(result).toBe(USER_BASE_URL)
}) })
it("uses default baseUrl when user provides no baseUrl", () => { it("returns undefined when user provides no baseUrl", () => {
const result = resolveBaseURL( const result = resolveBaseURL(USER_API_KEY, null, SERVER_BASE_URL)
USER_API_KEY,
null,
SERVER_BASE_URL,
DEFAULT_BASE_URL,
)
expect(result).toBe(DEFAULT_BASE_URL)
})
it("returns undefined when user provides no baseUrl and no default exists", () => {
const result = resolveBaseURL(
USER_API_KEY,
null,
SERVER_BASE_URL,
undefined,
)
expect(result).toBeUndefined() expect(result).toBeUndefined()
}) })
@@ -48,92 +31,47 @@ describe("resolveBaseURL", () => {
USER_API_KEY, USER_API_KEY,
undefined, undefined,
SERVER_BASE_URL, SERVER_BASE_URL,
undefined,
) )
// Should NOT return SERVER_BASE_URL // Should NOT return SERVER_BASE_URL
expect(result).not.toBe(SERVER_BASE_URL) expect(result).not.toBe(SERVER_BASE_URL)
expect(result).toBeUndefined() expect(result).toBeUndefined()
}) })
it("prefers user's baseUrl over default", () => {
const result = resolveBaseURL(
USER_API_KEY,
USER_BASE_URL,
SERVER_BASE_URL,
DEFAULT_BASE_URL,
)
expect(result).toBe(USER_BASE_URL)
})
}) })
describe("when using server credentials (no user API key)", () => { describe("when using server credentials (no user API key)", () => {
it("uses user's baseUrl when provided (overrides server)", () => { it("uses user's baseUrl when provided (overrides server)", () => {
const result = resolveBaseURL( const result = resolveBaseURL(null, USER_BASE_URL, SERVER_BASE_URL)
null,
USER_BASE_URL,
SERVER_BASE_URL,
DEFAULT_BASE_URL,
)
expect(result).toBe(USER_BASE_URL) expect(result).toBe(USER_BASE_URL)
}) })
it("falls back to server's baseUrl when no user baseUrl", () => { it("falls back to server's baseUrl when no user baseUrl", () => {
const result = resolveBaseURL( const result = resolveBaseURL(null, null, SERVER_BASE_URL)
null,
null,
SERVER_BASE_URL,
DEFAULT_BASE_URL,
)
expect(result).toBe(SERVER_BASE_URL) expect(result).toBe(SERVER_BASE_URL)
}) })
it("falls back to default when no user or server baseUrl", () => {
const result = resolveBaseURL(
null,
null,
undefined,
DEFAULT_BASE_URL,
)
expect(result).toBe(DEFAULT_BASE_URL)
})
it("returns undefined when no baseUrl available anywhere", () => { it("returns undefined when no baseUrl available anywhere", () => {
const result = resolveBaseURL(null, null, undefined, undefined) const result = resolveBaseURL(null, null, undefined)
expect(result).toBeUndefined() expect(result).toBeUndefined()
}) })
it("handles undefined apiKey same as null", () => { it("handles undefined apiKey same as null", () => {
const result = resolveBaseURL( const result = resolveBaseURL(undefined, null, SERVER_BASE_URL)
undefined,
null,
SERVER_BASE_URL,
DEFAULT_BASE_URL,
)
expect(result).toBe(SERVER_BASE_URL) expect(result).toBe(SERVER_BASE_URL)
}) })
}) })
describe("edge cases", () => { describe("edge cases", () => {
it("handles empty string apiKey as falsy (uses server config)", () => { it("handles empty string apiKey as falsy (uses server config)", () => {
const result = resolveBaseURL( const result = resolveBaseURL("", null, SERVER_BASE_URL)
"",
null,
SERVER_BASE_URL,
DEFAULT_BASE_URL,
)
// Empty string is falsy, so should use server config // Empty string is falsy, so should use server config
expect(result).toBe(SERVER_BASE_URL) expect(result).toBe(SERVER_BASE_URL)
}) })
it("handles empty string baseUrl as falsy", () => { it("handles empty string baseUrl as falsy", () => {
const result = resolveBaseURL( const result = resolveBaseURL(USER_API_KEY, "", SERVER_BASE_URL)
USER_API_KEY, // Empty string baseUrl is falsy; a user's key never goes to the
"", // server's URL, so nothing is left
SERVER_BASE_URL, expect(result).toBeUndefined()
DEFAULT_BASE_URL,
)
// Empty string baseUrl is falsy, should fall back to default
expect(result).toBe(DEFAULT_BASE_URL)
}) })
}) })
}) })
tests/unit/chat-helpers.test.ts
-86
View File
@@ -6,7 +6,6 @@ import { describe, expect, it } from "vitest"
import { import {
dropInvalidToolCalls, dropInvalidToolCalls,
fixToolInputJson, fixToolInputJson,
replaceHistoricalToolInputs,
validateFileParts, validateFileParts,
} from "@/lib/chat-helpers" } from "@/lib/chat-helpers"
@@ -94,91 +93,6 @@ describe("validateFileParts", () => {
}) })
}) })
describe("replaceHistoricalToolInputs", () => {
it("replaces display_diagram tool inputs with placeholder", () => {
const messages = [
{
role: "assistant",
content: [
{
type: "tool-call",
toolName: "display_diagram",
input: { xml: "<mxCell...>" },
},
],
},
]
const result = replaceHistoricalToolInputs(messages)
expect(result[0].content[0].input.placeholder).toContain(
"XML content replaced",
)
})
it("replaces edit_diagram tool inputs with placeholder", () => {
const messages = [
{
role: "assistant",
content: [
{
type: "tool-call",
toolName: "edit_diagram",
input: { operations: [] },
},
],
},
]
const result = replaceHistoricalToolInputs(messages)
expect(result[0].content[0].input.placeholder).toContain(
"XML content replaced",
)
})
it("leaves tool calls with invalid inputs for dropInvalidToolCalls", () => {
const messages = [
{
role: "assistant",
content: [
{
type: "tool-call",
toolName: "display_diagram",
input: {},
},
{
type: "tool-call",
toolName: "display_diagram",
input: null,
},
],
},
]
const result = replaceHistoricalToolInputs(messages)
expect(result[0].content).toEqual(messages[0].content)
})
it("preserves non-assistant messages", () => {
const messages = [{ role: "user", content: "hello" }]
const result = replaceHistoricalToolInputs(messages)
expect(result).toEqual(messages)
})
it("preserves other tool calls", () => {
const messages = [
{
role: "assistant",
content: [
{
type: "tool-call",
toolName: "other_tool",
input: { foo: "bar" },
},
],
},
]
const result = replaceHistoricalToolInputs(messages)
expect(result[0].content[0].input).toEqual({ foo: "bar" })
})
})
describe("dropInvalidToolCalls", () => { describe("dropInvalidToolCalls", () => {
it("drops an invalid tool-call together with its tool-result", () => { it("drops an invalid tool-call together with its tool-result", () => {
const messages = [ const messages = [
tests/unit/edgeone-function.test.ts
+21 -6
View File
@@ -1,22 +1,37 @@
// @vitest-environment node // @vitest-environment node
import { describe, expect, it } from "vitest" import { afterEach, beforeEach, describe, expect, it, vi } from "vitest"
import { onRequest } from "@/edge-functions/api/edgeai/chat/completions" import { onRequest } from "@/edge-functions/api/edgeai/chat/completions"
// EdgeOne's global AI object, answering with an empty stream
beforeEach(() => {
vi.stubGlobal("AI", {
chatCompletions: async () => new ReadableStream(),
})
})
afterEach(() => {
vi.unstubAllGlobals()
})
function request(headers: Record<string, string>): Request { function request(headers: Record<string, string>): Request {
return new Request("http://localhost/api/edgeai/chat/completions", { return new Request("http://localhost/api/edgeai/chat/completions", {
method: "POST", method: "POST",
headers, headers,
// Non-streaming requests return a mock reply without calling AI
body: JSON.stringify({ messages: [{ role: "user", content: "hi" }] }), body: JSON.stringify({ messages: [{ role: "user", content: "hi" }] }),
}) })
} }
const json = { "Content-Type": "application/json" } const json = { "Content-Type": "application/json" }
// An accepted request streams the model's reply
function expectStream(res: Response) {
expect(res.status).toBe(200)
expect(res.headers.get("content-type")).toContain("text/event-stream")
}
describe("EdgeOne chat completions function", () => { describe("EdgeOne chat completions function", () => {
it("sends no CORS headers", async () => { it("sends no CORS headers", async () => {
const res = await onRequest({ request: request(json), env: {} }) const res = await onRequest({ request: request(json), env: {} })
expect(res.status).toBe(200) expectStream(res)
expect(res.headers.get("access-control-allow-origin")).toBeNull() expect(res.headers.get("access-control-allow-origin")).toBeNull()
}) })
@@ -40,7 +55,7 @@ describe("EdgeOne chat completions function", () => {
}), }),
env: {}, env: {},
}) })
expect(withCharset.status).toBe(200) expectStream(withCharset)
}) })
it("checks the access code when ACCESS_CODE_LIST is set", async () => { it("checks the access code when ACCESS_CODE_LIST is set", async () => {
@@ -52,11 +67,11 @@ describe("EdgeOne chat completions function", () => {
request: request({ ...json, "x-access-code": "secret" }), request: request({ ...json, "x-access-code": "secret" }),
env, env,
}) })
expect(ok.status).toBe(200) expectStream(ok)
}) })
it("lets requests through when env is unavailable", async () => { it("lets requests through when env is unavailable", async () => {
const res = await onRequest({ request: request(json) }) const res = await onRequest({ request: request(json) })
expect(res.status).toBe(200) expectStream(res)
}) })
}) })
tests/unit/log-save-route.test.ts
+4 -2
View File
@@ -2,9 +2,11 @@
import { describe, expect, it, vi } from "vitest" import { describe, expect, it, vi } from "vitest"
import { POST as logSave } from "@/app/api/log-save/route" import { POST as logSave } from "@/app/api/log-save/route"
// A Langfuse client with a trace to attach the save score to // A Langfuse client with a trace to attach the save score to; the real
// scoreLatestTrace runs against it
const batch = vi.fn(async () => ({})) const batch = vi.fn(async () => ({}))
vi.mock("@/lib/langfuse", () => ({ vi.mock("@/lib/langfuse", async (importOriginal) => ({
...(await importOriginal<typeof import("@/lib/langfuse")>()),
getLangfuseClient: () => ({ getLangfuseClient: () => ({
api: { api: {
trace: { list: async () => ({ data: [{ id: "trace-1" }] }) }, trace: { list: async () => ({ data: [{ id: "trace-1" }] }) },
tests/unit/output-token-limit.test.ts
+37 -32
View File
@@ -1,19 +1,26 @@
import { describe, expect, it } from "vitest" import { describe, expect, it } from "vitest"
import { import {
DEFAULT_MAX_OUTPUT_TOKENS, DEFAULT_MAX_OUTPUT_TOKENS,
parseOutputTokenLimit, readCeiling,
rejectionText,
resolveMaxOutputTokens, resolveMaxOutputTokens,
retryOutputTokens, retryOutputTokens,
withOutputTokenLimitFallback, withOutputTokenLimitFallback,
} from "@/lib/output-token-limit" } from "@/lib/output-token-limit"
describe("parseOutputTokenLimit", () => { // The ceiling a rejection names, before the "too small to retry" check
const parse = (error: unknown) => {
const text = rejectionText(error)
return text ? readCeiling(text) : null
}
describe("readCeiling", () => {
it("reads the ceiling from a Bedrock rejection", () => { it("reads the ceiling from a Bedrock rejection", () => {
const error = { const error = {
message: message:
"The maximum tokens you requested exceeds the model limit of 4096. Try again with a maximum tokens value that is lower than 4096.", "The maximum tokens you requested exceeds the model limit of 4096. Try again with a maximum tokens value that is lower than 4096.",
} }
expect(parseOutputTokenLimit(error)).toBe(4096) expect(parse(error)).toBe(4096)
}) })
it("subtracts the input when the ceiling covers input plus output", () => { it("subtracts the input when the ceiling covers input plus output", () => {
@@ -22,7 +29,7 @@ describe("parseOutputTokenLimit", () => {
"This endpoint's maximum context length is 64000 tokens. However, you requested about 64025 tokens (25 of text input, 64000 in the output).", "This endpoint's maximum context length is 64000 tokens. However, you requested about 64025 tokens (25 of text input, 64000 in the output).",
} }
// 64000 - 25 - 1024 margin // 64000 - 25 - 1024 margin
expect(parseOutputTokenLimit(error)).toBe(62951) expect(parse(error)).toBe(62951)
}) })
it("reads the ceiling from an Anthropic rejection", () => { it("reads the ceiling from an Anthropic rejection", () => {
@@ -30,7 +37,7 @@ describe("parseOutputTokenLimit", () => {
message: message:
"max_tokens: 200000 > 64000, which is the maximum allowed number of output tokens for claude-sonnet-4-5", "max_tokens: 200000 > 64000, which is the maximum allowed number of output tokens for claude-sonnet-4-5",
} }
expect(parseOutputTokenLimit(error)).toBe(64000) expect(parse(error)).toBe(64000)
}) })
it("reads the ceiling from an OpenAI rejection", () => { it("reads the ceiling from an OpenAI rejection", () => {
@@ -38,7 +45,7 @@ describe("parseOutputTokenLimit", () => {
message: message:
"max_tokens is too large: 64000. This model supports at most 16384 completion tokens", "max_tokens is too large: 64000. This model supports at most 16384 completion tokens",
} }
expect(parseOutputTokenLimit(error)).toBe(16384) expect(parse(error)).toBe(16384)
}) })
it("looks in the response body too", () => { it("looks in the response body too", () => {
@@ -46,25 +53,25 @@ describe("parseOutputTokenLimit", () => {
message: "Bad request", message: "Bad request",
responseBody: '{"message":"exceeds the model limit of 10000."}', responseBody: '{"message":"exceeds the model limit of 10000."}',
} }
expect(parseOutputTokenLimit(error)).toBe(10000) expect(parse(error)).toBe(10000)
}) })
it("returns null for unrelated errors", () => { it("returns null for unrelated errors", () => {
expect(parseOutputTokenLimit({ message: "Invalid API key" })).toBeNull() expect(parse({ message: "Invalid API key" })).toBeNull()
expect(parseOutputTokenLimit(undefined)).toBeNull() expect(parse(undefined)).toBeNull()
}) })
it("ignores a number that is not about tokens", () => { it("ignores a number that is not about tokens", () => {
// An earlier draft matched "lower than N" generically, which turned any // An earlier draft matched "lower than N" generically, which turned any
// message shaped like this into a bogus budget // message shaped like this into a bogus budget
expect( expect(
parseOutputTokenLimit({ parse({
message: "temperature must be lower than 2", message: "temperature must be lower than 2",
statusCode: 400, statusCode: 400,
}), }),
).toBeNull() ).toBeNull()
expect( expect(
parseOutputTokenLimit({ parse({
message: "reduce requests to lower than 60 per minute", message: "reduce requests to lower than 60 per minute",
statusCode: 429, statusCode: 429,
}), }),
@@ -76,28 +83,26 @@ describe("parseOutputTokenLimit", () => {
message: "exceeds the model limit of 4096", message: "exceeds the model limit of 4096",
statusCode: 429, statusCode: 429,
} }
expect(parseOutputTokenLimit(error)).toBeNull() expect(parse(error)).toBeNull()
}) })
it("rejects a ceiling too small to hold a diagram", () => { it("reads a ceiling too small to hold a diagram as it is", () => {
expect( // retryOutputTokens is what refuses to retry on these
parseOutputTokenLimit({ message: "model limit of 200" }), expect(parse({ message: "model limit of 200" })).toBe(200)
).toBeNull()
// Context ceiling that leaves almost nothing after the input // Context ceiling that leaves almost nothing after the input
expect( expect(
parseOutputTokenLimit({ parse({
message: message:
"This endpoint's maximum context length is 64000 tokens. However, you requested about 128000 tokens (63500 of text input, 64000 in the output).", "This endpoint's maximum context length is 64000 tokens. However, you requested about 128000 tokens (63500 of text input, 64000 in the output).",
}), }),
).toBeNull() ).toBe(64000 - 63500 - 1024)
}) // The input alone fills the context
expect(
it("returns null when the input alone fills the context", () => { parse({
const error = { message:
message: "This endpoint's maximum context length is 1000 tokens. However, you requested about 65000 tokens (64000 of text input, 1000 in the output).",
"This endpoint's maximum context length is 1000 tokens. However, you requested about 65000 tokens (64000 of text input, 1000 in the output).", }),
} ).toBe(1000 - 64000 - 1024)
expect(parseOutputTokenLimit(error)).toBeNull()
}) })
it("reads the ceiling from a Volcengine Ark rejection", () => { it("reads the ceiling from a Volcengine Ark rejection", () => {
@@ -106,10 +111,10 @@ describe("parseOutputTokenLimit", () => {
"The parameter `max_tokens` specified in the request are not valid: integer above maximum value, expected a value <= 32768, but got 64000 instead.", "The parameter `max_tokens` specified in the request are not valid: integer above maximum value, expected a value <= 32768, but got 64000 instead.",
statusCode: 400, statusCode: 400,
} }
expect(parseOutputTokenLimit(error)).toBe(32768) expect(parse(error)).toBe(32768)
// Same message JSON-escaped in the response body // Same message JSON-escaped in the response body
expect( expect(
parseOutputTokenLimit({ parse({
message: "Bad request", message: "Bad request",
responseBody: responseBody:
'{"error":{"message":"The parameter `max_tokens` specified in the request are not valid: integer above maximum value, expected a value \\u003c= 16384, but got 64000 instead."}}', '{"error":{"message":"The parameter `max_tokens` specified in the request are not valid: integer above maximum value, expected a value \\u003c= 16384, but got 64000 instead."}}',
@@ -122,27 +127,27 @@ describe("parseOutputTokenLimit", () => {
message: message:
"<400> InternalError.Algo.InvalidParameter: Range of max_tokens should be [1, 8192]", "<400> InternalError.Algo.InvalidParameter: Range of max_tokens should be [1, 8192]",
} }
expect(parseOutputTokenLimit(error)).toBe(8192) expect(parse(error)).toBe(8192)
}) })
it("subtracts the input in SGLang and vLLM context rejections", () => { it("subtracts the input in SGLang and vLLM context rejections", () => {
// SGLang // SGLang
expect( expect(
parseOutputTokenLimit({ parse({
message: message:
"Requested token count exceeds the model's maximum context length of 32768 tokens. You requested a total of 70000 tokens: 6000 tokens from the input messages and 64000 tokens for the completion.", "Requested token count exceeds the model's maximum context length of 32768 tokens. You requested a total of 70000 tokens: 6000 tokens from the input messages and 64000 tokens for the completion.",
}), }),
).toBe(32768 - 6000 - 1024) ).toBe(32768 - 6000 - 1024)
// vLLM, older wording // vLLM, older wording
expect( expect(
parseOutputTokenLimit({ parse({
message: message:
"This model's maximum context length is 32768 tokens. However, you requested 70000 tokens (6000 in the messages, 64000 in the completion).", "This model's maximum context length is 32768 tokens. However, you requested 70000 tokens (6000 in the messages, 64000 in the completion).",
}), }),
).toBe(32768 - 6000 - 1024) ).toBe(32768 - 6000 - 1024)
// vLLM, newer wording // vLLM, newer wording
expect( expect(
parseOutputTokenLimit({ parse({
message: message:
"This model's maximum context length is 32768 tokens and your request has 6000 input tokens (64000 > 32768 - 6000).", "This model's maximum context length is 32768 tokens and your request has 6000 input tokens (64000 > 32768 - 6000).",
}), }),
tests/unit/validate-model-route.test.ts
+26 -8
View File
@@ -257,17 +257,37 @@ describe("testing EdgeOne", () => {
}) })
describe("the admin Test of the server's own base URL", () => { describe("the admin Test of the server's own base URL", () => {
const test = (headers: Record<string, string>) => // An admin panel entry without a URL of its own
const adminTest = () =>
testModel(
new Request("http://localhost/api/admin/test-model", {
method: "POST",
headers: {
"Content-Type": "application/json",
"x-admin-password": "admin-pw",
},
body: JSON.stringify({
provider: {
id: "p1",
provider: "openai",
apiKey: "panel-key",
models: ["gpt-5.5"],
},
modelId: "gpt-5.5",
}),
}),
)
// A user naming the same address in the Settings dialog
const userTest = () =>
validateModel( validateModel(
new Request("http://localhost/api/validate-model", { new Request("http://localhost/api/validate-model", {
method: "POST", method: "POST",
headers: { "Content-Type": "application/json", ...headers }, headers: { "Content-Type": "application/json" },
body: JSON.stringify({ body: JSON.stringify({
provider: "openai", provider: "openai",
apiKey: "panel-key", apiKey: "panel-key",
modelId: "gpt-5.5", modelId: "gpt-5.5",
baseUrl: "http://10.0.0.5:8000/v1", baseUrl: "http://10.0.0.5:8000/v1",
serverBaseUrl: true,
}), }),
}), }),
) )
@@ -280,12 +300,10 @@ describe("the admin Test of the server's own base URL", () => {
privateUrls.all = true privateUrls.all = true
try { try {
streamReply({ role: "assistant", content: "OK" }) streamReply({ role: "assistant", content: "OK" })
const admin = await ( const admin = await (await adminTest()).json()
await test({ "x-admin-password": "admin-pw" })
).json()
expect(admin.valid).toBe(true) expect(admin.valid).toBe(true)
// Anyone else claiming it is still refused // A user typing the same address is still refused
const other = await test({}) const other = await userTest()
expect(other.status).toBe(400) expect(other.status).toBe(400)
} finally { } finally {
privateUrls.all = false privateUrls.all = false