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feat: implement simple query service and enhance provider abstraction

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- Introduced a new Simple Query Service to streamline basic AI queries, allowing for structured JSON outputs.
- Updated existing routes to utilize the new service, replacing direct SDK calls with a unified interface for querying.
- Enhanced provider handling in various routes, including generate-spec, generate-features-from-spec, and validate-issue, to support both Claude and Cursor models seamlessly.
- Added structured output support for improved response handling and error management across the application.
This commit is contained in:
webdevcody
2026-01-12 17:33:54 -05:00
parent f3f5d05349
commit eb8ebe3ce0
12 changed files with 563 additions and 951 deletions
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2
apps/server/src/providers/claude-provider.ts
View File

@@ -99,6 +99,8 @@ export class ClaudeProvider extends BaseProvider {
...(maxThinkingTokens && { maxThinkingTokens }),
// Subagents configuration for specialized task delegation
...(options.agents && { agents: options.agents }),
// Pass through outputFormat for structured JSON outputs
...(options.outputFormat && { outputFormat: options.outputFormat }),
};
// Build prompt payload

8
apps/server/src/providers/index.ts
View File

@@ -30,3 +30,11 @@ export { OpencodeProvider } from './opencode-provider.js';
// Provider factory
export { ProviderFactory } from './provider-factory.js';
// Simple query service - unified interface for basic AI queries
export { simpleQuery, streamingQuery } from './simple-query-service.js';
export type {
SimpleQueryOptions,
SimpleQueryResult,
StreamingQueryOptions,
} from './simple-query-service.js';

240
apps/server/src/providers/simple-query-service.ts Normal file
View File

@@ -0,0 +1,240 @@
/**
* Simple Query Service - Simplified interface for basic AI queries
*
* Use this for routes that need simple text responses without
* complex event handling. This service abstracts away the provider
* selection and streaming details, providing a clean interface
* for common query patterns.
*
* Benefits:
* - No direct SDK imports needed in route files
* - Consistent provider routing based on model
* - Automatic text extraction from streaming responses
* - Structured output support for JSON schema responses
* - Eliminates duplicate extractTextFromStream() functions
*/
import { ProviderFactory } from './provider-factory.js';
import type { ProviderMessage, ContentBlock, ThinkingLevel } from '@automaker/types';
/**
* Options for simple query execution
*/
export interface SimpleQueryOptions {
/** The prompt to send to the AI (can be text or multi-part content) */
prompt: string | Array<{ type: string; text?: string; source?: object }>;
/** Model to use (with or without provider prefix) */
model?: string;
/** Working directory for the query */
cwd: string;
/** System prompt (combined with user prompt for some providers) */
systemPrompt?: string;
/** Maximum turns for agentic operations (default: 1) */
maxTurns?: number;
/** Tools to allow (default: [] for simple queries) */
allowedTools?: string[];
/** Abort controller for cancellation */
abortController?: AbortController;
/** Structured output format for JSON responses */
outputFormat?: {
type: 'json_schema';
schema: Record<string, unknown>;
};
/** Thinking level for Claude models */
thinkingLevel?: ThinkingLevel;
/** If true, runs in read-only mode (no file writes) */
readOnly?: boolean;
/** Setting sources for CLAUDE.md loading */
settingSources?: Array<'user' | 'project' | 'local'>;
}
/**
* Result from a simple query
*/
export interface SimpleQueryResult {
/** The accumulated text response */
text: string;
/** Structured output if outputFormat was specified and provider supports it */
structured_output?: Record<string, unknown>;
}
/**
* Options for streaming query execution
*/
export interface StreamingQueryOptions extends SimpleQueryOptions {
/** Callback for each text chunk received */
onText?: (text: string) => void;
/** Callback for tool use events */
onToolUse?: (tool: string, input: unknown) => void;
/** Callback for thinking blocks (if available) */
onThinking?: (thinking: string) => void;
}
/**
* Default model to use when none specified
*/
const DEFAULT_MODEL = 'claude-sonnet-4-20250514';
/**
* Execute a simple query and return the text result
*
* Use this for simple, non-streaming queries where you just need
* the final text response. For more complex use cases with progress
* callbacks, use streamingQuery() instead.
*
* @example
* ```typescript
* const result = await simpleQuery({
* prompt: 'Generate a title for: user authentication',
* cwd: process.cwd(),
* systemPrompt: 'You are a title generator...',
* maxTurns: 1,
* allowedTools: [],
* });
* console.log(result.text); // "Add user authentication"
* ```
*/
export async function simpleQuery(options: SimpleQueryOptions): Promise<SimpleQueryResult> {
const model = options.model || DEFAULT_MODEL;
const provider = ProviderFactory.getProviderForModel(model);
let responseText = '';
let structuredOutput: Record<string, unknown> | undefined;
// Build provider options
const providerOptions = {
prompt: options.prompt,
model: model,
cwd: options.cwd,
systemPrompt: options.systemPrompt,
maxTurns: options.maxTurns ?? 1,
allowedTools: options.allowedTools ?? [],
abortController: options.abortController,
outputFormat: options.outputFormat,
thinkingLevel: options.thinkingLevel,
readOnly: options.readOnly,
settingSources: options.settingSources,
};
for await (const msg of provider.executeQuery(providerOptions)) {
// Handle error messages
if (msg.type === 'error') {
const errorMessage = msg.error || 'Provider returned an error';
throw new Error(errorMessage);
}
// Extract text from assistant messages
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
}
// Handle result messages
if (msg.type === 'result') {
if (msg.subtype === 'success') {
// Use result text if longer than accumulated text
if (msg.result && msg.result.length > responseText.length) {
responseText = msg.result;
}
// Capture structured output if present
if (msg.structured_output) {
structuredOutput = msg.structured_output;
}
} else if (msg.subtype === 'error_max_turns') {
// Max turns reached - return what we have
break;
} else if (msg.subtype === 'error_max_structured_output_retries') {
throw new Error('Could not produce valid structured output after retries');
}
}
}
return { text: responseText, structured_output: structuredOutput };
}
/**
* Execute a streaming query with event callbacks
*
* Use this for queries where you need real-time progress updates,
* such as when displaying streaming output to a user.
*
* @example
* ```typescript
* const result = await streamingQuery({
* prompt: 'Analyze this project and suggest improvements',
* cwd: '/path/to/project',
* maxTurns: 250,
* allowedTools: ['Read', 'Glob', 'Grep'],
* onText: (text) => emitProgress(text),
* onToolUse: (tool, input) => emitToolUse(tool, input),
* });
* ```
*/
export async function streamingQuery(options: StreamingQueryOptions): Promise<SimpleQueryResult> {
const model = options.model || DEFAULT_MODEL;
const provider = ProviderFactory.getProviderForModel(model);
let responseText = '';
let structuredOutput: Record<string, unknown> | undefined;
// Build provider options
const providerOptions = {
prompt: options.prompt,
model: model,
cwd: options.cwd,
systemPrompt: options.systemPrompt,
maxTurns: options.maxTurns ?? 250,
allowedTools: options.allowedTools ?? ['Read', 'Glob', 'Grep'],
abortController: options.abortController,
outputFormat: options.outputFormat,
thinkingLevel: options.thinkingLevel,
readOnly: options.readOnly,
settingSources: options.settingSources,
};
for await (const msg of provider.executeQuery(providerOptions)) {
// Handle error messages
if (msg.type === 'error') {
const errorMessage = msg.error || 'Provider returned an error';
throw new Error(errorMessage);
}
// Extract content from assistant messages
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
options.onText?.(block.text);
} else if (block.type === 'tool_use' && block.name) {
options.onToolUse?.(block.name, block.input);
} else if (block.type === 'thinking' && block.thinking) {
options.onThinking?.(block.thinking);
}
}
}
// Handle result messages
if (msg.type === 'result') {
if (msg.subtype === 'success') {
// Use result text if longer than accumulated text
if (msg.result && msg.result.length > responseText.length) {
responseText = msg.result;
}
// Capture structured output if present
if (msg.structured_output) {
structuredOutput = msg.structured_output;
}
} else if (msg.subtype === 'error_max_turns') {
// Max turns reached - return what we have
break;
} else if (msg.subtype === 'error_max_structured_output_retries') {
throw new Error('Could not produce valid structured output after retries');
}
}
}
return { text: responseText, structured_output: structuredOutput };
}

142
apps/server/src/routes/app-spec/generate-features-from-spec.ts
View File

@@ -5,15 +5,12 @@
* (defaults to Sonnet for balanced speed and quality).
*/
import { query } from '@anthropic-ai/claude-agent-sdk';
import * as secureFs from '../../lib/secure-fs.js';
import type { EventEmitter } from '../../lib/events.js';
import { createLogger } from '@automaker/utils';
import { DEFAULT_PHASE_MODELS, isCursorModel, stripProviderPrefix } from '@automaker/types';
import { DEFAULT_PHASE_MODELS } from '@automaker/types';
import { resolvePhaseModel } from '@automaker/model-resolver';
import { createFeatureGenerationOptions } from '../../lib/sdk-options.js';
import { ProviderFactory } from '../../providers/provider-factory.js';
import { logAuthStatus } from './common.js';
import { streamingQuery } from '../../providers/simple-query-service.js';
import { parseAndCreateFeatures } from './parse-and-create-features.js';
import { getAppSpecPath } from '@automaker/platform';
import type { SettingsService } from '../../services/settings-service.js';
@@ -115,121 +112,30 @@ IMPORTANT: Do not ask for clarification. The specification is provided above. Ge
logger.info('Using model:', model);
let responseText = '';
let messageCount = 0;
// Use streamingQuery with event callbacks
const result = await streamingQuery({
prompt,
model,
cwd: projectPath,
maxTurns: 250,
allowedTools: ['Read', 'Glob', 'Grep'],
abortController,
thinkingLevel,
readOnly: true, // Feature generation only reads code, doesn't write
settingSources: autoLoadClaudeMd ? ['user', 'project', 'local'] : undefined,
onText: (text) => {
logger.debug(`Feature text block received (${text.length} chars)`);
events.emit('spec-regeneration:event', {
type: 'spec_regeneration_progress',
content: text,
projectPath: projectPath,
});
},
});
// Route to appropriate provider based on model type
if (isCursorModel(model)) {
// Use Cursor provider for Cursor models
logger.info('[FeatureGeneration] Using Cursor provider');
const responseText = result.text;
const provider = ProviderFactory.getProviderForModel(model);
// Strip provider prefix - providers expect bare model IDs
const bareModel = stripProviderPrefix(model);
// Add explicit instructions for Cursor to return JSON in response
const cursorPrompt = `${prompt}
CRITICAL INSTRUCTIONS:
1. DO NOT write any files. Return the JSON in your response only.
2. Respond with ONLY a JSON object - no explanations, no markdown, just raw JSON.
3. Your entire response should be valid JSON starting with { and ending with }. No text before or after.`;
for await (const msg of provider.executeQuery({
prompt: cursorPrompt,
model: bareModel,
cwd: projectPath,
maxTurns: 250,
allowedTools: ['Read', 'Glob', 'Grep'],
abortController,
readOnly: true, // Feature generation only reads code, doesn't write
})) {
messageCount++;
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
logger.debug(`Feature text block received (${block.text.length} chars)`);
events.emit('spec-regeneration:event', {
type: 'spec_regeneration_progress',
content: block.text,
projectPath: projectPath,
});
}
}
} else if (msg.type === 'result' && msg.subtype === 'success' && msg.result) {
// Use result if it's a final accumulated message
if (msg.result.length > responseText.length) {
responseText = msg.result;
}
}
}
} else {
// Use Claude SDK for Claude models
logger.info('[FeatureGeneration] Using Claude SDK');
const options = createFeatureGenerationOptions({
cwd: projectPath,
abortController,
autoLoadClaudeMd,
model,
thinkingLevel, // Pass thinking level for extended thinking
});
logger.debug('SDK Options:', JSON.stringify(options, null, 2));
logger.info('Calling Claude Agent SDK query() for features...');
logAuthStatus('Right before SDK query() for features');
let stream;
try {
stream = query({ prompt, options });
logger.debug('query() returned stream successfully');
} catch (queryError) {
logger.error('❌ query() threw an exception:');
logger.error('Error:', queryError);
throw queryError;
}
logger.debug('Starting to iterate over feature stream...');
try {
for await (const msg of stream) {
messageCount++;
logger.debug(
`Feature stream message #${messageCount}:`,
JSON.stringify({ type: msg.type, subtype: (msg as any).subtype }, null, 2)
);
if (msg.type === 'assistant' && msg.message.content) {
for (const block of msg.message.content) {
if (block.type === 'text') {
responseText += block.text;
logger.debug(`Feature text block received (${block.text.length} chars)`);
events.emit('spec-regeneration:event', {
type: 'spec_regeneration_progress',
content: block.text,
projectPath: projectPath,
});
}
}
} else if (msg.type === 'result' && (msg as any).subtype === 'success') {
logger.debug('Received success result for features');
responseText = (msg as any).result || responseText;
} else if ((msg as { type: string }).type === 'error') {
logger.error('❌ Received error message from feature stream:');
logger.error('Error message:', JSON.stringify(msg, null, 2));
}
}
} catch (streamError) {
logger.error('❌ Error while iterating feature stream:');
logger.error('Stream error:', streamError);
throw streamError;
}
}
logger.info(`Feature stream complete. Total messages: ${messageCount}`);
logger.info(`Feature stream complete.`);
logger.info(`Feature response length: ${responseText.length} chars`);
logger.info('========== FULL RESPONSE TEXT ==========');
logger.info(responseText);

220
apps/server/src/routes/app-spec/generate-spec.ts
View File

@@ -5,8 +5,6 @@
* (defaults to Opus for high-quality specification generation).
*/
import { query } from '@anthropic-ai/claude-agent-sdk';
import path from 'path';
import * as secureFs from '../../lib/secure-fs.js';
import type { EventEmitter } from '../../lib/events.js';
import {
@@ -16,12 +14,10 @@ import {
type SpecOutput,
} from '../../lib/app-spec-format.js';
import { createLogger } from '@automaker/utils';
import { DEFAULT_PHASE_MODELS, isCursorModel, stripProviderPrefix } from '@automaker/types';
import { DEFAULT_PHASE_MODELS, isCursorModel } from '@automaker/types';
import { resolvePhaseModel } from '@automaker/model-resolver';
import { createSpecGenerationOptions } from '../../lib/sdk-options.js';
import { extractJson } from '../../lib/json-extractor.js';
import { ProviderFactory } from '../../providers/provider-factory.js';
import { logAuthStatus } from './common.js';
import { streamingQuery } from '../../providers/simple-query-service.js';
import { generateFeaturesFromSpec } from './generate-features-from-spec.js';
import { ensureAutomakerDir, getAppSpecPath } from '@automaker/platform';
import type { SettingsService } from '../../services/settings-service.js';
@@ -109,21 +105,15 @@ ${getStructuredSpecPromptInstruction()}`;
logger.info('Using model:', model);
let responseText = '';
let messageCount = 0;
let structuredOutput: SpecOutput | null = null;
// Route to appropriate provider based on model type
if (isCursorModel(model)) {
// Use Cursor provider for Cursor models
logger.info('[SpecGeneration] Using Cursor provider');
// Determine if we should use structured output (Claude supports it, Cursor doesn't)
const useStructuredOutput = !isCursorModel(model);
const provider = ProviderFactory.getProviderForModel(model);
// Strip provider prefix - providers expect bare model IDs
const bareModel = stripProviderPrefix(model);
// For Cursor, include the JSON schema in the prompt with clear instructions
// to return JSON in the response (not write to a file)
const cursorPrompt = `${prompt}
// Build the final prompt - for Cursor, include JSON schema instructions
let finalPrompt = prompt;
if (!useStructuredOutput) {
finalPrompt = `${prompt}
CRITICAL INSTRUCTIONS:
1. DO NOT write any files. DO NOT create any files like "project_specification.json".
@@ -133,153 +123,57 @@ CRITICAL INSTRUCTIONS:
${JSON.stringify(specOutputSchema, null, 2)}
Your entire response should be valid JSON starting with { and ending with }. No text before or after.`;
for await (const msg of provider.executeQuery({
prompt: cursorPrompt,
model: bareModel,
cwd: projectPath,
maxTurns: 250,
allowedTools: ['Read', 'Glob', 'Grep'],
abortController,
readOnly: true, // Spec generation only reads code, we write the spec ourselves
})) {
messageCount++;
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
logger.info(
`Text block received (${block.text.length} chars), total now: ${responseText.length} chars`
);
events.emit('spec-regeneration:event', {
type: 'spec_regeneration_progress',
content: block.text,
projectPath: projectPath,
});
} else if (block.type === 'tool_use') {
logger.info('Tool use:', block.name);
events.emit('spec-regeneration:event', {
type: 'spec_tool',
tool: block.name,
input: block.input,
});
}
}
} else if (msg.type === 'result' && msg.subtype === 'success' && msg.result) {
// Use result if it's a final accumulated message
if (msg.result.length > responseText.length) {
responseText = msg.result;
}
}
}
// Parse JSON from the response text using shared utility
if (responseText) {
structuredOutput = extractJson<SpecOutput>(responseText, { logger });
}
} else {
// Use Claude SDK for Claude models
logger.info('[SpecGeneration] Using Claude SDK');
const options = createSpecGenerationOptions({
cwd: projectPath,
abortController,
autoLoadClaudeMd,
model,
thinkingLevel, // Pass thinking level for extended thinking
outputFormat: {
type: 'json_schema',
schema: specOutputSchema,
},
});
logger.debug('SDK Options:', JSON.stringify(options, null, 2));
logger.info('Calling Claude Agent SDK query()...');
// Log auth status right before the SDK call
logAuthStatus('Right before SDK query()');
let stream;
try {
stream = query({ prompt, options });
logger.debug('query() returned stream successfully');
} catch (queryError) {
logger.error('❌ query() threw an exception:');
logger.error('Error:', queryError);
throw queryError;
}
logger.info('Starting to iterate over stream...');
try {
for await (const msg of stream) {
messageCount++;
logger.info(
`Stream message #${messageCount}: type=${msg.type}, subtype=${(msg as any).subtype}`
);
if (msg.type === 'assistant') {
const msgAny = msg as any;
if (msgAny.message?.content) {
for (const block of msgAny.message.content) {
if (block.type === 'text') {
responseText += block.text;
logger.info(
`Text block received (${block.text.length} chars), total now: ${responseText.length} chars`
);
events.emit('spec-regeneration:event', {
type: 'spec_regeneration_progress',
content: block.text,
projectPath: projectPath,
});
} else if (block.type === 'tool_use') {
logger.info('Tool use:', block.name);
events.emit('spec-regeneration:event', {
type: 'spec_tool',
tool: block.name,
input: block.input,
});
}
}
}
} else if (msg.type === 'result' && (msg as any).subtype === 'success') {
logger.info('Received success result');
// Check for structured output - this is the reliable way to get spec data
const resultMsg = msg as any;
if (resultMsg.structured_output) {
structuredOutput = resultMsg.structured_output as SpecOutput;
logger.info('✅ Received structured output');
logger.debug('Structured output:', JSON.stringify(structuredOutput, null, 2));
} else {
logger.warn('⚠️ No structured output in result, will fall back to text parsing');
}
} else if (msg.type === 'result') {
// Handle error result types
const subtype = (msg as any).subtype;
logger.info(`Result message: subtype=${subtype}`);
if (subtype === 'error_max_turns') {
logger.error('❌ Hit max turns limit!');
} else if (subtype === 'error_max_structured_output_retries') {
logger.error('❌ Failed to produce valid structured output after retries');
throw new Error('Could not produce valid spec output');
}
} else if ((msg as { type: string }).type === 'error') {
logger.error('❌ Received error message from stream:');
logger.error('Error message:', JSON.stringify(msg, null, 2));
} else if (msg.type === 'user') {
// Log user messages (tool results)
logger.info(`User message (tool result): ${JSON.stringify(msg).substring(0, 500)}`);
}
}
} catch (streamError) {
logger.error('❌ Error while iterating stream:');
logger.error('Stream error:', streamError);
throw streamError;
}
}
logger.info(`Stream iteration complete. Total messages: ${messageCount}`);
// Use streamingQuery with event callbacks
const result = await streamingQuery({
prompt: finalPrompt,
model,
cwd: projectPath,
maxTurns: 250,
allowedTools: ['Read', 'Glob', 'Grep'],
abortController,
thinkingLevel,
readOnly: true, // Spec generation only reads code, we write the spec ourselves
settingSources: autoLoadClaudeMd ? ['user', 'project', 'local'] : undefined,
outputFormat: useStructuredOutput
? {
type: 'json_schema',
schema: specOutputSchema,
}
: undefined,
onText: (text) => {
responseText += text;
logger.info(
`Text block received (${text.length} chars), total now: ${responseText.length} chars`
);
events.emit('spec-regeneration:event', {
type: 'spec_regeneration_progress',
content: text,
projectPath: projectPath,
});
},
onToolUse: (tool, input) => {
logger.info('Tool use:', tool);
events.emit('spec-regeneration:event', {
type: 'spec_tool',
tool,
input,
});
},
});
// Get structured output if available
if (result.structured_output) {
structuredOutput = result.structured_output as unknown as SpecOutput;
logger.info('✅ Received structured output');
logger.debug('Structured output:', JSON.stringify(structuredOutput, null, 2));
} else if (!useStructuredOutput && responseText) {
// For non-Claude providers, parse JSON from response text
structuredOutput = extractJson<SpecOutput>(responseText, { logger });
}
logger.info(`Stream iteration complete.`);
logger.info(`Response text length: ${responseText.length} chars`);
// Determine XML content to save

113
apps/server/src/routes/context/routes/describe-file.ts
View File

@@ -11,13 +11,11 @@
*/
import type { Request, Response } from 'express';
import { query } from '@anthropic-ai/claude-agent-sdk';
import { createLogger } from '@automaker/utils';
import { DEFAULT_PHASE_MODELS, isCursorModel, stripProviderPrefix } from '@automaker/types';
import { DEFAULT_PHASE_MODELS } from '@automaker/types';
import { PathNotAllowedError } from '@automaker/platform';
import { resolvePhaseModel } from '@automaker/model-resolver';
import { createCustomOptions } from '../../../lib/sdk-options.js';
import { ProviderFactory } from '../../../providers/provider-factory.js';
import { simpleQuery } from '../../../providers/simple-query-service.js';
import * as secureFs from '../../../lib/secure-fs.js';
import * as path from 'path';
import type { SettingsService } from '../../../services/settings-service.js';
@@ -49,31 +47,6 @@ interface DescribeFileErrorResponse {
error: string;
}
/**
* Extract text content from Claude SDK response messages
*/
async function extractTextFromStream(
// eslint-disable-next-line @typescript-eslint/no-explicit-any
stream: AsyncIterable<any>
): Promise<string> {
let responseText = '';
for await (const msg of stream) {
if (msg.type === 'assistant' && msg.message?.content) {
const blocks = msg.message.content as Array<{ type: string; text?: string }>;
for (const block of blocks) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
} else if (msg.type === 'result' && msg.subtype === 'success') {
responseText = msg.result || responseText;
}
}
return responseText;
}
/**
* Create the describe-file request handler
*
@@ -159,16 +132,14 @@ export function createDescribeFileHandler(
// Build prompt with file content passed as structured data
// The file content is included directly, not via tool invocation
const instructionText = `Analyze the following file and provide a 1-2 sentence description suitable for use as context in an AI coding assistant. Focus on what the file contains, its purpose, and why an AI agent might want to use this context in the future (e.g., "API documentation for the authentication endpoints", "Configuration file for database connections", "Coding style guidelines for the project").
const prompt = `Analyze the following file and provide a 1-2 sentence description suitable for use as context in an AI coding assistant. Focus on what the file contains, its purpose, and why an AI agent might want to use this context in the future (e.g., "API documentation for the authentication endpoints", "Configuration file for database connections", "Coding style guidelines for the project").
Respond with ONLY the description text, no additional formatting, preamble, or explanation.
File: ${fileName}${truncated ? ' (truncated)' : ''}`;
File: ${fileName}${truncated ? ' (truncated)' : ''}
const promptContent = [
{ type: 'text' as const, text: instructionText },
{ type: 'text' as const, text: `\n\n--- FILE CONTENT ---\n${contentToAnalyze}` },
];
--- FILE CONTENT ---
${contentToAnalyze}`;
// Use the file's directory as the working directory
const cwd = path.dirname(resolvedPath);
@@ -190,67 +161,19 @@ File: ${fileName}${truncated ? ' (truncated)' : ''}`;
logger.info(`Resolved model: ${model}, thinkingLevel: ${thinkingLevel}`);
let description: string;
// Use simpleQuery - provider abstraction handles routing to correct provider
const result = await simpleQuery({
prompt,
model,
cwd,
maxTurns: 1,
allowedTools: [],
thinkingLevel,
readOnly: true, // File description only reads, doesn't write
settingSources: autoLoadClaudeMd ? ['user', 'project', 'local'] : undefined,
});
// Route to appropriate provider based on model type
if (isCursorModel(model)) {
// Use Cursor provider for Cursor models
logger.info(`Using Cursor provider for model: ${model}`);
const provider = ProviderFactory.getProviderForModel(model);
// Strip provider prefix - providers expect bare model IDs
const bareModel = stripProviderPrefix(model);
// Build a simple text prompt for Cursor (no multi-part content blocks)
const cursorPrompt = `${instructionText}\n\n--- FILE CONTENT ---\n${contentToAnalyze}`;
let responseText = '';
for await (const msg of provider.executeQuery({
prompt: cursorPrompt,
model: bareModel,
cwd,
maxTurns: 1,
allowedTools: [],
readOnly: true, // File description only reads, doesn't write
})) {
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
}
}
description = responseText;
} else {
// Use Claude SDK for Claude models
logger.info(`Using Claude SDK for model: ${model}`);
// Use centralized SDK options with proper cwd validation
// No tools needed since we're passing file content directly
const sdkOptions = createCustomOptions({
cwd,
model,
maxTurns: 1,
allowedTools: [],
autoLoadClaudeMd,
thinkingLevel, // Pass thinking level for extended thinking
});
const promptGenerator = (async function* () {
yield {
type: 'user' as const,
session_id: '',
message: { role: 'user' as const, content: promptContent },
parent_tool_use_id: null,
};
})();
const stream = query({ prompt: promptGenerator, options: sdkOptions });
// Extract the description from the response
description = await extractTextFromStream(stream);
}
const description = result.text;
if (!description || description.trim().length === 0) {
logger.warn('Received empty response from Claude');

196
apps/server/src/routes/context/routes/describe-image.ts
View File

@@ -12,12 +12,10 @@
*/
import type { Request, Response } from 'express';
import { query } from '@anthropic-ai/claude-agent-sdk';
import { createLogger, readImageAsBase64 } from '@automaker/utils';
import { DEFAULT_PHASE_MODELS, isCursorModel, stripProviderPrefix } from '@automaker/types';
import { DEFAULT_PHASE_MODELS, isCursorModel } from '@automaker/types';
import { resolvePhaseModel } from '@automaker/model-resolver';
import { createCustomOptions } from '../../../lib/sdk-options.js';
import { ProviderFactory } from '../../../providers/provider-factory.js';
import { simpleQuery } from '../../../providers/simple-query-service.js';
import * as secureFs from '../../../lib/secure-fs.js';
import * as path from 'path';
import type { SettingsService } from '../../../services/settings-service.js';
@@ -178,57 +176,10 @@ function mapDescribeImageError(rawMessage: string | undefined): {
return baseResponse;
}
/**
* Extract text content from Claude SDK response messages and log high-signal stream events.
*/
async function extractTextFromStream(
// eslint-disable-next-line @typescript-eslint/no-explicit-any
stream: AsyncIterable<any>,
requestId: string
): Promise<string> {
let responseText = '';
let messageCount = 0;
logger.info(`[${requestId}] [Stream] Begin reading SDK stream...`);
for await (const msg of stream) {
messageCount++;
const msgType = msg?.type;
const msgSubtype = msg?.subtype;
// Keep this concise but informative. Full error object is logged in catch blocks.
logger.info(
`[${requestId}] [Stream] #${messageCount} type=${String(msgType)} subtype=${String(msgSubtype ?? '')}`
);
if (msgType === 'assistant' && msg.message?.content) {
const blocks = msg.message.content as Array<{ type: string; text?: string }>;
logger.info(`[${requestId}] [Stream] assistant blocks=${blocks.length}`);
for (const block of blocks) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
}
if (msgType === 'result' && msgSubtype === 'success') {
if (typeof msg.result === 'string' && msg.result.length > 0) {
responseText = msg.result;
}
}
}
logger.info(
`[${requestId}] [Stream] End of stream. messages=${messageCount} textLength=${responseText.length}`
);
return responseText;
}
/**
* Create the describe-image request handler
*
* Uses Claude SDK query with multi-part content blocks to include the image (base64),
* Uses the provider abstraction with multi-part content blocks to include the image (base64),
* matching the agent runner behavior.
*
* @param settingsService - Optional settings service for loading autoLoadClaudeMd setting
@@ -309,27 +260,6 @@ export function createDescribeImageHandler(
`[${requestId}] image meta filename=${imageData.filename} mime=${imageData.mimeType} base64Len=${base64Length} estBytes=${estimatedBytes}`
);
// Build multi-part prompt with image block (no Read tool required)
const instructionText =
`Describe this image in 1-2 sentences suitable for use as context in an AI coding assistant. ` +
`Focus on what the image shows and its purpose (e.g., "UI mockup showing login form with email/password fields", ` +
`"Architecture diagram of microservices", "Screenshot of error message in terminal").\n\n` +
`Respond with ONLY the description text, no additional formatting, preamble, or explanation.`;
const promptContent = [
{ type: 'text' as const, text: instructionText },
{
type: 'image' as const,
source: {
type: 'base64' as const,
media_type: imageData.mimeType,
data: imageData.base64,
},
},
];
logger.info(`[${requestId}] Built multi-part prompt blocks=${promptContent.length}`);
const cwd = path.dirname(actualPath);
logger.info(`[${requestId}] Using cwd=${cwd}`);
@@ -348,85 +278,59 @@ export function createDescribeImageHandler(
logger.info(`[${requestId}] Using model: ${model}`);
let description: string;
// Build the instruction text
const instructionText =
`Describe this image in 1-2 sentences suitable for use as context in an AI coding assistant. ` +
`Focus on what the image shows and its purpose (e.g., "UI mockup showing login form with email/password fields", ` +
`"Architecture diagram of microservices", "Screenshot of error message in terminal").\n\n` +
`Respond with ONLY the description text, no additional formatting, preamble, or explanation.`;
// Build prompt based on provider capability
// Some providers (like Cursor) may not support image content blocks
let prompt: string | Array<{ type: string; text?: string; source?: object }>;
// Route to appropriate provider based on model type
if (isCursorModel(model)) {
// Use Cursor provider for Cursor models
// Note: Cursor may have limited support for image content blocks
logger.info(`[${requestId}] Using Cursor provider for model: ${model}`);
const provider = ProviderFactory.getProviderForModel(model);
// Strip provider prefix - providers expect bare model IDs
const bareModel = stripProviderPrefix(model);
// Build prompt with image reference for Cursor
// Note: Cursor CLI may not support base64 image blocks directly,
// so we include the image path as context
const cursorPrompt = `${instructionText}\n\nImage file: ${actualPath}\nMIME type: ${imageData.mimeType}`;
let responseText = '';
const queryStart = Date.now();
for await (const msg of provider.executeQuery({
prompt: cursorPrompt,
model: bareModel,
cwd,
maxTurns: 1,
allowedTools: ['Read'], // Allow Read tool so Cursor can read the image if needed
readOnly: true, // Image description only reads, doesn't write
})) {
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
}
}
logger.info(`[${requestId}] Cursor query completed in ${Date.now() - queryStart}ms`);
description = responseText;
// Cursor may not support base64 image blocks directly
// Use text prompt with image path reference
logger.info(`[${requestId}] Using text prompt for Cursor model`);
prompt = `${instructionText}\n\nImage file: ${actualPath}\nMIME type: ${imageData.mimeType}`;
} else {
// Use Claude SDK for Claude models (supports image content blocks)
logger.info(`[${requestId}] Using Claude SDK for model: ${model}`);
// Use the same centralized option builder used across the server (validates cwd)
const sdkOptions = createCustomOptions({
cwd,
model,
maxTurns: 1,
allowedTools: [],
autoLoadClaudeMd,
thinkingLevel, // Pass thinking level for extended thinking
});
logger.info(
`[${requestId}] SDK options model=${sdkOptions.model} maxTurns=${sdkOptions.maxTurns} allowedTools=${JSON.stringify(
sdkOptions.allowedTools
)}`
);
const promptGenerator = (async function* () {
yield {
type: 'user' as const,
session_id: '',
message: { role: 'user' as const, content: promptContent },
parent_tool_use_id: null,
};
})();
logger.info(`[${requestId}] Calling query()...`);
const queryStart = Date.now();
const stream = query({ prompt: promptGenerator, options: sdkOptions });
logger.info(`[${requestId}] query() returned stream in ${Date.now() - queryStart}ms`);
// Extract the description from the response
const extractStart = Date.now();
description = await extractTextFromStream(stream, requestId);
logger.info(`[${requestId}] extractMs=${Date.now() - extractStart}`);
// Claude and other vision-capable models support multi-part prompts with images
logger.info(`[${requestId}] Using multi-part prompt with image block`);
prompt = [
{ type: 'text', text: instructionText },
{
type: 'image',
source: {
type: 'base64',
media_type: imageData.mimeType,
data: imageData.base64,
},
},
];
}
logger.info(`[${requestId}] Calling simpleQuery...`);
const queryStart = Date.now();
// Use simpleQuery - provider abstraction handles routing
const result = await simpleQuery({
prompt,
model,
cwd,
maxTurns: 1,
allowedTools: isCursorModel(model) ? ['Read'] : [], // Allow Read for Cursor to read image if needed
thinkingLevel,
readOnly: true, // Image description only reads, doesn't write
settingSources: autoLoadClaudeMd ? ['user', 'project', 'local'] : undefined,
});
logger.info(`[${requestId}] simpleQuery completed in ${Date.now() - queryStart}ms`);
const description = result.text;
if (!description || description.trim().length === 0) {
logger.warn(`[${requestId}] Received empty response from Claude`);
logger.warn(`[${requestId}] Received empty response from AI`);
const response: DescribeImageErrorResponse = {
success: false,
error: 'Failed to generate description - empty response',

147
apps/server/src/routes/enhance-prompt/routes/enhance.ts
View File

@@ -1,23 +1,16 @@
/**
* POST /enhance-prompt endpoint - Enhance user input text
*
* Uses Claude AI or Cursor to enhance text based on the specified enhancement mode.
* Supports modes: improve, technical, simplify, acceptance
* Uses the provider abstraction to enhance text based on the specified
* enhancement mode. Works with any configured provider (Claude, Cursor, etc.).
* Supports modes: improve, technical, simplify, acceptance, ux-reviewer
*/
import type { Request, Response } from 'express';
import { query } from '@anthropic-ai/claude-agent-sdk';
import { createLogger } from '@automaker/utils';
import { resolveModelString } from '@automaker/model-resolver';
import {
CLAUDE_MODEL_MAP,
isCursorModel,
isOpencodeModel,
stripProviderPrefix,
ThinkingLevel,
getThinkingTokenBudget,
} from '@automaker/types';
import { ProviderFactory } from '../../../providers/provider-factory.js';
import { CLAUDE_MODEL_MAP, type ThinkingLevel } from '@automaker/types';
import { simpleQuery } from '../../../providers/simple-query-service.js';
import type { SettingsService } from '../../../services/settings-service.js';
import { getPromptCustomization } from '../../../lib/settings-helpers.js';
import {
@@ -38,7 +31,7 @@ interface EnhanceRequestBody {
enhancementMode: string;
/** Optional model override */
model?: string;
/** Optional thinking level for Claude models (ignored for Cursor models) */
/** Optional thinking level for Claude models */
thinkingLevel?: ThinkingLevel;
}
@@ -58,80 +51,6 @@ interface EnhanceErrorResponse {
error: string;
}
/**
* Extract text content from Claude SDK response messages
*
* @param stream - The async iterable from the query function
* @returns The extracted text content
*/
async function extractTextFromStream(
stream: AsyncIterable<{
type: string;
subtype?: string;
result?: string;
message?: {
content?: Array<{ type: string; text?: string }>;
};
}>
): Promise<string> {
let responseText = '';
for await (const msg of stream) {
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
} else if (msg.type === 'result' && msg.subtype === 'success') {
responseText = msg.result || responseText;
}
}
return responseText;
}
/**
* Execute enhancement using a provider (Cursor, OpenCode, etc.)
*
* @param prompt - The enhancement prompt
* @param model - The model to use
* @returns The enhanced text
*/
async function executeWithProvider(prompt: string, model: string): Promise<string> {
const provider = ProviderFactory.getProviderForModel(model);
// Strip provider prefix - providers expect bare model IDs
const bareModel = stripProviderPrefix(model);
let responseText = '';
for await (const msg of provider.executeQuery({
prompt,
model: bareModel,
cwd: process.cwd(), // Enhancement doesn't need a specific working directory
readOnly: true, // Prompt enhancement only generates text, doesn't write files
})) {
if (msg.type === 'error') {
// Throw error with the message from the provider
const errorMessage = msg.error || 'Provider returned an error';
throw new Error(errorMessage);
} else if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
} else if (msg.type === 'result' && msg.subtype === 'success' && msg.result) {
// Use result if it's a final accumulated message
if (msg.result.length > responseText.length) {
responseText = msg.result;
}
}
}
return responseText;
}
/**
* Create the enhance request handler
*
@@ -200,7 +119,6 @@ export function createEnhanceHandler(
logger.debug(`Using ${validMode} system prompt (length: ${systemPrompt.length} chars)`);
// Build the user prompt with few-shot examples
// This helps the model understand this is text transformation, not a coding task
const userPrompt = buildUserPrompt(validMode, trimmedText, true);
// Resolve the model - use the passed model, default to sonnet for quality
@@ -208,47 +126,20 @@ export function createEnhanceHandler(
logger.debug(`Using model: ${resolvedModel}`);
let enhancedText: string;
// Use simpleQuery - provider abstraction handles routing to correct provider
// The system prompt is combined with user prompt since some providers
// don't have a separate system prompt concept
const result = await simpleQuery({
prompt: `${systemPrompt}\n\n${userPrompt}`,
model: resolvedModel,
cwd: process.cwd(), // Enhancement doesn't need a specific working directory
maxTurns: 1,
allowedTools: [],
thinkingLevel,
readOnly: true, // Prompt enhancement only generates text, doesn't write files
});
// Route to appropriate provider based on model
if (isCursorModel(resolvedModel)) {
// Use Cursor provider for Cursor models
logger.info(`Using Cursor provider for model: ${resolvedModel}`);
// Cursor doesn't have a separate system prompt concept, so combine them
const combinedPrompt = `${systemPrompt}\n\n${userPrompt}`;
enhancedText = await executeWithProvider(combinedPrompt, resolvedModel);
} else if (isOpencodeModel(resolvedModel)) {
// Use OpenCode provider for OpenCode models (static and dynamic)
logger.info(`Using OpenCode provider for model: ${resolvedModel}`);
// OpenCode CLI handles the system prompt, so combine them
const combinedPrompt = `${systemPrompt}\n\n${userPrompt}`;
enhancedText = await executeWithProvider(combinedPrompt, resolvedModel);
} else {
// Use Claude SDK for Claude models
logger.info(`Using Claude provider for model: ${resolvedModel}`);
// Convert thinkingLevel to maxThinkingTokens for SDK
const maxThinkingTokens = getThinkingTokenBudget(thinkingLevel);
const queryOptions: Parameters<typeof query>[0]['options'] = {
model: resolvedModel,
systemPrompt,
maxTurns: 1,
allowedTools: [],
permissionMode: 'acceptEdits',
};
if (maxThinkingTokens) {
queryOptions.maxThinkingTokens = maxThinkingTokens;
}
const stream = query({
prompt: userPrompt,
options: queryOptions,
});
enhancedText = await extractTextFromStream(stream);
}
const enhancedText = result.text;
if (!enhancedText || enhancedText.trim().length === 0) {
logger.warn('Received empty response from AI');

52
apps/server/src/routes/features/routes/generate-title.ts
View File

@@ -1,13 +1,14 @@
/**
* POST /features/generate-title endpoint - Generate a concise title from description
*
* Uses Claude Haiku to generate a short, descriptive title from feature description.
* Uses the provider abstraction to generate a short, descriptive title
* from a feature description. Works with any configured provider (Claude, Cursor, etc.).
*/
import type { Request, Response } from 'express';
import { query } from '@anthropic-ai/claude-agent-sdk';
import { createLogger } from '@automaker/utils';
import { CLAUDE_MODEL_MAP } from '@automaker/model-resolver';
import { simpleQuery } from '../../../providers/simple-query-service.js';
const logger = createLogger('GenerateTitle');
@@ -34,33 +35,6 @@ Rules:
- No quotes, periods, or extra formatting
- Capture the essence of the feature in a scannable way`;
async function extractTextFromStream(
stream: AsyncIterable<{
type: string;
subtype?: string;
result?: string;
message?: {
content?: Array<{ type: string; text?: string }>;
};
}>
): Promise<string> {
let responseText = '';
for await (const msg of stream) {
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
}
}
} else if (msg.type === 'result' && msg.subtype === 'success') {
responseText = msg.result || responseText;
}
}
return responseText;
}
export function createGenerateTitleHandler(): (req: Request, res: Response) => Promise<void> {
return async (req: Request, res: Response): Promise<void> => {
try {
@@ -89,21 +63,19 @@ export function createGenerateTitleHandler(): (req: Request, res: Response) => P
const userPrompt = `Generate a concise title for this feature:\n\n${trimmedDescription}`;
const stream = query({
prompt: userPrompt,
options: {
model: CLAUDE_MODEL_MAP.haiku,
systemPrompt: SYSTEM_PROMPT,
maxTurns: 1,
allowedTools: [],
permissionMode: 'default',
},
// Use simpleQuery - provider abstraction handles all the streaming/extraction
const result = await simpleQuery({
prompt: `${SYSTEM_PROMPT}\n\n${userPrompt}`,
model: CLAUDE_MODEL_MAP.haiku,
cwd: process.cwd(),
maxTurns: 1,
allowedTools: [],
});
const title = await extractTextFromStream(stream);
const title = result.text;
if (!title || title.trim().length === 0) {
logger.warn('Received empty response from Claude');
logger.warn('Received empty response from AI');
const response: GenerateTitleErrorResponse = {
success: false,
error: 'Failed to generate title - empty response',

199
apps/server/src/routes/github/routes/validate-issue.ts
View File

@@ -1,5 +1,5 @@
/**
* POST /validate-issue endpoint - Validate a GitHub issue using Claude SDK or Cursor (async)
* POST /validate-issue endpoint - Validate a GitHub issue using provider abstraction (async)
*
* Scans the codebase to determine if an issue is valid, invalid, or needs clarification.
* Runs asynchronously and emits events for progress and completion.
@@ -7,7 +7,6 @@
*/
import type { Request, Response } from 'express';
import { query } from '@anthropic-ai/claude-agent-sdk';
import type { EventEmitter } from '../../../lib/events.js';
import type {
IssueValidationResult,
@@ -18,12 +17,11 @@ import type {
LinkedPRInfo,
ThinkingLevel,
} from '@automaker/types';
import { isCursorModel, DEFAULT_PHASE_MODELS, stripProviderPrefix } from '@automaker/types';
import { isCursorModel, DEFAULT_PHASE_MODELS } from '@automaker/types';
import { resolvePhaseModel } from '@automaker/model-resolver';
import { createSuggestionsOptions } from '../../../lib/sdk-options.js';
import { extractJson } from '../../../lib/json-extractor.js';
import { writeValidation } from '../../../lib/validation-storage.js';
import { ProviderFactory } from '../../../providers/provider-factory.js';
import { streamingQuery } from '../../../providers/simple-query-service.js';
import {
issueValidationSchema,
ISSUE_VALIDATION_SYSTEM_PROMPT,
@@ -102,7 +100,7 @@ async function runValidation(
try {
// Build the prompt (include comments and linked PRs if provided)
const prompt = buildValidationPrompt(
const basePrompt = buildValidationPrompt(
issueNumber,
issueTitle,
issueBody,
@@ -111,20 +109,15 @@ async function runValidation(
linkedPRs
);
let validationResult: IssueValidationResult | null = null;
let responseText = '';
// Route to appropriate provider based on model
if (isCursorModel(model)) {
// Use Cursor provider for Cursor models
logger.info(`Using Cursor provider for validation with model: ${model}`);
// Determine if we should use structured output (Claude supports it, Cursor doesn't)
const useStructuredOutput = !isCursorModel(model);
const provider = ProviderFactory.getProviderForModel(model);
// Strip provider prefix - providers expect bare model IDs
const bareModel = stripProviderPrefix(model);
// For Cursor, include the system prompt and schema in the user prompt
const cursorPrompt = `${ISSUE_VALIDATION_SYSTEM_PROMPT}
// Build the final prompt - for Cursor, include system prompt and JSON schema instructions
let finalPrompt = basePrompt;
if (!useStructuredOutput) {
finalPrompt = `${ISSUE_VALIDATION_SYSTEM_PROMPT}
CRITICAL INSTRUCTIONS:
1. DO NOT write any files. Return the JSON in your response only.
@@ -135,121 +128,71 @@ ${JSON.stringify(issueValidationSchema, null, 2)}
Your entire response should be valid JSON starting with { and ending with }. No text before or after.
${prompt}`;
for await (const msg of provider.executeQuery({
prompt: cursorPrompt,
model: bareModel,
cwd: projectPath,
readOnly: true, // Issue validation only reads code, doesn't write
})) {
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
// Emit progress event
const progressEvent: IssueValidationEvent = {
type: 'issue_validation_progress',
issueNumber,
content: block.text,
projectPath,
};
events.emit('issue-validation:event', progressEvent);
}
}
} else if (msg.type === 'result' && msg.subtype === 'success' && msg.result) {
// Use result if it's a final accumulated message
if (msg.result.length > responseText.length) {
responseText = msg.result;
}
}
}
// Parse JSON from the response text using shared utility
if (responseText) {
validationResult = extractJson<IssueValidationResult>(responseText, { logger });
}
} else {
// Use Claude SDK for Claude models
logger.info(`Using Claude provider for validation with model: ${model}`);
// Load autoLoadClaudeMd setting
const autoLoadClaudeMd = await getAutoLoadClaudeMdSetting(
projectPath,
settingsService,
'[ValidateIssue]'
);
// Use thinkingLevel from request if provided, otherwise fall back to settings
let effectiveThinkingLevel: ThinkingLevel | undefined = thinkingLevel;
if (!effectiveThinkingLevel) {
const settings = await settingsService?.getGlobalSettings();
const phaseModelEntry =
settings?.phaseModels?.validationModel || DEFAULT_PHASE_MODELS.validationModel;
const resolved = resolvePhaseModel(phaseModelEntry);
effectiveThinkingLevel = resolved.thinkingLevel;
}
// Create SDK options with structured output and abort controller
const options = createSuggestionsOptions({
cwd: projectPath,
model: model as ModelAlias,
systemPrompt: ISSUE_VALIDATION_SYSTEM_PROMPT,
abortController,
autoLoadClaudeMd,
thinkingLevel: effectiveThinkingLevel,
outputFormat: {
type: 'json_schema',
schema: issueValidationSchema as Record<string, unknown>,
},
});
// Execute the query
const stream = query({ prompt, options });
for await (const msg of stream) {
// Collect assistant text for debugging and emit progress
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text') {
responseText += block.text;
// Emit progress event
const progressEvent: IssueValidationEvent = {
type: 'issue_validation_progress',
issueNumber,
content: block.text,
projectPath,
};
events.emit('issue-validation:event', progressEvent);
}
}
}
// Extract structured output on success
if (msg.type === 'result' && msg.subtype === 'success') {
const resultMsg = msg as { structured_output?: IssueValidationResult };
if (resultMsg.structured_output) {
validationResult = resultMsg.structured_output;
logger.debug('Received structured output:', validationResult);
}
}
// Handle errors
if (msg.type === 'result') {
const resultMsg = msg as { subtype?: string };
if (resultMsg.subtype === 'error_max_structured_output_retries') {
logger.error('Failed to produce valid structured output after retries');
throw new Error('Could not produce valid validation output');
}
}
}
${basePrompt}`;
}
// Load autoLoadClaudeMd setting
const autoLoadClaudeMd = await getAutoLoadClaudeMdSetting(
projectPath,
settingsService,
'[ValidateIssue]'
);
// Use thinkingLevel from request if provided, otherwise fall back to settings
let effectiveThinkingLevel: ThinkingLevel | undefined = thinkingLevel;
if (!effectiveThinkingLevel) {
const settings = await settingsService?.getGlobalSettings();
const phaseModelEntry =
settings?.phaseModels?.validationModel || DEFAULT_PHASE_MODELS.validationModel;
const resolved = resolvePhaseModel(phaseModelEntry);
effectiveThinkingLevel = resolved.thinkingLevel;
}
logger.info(`Using model: ${model}`);
// Use streamingQuery with event callbacks
const result = await streamingQuery({
prompt: finalPrompt,
model: model as string,
cwd: projectPath,
systemPrompt: useStructuredOutput ? ISSUE_VALIDATION_SYSTEM_PROMPT : undefined,
abortController,
thinkingLevel: effectiveThinkingLevel,
readOnly: true, // Issue validation only reads code, doesn't write
settingSources: autoLoadClaudeMd ? ['user', 'project', 'local'] : undefined,
outputFormat: useStructuredOutput
? {
type: 'json_schema',
schema: issueValidationSchema as Record<string, unknown>,
}
: undefined,
onText: (text) => {
responseText += text;
// Emit progress event
const progressEvent: IssueValidationEvent = {
type: 'issue_validation_progress',
issueNumber,
content: text,
projectPath,
};
events.emit('issue-validation:event', progressEvent);
},
});
// Clear timeout
clearTimeout(timeoutId);
// Get validation result from structured output or parse from text
let validationResult: IssueValidationResult | null = null;
if (result.structured_output) {
validationResult = result.structured_output as unknown as IssueValidationResult;
logger.debug('Received structured output:', validationResult);
} else if (responseText) {
// Parse JSON from response text
validationResult = extractJson<IssueValidationResult>(responseText, { logger });
}
// Require validation result
if (!validationResult) {
logger.error('No validation result received from AI provider');
@@ -299,7 +242,7 @@ ${prompt}`;
/**
* Creates the handler for validating GitHub issues against the codebase.
*
* Uses Claude SDK with:
* Uses the provider abstraction with:
* - Read-only tools (Read, Glob, Grep) for codebase analysis
* - JSON schema structured output for reliable parsing
* - System prompt guiding the validation process

191
apps/server/src/routes/suggestions/generate-suggestions.ts
View File

@@ -5,19 +5,12 @@
* (AI Suggestions in the UI). Supports both Claude and Cursor models.
*/
import { query } from '@anthropic-ai/claude-agent-sdk';
import type { EventEmitter } from '../../lib/events.js';
import { createLogger } from '@automaker/utils';
import {
DEFAULT_PHASE_MODELS,
isCursorModel,
stripProviderPrefix,
type ThinkingLevel,
} from '@automaker/types';
import { DEFAULT_PHASE_MODELS, isCursorModel, type ThinkingLevel } from '@automaker/types';
import { resolvePhaseModel } from '@automaker/model-resolver';
import { createSuggestionsOptions } from '../../lib/sdk-options.js';
import { extractJsonWithArray } from '../../lib/json-extractor.js';
import { ProviderFactory } from '../../providers/provider-factory.js';
import { streamingQuery } from '../../providers/simple-query-service.js';
import { FeatureLoader } from '../../services/feature-loader.js';
import { getAppSpecPath } from '@automaker/platform';
import * as secureFs from '../../lib/secure-fs.js';
@@ -204,19 +197,14 @@ The response will be automatically formatted as structured JSON.`;
logger.info('[Suggestions] Using model:', model);
let responseText = '';
let structuredOutput: { suggestions: Array<Record<string, unknown>> } | null = null;
// Route to appropriate provider based on model type
if (isCursorModel(model)) {
// Use Cursor provider for Cursor models
logger.info('[Suggestions] Using Cursor provider');
// Determine if we should use structured output (Claude supports it, Cursor doesn't)
const useStructuredOutput = !isCursorModel(model);
const provider = ProviderFactory.getProviderForModel(model);
// Strip provider prefix - providers expect bare model IDs
const bareModel = stripProviderPrefix(model);
// For Cursor, include the JSON schema in the prompt with clear instructions
const cursorPrompt = `${prompt}
// Build the final prompt - for Cursor, include JSON schema instructions
let finalPrompt = prompt;
if (!useStructuredOutput) {
finalPrompt = `${prompt}
CRITICAL INSTRUCTIONS:
1. DO NOT write any files. Return the JSON in your response only.
@@ -226,104 +214,60 @@ CRITICAL INSTRUCTIONS:
${JSON.stringify(suggestionsSchema, null, 2)}
Your entire response should be valid JSON starting with { and ending with }. No text before or after.`;
for await (const msg of provider.executeQuery({
prompt: cursorPrompt,
model: bareModel,
cwd: projectPath,
maxTurns: 250,
allowedTools: ['Read', 'Glob', 'Grep'],
abortController,
readOnly: true, // Suggestions only reads code, doesn't write
})) {
if (msg.type === 'assistant' && msg.message?.content) {
for (const block of msg.message.content) {
if (block.type === 'text' && block.text) {
responseText += block.text;
events.emit('suggestions:event', {
type: 'suggestions_progress',
content: block.text,
});
} else if (block.type === 'tool_use') {
events.emit('suggestions:event', {
type: 'suggestions_tool',
tool: block.name,
input: block.input,
});
}
}
} else if (msg.type === 'result' && msg.subtype === 'success' && msg.result) {
// Use result if it's a final accumulated message (from Cursor provider)
logger.info('[Suggestions] Received result from Cursor, length:', msg.result.length);
logger.info('[Suggestions] Previous responseText length:', responseText.length);
if (msg.result.length > responseText.length) {
logger.info('[Suggestions] Using Cursor result (longer than accumulated text)');
responseText = msg.result;
} else {
logger.info('[Suggestions] Keeping accumulated text (longer than Cursor result)');
}
}
}
} else {
// Use Claude SDK for Claude models
logger.info('[Suggestions] Using Claude SDK');
const options = createSuggestionsOptions({
cwd: projectPath,
abortController,
autoLoadClaudeMd,
model, // Pass the model from settings
thinkingLevel, // Pass thinking level for extended thinking
outputFormat: {
type: 'json_schema',
schema: suggestionsSchema,
},
});
const stream = query({ prompt, options });
for await (const msg of stream) {
if (msg.type === 'assistant' && msg.message.content) {
for (const block of msg.message.content) {
if (block.type === 'text') {
responseText += block.text;
events.emit('suggestions:event', {
type: 'suggestions_progress',
content: block.text,
});
} else if (block.type === 'tool_use') {
events.emit('suggestions:event', {
type: 'suggestions_tool',
tool: block.name,
input: block.input,
});
}
}
} else if (msg.type === 'result' && msg.subtype === 'success') {
// Check for structured output
const resultMsg = msg as any;
if (resultMsg.structured_output) {
structuredOutput = resultMsg.structured_output as {
suggestions: Array<Record<string, unknown>>;
};
logger.debug('Received structured output:', structuredOutput);
}
} else if (msg.type === 'result') {
const resultMsg = msg as any;
if (resultMsg.subtype === 'error_max_structured_output_retries') {
logger.error('Failed to produce valid structured output after retries');
throw new Error('Could not produce valid suggestions output');
} else if (resultMsg.subtype === 'error_max_turns') {
logger.error('Hit max turns limit before completing suggestions generation');
logger.warn(`Response text length: ${responseText.length} chars`);
// Still try to parse what we have
}
}
}
}
// Use streamingQuery with event callbacks
const result = await streamingQuery({
prompt: finalPrompt,
model,
cwd: projectPath,
maxTurns: 250,
allowedTools: ['Read', 'Glob', 'Grep'],
abortController,
thinkingLevel,
readOnly: true, // Suggestions only reads code, doesn't write
settingSources: autoLoadClaudeMd ? ['user', 'project', 'local'] : undefined,
outputFormat: useStructuredOutput
? {
type: 'json_schema',
schema: suggestionsSchema,
}
: undefined,
onText: (text) => {
responseText += text;
events.emit('suggestions:event', {
type: 'suggestions_progress',
content: text,
});
},
onToolUse: (tool, input) => {
events.emit('suggestions:event', {
type: 'suggestions_tool',
tool,
input,
});
},
});
// Use structured output if available, otherwise fall back to parsing text
try {
let structuredOutput: { suggestions: Array<Record<string, unknown>> } | null = null;
if (result.structured_output) {
structuredOutput = result.structured_output as {
suggestions: Array<Record<string, unknown>>;
};
logger.debug('Received structured output:', structuredOutput);
} else if (responseText) {
// Fallback: try to parse from text using shared extraction utility
logger.warn('No structured output received, attempting to parse from text');
structuredOutput = extractJsonWithArray<{ suggestions: Array<Record<string, unknown>> }>(
responseText,
'suggestions',
{ logger }
);
}
if (structuredOutput && structuredOutput.suggestions) {
// Use structured output directly
events.emit('suggestions:event', {
@@ -334,24 +278,7 @@ Your entire response should be valid JSON starting with { and ending with }. No
})),
});
} else {
// Fallback: try to parse from text using shared extraction utility
logger.warn('No structured output received, attempting to parse from text');
const parsed = extractJsonWithArray<{ suggestions: Array<Record<string, unknown>> }>(
responseText,
'suggestions',
{ logger }
);
if (parsed && parsed.suggestions) {
events.emit('suggestions:event', {
type: 'suggestions_complete',
suggestions: parsed.suggestions.map((s: Record<string, unknown>, i: number) => ({
...s,
id: s.id || `suggestion-${Date.now()}-${i}`,
})),
});
} else {
throw new Error('No valid JSON found in response');
}
throw new Error('No valid JSON found in response');
}
} catch (error) {
// Log the parsing error for debugging