co-mono/plan.md
Mario Zechner 2296dc4052 refactor(ai): improve error handling and stop reason types
- Add 'aborted' as a distinct stop reason separate from 'error'
- Change AssistantMessage.error to errorMessage for clarity
- Update error event to include reason field ('error' | 'aborted')
- Map provider-specific safety/refusal reasons to 'error' stop reason
- Reorganize utility functions into utils/ directory
- Rename agent.ts to agent-loop.ts for better clarity
- Fix error handling in all providers to properly distinguish abort from error
2025-09-18 19:57:13 +02:00

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# Agent API Rework Plan
## Executive Summary
Complete rewrite of the agent API with no backward compatibility constraints to support:
1. **Granular streaming events** - Fine-grained deltas (`text_delta`, `thinking_delta`, `toolcall_delta`) with clear message boundaries
2. **Streaming tool execution** - Tools can progressively stream output via `AsyncIterable<ToolExecutionEvent>`
3. **Remote tool execution** - Automatically detect remote tools (missing `execute` function) and suspend/resume execution
4. **HTTP-friendly transport** - Minimize data transfer with server-managed sessions and SSE streaming
Key design:
- `AgentEvent` is completely redesigned for granular streaming
- `AgentTool.execute` can return `Promise` or `AsyncIterable` (detected at runtime)
- Clean session-based API: `createSession()` and `execute()`
- `ExecuteStream` with `result()` method for getting pending tool calls
- Server manages all state, client is stateless
- No legacy code or compatibility layers
## Problem Statement
The current agent API has several limitations that prevent it from being used effectively in distributed environments:
1. **Coarse Event Granularity**: `message_update` events send the full message instead of deltas, making HTTP streaming inefficient
2. **Blocking Tool Execution**: Tools must complete execution before any results can be streamed
3. **Local-Only Tools**: Tools must run in the same environment as the `prompt()` call, preventing remote tool execution
4. **No Suspension/Resume**: The API cannot pause execution for external tool handling and resume later
## Requirements
### R1: Fine-Grained Streaming Events
- Stream text deltas, not full messages
- Stream thinking/reasoning deltas
- Stream tool call argument deltas
- Stream tool execution output progressively
- Clear message boundaries with start/end events
### R2: Remote Tool Execution
- Detect remote tools by absence of `execute` function (JSON.stringify naturally omits functions)
- Pause execution when remote tool is called
- Resume execution when remote tool completes
- Support both synchronous (local) and asynchronous (remote) tools
### R3: HTTP-Friendly
- Events should be efficiently serializable for Server-Sent Events (SSE)
- Minimize data transfer - no large context objects in events
- Server manages session state, client sends only deltas
### R4: Minimal API Surface
- Keep the API simple and intuitive
- No backward compatibility constraints - clean slate design
- Avoid complex state management on the client side
## Proposed Solution
### Core Concepts
#### 1. Agent Sessions
Sessions that can be suspended and resumed for remote tool execution:
```typescript
interface AgentSession {
id: string;
status: 'running' | 'awaiting_tool_execution' | 'completed' | 'error';
model: Model; // Last used model
messages: Message[]; // Full conversation context
totalCost: number; // Accumulated cost across all turns
pendingToolCalls?: ToolCall[]; // When status is 'awaiting_tool_execution'
}
```
#### 2. Tool Execution
Tools always return an async iterable stream, making the API consistent:
```typescript
type ToolExecutionEventStream = AsyncIterable<ToolExecutionEvent>;
interface AgentTool<TParams = any> extends Tool {
label: string; // Already exists
// If execute is defined -> local tool
// If execute is undefined (omitted during JSON serialization) -> remote tool
execute?: (id: string, params: TParams) => ToolExecutionEventStream;
}
// Tool execution event for streaming
type ToolExecutionEvent =
| { type: 'delta'; delta: string }
| { type: 'complete'; output: string; details?: any };
// Detection logic remains simple
function isLocalTool(tool: AgentTool): boolean {
return tool.execute !== undefined;
}
```
#### 3. Message Types
Extend the Message union to handle errors and aborts cleanly:
```typescript
// Extended Message type for cleaner error handling
type Message =
| UserMessage
| AssistantMessage // stopReason: 'stop' | 'length' | 'tool_calls'
| ToolResultMessage
| ErrorMessage // New: explicit error messages
| AbortedMessage; // New: explicit abort messages
interface ErrorMessage {
role: 'error';
error: string;
partial?: AssistantMessage; // Partial message before error
}
interface AbortedMessage {
role: 'aborted';
partial: AssistantMessage; // Partial message before abort
}
```
#### 4. Granular Event System
Fine-grained events with message boundaries:
```typescript
type AgentEvent =
// Session lifecycle
| { type: 'session_start'; sessionId: string }
| { type: 'session_end'; sessionId: string; messages: Message[] } // Only NEW messages
| { type: 'awaiting_tool_execution'; sessionId: string; toolCalls: ToolCall[] }
// Message boundaries (role determined by message.role)
| { type: 'message_start'; role: Message['role'] }
| { type: 'message_end'; message: Message } // Includes usage/cost for assistant messages
// Assistant streaming (only during assistant messages)
| { type: 'text_start' }
| { type: 'text_delta'; delta: string }
| { type: 'text_end'; text: string }
| { type: 'thinking_start' }
| { type: 'thinking_delta'; delta: string }
| { type: 'thinking_end'; thinking: string }
| { type: 'toolcall_start'; index: number }
| { type: 'toolcall_delta'; index: number; delta: string }
| { type: 'toolcall_end'; index: number; toolCall: ToolCall }
// Tool execution (local tools only)
| { type: 'tool_execution_start'; toolCallId: string; toolName: string; args: any }
| { type: 'tool_execution_delta'; toolCallId: string; delta: string }
| { type: 'tool_execution_end'; toolCallId: string; output: string; details?: any }
// Errors
| { type: 'error'; error: string; message?: Message }
```
### New API Design
```typescript
// Create or restore a session
function createSession(
sessionId: string,
context: AgentContext,
options?: PromptOptions // Model, temperature, etc.
): AgentSession;
// Execute with event streaming
interface ExecuteResult {
status: 'completed' | 'awaiting_tool_execution';
messages: Message[]; // New messages added during execution
pendingToolCalls?: ToolCall[]; // Present when status is 'awaiting_tool_execution'
cost: number; // Cost for this execution
}
interface ExecuteStream extends AsyncIterable<AgentEvent> {
result(): Promise<ExecuteResult>;
}
function execute(
session: AgentSession,
input: UserMessage | ToolResultMessage[]
): ExecuteStream;
// Example usage - clean flow without nested loops
const session = createSession('session-123', {
messages: [],
tools: [localTool, remoteTool]
});
// Execute and handle events
const stream = execute(session, { role: 'user', content: 'Hello' });
for await (const event of stream) {
// Handle events for UI updates
console.log(event);
}
// Check result after stream completes
const result = await stream.result();
if (result.status === 'awaiting_tool_execution') {
// Execute remote tools externally
const toolResults = await executeRemoteTools(result.pendingToolCalls);
// Resume execution with tool results
const resumeStream = execute(session, toolResults);
for await (const event of resumeStream) {
console.log(event);
}
const finalResult = await resumeStream.result();
// Continue until no more pending tools...
}
```
### Tool Execution Streaming
All tools return a `ToolExecutionEventStream` for consistency:
```typescript
// Example streaming tool with progressive output
const streamingSearchTool: AgentTool = {
name: 'search',
label: 'Search',
parameters: Type.Object({ query: Type.String() }),
async *execute(id, { query }) {
// Stream deltas as they become available
yield { type: 'delta', delta: 'Searching for: ' };
yield { type: 'delta', delta: query };
yield { type: 'delta', delta: '\nResults:\n' };
for (const result of await search(query)) {
yield { type: 'delta', delta: `- ${result.title}\n` };
}
// Final complete event with full output and optional details
yield {
type: 'complete',
output: fullOutput,
details: { resultCount: 10 }
};
}
};
// Example simple tool (still returns AsyncIterable for consistency)
const simpleTool: AgentTool = {
name: 'calculate',
label: 'Calculate',
parameters: Type.Object({ expression: Type.String() }),
async *execute(id, { expression }) {
const result = eval(expression); // Don't do this in production!
// Even simple tools emit complete event
yield {
type: 'complete',
output: `${expression} = ${result}`,
details: { result }
};
}
};
// Helper for simple tools that don't need streaming
function createSimpleTool<TParams>(
config: Omit<AgentTool<TParams>, 'execute'>,
handler: (id: string, params: TParams) => Promise<{ output: string; details?: any }>
): AgentTool<TParams> {
return {
...config,
async *execute(id, params) {
const result = await handler(id, params);
yield { type: 'complete', ...result };
}
};
}
// Usage with helper
const calculateTool = createSimpleTool(
{
name: 'calculate',
label: 'Calculate',
parameters: Type.Object({ expression: Type.String() })
},
async (id, { expression }) => {
const result = eval(expression);
return {
output: `${expression} = ${result}`,
details: { result }
};
}
);
```
### HTTP Transport Layer
Server manages session state, client only sends inputs:
```typescript
// Server-side session store
class SessionStore {
private sessions = new Map<string, AgentSession>();
create(sessionId: string, context: AgentContext, options?: PromptOptions): AgentSession {
const session = createSession(sessionId, context, options);
this.sessions.set(sessionId, session);
return session;
}
get(sessionId: string): AgentSession | undefined {
return this.sessions.get(sessionId);
}
// Optional: Get context for UI sync
getContext(sessionId: string): AgentContext | undefined {
return this.sessions.get(sessionId)?.messages;
}
}
// API Endpoints
interface ExecuteRequest {
sessionId?: string; // Optional, server generates if not provided
input: UserMessage | ToolResultMessage[];
context?: AgentContext; // Only for new sessions
options?: PromptOptions; // Model, temperature, etc.
}
interface ExecuteResponse {
sessionId: string;
// SSE stream of AgentEvents
}
// Server implementation
app.post('/api/agent/execute', async (req, res) => {
const { sessionId = generateId(), input, context, options } = req.body;
// Get or create session
let session = sessionStore.get(sessionId);
if (!session) {
if (!context) {
return res.status(400).json({ error: 'Context required for new session' });
}
session = sessionStore.create(sessionId, context, options);
}
// Set up SSE
res.writeHead(200, {
'Content-Type': 'text/event-stream',
'Cache-Control': 'no-cache',
'Connection': 'keep-alive',
'X-Session-Id': sessionId, // Return session ID in header
});
// Stream events
const stream = execute(session, input);
for await (const event of stream) {
res.write(`data: ${JSON.stringify(event)}\n\n`);
}
// Get final result
const result = await stream.result();
// Send final event with status
res.write(`data: ${JSON.stringify({
type: 'execute_complete',
status: result.status,
pendingToolCalls: result.pendingToolCalls
})}\n\n`);
res.end();
});
// Optional: Get session context for UI sync
app.get('/api/agent/session/:sessionId', (req, res) => {
const context = sessionStore.getContext(req.params.sessionId);
if (!context) {
return res.status(404).json({ error: 'Session not found' });
}
res.json({ messages: context });
});
// Client implementation
async function executeOnServer(input: UserMessage, tools: AgentTool[]) {
// Note: tools with execute functions will have them stripped during JSON.stringify
const response = await fetch('/api/agent/execute', {
method: 'POST',
body: JSON.stringify({
input,
context: { messages: [], tools }, // Tools without execute = remote
options: { model: 'gpt-4o-mini' }
})
});
const sessionId = response.headers.get('X-Session-Id');
const reader = response.body.getReader();
const decoder = new TextDecoder();
let pendingToolCalls = [];
while (true) {
const { done, value } = await reader.read();
if (done) break;
const lines = decoder.decode(value).split('\n');
for (const line of lines) {
if (line.startsWith('data: ')) {
const event = JSON.parse(line.slice(6));
// Update UI with event
handleEvent(event);
if (event.type === 'execute_complete' && event.status === 'awaiting_tool_execution') {
pendingToolCalls = event.pendingToolCalls;
}
}
}
}
// Execute remote tools if needed
if (pendingToolCalls.length > 0) {
const toolResults = await executeLocalTools(pendingToolCalls);
// Resume on server
await fetch('/api/agent/execute', {
method: 'POST',
body: JSON.stringify({
sessionId,
input: toolResults
})
});
}
}
```
## Implementation Plan
### Phase 1: Core Event System Refactor
1. Define new granular `AgentEvent` types with message boundaries
2. Update agent loop to detect local vs remote tools (via `execute` presence)
3. Implement `ExecuteStream` with `result()` method
4. Map underlying streaming events to granular agent events
### Phase 2: Session Management
1. Implement `AgentSession` type with status tracking
2. Create `createSession()` and `execute()` functions
3. Handle suspension when remote tools detected
4. Track cost and model per session
### Phase 3: Streaming Tool Execution
1. Define `ToolExecutionEventStream` type alias
2. Update all tools to return `ToolExecutionEventStream`
3. Emit `tool_execution_delta` events during streaming
4. Provide `createSimpleTool` helper for non-streaming tools
### Phase 4: HTTP Transport
1. Implement server-side `SessionStore`
2. Create `/api/agent/execute` endpoint with SSE
3. Add `/api/agent/session/:id` for context sync
4. Build client SDK for SSE consumption
### Phase 5: Documentation & Examples
1. Create comprehensive documentation for new API
2. Build example applications demonstrating all features
3. Add TypeScript types and JSDoc comments
4. Create cookbook for common patterns
## Key Design Decisions
### Why AgentSession Instead of ExecutionSession?
- Clearer naming that matches the agent concept
- Consistent with `AgentContext`, `AgentTool`, `AgentEvent`
### Why Detect Remote Tools via Missing execute?
- JSON.stringify naturally omits functions
- No need for explicit `mode` field
- Zero configuration for remote tools
### Why ExecuteStream with result()?
- Follows the existing EventStream pattern
- Separates streaming (UI updates) from final state
- Clean way to get pending tool calls after streaming
### Why awaiting_tool_execution Instead of suspended?
- More descriptive of the actual state
- Clear indication that client action is required
- Better for debugging and logging
## Clean Break Strategy
Since we're not maintaining backward compatibility, we can:
1. **Remove all legacy code** - No need for wrapper functions or event mappers
2. **Simplify type definitions** - No union types for old/new formats
3. **Optimize for the new use cases** - Design purely for distributed execution
4. **Clear naming** - No need to avoid conflicts with existing names
5. **Breaking changes allowed** - Can restructure packages and exports as needed
This is a complete rewrite of the agent module with a new, cleaner API that fully supports:
- Granular streaming events
- Progressive tool execution
- Remote tool suspension/resumption
- Efficient HTTP transport
## Open Questions
1. **Tool Timeout**: How long should we wait for remote tool execution before timing out?
2. **Session Persistence**: Should sessions be stored in memory or persisted (Redis/DB)?
3. **Tool Chaining**: Can a remote tool trigger another LLM call that uses more tools?
4. **Error Recovery**: How to handle partial tool execution failures?
5. **Rate Limiting**: How to prevent abuse of the HTTP API?
6. **Error/Abort Messages**: Should we use explicit `ErrorMessage`/`AbortedMessage` types or keep errors in `AssistantMessage` with `stopReason: 'error'`? Explicit types are cleaner but add complexity.
## Next Steps
1. Implement Phase 1 - Core event system with granular events
2. Test with existing tools to ensure compatibility
3. Add streaming support to one built-in tool as proof of concept
4. Build minimal HTTP server to validate the design
5. Gather feedback and iterate before full implementation