Agent package + coding agent WIP, refactored web-ui prompts

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Mario Zechner 2025-10-17 11:47:01 +02:00
parent 4e7a340460
commit ffc9be8867
58 changed files with 5138 additions and 2206 deletions

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@ -1,15 +1,23 @@
# Coding Agent Architecture
# Agent Architecture
## Executive Summary
This document proposes extracting the agent infrastructure from `@mariozechner/pi-web-ui` and `@mariozechner/pi-agent` into a new headless coding agent package that can be reused across multiple UI implementations (TUI, VS Code extension, web interface).
This document proposes extracting the agent infrastructure from `@mariozechner/pi-web-ui` into two new packages:
1. **`@mariozechner/agent`** - General-purpose agent package with transport abstraction, state management, and attachment support
2. **`@mariozechner/coding-agent`** - Specialized coding agent built on the general agent, with file manipulation tools and session management
The new architecture will provide:
- **Headless agent core** with file manipulation tools (read, bash, edit, write)
- **Session management** for conversation persistence and resume capability
- **General agent core** with transport abstraction (ProviderTransport, AppTransport)
- **Reactive state management** with subscribe/emit pattern
- **Attachment support** (type definitions only - processing stays in consumers)
- **Message transformation** pipeline for filtering and adapting messages
- **Message queueing** for out-of-band message injection
- **Full abort support** throughout the execution pipeline
- **Event-driven API** for flexible UI integration
- **Clean separation** between agent logic and presentation layer
- **Coding-specific tools** (read, bash, edit, write) in a specialized package
- **Session management** for conversation persistence and resume capability
## Current Architecture Analysis
@ -18,7 +26,7 @@ The new architecture will provide:
```
pi-mono/
├── packages/ai/ # Core AI streaming (GOOD - keep as-is)
├── packages/web-ui/ # Web UI with agent (GOOD - keep separate)
├── packages/web-ui/ # Web UI with embedded agent (EXTRACT core agent logic)
├── packages/agent/ # OLD - needs to be replaced
├── packages/tui/ # Terminal UI lib (GOOD - low-level primitives)
├── packages/proxy/ # CORS proxy (unrelated)
@ -77,9 +85,9 @@ interface AgentToolResult<T> {
}
```
### packages/web-ui/agent - Web Agent
### packages/web-ui/src/agent - Web Agent
**Status:** ✅ Good for web use cases, keep separate
**Status:** ✅ KEEP AS-IS for now, will be replaced later after new packages are proven
**Architecture:**
```typescript
@ -94,60 +102,49 @@ class Agent {
async prompt(input: string, attachments?: Attachment[]): Promise<void>
abort(): void
subscribe(fn: (e: AgentEvent) => void): () => void
setSystemPrompt(v: string): void
setModel(m: Model<any>): void
setThinkingLevel(l: ThinkingLevel): void
setTools(t: AgentTool<any>[]): void
replaceMessages(ms: AppMessage[]): void
appendMessage(m: AppMessage): void
async queueMessage(m: AppMessage): Promise<void>
clearMessages(): void
}
```
**Key Features:**
- **Transport abstraction** (ProviderTransport for direct API, AppTransport for server-side)
- **Attachment handling** (images, documents with text extraction)
- **Message transformation** (app messages → LLM messages)
- **Reactive state** (subscribe pattern for UI updates)
- **Message queue** for injecting tool results/errors asynchronously
**Key Features (will be basis for new `@mariozechner/agent` package):**
- ✅ **Transport abstraction** (ProviderTransport for direct API, AppTransport for server-side proxy)
- ✅ **Attachment type definition** (id, type, fileName, mimeType, size, content, extractedText, preview)
- ✅ **Message transformation** pipeline (app messages → LLM messages, with filtering)
- ✅ **Reactive state** (subscribe/emit pattern for UI updates)
- ✅ **Message queueing** for injecting messages out-of-band during agent loop
- ✅ **Abort support** (AbortController per prompt)
- ✅ **State management** (systemPrompt, model, thinkingLevel, tools, messages, isStreaming, etc.)
**Why it's different from coding agent:**
- Browser-specific concerns (CORS, attachments)
- Transport layer for flexible API routing
- Tied to web UI state management
- Supports rich media attachments
**Strategy:**
1. Use this implementation as the **reference design** for `@mariozechner/agent`
2. Create new `@mariozechner/agent` package by copying/adapting this code
3. Keep web-ui using its own embedded agent until new package is proven stable
4. Eventually migrate web-ui to use `@mariozechner/agent` (Phase 2 of migration)
5. Document processing (PDF/DOCX/PPTX/Excel) stays in web-ui permanently
### packages/agent - OLD Implementation
**Status:** ⚠️ MUST BE REPLACED
**Status:** ⚠️ REMOVE COMPLETELY
**Architecture:**
```typescript
class Agent {
constructor(
config: AgentConfig,
renderer?: AgentEventReceiver,
sessionManager?: SessionManager
)
**Why it should be removed:**
1. **Tightly coupled to OpenAI SDK** - Not provider-agnostic, hardcoded to OpenAI's API
2. **Outdated architecture** - Superseded by web-ui's better agent design
3. **Mixed concerns** - Agent logic + tool implementations + rendering all in one package
4. **Limited scope** - Cannot be reused across different UI implementations
async ask(userMessage: string): Promise<void>
interrupt(): void
setEvents(events: AgentEvent[]): void
}
```
**What to salvage before removal:**
1. **SessionManager** - Port to `@mariozechner/coding-agent` (JSONL-based session persistence)
2. **Tool implementations** - Adapt read, bash, edit, write tools for coding-agent
3. **Renderer abstractions** - Port TuiRenderer/ConsoleRenderer/JsonRenderer concepts to coding-agent-tui
**Problems:**
1. **Tightly coupled to OpenAI SDK** (not provider-agnostic)
2. **Hardcoded tools** (read, list, bash, glob, rg)
3. **Mixed concerns** (agent logic + tool implementations in same package)
4. **No separation** between core loop and UI rendering
5. **Two API paths** (completions vs responses) with branching logic
**Good parts to preserve:**
1. **SessionManager** - JSONL-based session persistence
2. **Event receiver pattern** - Clean UI integration
3. **Abort support** - Proper signal handling
4. **Renderer abstraction** (ConsoleRenderer, TuiRenderer, JsonRenderer)
**Tools implemented:**
- `read`: Read file contents (1MB limit with truncation)
- `list`: List directory contents
- `bash`: Execute shell command with abort support
- `glob`: Find files matching glob pattern
- `rg`: Run ripgrep search
**Action:** Delete this package entirely after extracting useful components to the new packages.
## Proposed Architecture
@ -155,132 +152,440 @@ class Agent {
```
pi-mono/
├── packages/ai/ # [unchanged] Core streaming
├── packages/coding-agent/ # [NEW] Headless coding agent
├── packages/ai/ # [unchanged] Core streaming library
├── packages/agent/ # [NEW] General-purpose agent
│ ├── src/
│ │ ├── agent.ts # Main agent class
│ │ ├── session-manager.ts # Session persistence
│ │ ├── agent.ts # Main Agent class
│ │ ├── types.ts # AgentState, AgentEvent, Attachment, etc.
│ │ ├── transports/
│ │ │ ├── types.ts # AgentTransport interface
│ │ │ ├── ProviderTransport.ts # Direct API calls
│ │ │ ├── AppTransport.ts # Server-side proxy
│ │ │ ├── proxy-types.ts # Proxy event types
│ │ │ └── index.ts # Transport exports
│ │ └── index.ts # Public API
│ └── package.json
├── packages/coding-agent/ # [NEW] Coding-specific agent + CLI
│ ├── src/
│ │ ├── coding-agent.ts # CodingAgent wrapper (uses @mariozechner/agent)
│ │ ├── session-manager.ts # Session persistence (JSONL)
│ │ ├── tools/
│ │ │ ├── read-tool.ts # Read files (with pagination)
│ │ │ ├── bash-tool.ts # Shell execution
│ │ │ ├── edit-tool.ts # File editing (old_string → new_string)
│ │ │ ├── write-tool.ts # File creation/replacement
│ │ │ └── index.ts # Tool exports
│ │ └── types.ts # Public types
│ └── package.json
│ │ ├── cli/
│ │ │ ├── index.ts # CLI entry point
│ │ │ ├── renderers/
│ │ │ │ ├── tui-renderer.ts # Rich terminal UI
│ │ │ │ ├── console-renderer.ts # Simple console output
│ │ │ │ └── json-renderer.ts # JSONL output for piping
│ │ │ └── main.ts # CLI app logic
│ │ ├── types.ts # Public types
│ │ └── index.ts # Public API (agent + tools)
│ └── package.json # Exports both library + CLI binary
├── packages/coding-agent-tui/ # [NEW] Terminal interface
├── packages/web-ui/ # [updated] Uses @mariozechner/agent
│ ├── src/
│ │ ├── cli.ts # CLI entry point
│ │ ├── renderers/
│ │ │ ├── tui-renderer.ts # Rich terminal UI
│ │ │ ├── console-renderer.ts # Simple console output
│ │ │ └── json-renderer.ts # JSONL output for piping
│ │ └── main.ts # App logic
│ └── package.json
│ │ ├── utils/
│ │ │ └── attachment-utils.ts # Document processing (keep here)
│ │ └── ... # Other web UI code
│ └── package.json # Now depends on @mariozechner/agent
├── packages/web-ui/ # [unchanged] Web UI keeps its own agent
└── packages/tui/ # [unchanged] Low-level terminal primitives
```
### Dependency Graph
```
┌─────────────────────┐
@mariozechner/
│ pi-ai │ ← Core streaming, tool interface
└──────────┬──────────┘
┌─────────────────────┐
@mariozechner/
│ pi-ai │ ← Core streaming, tool interface
└──────────┬──────────┘
│ depends on
┌─────────────────────┐
@mariozechner/
│ coding-agent │ ← Headless agent + file tools
└──────────┬──────────┘
┌─────────────────────┐
@mariozechner/
│ agent │ ← General agent (transports, state, attachments)
└──────────┬──────────┘
│ depends on
┌──────────┬──────────┐
↓ ↓ ↓
┌────────┐ ┌───────┐ ┌────────┐
│ TUI │ │ VSCode│ │ Web UI │
│ Client │ │ Ext │ │ (own) │
└────────┘ └───────┘ └────────┘
┌───────────────┴───────────────┐
↓ ↓
┌─────────────────────┐ ┌─────────────────────┐
@mariozechner/ │ │ @mariozechner/
│ coding-agent │ │ pi-web-ui │
│ (lib + CLI + tools) │ │ (+ doc processing) │
└─────────────────────┘ └─────────────────────┘
```
## Package: @mariozechner/agent
### Core Types
```typescript
export interface Attachment {
id: string;
type: "image" | "document";
fileName: string;
mimeType: string;
size: number;
content: string; // base64 encoded (without data URL prefix)
extractedText?: string; // For documents
preview?: string; // base64 image preview
}
export type ThinkingLevel = "off" | "minimal" | "low" | "medium" | "high";
// AppMessage abstraction - extends base LLM messages with app-specific features
export type UserMessageWithAttachments = UserMessage & { attachments?: Attachment[] };
// Extensible interface for custom app messages (via declaration merging)
// Apps can add their own message types:
// declare module "@mariozechner/agent" {
// interface CustomMessages {
// artifact: ArtifactMessage;
// notification: NotificationMessage;
// }
// }
export interface CustomMessages {
// Empty by default - apps extend via declaration merging
}
// AppMessage: Union of LLM messages + attachments + custom messages
export type AppMessage =
| AssistantMessage
| UserMessageWithAttachments
| ToolResultMessage
| CustomMessages[keyof CustomMessages];
export interface AgentState {
systemPrompt: string;
model: Model<any>;
thinkingLevel: ThinkingLevel;
tools: AgentTool<any>[];
messages: AppMessage[]; // Can include attachments + custom message types
isStreaming: boolean;
streamMessage: Message | null;
pendingToolCalls: Set<string>;
error?: string;
}
export type AgentEvent =
| { type: "state-update"; state: AgentState }
| { type: "started" }
| { type: "completed" };
```
### AppMessage Abstraction
The `AppMessage` type is a key abstraction that extends base LLM messages with app-specific features while maintaining type safety and extensibility.
**Key Benefits:**
1. **Extends base messages** - Adds `attachments` field to `UserMessage` for file uploads
2. **Type-safe extensibility** - Apps can add custom message types via declaration merging
3. **Backward compatible** - Works seamlessly with base LLM messages from `@mariozechner/pi-ai`
4. **Message transformation** - Filters app-specific fields before sending to LLM
**Usage Example (Web UI):**
```typescript
import type { AppMessage } from "@mariozechner/agent";
// Extend with custom message type for artifacts
declare module "@mariozechner/agent" {
interface CustomMessages {
artifact: ArtifactMessage;
}
}
interface ArtifactMessage {
role: "artifact";
action: "create" | "update" | "delete";
filename: string;
content?: string;
title?: string;
timestamp: string;
}
// Now AppMessage includes: AssistantMessage | UserMessageWithAttachments | ToolResultMessage | ArtifactMessage
const messages: AppMessage[] = [
{ role: "user", content: "Hello", attachments: [attachment] },
{ role: "assistant", content: [{ type: "text", text: "Hi!" }], /* ... */ },
{ role: "artifact", action: "create", filename: "test.ts", content: "...", timestamp: "..." }
];
```
**Usage Example (Coding Agent):**
```typescript
import type { AppMessage } from "@mariozechner/agent";
// Coding agent can extend with session metadata
declare module "@mariozechner/agent" {
interface CustomMessages {
session_metadata: SessionMetadataMessage;
}
}
interface SessionMetadataMessage {
role: "session_metadata";
sessionId: string;
timestamp: string;
workingDirectory: string;
}
```
**Message Transformation:**
The `messageTransformer` function converts app messages to LLM-compatible messages, including handling attachments:
```typescript
function defaultMessageTransformer(messages: AppMessage[]): Message[] {
return messages
.filter((m) => {
// Only keep standard LLM message roles
return m.role === "user" || m.role === "assistant" || m.role === "toolResult";
})
.map((m) => {
if (m.role === "user") {
const { attachments, ...baseMessage } = m as any;
// If no attachments, return as-is
if (!attachments || attachments.length === 0) {
return baseMessage as Message;
}
// Convert attachments to content blocks
const content = Array.isArray(baseMessage.content)
? [...baseMessage.content]
: [{ type: "text", text: baseMessage.content }];
for (const attachment of attachments) {
// Add image blocks for image attachments
if (attachment.type === "image") {
content.push({
type: "image",
data: attachment.content,
mimeType: attachment.mimeType
});
}
// Add text blocks for documents with extracted text
else if (attachment.type === "document" && attachment.extractedText) {
content.push({
type: "text",
text: attachment.extractedText
});
}
}
return { ...baseMessage, content } as Message;
}
return m as Message;
});
}
```
This ensures that:
- Custom message types (like `artifact`, `session_metadata`) are filtered out
- Image attachments are converted to `ImageContent` blocks
- Document attachments with extracted text are converted to `TextContent` blocks
- The `attachments` field itself is stripped (replaced by proper content blocks)
- LLM receives only standard `Message` types from `@mariozechner/pi-ai`
### Agent Class
```typescript
export interface AgentOptions {
initialState?: Partial<AgentState>;
transport: AgentTransport;
// Transform app messages to LLM-compatible messages before sending
messageTransformer?: (messages: AppMessage[]) => Message[] | Promise<Message[]>;
}
export class Agent {
constructor(opts: AgentOptions);
get state(): AgentState;
subscribe(fn: (e: AgentEvent) => void): () => void;
// State mutators
setSystemPrompt(v: string): void;
setModel(m: Model<any>): void;
setThinkingLevel(l: ThinkingLevel): void;
setTools(t: AgentTool<any>[]): void;
replaceMessages(ms: AppMessage[]): void;
appendMessage(m: AppMessage): void;
async queueMessage(m: AppMessage): Promise<void>;
clearMessages(): void;
// Main prompt method
async prompt(input: string, attachments?: Attachment[]): Promise<void>;
// Abort current operation
abort(): void;
}
```
**Key Features:**
1. **Reactive state** - Subscribe to state updates for UI binding
2. **Transport abstraction** - Pluggable backends (direct API, proxy server, etc.)
3. **Message transformation** - Convert app-specific messages to LLM format
4. **Message queueing** - Inject messages during agent loop (for tool results, errors)
5. **Attachment support** - Type-safe attachment handling (processing is external)
6. **Abort support** - Cancel in-progress operations
### Transport Interface
```typescript
export interface AgentRunConfig {
systemPrompt: string;
tools: AgentTool<any>[];
model: Model<any>;
reasoning?: "low" | "medium" | "high";
getQueuedMessages?: <T>() => Promise<QueuedMessage<T>[]>;
}
export interface AgentTransport {
run(
messages: Message[],
userMessage: Message,
config: AgentRunConfig,
signal?: AbortSignal,
): AsyncIterable<AgentEvent>;
}
```
### ProviderTransport
```typescript
export class ProviderTransport implements AgentTransport {
async *run(messages: Message[], userMessage: Message, cfg: AgentRunConfig, signal?: AbortSignal) {
// Calls LLM providers directly using agentLoop from @mariozechner/pi-ai
// Optionally routes through CORS proxy if configured
}
}
```
### AppTransport
```typescript
export class AppTransport implements AgentTransport {
constructor(proxyUrl: string);
async *run(messages: Message[], userMessage: Message, cfg: AgentRunConfig, signal?: AbortSignal) {
// Routes requests through app server with user authentication
// Server manages API keys and usage tracking
}
}
```
## Package: @mariozechner/coding-agent
### Core Agent Class
### CodingAgent Class
```typescript
export interface CodingAgentConfig {
export interface CodingAgentOptions {
systemPrompt: string;
model: Model<any>;
reasoning?: "low" | "medium" | "high";
apiKey: string;
}
export interface CodingAgentOptions {
config: CodingAgentConfig;
sessionManager?: SessionManager;
workingDirectory?: string;
sessionManager?: SessionManager;
}
export class CodingAgent {
constructor(options: CodingAgentOptions);
// Access underlying agent
get agent(): Agent;
// State accessors
get state(): AgentState;
subscribe(fn: (e: AgentEvent) => void): () => void;
// Send a message to the agent
async prompt(message: string, signal?: AbortSignal): AsyncIterable<AgentEvent>;
async prompt(message: string, attachments?: Attachment[]): Promise<void>;
// Restore from session events (for --continue mode)
setMessages(messages: Message[]): void;
// Abort current operation
abort(): void;
// Get current message history
getMessages(): Message[];
// Message management for session restoration
replaceMessages(messages: AppMessage[]): void;
getMessages(): AppMessage[];
}
```
**Key design decisions:**
1. **AsyncIterable instead of callbacks** - More flexible for consumers
2. **Signal per prompt** - Each prompt() call accepts its own AbortSignal
3. **No internal state management** - Consumers handle UI state
4. **Simple message management** - Get/set for session restoration
1. **Wraps @mariozechner/agent** - Builds on the general agent package
2. **Pre-configured tools** - Includes read, bash, edit, write tools
3. **Session management** - Optional JSONL-based session persistence
4. **Working directory context** - All file operations relative to this directory
5. **Simple API** - Hides transport complexity, uses ProviderTransport by default
### Usage Example (TUI)
```typescript
import { CodingAgent } from "@mariozechner/coding-agent";
import { SessionManager } from "@mariozechner/coding-agent";
import { getModel } from "@mariozechner/pi-ai";
const session = new SessionManager({ continue: true });
const agent = new CodingAgent({
config: {
systemPrompt: "You are a coding assistant...",
model: getModel("openai", "gpt-4"),
apiKey: process.env.OPENAI_API_KEY!,
},
sessionManager: session,
workingDirectory: process.cwd(),
sessionManager: session,
});
// Restore previous session
if (session.hasData()) {
agent.setMessages(session.getMessages());
agent.replaceMessages(session.getMessages());
}
// Send prompt with abort support
const controller = new AbortController();
for await (const event of agent.prompt("Fix the bug in server.ts", controller.signal)) {
switch (event.type) {
case "message_update":
renderer.updateAssistant(event.message);
break;
case "tool_execution_start":
renderer.showTool(event.toolName, event.args);
break;
case "tool_execution_end":
renderer.showToolResult(event.toolName, event.result);
break;
// Subscribe to state changes
agent.subscribe((event) => {
if (event.type === "state-update") {
renderer.render(event.state);
} else if (event.type === "completed") {
session.save(agent.getMessages());
}
}
});
// Send prompt
await agent.prompt("Fix the bug in server.ts");
```
### Usage Example (Web UI)
```typescript
import { Agent, ProviderTransport, Attachment } from "@mariozechner/agent";
import { getModel } from "@mariozechner/pi-ai";
import { loadAttachment } from "./utils/attachment-utils"; // Web UI keeps this
const agent = new Agent({
transport: new ProviderTransport(),
initialState: {
systemPrompt: "You are a helpful assistant...",
model: getModel("google", "gemini-2.5-flash"),
thinkingLevel: "low",
tools: [],
},
});
// Subscribe to state changes for UI updates
agent.subscribe((event) => {
if (event.type === "state-update") {
updateUI(event.state);
}
});
// Handle file upload and send prompt
const file = await fileInput.files[0];
const attachment = await loadAttachment(file); // Processes PDF/DOCX/etc
await agent.prompt("Analyze this document", [attachment]);
```
### Session Manager
@ -300,8 +605,7 @@ export interface SessionMetadata {
export interface SessionData {
metadata: SessionMetadata;
messages: Message[]; // Conversation history
totalUsage: TokenUsage; // Aggregated token usage
messages: AppMessage[]; // Conversation history
}
export class SessionManager {
@ -310,8 +614,8 @@ export class SessionManager {
// Start a new session (writes metadata)
startSession(config: CodingAgentConfig): void;
// Log an event (appends to JSONL)
appendEvent(event: AgentEvent): void;
// Append a message to the session (appends to JSONL)
appendMessage(message: AppMessage): void;
// Check if session has existing data
hasData(): boolean;
@ -320,7 +624,7 @@ export class SessionManager {
getData(): SessionData | null;
// Get just the messages for agent restoration
getMessages(): Message[];
getMessages(): AppMessage[];
// Get session file path
getFilePath(): string;
@ -332,12 +636,19 @@ export class SessionManager {
**Session Storage Format (JSONL):**
```jsonl
{"type":"session","id":"uuid","timestamp":"2025-10-12T10:00:00Z","cwd":"/path","config":{...}}
{"type":"event","timestamp":"2025-10-12T10:00:01Z","event":{"type":"turn_start"}}
{"type":"event","timestamp":"2025-10-12T10:00:02Z","event":{"type":"message_start",...}}
{"type":"event","timestamp":"2025-10-12T10:00:03Z","event":{"type":"message_end",...}}
{"type":"metadata","id":"uuid","timestamp":"2025-10-12T10:00:00Z","cwd":"/path","config":{...}}
{"type":"message","message":{"role":"user","content":"Fix the bug in server.ts"}}
{"type":"message","message":{"role":"assistant","content":[{"type":"text","text":"I'll help..."}],...}}
{"type":"message","message":{"role":"toolResult","toolCallId":"call_123","output":"..."}}
{"type":"message","message":{"role":"assistant","content":[{"type":"text","text":"Fixed!"}],...}}
```
**How it works:**
- First line is session metadata (id, timestamp, working directory, config)
- Each subsequent line is an `AppMessage` from `agent.state.messages`
- Messages are appended as they're added to the agent state (append-only)
- On session restore, read all message lines to reconstruct conversation history
**Session File Naming:**
```
~/.pi/sessions/--path-to-project--/
@ -643,9 +954,11 @@ export class WriteTool implements AgentTool<typeof writeToolSchema, WriteToolDet
}
```
## Package: @mariozechner/coding-agent-tui
## CLI Interface (included in @mariozechner/coding-agent)
### CLI Interface
The coding-agent package includes both a library and a CLI interface in one package.
### CLI Usage
```bash
# Interactive mode (default)
@ -667,7 +980,7 @@ coding-agent --model openai/gpt-4 --api-key $KEY
coding-agent --json < prompts.jsonl > results.jsonl
```
### Arguments
### CLI Arguments
```typescript
{
@ -818,33 +1131,58 @@ app.listen(3000);
## Migration Plan
### Phase 1: Extract Core Package
### Phase 1: Create General Agent Package
1. Create `packages/agent/` structure
2. **COPY** Agent class from web-ui/src/agent/agent.ts (don't extract yet)
3. Copy types (AgentState, AgentEvent, Attachment, DebugLogEntry, ThinkingLevel)
4. Copy transports (types.ts, ProviderTransport.ts, AppTransport.ts, proxy-types.ts)
5. Adapt code to work as standalone package
6. Write unit tests for Agent class
7. Write tests for both transports
8. Publish `@mariozechner/agent@0.1.0`
9. **Keep web-ui unchanged** - it continues using its embedded agent
### Phase 2: Create Coding Agent Package (with CLI)
1. Create `packages/coding-agent/` structure
2. Port SessionManager from old agent package
3. Implement BashTool, EditTool, WriteTool
4. Implement CodingAgent class using pi-ai/agentLoop
5. Write tests for each tool
6. Write integration tests
3. Implement ReadTool, BashTool, EditTool, WriteTool
4. Implement CodingAgent class (wraps @mariozechner/agent)
5. Implement CLI in `src/cli/` directory:
- CLI entry point (index.ts)
- TuiRenderer, ConsoleRenderer, JsonRenderer
- Argument parsing
- Interactive and single-shot modes
6. Write tests for tools and agent
7. Write integration tests for CLI
8. Publish `@mariozechner/coding-agent@0.1.0` (includes library + CLI binary)
### Phase 2: Build TUI
1. Create `packages/coding-agent-tui/`
2. Port TuiRenderer from old agent package
3. Port ConsoleRenderer, JsonRenderer
4. Implement CLI argument parsing
5. Implement interactive and single-shot modes
6. Test session resume functionality
### Phase 3: Prove Out New Packages
1. Use coding-agent (library + CLI) extensively
2. Fix bugs and iterate on API design
3. Gather feedback from real usage
4. Ensure stability and performance
### Phase 3: Update Dependencies
1. Update web-ui if needed (should be unaffected)
2. Deprecate old agent package
3. Update documentation
4. Update examples
### Phase 4: Migrate Web UI (OPTIONAL, later)
1. Once new `@mariozechner/agent` is proven stable
2. Update web-ui package.json to depend on `@mariozechner/agent`
3. Remove src/agent/agent.ts, src/agent/types.ts, src/agent/transports/
4. Keep src/utils/attachment-utils.ts (document processing)
5. Update imports to use `@mariozechner/agent`
6. Test that web UI still works correctly
7. Verify document attachments (PDF, DOCX, etc.) still work
### Phase 4: Future Enhancements
1. Build VS Code extension
2. Add more tools (grep, find, etc.) as optional
### Phase 5: Cleanup
1. Deprecate/remove old `packages/agent/` package
2. Update all documentation
3. Create migration guide
4. Add examples for all use cases
### Phase 6: Future Enhancements
1. Build VS Code extension using `@mariozechner/coding-agent`
2. Add more tools (grep, find, glob, etc.) as optional plugins
3. Plugin system for custom tools
4. Parallel tool execution
5. Streaming tool output for long-running commands
## Open Questions & Decisions
@ -975,14 +1313,29 @@ Error: Cannot read binary file 'dist/app.js'. Use bash tool if you need to inspe
This architecture provides:
**Headless core** - Clean separation between agent logic and UI
**Reusable** - Same agent for TUI, VS Code, web, APIs
**Composable** - Build on pi-ai primitives
**Abortable** - First-class cancellation support
**Session persistence** - Resume conversations seamlessly
### General Agent Package (`@mariozechner/agent`)
**Transport abstraction** - Pluggable backends (ProviderTransport, AppTransport)
**Reactive state** - Subscribe/emit pattern for UI binding
**Message transformation** - Flexible pipeline for message filtering/adaptation
**Message queueing** - Out-of-band message injection during agent loop
**Attachment support** - Type-safe attachment handling (processing is external)
**Abort support** - First-class cancellation with AbortController
**Provider agnostic** - Works with any LLM provider via @mariozechner/pi-ai
**Type-safe** - Full TypeScript with proper types
### Coding Agent Package (`@mariozechner/coding-agent`)
**Builds on general agent** - Leverages transport abstraction and state management
**Session persistence** - JSONL-based session storage and resume
**Focused tools** - read, bash, edit, write (4 tools, no more)
**Smart pagination** - 5000-line chunks with offset/limit
**Type-safe** - Full TypeScript with schema validation
**Smart pagination** - 5000-line chunks with offset/limit for ReadTool
**Working directory context** - All tools operate relative to project root
**Simple API** - Hides complexity, easy to use
**Testable** - Pure functions, mockable dependencies
The key insight is to **keep web-ui's agent separate** (it has different concerns) while creating a **new focused coding agent** for file manipulation workflows that can be shared across non-web interfaces.
### Key Architectural Insights
1. **Extract, don't rewrite** - The web-ui agent is well-designed; extract it into a general package
2. **Separation of concerns** - Document processing (PDF/DOCX/etc.) stays in web-ui, only type definitions move to general agent
3. **Layered architecture** - pi-ai → agent → coding-agent → coding-agent-tui
4. **Reusable across UIs** - Web UI and coding agent both use the same general agent package
5. **Pluggable transports** - Easy to add new backends (local API, proxy server, etc.)
6. **Attachment flexibility** - Type is defined centrally, processing is done by consumers

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@ -806,6 +923,10 @@
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@ -845,6 +966,10 @@
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@ -1997,6 +2122,22 @@
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},
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@ -4679,6 +5014,21 @@
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}
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},
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},
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}
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"resolved": "https://registry.npmjs.org/why-is-node-running/-/why-is-node-running-2.3.0.tgz",
@ -4732,6 +5082,24 @@
"url": "https://github.com/chalk/wrap-ansi?sponsor=1"
}
},
"node_modules/wrap-ansi-cjs": {
"name": "wrap-ansi",
"version": "7.0.0",
"resolved": "https://registry.npmjs.org/wrap-ansi/-/wrap-ansi-7.0.0.tgz",
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"string-width": "^4.1.0",
"strip-ansi": "^6.0.0"
},
"engines": {
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},
"funding": {
"url": "https://github.com/chalk/wrap-ansi?sponsor=1"
}
},
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"version": "1.0.2",
"resolved": "https://registry.npmjs.org/wrappy/-/wrappy-1.0.2.tgz",
@ -4853,6 +5221,22 @@
"name": "@mariozechner/pi-agent",
"version": "0.5.44",
"license": "MIT",
"dependencies": {
"@mariozechner/pi-ai": "^0.5.44"
},
"devDependencies": {
"@types/node": "^24.3.0",
"typescript": "^5.7.3",
"vitest": "^3.2.4"
},
"engines": {
"node": ">=20.0.0"
}
},
"packages/agent-old": {
"name": "@mariozechner/pi-agent-old",
"version": "0.5.44",
"license": "MIT",
"dependencies": {
"@mariozechner/pi-tui": "^0.5.44",
"@types/glob": "^8.1.0",
@ -4868,78 +5252,7 @@
"node": ">=20.0.0"
}
},
"packages/agent/node_modules/@isaacs/balanced-match": {
"version": "4.0.1",
"license": "MIT",
"engines": {
"node": "20 || >=22"
}
},
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"license": "MIT",
"dependencies": {
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},
"engines": {
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}
},
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"license": "ISC",
"dependencies": {
"string-width": "^5.1.2",
"string-width-cjs": "npm:string-width@^4.2.0",
"strip-ansi": "^7.0.1",
"strip-ansi-cjs": "npm:strip-ansi@^6.0.1",
"wrap-ansi": "^8.1.0",
"wrap-ansi-cjs": "npm:wrap-ansi@^7.0.0"
},
"engines": {
"node": ">=12"
}
},
"packages/agent/node_modules/@isaacs/cliui/node_modules/ansi-regex": {
"version": "6.2.2",
"resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.2.2.tgz",
"integrity": "sha512-Bq3SmSpyFHaWjPk8If9yc6svM8c56dB5BAtW4Qbw5jHTwwXXcTLoRMkpDJp6VL0XzlWaCHTXrkFURMYmD0sLqg==",
"license": "MIT",
"engines": {
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},
"funding": {
"url": "https://github.com/chalk/ansi-regex?sponsor=1"
}
},
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"resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.2.tgz",
"integrity": "sha512-gmBGslpoQJtgnMAvOVqGZpEz9dyoKTCzy2nfz/n8aIFhN/jCE/rCmcxabB6jOOHV+0WNnylOxaxBQPSvcWklhA==",
"license": "MIT",
"dependencies": {
"ansi-regex": "^6.0.1"
},
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/strip-ansi?sponsor=1"
}
},
"packages/agent/node_modules/@types/glob": {
"version": "8.1.0",
"license": "MIT",
"dependencies": {
"@types/minimatch": "^5.1.2",
"@types/node": "*"
}
},
"packages/agent/node_modules/@types/minimatch": {
"version": "5.1.2",
"license": "MIT"
},
"packages/agent/node_modules/chalk": {
"packages/agent-old/node_modules/chalk": {
"version": "5.6.2",
"resolved": "https://registry.npmjs.org/chalk/-/chalk-5.6.2.tgz",
"integrity": "sha512-7NzBL0rN6fMUW+f7A6Io4h40qQlG+xGmtMxfbnH/K7TAtt8JQWVQK+6g0UXKMeVJoyV5EkkNsErQ8pVD3bLHbA==",
@ -4951,309 +5264,23 @@
"url": "https://github.com/chalk/chalk?sponsor=1"
}
},
"packages/agent/node_modules/cross-spawn": {
"version": "7.0.6",
"packages/agent/node_modules/@types/node": {
"version": "24.8.0",
"resolved": "https://registry.npmjs.org/@types/node/-/node-24.8.0.tgz",
"integrity": "sha512-5x08bUtU8hfboMTrJ7mEO4CpepS9yBwAqcL52y86SWNmbPX8LVbNs3EP4cNrIZgdjk2NAlP2ahNihozpoZIxSg==",
"dev": true,
"license": "MIT",
"dependencies": {
"path-key": "^3.1.0",
"shebang-command": "^2.0.0",
"which": "^2.0.1"
},
"engines": {
"node": ">= 8"
"undici-types": "~7.14.0"
}
},
"packages/agent/node_modules/eastasianwidth": {
"version": "0.2.0",
"packages/agent/node_modules/undici-types": {
"version": "7.14.0",
"resolved": "https://registry.npmjs.org/undici-types/-/undici-types-7.14.0.tgz",
"integrity": "sha512-QQiYxHuyZ9gQUIrmPo3IA+hUl4KYk8uSA7cHrcKd/l3p1OTpZcM0Tbp9x7FAtXdAYhlasd60ncPpgu6ihG6TOA==",
"dev": true,
"license": "MIT"
},
"packages/agent/node_modules/emoji-regex": {
"version": "9.2.2",
"license": "MIT"
},
"packages/agent/node_modules/foreground-child": {
"version": "3.3.1",
"license": "ISC",
"dependencies": {
"cross-spawn": "^7.0.6",
"signal-exit": "^4.0.1"
},
"engines": {
"node": ">=14"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"packages/agent/node_modules/glob": {
"version": "11.0.3",
"license": "ISC",
"dependencies": {
"foreground-child": "^3.3.1",
"jackspeak": "^4.1.1",
"minimatch": "^10.0.3",
"minipass": "^7.1.2",
"package-json-from-dist": "^1.0.0",
"path-scurry": "^2.0.0"
},
"bin": {
"glob": "dist/esm/bin.mjs"
},
"engines": {
"node": "20 || >=22"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"packages/agent/node_modules/isexe": {
"version": "2.0.0",
"license": "ISC"
},
"packages/agent/node_modules/jackspeak": {
"version": "4.1.1",
"license": "BlueOak-1.0.0",
"dependencies": {
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},
"engines": {
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},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"packages/agent/node_modules/lru-cache": {
"version": "11.1.0",
"license": "ISC",
"engines": {
"node": "20 || >=22"
}
},
"packages/agent/node_modules/minimatch": {
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"license": "ISC",
"dependencies": {
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},
"engines": {
"node": "20 || >=22"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"packages/agent/node_modules/package-json-from-dist": {
"version": "1.0.1",
"license": "BlueOak-1.0.0"
},
"packages/agent/node_modules/path-key": {
"version": "3.1.1",
"license": "MIT",
"engines": {
"node": ">=8"
}
},
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"version": "2.0.0",
"license": "BlueOak-1.0.0",
"dependencies": {
"lru-cache": "^11.0.0",
"minipass": "^7.1.2"
},
"engines": {
"node": "20 || >=22"
},
"funding": {
"url": "https://github.com/sponsors/isaacs"
}
},
"packages/agent/node_modules/shebang-command": {
"version": "2.0.0",
"license": "MIT",
"dependencies": {
"shebang-regex": "^3.0.0"
},
"engines": {
"node": ">=8"
}
},
"packages/agent/node_modules/shebang-regex": {
"version": "3.0.0",
"license": "MIT",
"engines": {
"node": ">=8"
}
},
"packages/agent/node_modules/string-width": {
"version": "5.1.2",
"license": "MIT",
"dependencies": {
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"emoji-regex": "^9.2.2",
"strip-ansi": "^7.0.1"
},
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/sponsors/sindresorhus"
}
},
"packages/agent/node_modules/string-width-cjs": {
"name": "string-width",
"version": "4.2.3",
"license": "MIT",
"dependencies": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
"strip-ansi": "^6.0.1"
},
"engines": {
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}
},
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"license": "MIT"
},
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"engines": {
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},
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"url": "https://github.com/chalk/ansi-regex?sponsor=1"
}
},
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},
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},
"funding": {
"url": "https://github.com/chalk/strip-ansi?sponsor=1"
}
},
"packages/agent/node_modules/strip-ansi-cjs": {
"name": "strip-ansi",
"version": "6.0.1",
"license": "MIT",
"dependencies": {
"ansi-regex": "^5.0.1"
},
"engines": {
"node": ">=8"
}
},
"packages/agent/node_modules/which": {
"version": "2.0.2",
"license": "ISC",
"dependencies": {
"isexe": "^2.0.0"
},
"bin": {
"node-which": "bin/node-which"
},
"engines": {
"node": ">= 8"
}
},
"packages/agent/node_modules/wrap-ansi": {
"version": "8.1.0",
"license": "MIT",
"dependencies": {
"ansi-styles": "^6.1.0",
"string-width": "^5.0.1",
"strip-ansi": "^7.0.1"
},
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/wrap-ansi?sponsor=1"
}
},
"packages/agent/node_modules/wrap-ansi-cjs": {
"name": "wrap-ansi",
"version": "7.0.0",
"license": "MIT",
"dependencies": {
"ansi-styles": "^4.0.0",
"string-width": "^4.1.0",
"strip-ansi": "^6.0.0"
},
"engines": {
"node": ">=10"
},
"funding": {
"url": "https://github.com/chalk/wrap-ansi?sponsor=1"
}
},
"packages/agent/node_modules/wrap-ansi-cjs/node_modules/emoji-regex": {
"version": "8.0.0",
"license": "MIT"
},
"packages/agent/node_modules/wrap-ansi-cjs/node_modules/string-width": {
"version": "4.2.3",
"license": "MIT",
"dependencies": {
"emoji-regex": "^8.0.0",
"is-fullwidth-code-point": "^3.0.0",
"strip-ansi": "^6.0.1"
},
"engines": {
"node": ">=8"
}
},
"packages/agent/node_modules/wrap-ansi/node_modules/ansi-regex": {
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"resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-6.2.2.tgz",
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"license": "MIT",
"engines": {
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},
"funding": {
"url": "https://github.com/chalk/ansi-regex?sponsor=1"
}
},
"packages/agent/node_modules/wrap-ansi/node_modules/ansi-styles": {
"version": "6.2.3",
"resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-6.2.3.tgz",
"integrity": "sha512-4Dj6M28JB+oAH8kFkTLUo+a2jwOFkuqb3yucU0CANcRRUbxS0cP0nZYCGjcc3BNXwRIsUVmDGgzawme7zvJHvg==",
"license": "MIT",
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/ansi-styles?sponsor=1"
}
},
"packages/agent/node_modules/wrap-ansi/node_modules/strip-ansi": {
"version": "7.1.2",
"resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-7.1.2.tgz",
"integrity": "sha512-gmBGslpoQJtgnMAvOVqGZpEz9dyoKTCzy2nfz/n8aIFhN/jCE/rCmcxabB6jOOHV+0WNnylOxaxBQPSvcWklhA==",
"license": "MIT",
"dependencies": {
"ansi-regex": "^6.0.1"
},
"engines": {
"node": ">=12"
},
"funding": {
"url": "https://github.com/chalk/strip-ansi?sponsor=1"
}
},
"packages/ai": {
"name": "@mariozechner/pi-ai",
"version": "0.5.44",
@ -5351,12 +5378,64 @@
"ws": "^8.18.0"
}
},
"packages/coding-agent": {
"name": "@mariozechner/coding-agent",
"version": "0.5.44",
"license": "MIT",
"dependencies": {
"@mariozechner/pi-agent": "^0.5.44",
"@mariozechner/pi-ai": "^0.5.44",
"@mariozechner/pi-tui": "^0.5.44",
"chalk": "^5.5.0",
"glob": "^11.0.3"
},
"bin": {
"coding-agent": "dist/cli.js"
},
"devDependencies": {
"@types/node": "^24.3.0",
"typescript": "^5.7.3",
"vitest": "^3.2.4"
},
"engines": {
"node": ">=20.0.0"
}
},
"packages/coding-agent/node_modules/@types/node": {
"version": "24.8.0",
"resolved": "https://registry.npmjs.org/@types/node/-/node-24.8.0.tgz",
"integrity": "sha512-5x08bUtU8hfboMTrJ7mEO4CpepS9yBwAqcL52y86SWNmbPX8LVbNs3EP4cNrIZgdjk2NAlP2ahNihozpoZIxSg==",
"dev": true,
"license": "MIT",
"dependencies": {
"undici-types": "~7.14.0"
}
},
"packages/coding-agent/node_modules/chalk": {
"version": "5.6.2",
"resolved": "https://registry.npmjs.org/chalk/-/chalk-5.6.2.tgz",
"integrity": "sha512-7NzBL0rN6fMUW+f7A6Io4h40qQlG+xGmtMxfbnH/K7TAtt8JQWVQK+6g0UXKMeVJoyV5EkkNsErQ8pVD3bLHbA==",
"license": "MIT",
"engines": {
"node": "^12.17.0 || ^14.13 || >=16.0.0"
},
"funding": {
"url": "https://github.com/chalk/chalk?sponsor=1"
}
},
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"resolved": "https://registry.npmjs.org/undici-types/-/undici-types-7.14.0.tgz",
"integrity": "sha512-QQiYxHuyZ9gQUIrmPo3IA+hUl4KYk8uSA7cHrcKd/l3p1OTpZcM0Tbp9x7FAtXdAYhlasd60ncPpgu6ihG6TOA==",
"dev": true,
"license": "MIT"
},
"packages/pods": {
"name": "@mariozechner/pi",
"version": "0.5.44",
"license": "MIT",
"dependencies": {
"@mariozechner/pi-agent": "^0.5.44",
"@mariozechner/pi-agent-old": "^0.5.44",
"chalk": "^5.5.0"
},
"bin": {

View file

@ -7,7 +7,7 @@
],
"scripts": {
"clean": "npm run clean --workspaces",
"build": "npm run build -w @mariozechner/pi-tui && npm run build -w @mariozechner/pi-ai && npm run build -w @mariozechner/pi-web-ui && npm run build -w @mariozechner/pi-agent && npm run build -w @mariozechner/pi-proxy && npm run build -w @mariozechner/pi",
"build": "npm run build -w @mariozechner/pi-tui && npm run build -w @mariozechner/pi-ai && npm run build -w @mariozechner/pi-agent && npm run build -w @mariozechner/pi-agent-old && npm run build -w @mariozechner/coding-agent && npm run build -w @mariozechner/pi-web-ui && npm run build -w @mariozechner/pi-proxy && npm run build -w @mariozechner/pi",
"dev": "concurrently --names \"ai,web-ui,tui,proxy\" --prefix-colors \"cyan,green,magenta,blue\" \"npm run dev -w @mariozechner/pi-ai\" \"npm run dev -w @mariozechner/pi-web-ui\" \"npm run dev -w @mariozechner/pi-tui\" \"npm run dev -w @mariozechner/pi-proxy\"",
"check": "biome check --write . && npm run check --workspaces && tsc --noEmit",
"test": "npm run test --workspaces --if-present",

View file

@ -0,0 +1,47 @@
{
"name": "@mariozechner/pi-agent-old",
"version": "0.5.44",
"description": "General-purpose agent with tool calling and session persistence",
"type": "module",
"bin": {
"pi-agent": "dist/cli.js"
},
"main": "./dist/index.js",
"types": "./dist/index.d.ts",
"files": [
"dist"
],
"scripts": {
"clean": "rm -rf dist",
"build": "tsc -p tsconfig.build.json && chmod +x dist/cli.js",
"check": "biome check --write .",
"prepublishOnly": "npm run clean && npm run build"
},
"dependencies": {
"@mariozechner/pi-tui": "^0.5.44",
"@types/glob": "^8.1.0",
"chalk": "^5.5.0",
"glob": "^11.0.3",
"openai": "^5.12.2"
},
"devDependencies": {},
"keywords": [
"agent",
"ai",
"llm",
"openai",
"claude",
"cli",
"tui"
],
"author": "Mario Zechner",
"license": "MIT",
"repository": {
"type": "git",
"url": "git+https://github.com/badlogic/pi-mono.git",
"directory": "packages/agent"
},
"engines": {
"node": ">=20.0.0"
}
}

View file

@ -0,0 +1,741 @@
import OpenAI from "openai";
import type { ResponseFunctionToolCallOutputItem } from "openai/resources/responses/responses.mjs";
import type { SessionManager } from "./session-manager.js";
import { executeTool, toolsForChat, toolsForResponses } from "./tools/tools.js";
export type AgentEvent =
| { type: "session_start"; sessionId: string; model: string; api: string; baseURL: string; systemPrompt: string }
| { type: "assistant_start" }
| { type: "reasoning"; text: string }
| { type: "tool_call"; toolCallId: string; name: string; args: string }
| { type: "tool_result"; toolCallId: string; result: string; isError: boolean }
| { type: "assistant_message"; text: string }
| { type: "error"; message: string }
| { type: "user_message"; text: string }
| { type: "interrupted" }
| {
type: "token_usage";
inputTokens: number;
outputTokens: number;
totalTokens: number;
cacheReadTokens: number;
cacheWriteTokens: number;
reasoningTokens: number;
};
export interface AgentEventReceiver {
on(event: AgentEvent): Promise<void>;
}
export interface AgentConfig {
apiKey: string;
baseURL: string;
model: string;
api: "completions" | "responses";
systemPrompt: string;
}
export interface ToolCall {
name: string;
arguments: string;
id: string;
}
// Cache for model reasoning support detection per API type
const modelReasoningSupport = new Map<string, { completions?: boolean; responses?: boolean }>();
// Provider detection based on base URL
function detectProvider(baseURL?: string): "openai" | "gemini" | "groq" | "anthropic" | "openrouter" | "other" {
if (!baseURL) return "openai";
if (baseURL.includes("api.openai.com")) return "openai";
if (baseURL.includes("generativelanguage.googleapis.com")) return "gemini";
if (baseURL.includes("api.groq.com")) return "groq";
if (baseURL.includes("api.anthropic.com")) return "anthropic";
if (baseURL.includes("openrouter.ai")) return "openrouter";
return "other";
}
// Parse provider-specific reasoning from message content
function parseReasoningFromMessage(message: any, baseURL?: string): { cleanContent: string; reasoningTexts: string[] } {
const provider = detectProvider(baseURL);
const reasoningTexts: string[] = [];
let cleanContent = message.content || "";
switch (provider) {
case "gemini":
// Gemini returns thinking in <thought> tags
if (cleanContent.includes("<thought>")) {
const thoughtMatches = cleanContent.matchAll(/<thought>([\s\S]*?)<\/thought>/g);
for (const match of thoughtMatches) {
reasoningTexts.push(match[1].trim());
}
// Remove all thought tags from the response
cleanContent = cleanContent.replace(/<thought>[\s\S]*?<\/thought>/g, "").trim();
}
break;
case "groq":
// Groq returns reasoning in a separate field when reasoning_format is "parsed"
if (message.reasoning) {
reasoningTexts.push(message.reasoning);
}
break;
case "openrouter":
// OpenRouter returns reasoning in message.reasoning field
if (message.reasoning) {
reasoningTexts.push(message.reasoning);
}
break;
default:
// Other providers don't embed reasoning in message content
break;
}
return { cleanContent, reasoningTexts };
}
// Adjust request options based on provider-specific requirements
function adjustRequestForProvider(
requestOptions: any,
api: "completions" | "responses",
baseURL?: string,
supportsReasoning?: boolean,
): any {
const provider = detectProvider(baseURL);
// Handle provider-specific adjustments
switch (provider) {
case "gemini":
if (api === "completions" && supportsReasoning && requestOptions.reasoning_effort) {
// Gemini needs extra_body for thinking content
// Can't use both reasoning_effort and thinking_config
const budget =
requestOptions.reasoning_effort === "low"
? 1024
: requestOptions.reasoning_effort === "medium"
? 8192
: 24576;
requestOptions.extra_body = {
google: {
thinking_config: {
thinking_budget: budget,
include_thoughts: true,
},
},
};
// Remove reasoning_effort when using thinking_config
delete requestOptions.reasoning_effort;
}
break;
case "groq":
if (api === "responses" && requestOptions.reasoning) {
// Groq responses API doesn't support reasoning.summary
delete requestOptions.reasoning.summary;
} else if (api === "completions" && supportsReasoning && requestOptions.reasoning_effort) {
// Groq Chat Completions uses reasoning_format instead of reasoning_effort alone
requestOptions.reasoning_format = "parsed";
// Keep reasoning_effort for Groq
}
break;
case "anthropic":
// Anthropic's OpenAI compatibility has its own quirks
// But thinking content isn't available via OpenAI compat layer
break;
case "openrouter":
// OpenRouter uses a unified reasoning parameter format
if (api === "completions" && supportsReasoning && requestOptions.reasoning_effort) {
// Convert reasoning_effort to OpenRouter's reasoning format
requestOptions.reasoning = {
effort:
requestOptions.reasoning_effort === "low"
? "low"
: requestOptions.reasoning_effort === "minimal"
? "low"
: requestOptions.reasoning_effort === "medium"
? "medium"
: "high",
};
delete requestOptions.reasoning_effort;
}
break;
default:
// OpenAI and others use standard format
break;
}
return requestOptions;
}
async function checkReasoningSupport(
client: OpenAI,
model: string,
api: "completions" | "responses",
baseURL?: string,
signal?: AbortSignal,
): Promise<boolean> {
// Check if already aborted
if (signal?.aborted) {
throw new Error("Interrupted");
}
// Check cache first
const cacheKey = model;
const cached = modelReasoningSupport.get(cacheKey);
if (cached && cached[api] !== undefined) {
return cached[api]!;
}
let supportsReasoning = false;
const provider = detectProvider(baseURL);
if (api === "responses") {
// Try a minimal request with reasoning parameter for Responses API
try {
const testRequest: any = {
model,
input: "test",
max_output_tokens: 1024,
reasoning: {
effort: "low", // Use low instead of minimal to ensure we get summaries
},
};
await client.responses.create(testRequest, { signal });
supportsReasoning = true;
} catch (error) {
supportsReasoning = false;
}
} else {
// For Chat Completions API, try with reasoning parameter
try {
const testRequest: any = {
model,
messages: [{ role: "user", content: "test" }],
max_completion_tokens: 1024,
};
// Add provider-specific reasoning parameters
if (provider === "gemini") {
// Gemini uses extra_body for thinking
testRequest.extra_body = {
google: {
thinking_config: {
thinking_budget: 100, // Minimum viable budget for test
include_thoughts: true,
},
},
};
} else if (provider === "groq") {
// Groq uses both reasoning_format and reasoning_effort
testRequest.reasoning_format = "parsed";
testRequest.reasoning_effort = "low";
} else {
// Others use reasoning_effort
testRequest.reasoning_effort = "minimal";
}
await client.chat.completions.create(testRequest, { signal });
supportsReasoning = true;
} catch (error) {
supportsReasoning = false;
}
}
// Update cache
const existing = modelReasoningSupport.get(cacheKey) || {};
existing[api] = supportsReasoning;
modelReasoningSupport.set(cacheKey, existing);
return supportsReasoning;
}
export async function callModelResponsesApi(
client: OpenAI,
model: string,
messages: any[],
signal?: AbortSignal,
eventReceiver?: AgentEventReceiver,
supportsReasoning?: boolean,
baseURL?: string,
): Promise<void> {
let conversationDone = false;
while (!conversationDone) {
// Check if we've been interrupted
if (signal?.aborted) {
throw new Error("Interrupted");
}
// Build request options
let requestOptions: any = {
model,
input: messages,
tools: toolsForResponses as any,
tool_choice: "auto",
parallel_tool_calls: true,
max_output_tokens: 2000, // TODO make configurable
...(supportsReasoning && {
reasoning: {
effort: "minimal", // Use minimal effort for responses API
summary: "detailed", // Request detailed reasoning summaries
},
}),
};
// Apply provider-specific adjustments
requestOptions = adjustRequestForProvider(requestOptions, "responses", baseURL, supportsReasoning);
const response = await client.responses.create(requestOptions, { signal });
// Report token usage if available (responses API format)
if (response.usage) {
const usage = response.usage;
eventReceiver?.on({
type: "token_usage",
inputTokens: usage.input_tokens || 0,
outputTokens: usage.output_tokens || 0,
totalTokens: usage.total_tokens || 0,
cacheReadTokens: usage.input_tokens_details?.cached_tokens || 0,
cacheWriteTokens: 0, // Not available in API
reasoningTokens: usage.output_tokens_details?.reasoning_tokens || 0,
});
}
const output = response.output;
if (!output) break;
for (const item of output) {
// gpt-oss vLLM quirk: need to remove type from "message" events
if (item.id === "message") {
const { type, ...message } = item;
messages.push(item);
} else {
messages.push(item);
}
switch (item.type) {
case "reasoning": {
// Handle both content (o1/o3) and summary (gpt-5) formats
const reasoningItems = item.content || item.summary || [];
for (const content of reasoningItems) {
if (content.type === "reasoning_text" || content.type === "summary_text") {
await eventReceiver?.on({ type: "reasoning", text: content.text });
}
}
break;
}
case "message": {
for (const content of item.content || []) {
if (content.type === "output_text") {
await eventReceiver?.on({ type: "assistant_message", text: content.text });
} else if (content.type === "refusal") {
await eventReceiver?.on({ type: "error", message: `Refusal: ${content.refusal}` });
}
conversationDone = true;
}
break;
}
case "function_call": {
if (signal?.aborted) {
throw new Error("Interrupted");
}
try {
await eventReceiver?.on({
type: "tool_call",
toolCallId: item.call_id || "",
name: item.name,
args: item.arguments,
});
const result = await executeTool(item.name, item.arguments, signal);
await eventReceiver?.on({
type: "tool_result",
toolCallId: item.call_id || "",
result,
isError: false,
});
// Add tool result to messages
const toolResultMsg = {
type: "function_call_output",
call_id: item.call_id,
output: result,
} as ResponseFunctionToolCallOutputItem;
messages.push(toolResultMsg);
} catch (e: any) {
await eventReceiver?.on({
type: "tool_result",
toolCallId: item.call_id || "",
result: e.message,
isError: true,
});
const errorMsg = {
type: "function_call_output",
call_id: item.id,
output: e.message,
isError: true,
};
messages.push(errorMsg);
}
break;
}
default: {
eventReceiver?.on({ type: "error", message: `Unknown output type in LLM response: ${item.type}` });
break;
}
}
}
}
}
export async function callModelChatCompletionsApi(
client: OpenAI,
model: string,
messages: any[],
signal?: AbortSignal,
eventReceiver?: AgentEventReceiver,
supportsReasoning?: boolean,
baseURL?: string,
): Promise<void> {
let assistantResponded = false;
while (!assistantResponded) {
if (signal?.aborted) {
throw new Error("Interrupted");
}
// Build request options
let requestOptions: any = {
model,
messages,
tools: toolsForChat,
tool_choice: "auto",
max_completion_tokens: 2000, // TODO make configurable
...(supportsReasoning && {
reasoning_effort: "low", // Use low effort for completions API
}),
};
// Apply provider-specific adjustments
requestOptions = adjustRequestForProvider(requestOptions, "completions", baseURL, supportsReasoning);
const response = await client.chat.completions.create(requestOptions, { signal });
const message = response.choices[0].message;
// Report token usage if available
if (response.usage) {
const usage = response.usage;
await eventReceiver?.on({
type: "token_usage",
inputTokens: usage.prompt_tokens || 0,
outputTokens: usage.completion_tokens || 0,
totalTokens: usage.total_tokens || 0,
cacheReadTokens: usage.prompt_tokens_details?.cached_tokens || 0,
cacheWriteTokens: 0, // Not available in API
reasoningTokens: usage.completion_tokens_details?.reasoning_tokens || 0,
});
}
if (message.tool_calls && message.tool_calls.length > 0) {
// Add assistant message with tool calls to history
const assistantMsg: any = {
role: "assistant",
content: message.content || null,
tool_calls: message.tool_calls,
};
messages.push(assistantMsg);
// Display and execute each tool call
for (const toolCall of message.tool_calls) {
// Check if interrupted before executing tool
if (signal?.aborted) {
throw new Error("Interrupted");
}
try {
const funcName = toolCall.type === "function" ? toolCall.function.name : toolCall.custom.name;
const funcArgs = toolCall.type === "function" ? toolCall.function.arguments : toolCall.custom.input;
await eventReceiver?.on({ type: "tool_call", toolCallId: toolCall.id, name: funcName, args: funcArgs });
const result = await executeTool(funcName, funcArgs, signal);
await eventReceiver?.on({ type: "tool_result", toolCallId: toolCall.id, result, isError: false });
// Add tool result to messages
const toolMsg = {
role: "tool",
tool_call_id: toolCall.id,
content: result,
};
messages.push(toolMsg);
} catch (e: any) {
eventReceiver?.on({ type: "tool_result", toolCallId: toolCall.id, result: e.message, isError: true });
const errorMsg = {
role: "tool",
tool_call_id: toolCall.id,
content: e.message,
};
messages.push(errorMsg);
}
}
} else if (message.content) {
// Parse provider-specific reasoning from message
const { cleanContent, reasoningTexts } = parseReasoningFromMessage(message, baseURL);
// Emit reasoning events if any
for (const reasoning of reasoningTexts) {
await eventReceiver?.on({ type: "reasoning", text: reasoning });
}
// Emit the cleaned assistant message
await eventReceiver?.on({ type: "assistant_message", text: cleanContent });
const finalMsg = { role: "assistant", content: cleanContent };
messages.push(finalMsg);
assistantResponded = true;
}
}
}
export class Agent {
private client: OpenAI;
public readonly config: AgentConfig;
private messages: any[] = [];
private renderer?: AgentEventReceiver;
private sessionManager?: SessionManager;
private comboReceiver: AgentEventReceiver;
private abortController: AbortController | null = null;
private supportsReasoning: boolean | null = null;
constructor(config: AgentConfig, renderer?: AgentEventReceiver, sessionManager?: SessionManager) {
this.config = config;
this.client = new OpenAI({
apiKey: config.apiKey,
baseURL: config.baseURL,
});
// Use provided renderer or default to console
this.renderer = renderer;
this.sessionManager = sessionManager;
this.comboReceiver = {
on: async (event: AgentEvent): Promise<void> => {
await this.renderer?.on(event);
await this.sessionManager?.on(event);
},
};
// Initialize with system prompt if provided
if (config.systemPrompt) {
this.messages.push({
role: "developer",
content: config.systemPrompt,
});
}
// Start session logging if we have a session manager
if (sessionManager) {
sessionManager.startSession(this.config);
// Emit session_start event
this.comboReceiver.on({
type: "session_start",
sessionId: sessionManager.getSessionId(),
model: config.model,
api: config.api,
baseURL: config.baseURL,
systemPrompt: config.systemPrompt,
});
}
}
async ask(userMessage: string): Promise<void> {
// Render user message through the event system
this.comboReceiver.on({ type: "user_message", text: userMessage });
// Add user message
const userMsg = { role: "user", content: userMessage };
this.messages.push(userMsg);
// Create a new AbortController for this chat session
this.abortController = new AbortController();
try {
await this.comboReceiver.on({ type: "assistant_start" });
// Check reasoning support only once per agent instance
if (this.supportsReasoning === null) {
this.supportsReasoning = await checkReasoningSupport(
this.client,
this.config.model,
this.config.api,
this.config.baseURL,
this.abortController.signal,
);
}
if (this.config.api === "responses") {
await callModelResponsesApi(
this.client,
this.config.model,
this.messages,
this.abortController.signal,
this.comboReceiver,
this.supportsReasoning,
this.config.baseURL,
);
} else {
await callModelChatCompletionsApi(
this.client,
this.config.model,
this.messages,
this.abortController.signal,
this.comboReceiver,
this.supportsReasoning,
this.config.baseURL,
);
}
} catch (e) {
// Check if this was an interruption by checking the abort signal
if (this.abortController.signal.aborted) {
// Emit interrupted event so UI can clean up properly
await this.comboReceiver?.on({ type: "interrupted" });
return;
}
throw e;
} finally {
this.abortController = null;
}
}
interrupt(): void {
this.abortController?.abort();
}
setEvents(events: AgentEvent[]): void {
// Reconstruct messages from events based on API type
this.messages = [];
if (this.config.api === "responses") {
// Responses API format
if (this.config.systemPrompt) {
this.messages.push({
role: "developer",
content: this.config.systemPrompt,
});
}
for (const event of events) {
switch (event.type) {
case "user_message":
this.messages.push({
role: "user",
content: [{ type: "input_text", text: event.text }],
});
break;
case "reasoning":
// Add reasoning message
this.messages.push({
type: "reasoning",
content: [{ type: "reasoning_text", text: event.text }],
});
break;
case "tool_call":
// Add function call
this.messages.push({
type: "function_call",
id: event.toolCallId,
name: event.name,
arguments: event.args,
});
break;
case "tool_result":
// Add function result
this.messages.push({
type: "function_call_output",
call_id: event.toolCallId,
output: event.result,
});
break;
case "assistant_message":
// Add final message
this.messages.push({
type: "message",
content: [{ type: "output_text", text: event.text }],
});
break;
}
}
} else {
// Chat Completions API format
if (this.config.systemPrompt) {
this.messages.push({ role: "system", content: this.config.systemPrompt });
}
// Track tool calls in progress
let pendingToolCalls: any[] = [];
for (const event of events) {
switch (event.type) {
case "user_message":
this.messages.push({ role: "user", content: event.text });
break;
case "assistant_start":
// Reset pending tool calls for new assistant response
pendingToolCalls = [];
break;
case "tool_call":
// Accumulate tool calls
pendingToolCalls.push({
id: event.toolCallId,
type: "function",
function: {
name: event.name,
arguments: event.args,
},
});
break;
case "tool_result":
// When we see the first tool result, add the assistant message with all tool calls
if (pendingToolCalls.length > 0) {
this.messages.push({
role: "assistant",
content: null,
tool_calls: pendingToolCalls,
});
pendingToolCalls = [];
}
// Add the tool result
this.messages.push({
role: "tool",
tool_call_id: event.toolCallId,
content: event.result,
});
break;
case "assistant_message":
// Final assistant response (no tool calls)
this.messages.push({ role: "assistant", content: event.text });
break;
// Skip other event types (thinking, error, interrupted, token_usage)
}
}
}
}
}

View file

@ -0,0 +1,15 @@
// Main exports for pi-agent package
export type { AgentConfig, AgentEvent, AgentEventReceiver } from "./agent.js";
export { Agent } from "./agent.js";
export type { ArgDef, ArgDefs, ParsedArgs } from "./args.js";
// CLI utilities
export { parseArgs, printHelp } from "./args.js";
// CLI main function
export { main } from "./main.js";
// Renderers
export { ConsoleRenderer } from "./renderers/console-renderer.js";
export { JsonRenderer } from "./renderers/json-renderer.js";
export { TuiRenderer } from "./renderers/tui-renderer.js";
export type { SessionData, SessionEvent, SessionHeader } from "./session-manager.js";
export { SessionManager } from "./session-manager.js";

View file

@ -0,0 +1,9 @@
{
"extends": "../../tsconfig.base.json",
"compilerOptions": {
"outDir": "./dist",
"rootDir": "./src"
},
"include": ["src/**/*"],
"exclude": ["node_modules", "dist"]
}

View file

@ -1,38 +1,31 @@
{
"name": "@mariozechner/pi-agent",
"version": "0.5.44",
"description": "General-purpose agent with tool calling and session persistence",
"description": "General-purpose agent with transport abstraction, state management, and attachment support",
"type": "module",
"bin": {
"pi-agent": "dist/cli.js"
},
"main": "./dist/index.js",
"types": "./dist/index.d.ts",
"files": [
"dist"
"dist",
"README.md"
],
"scripts": {
"clean": "rm -rf dist",
"build": "tsc -p tsconfig.build.json && chmod +x dist/cli.js",
"check": "biome check --write .",
"build": "tsc -p tsconfig.build.json",
"dev": "tsc -p tsconfig.build.json --watch --preserveWatchOutput",
"check": "tsc --noEmit",
"test": "vitest --run",
"prepublishOnly": "npm run clean && npm run build"
},
"dependencies": {
"@mariozechner/pi-tui": "^0.5.44",
"@types/glob": "^8.1.0",
"chalk": "^5.5.0",
"glob": "^11.0.3",
"openai": "^5.12.2"
"@mariozechner/pi-ai": "^0.5.44"
},
"devDependencies": {},
"keywords": [
"agent",
"ai",
"agent",
"llm",
"openai",
"claude",
"cli",
"tui"
"transport",
"state-management"
],
"author": "Mario Zechner",
"license": "MIT",
@ -43,5 +36,10 @@
},
"engines": {
"node": ">=20.0.0"
},
"devDependencies": {
"@types/node": "^24.3.0",
"typescript": "^5.7.3",
"vitest": "^3.2.4"
}
}

View file

@ -1,741 +1,283 @@
import OpenAI from "openai";
import type { ResponseFunctionToolCallOutputItem } from "openai/resources/responses/responses.mjs";
import type { SessionManager } from "./session-manager.js";
import { executeTool, toolsForChat, toolsForResponses } from "./tools/tools.js";
import type { ImageContent, Message, QueuedMessage, TextContent } from "@mariozechner/pi-ai";
import { getModel } from "@mariozechner/pi-ai";
import type { AgentTransport } from "./transports/types.js";
import type { AgentEvent, AgentState, AppMessage, Attachment, ThinkingLevel } from "./types.js";
export type AgentEvent =
| { type: "session_start"; sessionId: string; model: string; api: string; baseURL: string; systemPrompt: string }
| { type: "assistant_start" }
| { type: "reasoning"; text: string }
| { type: "tool_call"; toolCallId: string; name: string; args: string }
| { type: "tool_result"; toolCallId: string; result: string; isError: boolean }
| { type: "assistant_message"; text: string }
| { type: "error"; message: string }
| { type: "user_message"; text: string }
| { type: "interrupted" }
| {
type: "token_usage";
inputTokens: number;
outputTokens: number;
totalTokens: number;
cacheReadTokens: number;
cacheWriteTokens: number;
reasoningTokens: number;
};
/**
* Default message transformer: Keep only LLM-compatible messages, strip app-specific fields.
* Converts attachments to proper content blocks (images ImageContent, documents TextContent).
*/
function defaultMessageTransformer(messages: AppMessage[]): Message[] {
return messages
.filter((m) => {
// Only keep standard LLM message roles
return m.role === "user" || m.role === "assistant" || m.role === "toolResult";
})
.map((m) => {
if (m.role === "user") {
const { attachments, ...rest } = m as any;
export interface AgentEventReceiver {
on(event: AgentEvent): Promise<void>;
}
export interface AgentConfig {
apiKey: string;
baseURL: string;
model: string;
api: "completions" | "responses";
systemPrompt: string;
}
export interface ToolCall {
name: string;
arguments: string;
id: string;
}
// Cache for model reasoning support detection per API type
const modelReasoningSupport = new Map<string, { completions?: boolean; responses?: boolean }>();
// Provider detection based on base URL
function detectProvider(baseURL?: string): "openai" | "gemini" | "groq" | "anthropic" | "openrouter" | "other" {
if (!baseURL) return "openai";
if (baseURL.includes("api.openai.com")) return "openai";
if (baseURL.includes("generativelanguage.googleapis.com")) return "gemini";
if (baseURL.includes("api.groq.com")) return "groq";
if (baseURL.includes("api.anthropic.com")) return "anthropic";
if (baseURL.includes("openrouter.ai")) return "openrouter";
return "other";
}
// Parse provider-specific reasoning from message content
function parseReasoningFromMessage(message: any, baseURL?: string): { cleanContent: string; reasoningTexts: string[] } {
const provider = detectProvider(baseURL);
const reasoningTexts: string[] = [];
let cleanContent = message.content || "";
switch (provider) {
case "gemini":
// Gemini returns thinking in <thought> tags
if (cleanContent.includes("<thought>")) {
const thoughtMatches = cleanContent.matchAll(/<thought>([\s\S]*?)<\/thought>/g);
for (const match of thoughtMatches) {
reasoningTexts.push(match[1].trim());
}
// Remove all thought tags from the response
cleanContent = cleanContent.replace(/<thought>[\s\S]*?<\/thought>/g, "").trim();
}
break;
case "groq":
// Groq returns reasoning in a separate field when reasoning_format is "parsed"
if (message.reasoning) {
reasoningTexts.push(message.reasoning);
}
break;
case "openrouter":
// OpenRouter returns reasoning in message.reasoning field
if (message.reasoning) {
reasoningTexts.push(message.reasoning);
}
break;
default:
// Other providers don't embed reasoning in message content
break;
// If no attachments, return as-is
if (!attachments || attachments.length === 0) {
return rest as Message;
}
return { cleanContent, reasoningTexts };
}
// Convert attachments to content blocks
const content = Array.isArray(rest.content) ? [...rest.content] : [{ type: "text", text: rest.content }];
// Adjust request options based on provider-specific requirements
function adjustRequestForProvider(
requestOptions: any,
api: "completions" | "responses",
baseURL?: string,
supportsReasoning?: boolean,
): any {
const provider = detectProvider(baseURL);
// Handle provider-specific adjustments
switch (provider) {
case "gemini":
if (api === "completions" && supportsReasoning && requestOptions.reasoning_effort) {
// Gemini needs extra_body for thinking content
// Can't use both reasoning_effort and thinking_config
const budget =
requestOptions.reasoning_effort === "low"
? 1024
: requestOptions.reasoning_effort === "medium"
? 8192
: 24576;
requestOptions.extra_body = {
google: {
thinking_config: {
thinking_budget: budget,
include_thoughts: true,
},
},
};
// Remove reasoning_effort when using thinking_config
delete requestOptions.reasoning_effort;
for (const attachment of attachments as Attachment[]) {
// Add image blocks for image attachments
if (attachment.type === "image") {
content.push({
type: "image",
data: attachment.content,
mimeType: attachment.mimeType,
} as ImageContent);
}
break;
case "groq":
if (api === "responses" && requestOptions.reasoning) {
// Groq responses API doesn't support reasoning.summary
delete requestOptions.reasoning.summary;
} else if (api === "completions" && supportsReasoning && requestOptions.reasoning_effort) {
// Groq Chat Completions uses reasoning_format instead of reasoning_effort alone
requestOptions.reasoning_format = "parsed";
// Keep reasoning_effort for Groq
}
break;
case "anthropic":
// Anthropic's OpenAI compatibility has its own quirks
// But thinking content isn't available via OpenAI compat layer
break;
case "openrouter":
// OpenRouter uses a unified reasoning parameter format
if (api === "completions" && supportsReasoning && requestOptions.reasoning_effort) {
// Convert reasoning_effort to OpenRouter's reasoning format
requestOptions.reasoning = {
effort:
requestOptions.reasoning_effort === "low"
? "low"
: requestOptions.reasoning_effort === "minimal"
? "low"
: requestOptions.reasoning_effort === "medium"
? "medium"
: "high",
};
delete requestOptions.reasoning_effort;
}
break;
default:
// OpenAI and others use standard format
break;
}
return requestOptions;
}
async function checkReasoningSupport(
client: OpenAI,
model: string,
api: "completions" | "responses",
baseURL?: string,
signal?: AbortSignal,
): Promise<boolean> {
// Check if already aborted
if (signal?.aborted) {
throw new Error("Interrupted");
}
// Check cache first
const cacheKey = model;
const cached = modelReasoningSupport.get(cacheKey);
if (cached && cached[api] !== undefined) {
return cached[api]!;
}
let supportsReasoning = false;
const provider = detectProvider(baseURL);
if (api === "responses") {
// Try a minimal request with reasoning parameter for Responses API
try {
const testRequest: any = {
model,
input: "test",
max_output_tokens: 1024,
reasoning: {
effort: "low", // Use low instead of minimal to ensure we get summaries
},
};
await client.responses.create(testRequest, { signal });
supportsReasoning = true;
} catch (error) {
supportsReasoning = false;
}
} else {
// For Chat Completions API, try with reasoning parameter
try {
const testRequest: any = {
model,
messages: [{ role: "user", content: "test" }],
max_completion_tokens: 1024,
};
// Add provider-specific reasoning parameters
if (provider === "gemini") {
// Gemini uses extra_body for thinking
testRequest.extra_body = {
google: {
thinking_config: {
thinking_budget: 100, // Minimum viable budget for test
include_thoughts: true,
},
},
};
} else if (provider === "groq") {
// Groq uses both reasoning_format and reasoning_effort
testRequest.reasoning_format = "parsed";
testRequest.reasoning_effort = "low";
} else {
// Others use reasoning_effort
testRequest.reasoning_effort = "minimal";
}
await client.chat.completions.create(testRequest, { signal });
supportsReasoning = true;
} catch (error) {
supportsReasoning = false;
// Add text blocks for documents with extracted text
else if (attachment.type === "document" && attachment.extractedText) {
content.push({
type: "text",
text: `\n\n[Document: ${attachment.fileName}]\n${attachment.extractedText}`,
isDocument: true,
} as TextContent);
}
}
// Update cache
const existing = modelReasoningSupport.get(cacheKey) || {};
existing[api] = supportsReasoning;
modelReasoningSupport.set(cacheKey, existing);
return supportsReasoning;
}
export async function callModelResponsesApi(
client: OpenAI,
model: string,
messages: any[],
signal?: AbortSignal,
eventReceiver?: AgentEventReceiver,
supportsReasoning?: boolean,
baseURL?: string,
): Promise<void> {
let conversationDone = false;
while (!conversationDone) {
// Check if we've been interrupted
if (signal?.aborted) {
throw new Error("Interrupted");
return { ...rest, content } as Message;
}
// Build request options
let requestOptions: any = {
model,
input: messages,
tools: toolsForResponses as any,
tool_choice: "auto",
parallel_tool_calls: true,
max_output_tokens: 2000, // TODO make configurable
...(supportsReasoning && {
reasoning: {
effort: "minimal", // Use minimal effort for responses API
summary: "detailed", // Request detailed reasoning summaries
},
}),
};
// Apply provider-specific adjustments
requestOptions = adjustRequestForProvider(requestOptions, "responses", baseURL, supportsReasoning);
const response = await client.responses.create(requestOptions, { signal });
// Report token usage if available (responses API format)
if (response.usage) {
const usage = response.usage;
eventReceiver?.on({
type: "token_usage",
inputTokens: usage.input_tokens || 0,
outputTokens: usage.output_tokens || 0,
totalTokens: usage.total_tokens || 0,
cacheReadTokens: usage.input_tokens_details?.cached_tokens || 0,
cacheWriteTokens: 0, // Not available in API
reasoningTokens: usage.output_tokens_details?.reasoning_tokens || 0,
return m as Message;
});
}
const output = response.output;
if (!output) break;
for (const item of output) {
// gpt-oss vLLM quirk: need to remove type from "message" events
if (item.id === "message") {
const { type, ...message } = item;
messages.push(item);
} else {
messages.push(item);
}
switch (item.type) {
case "reasoning": {
// Handle both content (o1/o3) and summary (gpt-5) formats
const reasoningItems = item.content || item.summary || [];
for (const content of reasoningItems) {
if (content.type === "reasoning_text" || content.type === "summary_text") {
await eventReceiver?.on({ type: "reasoning", text: content.text });
}
}
break;
}
case "message": {
for (const content of item.content || []) {
if (content.type === "output_text") {
await eventReceiver?.on({ type: "assistant_message", text: content.text });
} else if (content.type === "refusal") {
await eventReceiver?.on({ type: "error", message: `Refusal: ${content.refusal}` });
}
conversationDone = true;
}
break;
}
case "function_call": {
if (signal?.aborted) {
throw new Error("Interrupted");
}
try {
await eventReceiver?.on({
type: "tool_call",
toolCallId: item.call_id || "",
name: item.name,
args: item.arguments,
});
const result = await executeTool(item.name, item.arguments, signal);
await eventReceiver?.on({
type: "tool_result",
toolCallId: item.call_id || "",
result,
isError: false,
});
// Add tool result to messages
const toolResultMsg = {
type: "function_call_output",
call_id: item.call_id,
output: result,
} as ResponseFunctionToolCallOutputItem;
messages.push(toolResultMsg);
} catch (e: any) {
await eventReceiver?.on({
type: "tool_result",
toolCallId: item.call_id || "",
result: e.message,
isError: true,
});
const errorMsg = {
type: "function_call_output",
call_id: item.id,
output: e.message,
isError: true,
};
messages.push(errorMsg);
}
break;
}
default: {
eventReceiver?.on({ type: "error", message: `Unknown output type in LLM response: ${item.type}` });
break;
}
}
}
}
}
export async function callModelChatCompletionsApi(
client: OpenAI,
model: string,
messages: any[],
signal?: AbortSignal,
eventReceiver?: AgentEventReceiver,
supportsReasoning?: boolean,
baseURL?: string,
): Promise<void> {
let assistantResponded = false;
while (!assistantResponded) {
if (signal?.aborted) {
throw new Error("Interrupted");
}
// Build request options
let requestOptions: any = {
model,
messages,
tools: toolsForChat,
tool_choice: "auto",
max_completion_tokens: 2000, // TODO make configurable
...(supportsReasoning && {
reasoning_effort: "low", // Use low effort for completions API
}),
};
// Apply provider-specific adjustments
requestOptions = adjustRequestForProvider(requestOptions, "completions", baseURL, supportsReasoning);
const response = await client.chat.completions.create(requestOptions, { signal });
const message = response.choices[0].message;
// Report token usage if available
if (response.usage) {
const usage = response.usage;
await eventReceiver?.on({
type: "token_usage",
inputTokens: usage.prompt_tokens || 0,
outputTokens: usage.completion_tokens || 0,
totalTokens: usage.total_tokens || 0,
cacheReadTokens: usage.prompt_tokens_details?.cached_tokens || 0,
cacheWriteTokens: 0, // Not available in API
reasoningTokens: usage.completion_tokens_details?.reasoning_tokens || 0,
});
}
if (message.tool_calls && message.tool_calls.length > 0) {
// Add assistant message with tool calls to history
const assistantMsg: any = {
role: "assistant",
content: message.content || null,
tool_calls: message.tool_calls,
};
messages.push(assistantMsg);
// Display and execute each tool call
for (const toolCall of message.tool_calls) {
// Check if interrupted before executing tool
if (signal?.aborted) {
throw new Error("Interrupted");
}
try {
const funcName = toolCall.type === "function" ? toolCall.function.name : toolCall.custom.name;
const funcArgs = toolCall.type === "function" ? toolCall.function.arguments : toolCall.custom.input;
await eventReceiver?.on({ type: "tool_call", toolCallId: toolCall.id, name: funcName, args: funcArgs });
const result = await executeTool(funcName, funcArgs, signal);
await eventReceiver?.on({ type: "tool_result", toolCallId: toolCall.id, result, isError: false });
// Add tool result to messages
const toolMsg = {
role: "tool",
tool_call_id: toolCall.id,
content: result,
};
messages.push(toolMsg);
} catch (e: any) {
eventReceiver?.on({ type: "tool_result", toolCallId: toolCall.id, result: e.message, isError: true });
const errorMsg = {
role: "tool",
tool_call_id: toolCall.id,
content: e.message,
};
messages.push(errorMsg);
}
}
} else if (message.content) {
// Parse provider-specific reasoning from message
const { cleanContent, reasoningTexts } = parseReasoningFromMessage(message, baseURL);
// Emit reasoning events if any
for (const reasoning of reasoningTexts) {
await eventReceiver?.on({ type: "reasoning", text: reasoning });
}
// Emit the cleaned assistant message
await eventReceiver?.on({ type: "assistant_message", text: cleanContent });
const finalMsg = { role: "assistant", content: cleanContent };
messages.push(finalMsg);
assistantResponded = true;
}
}
export interface AgentOptions {
initialState?: Partial<AgentState>;
transport: AgentTransport;
// Transform app messages to LLM-compatible messages before sending to transport
messageTransformer?: (messages: AppMessage[]) => Message[] | Promise<Message[]>;
}
export class Agent {
private client: OpenAI;
public readonly config: AgentConfig;
private messages: any[] = [];
private renderer?: AgentEventReceiver;
private sessionManager?: SessionManager;
private comboReceiver: AgentEventReceiver;
private abortController: AbortController | null = null;
private supportsReasoning: boolean | null = null;
constructor(config: AgentConfig, renderer?: AgentEventReceiver, sessionManager?: SessionManager) {
this.config = config;
this.client = new OpenAI({
apiKey: config.apiKey,
baseURL: config.baseURL,
});
// Use provided renderer or default to console
this.renderer = renderer;
this.sessionManager = sessionManager;
this.comboReceiver = {
on: async (event: AgentEvent): Promise<void> => {
await this.renderer?.on(event);
await this.sessionManager?.on(event);
},
private _state: AgentState = {
systemPrompt: "",
model: getModel("google", "gemini-2.5-flash-lite-preview-06-17"),
thinkingLevel: "off",
tools: [],
messages: [],
isStreaming: false,
streamMessage: null,
pendingToolCalls: new Set<string>(),
error: undefined,
};
private listeners = new Set<(e: AgentEvent) => void>();
private abortController?: AbortController;
private transport: AgentTransport;
private messageTransformer: (messages: AppMessage[]) => Message[] | Promise<Message[]>;
private messageQueue: Array<QueuedMessage<AppMessage>> = [];
// Initialize with system prompt if provided
if (config.systemPrompt) {
this.messages.push({
role: "developer",
content: config.systemPrompt,
constructor(opts: AgentOptions) {
this._state = { ...this._state, ...opts.initialState };
this.transport = opts.transport;
this.messageTransformer = opts.messageTransformer || defaultMessageTransformer;
}
get state(): AgentState {
return this._state;
}
subscribe(fn: (e: AgentEvent) => void): () => void {
this.listeners.add(fn);
fn({ type: "state-update", state: this._state });
return () => this.listeners.delete(fn);
}
// State mutators
setSystemPrompt(v: string) {
this.patch({ systemPrompt: v });
}
setModel(m: typeof this._state.model) {
this.patch({ model: m });
}
setThinkingLevel(l: ThinkingLevel) {
this.patch({ thinkingLevel: l });
}
setTools(t: typeof this._state.tools) {
this.patch({ tools: t });
}
replaceMessages(ms: AppMessage[]) {
this.patch({ messages: ms.slice() });
}
appendMessage(m: AppMessage) {
this.patch({ messages: [...this._state.messages, m] });
}
async queueMessage(m: AppMessage) {
// Transform message and queue it for injection at next turn
const transformed = await this.messageTransformer([m]);
this.messageQueue.push({
original: m,
llm: transformed[0], // undefined if filtered out
});
}
// Start session logging if we have a session manager
if (sessionManager) {
sessionManager.startSession(this.config);
// Emit session_start event
this.comboReceiver.on({
type: "session_start",
sessionId: sessionManager.getSessionId(),
model: config.model,
api: config.api,
baseURL: config.baseURL,
systemPrompt: config.systemPrompt,
});
}
clearMessages() {
this.patch({ messages: [] });
}
async ask(userMessage: string): Promise<void> {
// Render user message through the event system
this.comboReceiver.on({ type: "user_message", text: userMessage });
// Add user message
const userMsg = { role: "user", content: userMessage };
this.messages.push(userMsg);
// Create a new AbortController for this chat session
this.abortController = new AbortController();
try {
await this.comboReceiver.on({ type: "assistant_start" });
// Check reasoning support only once per agent instance
if (this.supportsReasoning === null) {
this.supportsReasoning = await checkReasoningSupport(
this.client,
this.config.model,
this.config.api,
this.config.baseURL,
this.abortController.signal,
);
}
if (this.config.api === "responses") {
await callModelResponsesApi(
this.client,
this.config.model,
this.messages,
this.abortController.signal,
this.comboReceiver,
this.supportsReasoning,
this.config.baseURL,
);
} else {
await callModelChatCompletionsApi(
this.client,
this.config.model,
this.messages,
this.abortController.signal,
this.comboReceiver,
this.supportsReasoning,
this.config.baseURL,
);
}
} catch (e) {
// Check if this was an interruption by checking the abort signal
if (this.abortController.signal.aborted) {
// Emit interrupted event so UI can clean up properly
await this.comboReceiver?.on({ type: "interrupted" });
return;
}
throw e;
} finally {
this.abortController = null;
}
}
interrupt(): void {
abort() {
this.abortController?.abort();
}
setEvents(events: AgentEvent[]): void {
// Reconstruct messages from events based on API type
this.messages = [];
if (this.config.api === "responses") {
// Responses API format
if (this.config.systemPrompt) {
this.messages.push({
role: "developer",
content: this.config.systemPrompt,
});
async prompt(input: string, attachments?: Attachment[]) {
const model = this._state.model;
if (!model) {
throw new Error("No model configured");
}
for (const event of events) {
switch (event.type) {
case "user_message":
this.messages.push({
// Build user message with attachments
const content: Array<TextContent | ImageContent> = [{ type: "text", text: input }];
if (attachments?.length) {
for (const a of attachments) {
if (a.type === "image") {
content.push({ type: "image", data: a.content, mimeType: a.mimeType });
} else if (a.type === "document" && a.extractedText) {
content.push({
type: "text",
text: `\n\n[Document: ${a.fileName}]\n${a.extractedText}`,
isDocument: true,
} as TextContent);
}
}
}
const userMessage: AppMessage = {
role: "user",
content: [{ type: "input_text", text: event.text }],
});
break;
content,
attachments: attachments?.length ? attachments : undefined,
};
case "reasoning":
// Add reasoning message
this.messages.push({
type: "reasoning",
content: [{ type: "reasoning_text", text: event.text }],
});
break;
this.abortController = new AbortController();
this.patch({ isStreaming: true, streamMessage: null, error: undefined });
this.emit({ type: "started" });
case "tool_call":
// Add function call
this.messages.push({
type: "function_call",
id: event.toolCallId,
name: event.name,
arguments: event.args,
});
break;
const reasoning =
this._state.thinkingLevel === "off"
? undefined
: this._state.thinkingLevel === "minimal"
? "low"
: this._state.thinkingLevel;
case "tool_result":
// Add function result
this.messages.push({
type: "function_call_output",
call_id: event.toolCallId,
output: event.result,
});
break;
case "assistant_message":
// Add final message
this.messages.push({
type: "message",
content: [{ type: "output_text", text: event.text }],
});
break;
}
}
} else {
// Chat Completions API format
if (this.config.systemPrompt) {
this.messages.push({ role: "system", content: this.config.systemPrompt });
}
// Track tool calls in progress
let pendingToolCalls: any[] = [];
for (const event of events) {
switch (event.type) {
case "user_message":
this.messages.push({ role: "user", content: event.text });
break;
case "assistant_start":
// Reset pending tool calls for new assistant response
pendingToolCalls = [];
break;
case "tool_call":
// Accumulate tool calls
pendingToolCalls.push({
id: event.toolCallId,
type: "function",
function: {
name: event.name,
arguments: event.args,
const cfg = {
systemPrompt: this._state.systemPrompt,
tools: this._state.tools,
model,
reasoning,
getQueuedMessages: async <T>() => {
// Return queued messages (they'll be added to state via message_end event)
const queued = this.messageQueue.slice();
this.messageQueue = [];
return queued as QueuedMessage<T>[];
},
});
break;
};
case "tool_result":
// When we see the first tool result, add the assistant message with all tool calls
if (pendingToolCalls.length > 0) {
this.messages.push({
try {
let partial: Message | null = null;
// Transform app messages to LLM-compatible messages (initial set)
const llmMessages = await this.messageTransformer(this._state.messages);
for await (const ev of this.transport.run(
llmMessages,
userMessage as Message,
cfg,
this.abortController.signal,
)) {
switch (ev.type) {
case "message_start":
case "message_update": {
partial = ev.message;
this.patch({ streamMessage: ev.message });
break;
}
case "message_end": {
partial = null;
this.appendMessage(ev.message as AppMessage);
this.patch({ streamMessage: null });
break;
}
case "tool_execution_start": {
const s = new Set(this._state.pendingToolCalls);
s.add(ev.toolCallId);
this.patch({ pendingToolCalls: s });
break;
}
case "tool_execution_end": {
const s = new Set(this._state.pendingToolCalls);
s.delete(ev.toolCallId);
this.patch({ pendingToolCalls: s });
break;
}
case "agent_end": {
this.patch({ streamMessage: null });
break;
}
}
}
if (partial && partial.role === "assistant" && partial.content.length > 0) {
const onlyEmpty = !partial.content.some(
(c) =>
(c.type === "thinking" && c.thinking.trim().length > 0) ||
(c.type === "text" && c.text.trim().length > 0) ||
(c.type === "toolCall" && c.name.trim().length > 0),
);
if (!onlyEmpty) {
this.appendMessage(partial as AppMessage);
} else {
if (this.abortController?.signal.aborted) {
throw new Error("Request was aborted");
}
}
}
} catch (err: any) {
const msg: Message = {
role: "assistant",
content: null,
tool_calls: pendingToolCalls,
});
pendingToolCalls = [];
content: [{ type: "text", text: "" }],
api: model.api,
provider: model.provider,
model: model.id,
usage: {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
},
stopReason: this.abortController?.signal.aborted ? "aborted" : "error",
errorMessage: err?.message || String(err),
};
this.appendMessage(msg as AppMessage);
this.patch({ error: err?.message || String(err) });
} finally {
this.patch({ isStreaming: false, streamMessage: null, pendingToolCalls: new Set<string>() });
this.abortController = undefined;
this.emit({ type: "completed" });
}
}
// Add the tool result
this.messages.push({
role: "tool",
tool_call_id: event.toolCallId,
content: event.result,
});
break;
case "assistant_message":
// Final assistant response (no tool calls)
this.messages.push({ role: "assistant", content: event.text });
break;
private patch(p: Partial<AgentState>): void {
this._state = { ...this._state, ...p };
this.emit({ type: "state-update", state: this._state });
}
// Skip other event types (thinking, error, interrupted, token_usage)
}
}
private emit(e: AgentEvent) {
for (const listener of this.listeners) {
listener(e);
}
}
}

View file

@ -1,15 +1,22 @@
// Main exports for pi-agent package
export type { AgentConfig, AgentEvent, AgentEventReceiver } from "./agent.js";
export { Agent } from "./agent.js";
export type { ArgDef, ArgDefs, ParsedArgs } from "./args.js";
// CLI utilities
export { parseArgs, printHelp } from "./args.js";
// CLI main function
export { main } from "./main.js";
// Renderers
export { ConsoleRenderer } from "./renderers/console-renderer.js";
export { JsonRenderer } from "./renderers/json-renderer.js";
export { TuiRenderer } from "./renderers/tui-renderer.js";
export type { SessionData, SessionEvent, SessionHeader } from "./session-manager.js";
export { SessionManager } from "./session-manager.js";
// Core Agent
export { Agent, type AgentOptions } from "./agent.js";
// Transports
export {
type AgentRunConfig,
type AgentTransport,
AppTransport,
type AppTransportOptions,
ProviderTransport,
type ProviderTransportOptions,
type ProxyAssistantMessageEvent,
} from "./transports/index.js";
// Types
export type {
AgentEvent,
AgentState,
AppMessage,
Attachment,
CustomMessages,
ThinkingLevel,
UserMessageWithAttachments,
} from "./types.js";

View file

@ -0,0 +1,374 @@
import type {
AgentContext,
AgentLoopConfig,
Api,
AssistantMessage,
AssistantMessageEvent,
Context,
Message,
Model,
SimpleStreamOptions,
ToolCall,
UserMessage,
} from "@mariozechner/pi-ai";
import { agentLoop } from "@mariozechner/pi-ai";
import { AssistantMessageEventStream } from "@mariozechner/pi-ai/dist/utils/event-stream.js";
import { parseStreamingJson } from "@mariozechner/pi-ai/dist/utils/json-parse.js";
import type { ProxyAssistantMessageEvent } from "./proxy-types.js";
import type { AgentRunConfig, AgentTransport } from "./types.js";
/**
* Stream function that proxies through a server instead of calling providers directly.
* The server strips the partial field from delta events to reduce bandwidth.
* We reconstruct the partial message client-side.
*/
function streamSimpleProxy(
model: Model<any>,
context: Context,
options: SimpleStreamOptions & { authToken: string },
proxyUrl: string,
): AssistantMessageEventStream {
const stream = new AssistantMessageEventStream();
(async () => {
// Initialize the partial message that we'll build up from events
const partial: AssistantMessage = {
role: "assistant",
stopReason: "stop",
content: [],
api: model.api,
provider: model.provider,
model: model.id,
usage: {
input: 0,
output: 0,
cacheRead: 0,
cacheWrite: 0,
cost: { input: 0, output: 0, cacheRead: 0, cacheWrite: 0, total: 0 },
},
};
let reader: ReadableStreamDefaultReader<Uint8Array> | undefined;
// Set up abort handler to cancel the reader
const abortHandler = () => {
if (reader) {
reader.cancel("Request aborted by user").catch(() => {});
}
};
if (options.signal) {
options.signal.addEventListener("abort", abortHandler);
}
try {
const response = await fetch(`${proxyUrl}/api/stream`, {
method: "POST",
headers: {
Authorization: `Bearer ${options.authToken}`,
"Content-Type": "application/json",
},
body: JSON.stringify({
model,
context,
options: {
temperature: options.temperature,
maxTokens: options.maxTokens,
reasoning: options.reasoning,
// Don't send apiKey or signal - those are added server-side
},
}),
signal: options.signal,
});
if (!response.ok) {
let errorMessage = `Proxy error: ${response.status} ${response.statusText}`;
try {
const errorData = (await response.json()) as { error?: string };
if (errorData.error) {
errorMessage = `Proxy error: ${errorData.error}`;
}
} catch {
// Couldn't parse error response, use default message
}
throw new Error(errorMessage);
}
// Parse SSE stream
reader = response.body!.getReader();
const decoder = new TextDecoder();
let buffer = "";
while (true) {
const { done, value } = await reader.read();
if (done) break;
// Check if aborted after reading
if (options.signal?.aborted) {
throw new Error("Request aborted by user");
}
buffer += decoder.decode(value, { stream: true });
const lines = buffer.split("\n");
buffer = lines.pop() || "";
for (const line of lines) {
if (line.startsWith("data: ")) {
const data = line.slice(6).trim();
if (data) {
const proxyEvent = JSON.parse(data) as ProxyAssistantMessageEvent;
let event: AssistantMessageEvent | undefined;
// Handle different event types
// Server sends events with partial for non-delta events,
// and without partial for delta events
switch (proxyEvent.type) {
case "start":
event = { type: "start", partial };
break;
case "text_start":
partial.content[proxyEvent.contentIndex] = {
type: "text",
text: "",
};
event = { type: "text_start", contentIndex: proxyEvent.contentIndex, partial };
break;
case "text_delta": {
const content = partial.content[proxyEvent.contentIndex];
if (content?.type === "text") {
content.text += proxyEvent.delta;
event = {
type: "text_delta",
contentIndex: proxyEvent.contentIndex,
delta: proxyEvent.delta,
partial,
};
} else {
throw new Error("Received text_delta for non-text content");
}
break;
}
case "text_end": {
const content = partial.content[proxyEvent.contentIndex];
if (content?.type === "text") {
content.textSignature = proxyEvent.contentSignature;
event = {
type: "text_end",
contentIndex: proxyEvent.contentIndex,
content: content.text,
partial,
};
} else {
throw new Error("Received text_end for non-text content");
}
break;
}
case "thinking_start":
partial.content[proxyEvent.contentIndex] = {
type: "thinking",
thinking: "",
};
event = { type: "thinking_start", contentIndex: proxyEvent.contentIndex, partial };
break;
case "thinking_delta": {
const content = partial.content[proxyEvent.contentIndex];
if (content?.type === "thinking") {
content.thinking += proxyEvent.delta;
event = {
type: "thinking_delta",
contentIndex: proxyEvent.contentIndex,
delta: proxyEvent.delta,
partial,
};
} else {
throw new Error("Received thinking_delta for non-thinking content");
}
break;
}
case "thinking_end": {
const content = partial.content[proxyEvent.contentIndex];
if (content?.type === "thinking") {
content.thinkingSignature = proxyEvent.contentSignature;
event = {
type: "thinking_end",
contentIndex: proxyEvent.contentIndex,
content: content.thinking,
partial,
};
} else {
throw new Error("Received thinking_end for non-thinking content");
}
break;
}
case "toolcall_start":
partial.content[proxyEvent.contentIndex] = {
type: "toolCall",
id: proxyEvent.id,
name: proxyEvent.toolName,
arguments: {},
partialJson: "",
} satisfies ToolCall & { partialJson: string } as ToolCall;
event = { type: "toolcall_start", contentIndex: proxyEvent.contentIndex, partial };
break;
case "toolcall_delta": {
const content = partial.content[proxyEvent.contentIndex];
if (content?.type === "toolCall") {
(content as any).partialJson += proxyEvent.delta;
content.arguments = parseStreamingJson((content as any).partialJson) || {};
event = {
type: "toolcall_delta",
contentIndex: proxyEvent.contentIndex,
delta: proxyEvent.delta,
partial,
};
partial.content[proxyEvent.contentIndex] = { ...content }; // Trigger reactivity
} else {
throw new Error("Received toolcall_delta for non-toolCall content");
}
break;
}
case "toolcall_end": {
const content = partial.content[proxyEvent.contentIndex];
if (content?.type === "toolCall") {
delete (content as any).partialJson;
event = {
type: "toolcall_end",
contentIndex: proxyEvent.contentIndex,
toolCall: content,
partial,
};
}
break;
}
case "done":
partial.stopReason = proxyEvent.reason;
partial.usage = proxyEvent.usage;
event = { type: "done", reason: proxyEvent.reason, message: partial };
break;
case "error":
partial.stopReason = proxyEvent.reason;
partial.errorMessage = proxyEvent.errorMessage;
partial.usage = proxyEvent.usage;
event = { type: "error", reason: proxyEvent.reason, error: partial };
break;
default: {
// Exhaustive check
const _exhaustiveCheck: never = proxyEvent;
console.warn(`Unhandled event type: ${(proxyEvent as any).type}`);
break;
}
}
// Push the event to stream
if (event) {
stream.push(event);
} else {
throw new Error("Failed to create event from proxy event");
}
}
}
}
}
// Check if aborted after reading
if (options.signal?.aborted) {
throw new Error("Request aborted by user");
}
stream.end();
} catch (error) {
const errorMessage = error instanceof Error ? error.message : String(error);
partial.stopReason = options.signal?.aborted ? "aborted" : "error";
partial.errorMessage = errorMessage;
stream.push({
type: "error",
reason: partial.stopReason,
error: partial,
} satisfies AssistantMessageEvent);
stream.end();
} finally {
// Clean up abort handler
if (options.signal) {
options.signal.removeEventListener("abort", abortHandler);
}
}
})();
return stream;
}
export interface AppTransportOptions {
/**
* Proxy server URL. The server manages user accounts and proxies requests to LLM providers.
* Example: "https://genai.mariozechner.at"
*/
proxyUrl: string;
/**
* Function to retrieve auth token for the proxy server.
* The token is used for user authentication and authorization.
*/
getAuthToken: () => Promise<string> | string;
}
/**
* Transport that uses an app server with user authentication tokens.
* The server manages user accounts and proxies requests to LLM providers.
*/
export class AppTransport implements AgentTransport {
private options: AppTransportOptions;
constructor(options: AppTransportOptions) {
this.options = options;
}
async *run(messages: Message[], userMessage: Message, cfg: AgentRunConfig, signal?: AbortSignal) {
const authToken = await this.options.getAuthToken();
if (!authToken) {
throw new Error("Auth token is required for AppTransport");
}
// Use proxy - no local API key needed
const streamFn = <TApi extends Api>(model: Model<TApi>, context: Context, options?: SimpleStreamOptions) => {
return streamSimpleProxy(
model,
context,
{
...options,
authToken,
},
this.options.proxyUrl,
);
};
// Messages are already LLM-compatible (filtered by Agent)
const context: AgentContext = {
systemPrompt: cfg.systemPrompt,
messages,
tools: cfg.tools,
};
const pc: AgentLoopConfig = {
model: cfg.model,
reasoning: cfg.reasoning,
getQueuedMessages: cfg.getQueuedMessages,
};
// Yield events from the upstream agentLoop iterator
// Pass streamFn as the 5th parameter to use proxy
for await (const ev of agentLoop(userMessage as unknown as UserMessage, context, pc, signal, streamFn as any)) {
yield ev;
}
}
}

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import {
type AgentContext,
type AgentLoopConfig,
agentLoop,
type Message,
type UserMessage,
} from "@mariozechner/pi-ai";
import type { AgentRunConfig, AgentTransport } from "./types.js";
export interface ProviderTransportOptions {
/**
* Function to retrieve API key for a given provider.
* If not provided, transport will try to use environment variables.
*/
getApiKey?: (provider: string) => Promise<string | undefined> | string | undefined;
/**
* Optional CORS proxy URL for browser environments.
* If provided, all requests will be routed through this proxy.
* Format: "https://proxy.example.com"
*/
corsProxyUrl?: string;
}
/**
* Transport that calls LLM providers directly.
* Optionally routes calls through a CORS proxy if configured.
*/
export class ProviderTransport implements AgentTransport {
private options: ProviderTransportOptions;
constructor(options: ProviderTransportOptions = {}) {
this.options = options;
}
async *run(messages: Message[], userMessage: Message, cfg: AgentRunConfig, signal?: AbortSignal) {
// Get API key
let apiKey: string | undefined;
if (this.options.getApiKey) {
apiKey = await this.options.getApiKey(cfg.model.provider);
}
if (!apiKey) {
throw new Error(`No API key found for provider: ${cfg.model.provider}`);
}
// Clone model and modify baseUrl if CORS proxy is enabled
let model = cfg.model;
if (this.options.corsProxyUrl && cfg.model.baseUrl) {
model = {
...cfg.model,
baseUrl: `${this.options.corsProxyUrl}/?url=${encodeURIComponent(cfg.model.baseUrl)}`,
};
}
// Messages are already LLM-compatible (filtered by Agent)
const context: AgentContext = {
systemPrompt: cfg.systemPrompt,
messages,
tools: cfg.tools,
};
const pc: AgentLoopConfig = {
model,
reasoning: cfg.reasoning,
apiKey,
getQueuedMessages: cfg.getQueuedMessages,
};
// Yield events from agentLoop
for await (const ev of agentLoop(userMessage as unknown as UserMessage, context, pc, signal)) {
yield ev;
}
}
}

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export { AppTransport, type AppTransportOptions } from "./AppTransport.js";
export { ProviderTransport, type ProviderTransportOptions } from "./ProviderTransport.js";
export type { ProxyAssistantMessageEvent } from "./proxy-types.js";
export type { AgentRunConfig, AgentTransport } from "./types.js";

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import type { StopReason, Usage } from "@mariozechner/pi-ai";
/**
* Event types emitted by the proxy server.
* The server strips the `partial` field from delta events to reduce bandwidth.
* Clients reconstruct the partial message from these events.
*/
export type ProxyAssistantMessageEvent =
| { type: "start" }
| { type: "text_start"; contentIndex: number }
| { type: "text_delta"; contentIndex: number; delta: string }
| { type: "text_end"; contentIndex: number; contentSignature?: string }
| { type: "thinking_start"; contentIndex: number }
| { type: "thinking_delta"; contentIndex: number; delta: string }
| { type: "thinking_end"; contentIndex: number; contentSignature?: string }
| { type: "toolcall_start"; contentIndex: number; id: string; toolName: string }
| { type: "toolcall_delta"; contentIndex: number; delta: string }
| { type: "toolcall_end"; contentIndex: number }
| { type: "done"; reason: Extract<StopReason, "stop" | "length" | "toolUse">; usage: Usage }
| { type: "error"; reason: Extract<StopReason, "aborted" | "error">; errorMessage: string; usage: Usage };

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import type { AgentEvent, AgentTool, Message, Model, QueuedMessage } from "@mariozechner/pi-ai";
/**
* The minimal configuration needed to run an agent turn.
*/
export interface AgentRunConfig {
systemPrompt: string;
tools: AgentTool<any>[];
model: Model<any>;
reasoning?: "low" | "medium" | "high";
getQueuedMessages?: <T>() => Promise<QueuedMessage<T>[]>;
}
/**
* Transport interface for executing agent turns.
* Transports handle the communication with LLM providers,
* abstracting away the details of API calls, proxies, etc.
*
* Events yielded must match the @mariozechner/pi-ai AgentEvent types.
*/
export interface AgentTransport {
run(
messages: Message[],
userMessage: Message,
config: AgentRunConfig,
signal?: AbortSignal,
): AsyncIterable<AgentEvent>;
}

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import type { AgentTool, AssistantMessage, Message, Model, UserMessage } from "@mariozechner/pi-ai";
/**
* Attachment type definition.
* Processing is done by consumers (e.g., document extraction in web-ui).
*/
export interface Attachment {
id: string;
type: "image" | "document";
fileName: string;
mimeType: string;
size: number;
content: string; // base64 encoded (without data URL prefix)
extractedText?: string; // For documents
preview?: string; // base64 image preview
}
/**
* Thinking/reasoning level for models that support it.
*/
export type ThinkingLevel = "off" | "minimal" | "low" | "medium" | "high";
/**
* User message with optional attachments.
*/
export type UserMessageWithAttachments = UserMessage & { attachments?: Attachment[] };
/**
* Extensible interface for custom app messages.
* Apps can extend via declaration merging:
*
* @example
* ```typescript
* declare module "@mariozechner/agent" {
* interface CustomMessages {
* artifact: ArtifactMessage;
* notification: NotificationMessage;
* }
* }
* ```
*/
export interface CustomMessages {
// Empty by default - apps extend via declaration merging
}
/**
* AppMessage: Union of LLM messages + attachments + custom messages.
* This abstraction allows apps to add custom message types while maintaining
* type safety and compatibility with the base LLM messages.
*/
export type AppMessage =
| AssistantMessage
| UserMessageWithAttachments
| Message // Includes ToolResultMessage
| CustomMessages[keyof CustomMessages];
/**
* Agent state containing all configuration and conversation data.
*/
export interface AgentState {
systemPrompt: string;
model: Model<any>;
thinkingLevel: ThinkingLevel;
tools: AgentTool<any>[];
messages: AppMessage[]; // Can include attachments + custom message types
isStreaming: boolean;
streamMessage: Message | null;
pendingToolCalls: Set<string>;
error?: string;
}
/**
* Events emitted by the Agent for UI updates.
*/
export type AgentEvent = { type: "state-update"; state: AgentState } | { type: "started" } | { type: "completed" };

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import { getModel } from "@mariozechner/pi-ai";
import { describe, expect, it } from "vitest";
import { Agent, ProviderTransport } from "../src/index.js";
describe("Agent", () => {
it("should create an agent instance with default state", () => {
const agent = new Agent({
transport: new ProviderTransport(),
});
expect(agent.state).toBeDefined();
expect(agent.state.systemPrompt).toBe("");
expect(agent.state.model).toBeDefined();
expect(agent.state.thinkingLevel).toBe("off");
expect(agent.state.tools).toEqual([]);
expect(agent.state.messages).toEqual([]);
expect(agent.state.isStreaming).toBe(false);
expect(agent.state.streamMessage).toBe(null);
expect(agent.state.pendingToolCalls).toEqual(new Set());
expect(agent.state.error).toBeUndefined();
});
it("should create an agent instance with custom initial state", () => {
const customModel = getModel("openai", "gpt-4o-mini");
const agent = new Agent({
transport: new ProviderTransport(),
initialState: {
systemPrompt: "You are a helpful assistant.",
model: customModel,
thinkingLevel: "low",
},
});
expect(agent.state.systemPrompt).toBe("You are a helpful assistant.");
expect(agent.state.model).toBe(customModel);
expect(agent.state.thinkingLevel).toBe("low");
});
it("should subscribe to state updates", () => {
const agent = new Agent({
transport: new ProviderTransport(),
});
let updateCount = 0;
const unsubscribe = agent.subscribe((event) => {
if (event.type === "state-update") {
updateCount++;
}
});
// Initial state update on subscribe
expect(updateCount).toBe(1);
// Update state
agent.setSystemPrompt("Test prompt");
expect(updateCount).toBe(2);
expect(agent.state.systemPrompt).toBe("Test prompt");
// Unsubscribe should work
unsubscribe();
agent.setSystemPrompt("Another prompt");
expect(updateCount).toBe(2); // Should not increase
});
it("should update state with mutators", () => {
const agent = new Agent({
transport: new ProviderTransport(),
});
// Test setSystemPrompt
agent.setSystemPrompt("Custom prompt");
expect(agent.state.systemPrompt).toBe("Custom prompt");
// Test setModel
const newModel = getModel("google", "gemini-2.5-flash");
agent.setModel(newModel);
expect(agent.state.model).toBe(newModel);
// Test setThinkingLevel
agent.setThinkingLevel("high");
expect(agent.state.thinkingLevel).toBe("high");
// Test setTools
const tools = [{ name: "test", description: "test tool" } as any];
agent.setTools(tools);
expect(agent.state.tools).toBe(tools);
// Test replaceMessages
const messages = [{ role: "user" as const, content: "Hello" }];
agent.replaceMessages(messages);
expect(agent.state.messages).toEqual(messages);
expect(agent.state.messages).not.toBe(messages); // Should be a copy
// Test appendMessage
const newMessage = { role: "assistant" as const, content: [{ type: "text" as const, text: "Hi" }] };
agent.appendMessage(newMessage as any);
expect(agent.state.messages).toHaveLength(2);
expect(agent.state.messages[1]).toBe(newMessage);
// Test clearMessages
agent.clearMessages();
expect(agent.state.messages).toEqual([]);
});
it("should support message queueing", async () => {
const agent = new Agent({
transport: new ProviderTransport(),
});
const message = { role: "user" as const, content: "Queued message" };
await agent.queueMessage(message);
// The message is queued but not yet in state.messages
expect(agent.state.messages).not.toContainEqual(message);
});
it("should handle abort controller", () => {
const agent = new Agent({
transport: new ProviderTransport(),
});
// Should not throw even if nothing is running
expect(() => agent.abort()).not.toThrow();
});
});
describe("ProviderTransport", () => {
it("should create a provider transport instance", () => {
const transport = new ProviderTransport();
expect(transport).toBeDefined();
});
it("should create a provider transport with options", () => {
const transport = new ProviderTransport({
getApiKey: async (provider) => `test-key-${provider}`,
corsProxyUrl: "https://proxy.example.com",
});
expect(transport).toBeDefined();
});
});

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import type { Model } from "@mariozechner/pi-ai";
import { calculateTool, getModel } from "@mariozechner/pi-ai";
import { describe, expect, it } from "vitest";
import { Agent, ProviderTransport } from "../src/index.js";
async function basicPrompt(model: Model<any>) {
const agent = new Agent({
initialState: {
systemPrompt: "You are a helpful assistant. Keep your responses concise.",
model,
thinkingLevel: "off",
tools: [],
},
transport: new ProviderTransport({
getApiKey: async (provider) => {
// Map provider names to env var names
const envVarMap: Record<string, string> = {
google: "GEMINI_API_KEY",
openai: "OPENAI_API_KEY",
anthropic: "ANTHROPIC_API_KEY",
xai: "XAI_API_KEY",
groq: "GROQ_API_KEY",
cerebras: "CEREBRAS_API_KEY",
zai: "ZAI_API_KEY",
};
const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
return process.env[envVar];
},
}),
});
await agent.prompt("What is 2+2? Answer with just the number.");
expect(agent.state.isStreaming).toBe(false);
expect(agent.state.messages.length).toBe(2);
expect(agent.state.messages[0].role).toBe("user");
expect(agent.state.messages[1].role).toBe("assistant");
const assistantMessage = agent.state.messages[1];
if (assistantMessage.role !== "assistant") throw new Error("Expected assistant message");
expect(assistantMessage.content.length).toBeGreaterThan(0);
const textContent = assistantMessage.content.find((c) => c.type === "text");
expect(textContent).toBeDefined();
if (textContent?.type !== "text") throw new Error("Expected text content");
expect(textContent.text).toContain("4");
}
async function toolExecution(model: Model<any>) {
const agent = new Agent({
initialState: {
systemPrompt: "You are a helpful assistant. Always use the calculator tool for math.",
model,
thinkingLevel: "off",
tools: [calculateTool],
},
transport: new ProviderTransport({
getApiKey: async (provider) => {
// Map provider names to env var names
const envVarMap: Record<string, string> = {
google: "GEMINI_API_KEY",
openai: "OPENAI_API_KEY",
anthropic: "ANTHROPIC_API_KEY",
xai: "XAI_API_KEY",
groq: "GROQ_API_KEY",
cerebras: "CEREBRAS_API_KEY",
zai: "ZAI_API_KEY",
};
const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
return process.env[envVar];
},
}),
});
await agent.prompt("Calculate 123 * 456 using the calculator tool.");
expect(agent.state.isStreaming).toBe(false);
expect(agent.state.messages.length).toBeGreaterThanOrEqual(3);
const toolResultMsg = agent.state.messages.find((m) => m.role === "toolResult");
expect(toolResultMsg).toBeDefined();
if (toolResultMsg?.role !== "toolResult") throw new Error("Expected tool result message");
expect(toolResultMsg.output).toBeDefined();
const expectedResult = 123 * 456;
expect(toolResultMsg.output).toContain(String(expectedResult));
const finalMessage = agent.state.messages[agent.state.messages.length - 1];
if (finalMessage.role !== "assistant") throw new Error("Expected final assistant message");
const finalText = finalMessage.content.find((c) => c.type === "text");
expect(finalText).toBeDefined();
if (finalText?.type !== "text") throw new Error("Expected text content");
// Check for number with or without comma formatting
const hasNumber =
finalText.text.includes(String(expectedResult)) ||
finalText.text.includes("56,088") ||
finalText.text.includes("56088");
expect(hasNumber).toBe(true);
}
async function abortExecution(model: Model<any>) {
const agent = new Agent({
initialState: {
systemPrompt: "You are a helpful assistant.",
model,
thinkingLevel: "off",
tools: [calculateTool],
},
transport: new ProviderTransport({
getApiKey: async (provider) => {
// Map provider names to env var names
const envVarMap: Record<string, string> = {
google: "GEMINI_API_KEY",
openai: "OPENAI_API_KEY",
anthropic: "ANTHROPIC_API_KEY",
xai: "XAI_API_KEY",
groq: "GROQ_API_KEY",
cerebras: "CEREBRAS_API_KEY",
zai: "ZAI_API_KEY",
};
const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
return process.env[envVar];
},
}),
});
const promptPromise = agent.prompt("Calculate 100 * 200, then 300 * 400, then sum the results.");
setTimeout(() => {
agent.abort();
}, 100);
await promptPromise;
expect(agent.state.isStreaming).toBe(false);
expect(agent.state.messages.length).toBeGreaterThanOrEqual(2);
const lastMessage = agent.state.messages[agent.state.messages.length - 1];
if (lastMessage.role !== "assistant") throw new Error("Expected assistant message");
expect(lastMessage.stopReason).toBe("aborted");
expect(lastMessage.errorMessage).toBeDefined();
}
async function stateUpdates(model: Model<any>) {
const agent = new Agent({
initialState: {
systemPrompt: "You are a helpful assistant.",
model,
thinkingLevel: "off",
tools: [],
},
transport: new ProviderTransport({
getApiKey: async (provider) => {
// Map provider names to env var names
const envVarMap: Record<string, string> = {
google: "GEMINI_API_KEY",
openai: "OPENAI_API_KEY",
anthropic: "ANTHROPIC_API_KEY",
xai: "XAI_API_KEY",
groq: "GROQ_API_KEY",
cerebras: "CEREBRAS_API_KEY",
zai: "ZAI_API_KEY",
};
const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
return process.env[envVar];
},
}),
});
const stateSnapshots: Array<{ isStreaming: boolean; messageCount: number; hasStreamMessage: boolean }> = [];
agent.subscribe((event) => {
if (event.type === "state-update") {
stateSnapshots.push({
isStreaming: event.state.isStreaming,
messageCount: event.state.messages.length,
hasStreamMessage: event.state.streamMessage !== null,
});
}
});
await agent.prompt("Count from 1 to 5.");
const streamingStates = stateSnapshots.filter((s) => s.isStreaming);
const nonStreamingStates = stateSnapshots.filter((s) => !s.isStreaming);
expect(streamingStates.length).toBeGreaterThan(0);
expect(nonStreamingStates.length).toBeGreaterThan(0);
const finalState = stateSnapshots[stateSnapshots.length - 1];
expect(finalState.isStreaming).toBe(false);
expect(finalState.messageCount).toBe(2);
}
async function multiTurnConversation(model: Model<any>) {
const agent = new Agent({
initialState: {
systemPrompt: "You are a helpful assistant.",
model,
thinkingLevel: "off",
tools: [],
},
transport: new ProviderTransport({
getApiKey: async (provider) => {
// Map provider names to env var names
const envVarMap: Record<string, string> = {
google: "GEMINI_API_KEY",
openai: "OPENAI_API_KEY",
anthropic: "ANTHROPIC_API_KEY",
xai: "XAI_API_KEY",
groq: "GROQ_API_KEY",
cerebras: "CEREBRAS_API_KEY",
zai: "ZAI_API_KEY",
};
const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
return process.env[envVar];
},
}),
});
await agent.prompt("My name is Alice.");
expect(agent.state.messages.length).toBe(2);
await agent.prompt("What is my name?");
expect(agent.state.messages.length).toBe(4);
const lastMessage = agent.state.messages[3];
if (lastMessage.role !== "assistant") throw new Error("Expected assistant message");
const lastText = lastMessage.content.find((c) => c.type === "text");
if (lastText?.type !== "text") throw new Error("Expected text content");
expect(lastText.text.toLowerCase()).toContain("alice");
}
describe("Agent E2E Tests", () => {
describe.skipIf(!process.env.GEMINI_API_KEY)("Google Provider (gemini-2.5-flash)", () => {
const model = getModel("google", "gemini-2.5-flash");
it("should handle basic text prompt", async () => {
await basicPrompt(model);
});
it("should execute tools correctly", async () => {
await toolExecution(model);
});
it("should handle abort during execution", async () => {
await abortExecution(model);
});
it("should emit state updates during streaming", async () => {
await stateUpdates(model);
});
it("should maintain context across multiple turns", async () => {
await multiTurnConversation(model);
});
});
describe.skipIf(!process.env.OPENAI_API_KEY)("OpenAI Provider (gpt-4o-mini)", () => {
const model = getModel("openai", "gpt-4o-mini");
it("should handle basic text prompt", async () => {
await basicPrompt(model);
});
it("should execute tools correctly", async () => {
await toolExecution(model);
});
it("should handle abort during execution", async () => {
await abortExecution(model);
});
it("should emit state updates during streaming", async () => {
await stateUpdates(model);
});
it("should maintain context across multiple turns", async () => {
await multiTurnConversation(model);
});
});
describe.skipIf(!process.env.ANTHROPIC_API_KEY)("Anthropic Provider (claude-3-5-haiku-20241022)", () => {
const model = getModel("anthropic", "claude-3-5-haiku-20241022");
it("should handle basic text prompt", async () => {
await basicPrompt(model);
});
it("should execute tools correctly", async () => {
await toolExecution(model);
});
it("should handle abort during execution", async () => {
await abortExecution(model);
});
it("should emit state updates during streaming", async () => {
await stateUpdates(model);
});
it("should maintain context across multiple turns", async () => {
await multiTurnConversation(model);
});
});
describe.skipIf(!process.env.XAI_API_KEY)("xAI Provider (grok-3)", () => {
const model = getModel("xai", "grok-3");
it("should handle basic text prompt", async () => {
await basicPrompt(model);
});
it("should execute tools correctly", async () => {
await toolExecution(model);
});
it("should handle abort during execution", async () => {
await abortExecution(model);
});
it("should emit state updates during streaming", async () => {
await stateUpdates(model);
});
it("should maintain context across multiple turns", async () => {
await multiTurnConversation(model);
});
});
describe.skipIf(!process.env.GROQ_API_KEY)("Groq Provider (openai/gpt-oss-20b)", () => {
const model = getModel("groq", "openai/gpt-oss-20b");
it("should handle basic text prompt", async () => {
await basicPrompt(model);
});
it("should execute tools correctly", async () => {
await toolExecution(model);
});
it("should handle abort during execution", async () => {
await abortExecution(model);
});
it("should emit state updates during streaming", async () => {
await stateUpdates(model);
});
it("should maintain context across multiple turns", async () => {
await multiTurnConversation(model);
});
});
describe.skipIf(!process.env.CEREBRAS_API_KEY)("Cerebras Provider (gpt-oss-120b)", () => {
const model = getModel("cerebras", "gpt-oss-120b");
it("should handle basic text prompt", async () => {
await basicPrompt(model);
});
it("should execute tools correctly", async () => {
await toolExecution(model);
});
it("should handle abort during execution", async () => {
await abortExecution(model);
});
it("should emit state updates during streaming", async () => {
await stateUpdates(model);
});
it("should maintain context across multiple turns", async () => {
await multiTurnConversation(model);
});
});
describe.skipIf(!process.env.ZAI_API_KEY)("zAI Provider (glm-4.5-air)", () => {
const model = getModel("zai", "glm-4.5-air");
it("should handle basic text prompt", async () => {
await basicPrompt(model);
});
it("should execute tools correctly", async () => {
await toolExecution(model);
});
it("should handle abort during execution", async () => {
await abortExecution(model);
});
it("should emit state updates during streaming", async () => {
await stateUpdates(model);
});
it("should maintain context across multiple turns", async () => {
await multiTurnConversation(model);
});
});
});

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@ -4,6 +4,6 @@
"outDir": "./dist",
"rootDir": "./src"
},
"include": ["src/**/*"],
"exclude": ["node_modules", "dist"]
"include": ["src/**/*.ts"],
"exclude": ["node_modules", "dist", "**/*.d.ts", "src/**/*.d.ts"]
}

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import { defineConfig } from "vitest/config";
export default defineConfig({
test: {
globals: true,
environment: "node",
testTimeout: 10000, // 10 seconds
},
});

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{
"name": "@mariozechner/coding-agent",
"version": "0.5.44",
"description": "Coding agent CLI with read, bash, edit, write tools and session management",
"type": "module",
"bin": {
"coding-agent": "dist/cli.js"
},
"main": "./dist/index.js",
"types": "./dist/index.d.ts",
"files": [
"dist"
],
"scripts": {
"clean": "rm -rf dist",
"build": "tsc -p tsconfig.build.json && chmod +x dist/cli.js",
"dev": "tsc -p tsconfig.build.json --watch --preserveWatchOutput",
"check": "tsc --noEmit",
"test": "vitest --run",
"prepublishOnly": "npm run clean && npm run build"
},
"dependencies": {
"@mariozechner/pi-agent": "^0.5.44",
"@mariozechner/pi-ai": "^0.5.44",
"@mariozechner/pi-tui": "^0.5.44",
"chalk": "^5.5.0",
"glob": "^11.0.3"
},
"devDependencies": {
"@types/node": "^24.3.0",
"typescript": "^5.7.3",
"vitest": "^3.2.4"
},
"keywords": [
"coding-agent",
"ai",
"llm",
"cli",
"tui",
"agent"
],
"author": "Mario Zechner",
"license": "MIT",
"repository": {
"type": "git",
"url": "git+https://github.com/badlogic/pi-mono.git",
"directory": "packages/coding-agent"
},
"engines": {
"node": ">=20.0.0"
}
}

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#!/usr/bin/env node
import { main } from "./main.js";
main(process.argv.slice(2)).catch((err) => {
console.error(err);
process.exit(1);
});

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export { main } from "./main.js";
export { SessionManager } from "./session-manager.js";
export { bashTool, codingTools, editTool, readTool, writeTool } from "./tools/index.js";

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import { Agent, ProviderTransport } from "@mariozechner/pi-agent";
import { getModel } from "@mariozechner/pi-ai";
import chalk from "chalk";
import { SessionManager } from "./session-manager.js";
import { codingTools } from "./tools/index.js";
interface Args {
provider?: string;
model?: string;
apiKey?: string;
systemPrompt?: string;
continue?: boolean;
help?: boolean;
messages: string[];
}
function parseArgs(args: string[]): Args {
const result: Args = {
messages: [],
};
for (let i = 0; i < args.length; i++) {
const arg = args[i];
if (arg === "--help" || arg === "-h") {
result.help = true;
} else if (arg === "--continue" || arg === "-c") {
result.continue = true;
} else if (arg === "--provider" && i + 1 < args.length) {
result.provider = args[++i];
} else if (arg === "--model" && i + 1 < args.length) {
result.model = args[++i];
} else if (arg === "--api-key" && i + 1 < args.length) {
result.apiKey = args[++i];
} else if (arg === "--system-prompt" && i + 1 < args.length) {
result.systemPrompt = args[++i];
} else if (!arg.startsWith("-")) {
result.messages.push(arg);
}
}
return result;
}
function printHelp() {
console.log(`${chalk.bold("coding-agent")} - AI coding assistant with read, bash, edit, write tools
${chalk.bold("Usage:")}
coding-agent [options] [messages...]
${chalk.bold("Options:")}
--provider <name> Provider name (default: google)
--model <id> Model ID (default: gemini-2.5-flash)
--api-key <key> API key (defaults to env vars)
--system-prompt <text> System prompt (default: coding assistant prompt)
--continue, -c Continue previous session
--help, -h Show this help
${chalk.bold("Examples:")}
# Single message
coding-agent "List all .ts files in src/"
# Multiple messages
coding-agent "Read package.json" "What dependencies do we have?"
# Continue previous session
coding-agent --continue "What did we discuss?"
# Use different model
coding-agent --provider openai --model gpt-4o-mini "Help me refactor this code"
${chalk.bold("Environment Variables:")}
GEMINI_API_KEY - Google Gemini API key
OPENAI_API_KEY - OpenAI API key
ANTHROPIC_API_KEY - Anthropic API key
CODING_AGENT_DIR - Session storage directory (default: ~/.coding-agent)
${chalk.bold("Available Tools:")}
read - Read file contents
bash - Execute bash commands
edit - Edit files with find/replace
write - Write files (creates/overwrites)
`);
}
const DEFAULT_SYSTEM_PROMPT = `You are an expert coding assistant. You help users with coding tasks by reading files, executing commands, editing code, and writing new files.
Available tools:
- read: Read file contents
- bash: Execute bash commands (ls, grep, find, etc.)
- edit: Make surgical edits to files (find exact text and replace)
- write: Create or overwrite files
Guidelines:
- Always use bash tool for file operations like ls, grep, find
- Use read to examine files before editing
- Use edit for precise changes (old text must match exactly)
- Use write only for new files or complete rewrites
- Be concise in your responses
- Show file paths clearly when working with files
Current directory: ${process.cwd()}`;
export async function main(args: string[]) {
const parsed = parseArgs(args);
if (parsed.help) {
printHelp();
return;
}
// Setup session manager
const sessionManager = new SessionManager(parsed.continue);
// Determine provider and model
const provider = (parsed.provider || "google") as any;
const modelId = parsed.model || "gemini-2.5-flash";
// Get API key
let apiKey = parsed.apiKey;
if (!apiKey) {
const envVarMap: Record<string, string> = {
google: "GEMINI_API_KEY",
openai: "OPENAI_API_KEY",
anthropic: "ANTHROPIC_API_KEY",
xai: "XAI_API_KEY",
groq: "GROQ_API_KEY",
cerebras: "CEREBRAS_API_KEY",
zai: "ZAI_API_KEY",
};
const envVar = envVarMap[provider] || `${provider.toUpperCase()}_API_KEY`;
apiKey = process.env[envVar];
if (!apiKey) {
console.error(chalk.red(`Error: No API key found for provider "${provider}"`));
console.error(chalk.dim(`Set ${envVar} environment variable or use --api-key flag`));
process.exit(1);
}
}
// Create agent
const model = getModel(provider, modelId);
const systemPrompt = parsed.systemPrompt || DEFAULT_SYSTEM_PROMPT;
const agent = new Agent({
initialState: {
systemPrompt,
model,
thinkingLevel: "off",
tools: codingTools,
},
transport: new ProviderTransport({
getApiKey: async () => apiKey!,
}),
});
// Load previous messages if continuing
if (parsed.continue) {
const messages = sessionManager.loadMessages();
if (messages.length > 0) {
console.log(chalk.dim(`Loaded ${messages.length} messages from previous session`));
agent.replaceMessages(messages);
}
}
// Start session
sessionManager.startSession(agent.state);
// Subscribe to state updates to save messages
agent.subscribe((event) => {
if (event.type === "state-update") {
// Save any new messages
const currentMessages = event.state.messages;
const loadedMessages = sessionManager.loadMessages();
if (currentMessages.length > loadedMessages.length) {
for (let i = loadedMessages.length; i < currentMessages.length; i++) {
sessionManager.saveMessage(currentMessages[i]);
}
}
}
sessionManager.saveEvent(event);
});
// Process messages
if (parsed.messages.length === 0) {
console.log(chalk.yellow("No messages provided. Use --help for usage information."));
console.log(chalk.dim(`Session saved to: ${sessionManager.getSessionFile()}`));
return;
}
for (const message of parsed.messages) {
console.log(chalk.blue(`\n> ${message}\n`));
await agent.prompt(message);
// Print response
const lastMessage = agent.state.messages[agent.state.messages.length - 1];
if (lastMessage.role === "assistant") {
for (const content of lastMessage.content) {
if (content.type === "text") {
console.log(content.text);
}
}
}
}
console.log(chalk.dim(`\nSession saved to: ${sessionManager.getSessionFile()}`));
}

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import type { AgentEvent, AgentState } from "@mariozechner/pi-agent";
import { randomBytes } from "crypto";
import { appendFileSync, existsSync, mkdirSync, readdirSync, readFileSync, statSync } from "fs";
import { homedir } from "os";
import { join, resolve } from "path";
function uuidv4(): string {
const bytes = randomBytes(16);
bytes[6] = (bytes[6] & 0x0f) | 0x40;
bytes[8] = (bytes[8] & 0x3f) | 0x80;
const hex = bytes.toString("hex");
return `${hex.slice(0, 8)}-${hex.slice(8, 12)}-${hex.slice(12, 16)}-${hex.slice(16, 20)}-${hex.slice(20, 32)}`;
}
export interface SessionHeader {
type: "session";
id: string;
timestamp: string;
cwd: string;
systemPrompt: string;
model: string;
}
export interface SessionMessageEntry {
type: "message";
timestamp: string;
message: any; // AppMessage from agent state
}
export interface SessionEventEntry {
type: "event";
timestamp: string;
event: AgentEvent;
}
export class SessionManager {
private sessionId!: string;
private sessionFile!: string;
private sessionDir: string;
constructor(continueSession: boolean = false) {
this.sessionDir = this.getSessionDirectory();
if (continueSession) {
const mostRecent = this.findMostRecentlyModifiedSession();
if (mostRecent) {
this.sessionFile = mostRecent;
this.loadSessionId();
} else {
this.initNewSession();
}
} else {
this.initNewSession();
}
}
private getSessionDirectory(): string {
const cwd = process.cwd();
const safePath = "--" + cwd.replace(/^\//, "").replace(/\//g, "-") + "--";
const configDir = resolve(process.env.CODING_AGENT_DIR || join(homedir(), ".coding-agent"));
const sessionDir = join(configDir, "sessions", safePath);
if (!existsSync(sessionDir)) {
mkdirSync(sessionDir, { recursive: true });
}
return sessionDir;
}
private initNewSession(): void {
this.sessionId = uuidv4();
const timestamp = new Date().toISOString().replace(/[:.]/g, "-");
this.sessionFile = join(this.sessionDir, `${timestamp}_${this.sessionId}.jsonl`);
}
private findMostRecentlyModifiedSession(): string | null {
try {
const files = readdirSync(this.sessionDir)
.filter((f) => f.endsWith(".jsonl"))
.map((f) => ({
name: f,
path: join(this.sessionDir, f),
mtime: statSync(join(this.sessionDir, f)).mtime,
}))
.sort((a, b) => b.mtime.getTime() - a.mtime.getTime());
return files[0]?.path || null;
} catch {
return null;
}
}
private loadSessionId(): void {
if (!existsSync(this.sessionFile)) return;
const lines = readFileSync(this.sessionFile, "utf8").trim().split("\n");
for (const line of lines) {
try {
const entry = JSON.parse(line);
if (entry.type === "session") {
this.sessionId = entry.id;
return;
}
} catch {
// Skip malformed lines
}
}
this.sessionId = uuidv4();
}
startSession(state: AgentState): void {
const entry: SessionHeader = {
type: "session",
id: this.sessionId,
timestamp: new Date().toISOString(),
cwd: process.cwd(),
systemPrompt: state.systemPrompt,
model: `${state.model.provider}/${state.model.id}`,
};
appendFileSync(this.sessionFile, JSON.stringify(entry) + "\n");
}
saveMessage(message: any): void {
const entry: SessionMessageEntry = {
type: "message",
timestamp: new Date().toISOString(),
message,
};
appendFileSync(this.sessionFile, JSON.stringify(entry) + "\n");
}
saveEvent(event: AgentEvent): void {
const entry: SessionEventEntry = {
type: "event",
timestamp: new Date().toISOString(),
event,
};
appendFileSync(this.sessionFile, JSON.stringify(entry) + "\n");
}
loadMessages(): any[] {
if (!existsSync(this.sessionFile)) return [];
const messages: any[] = [];
const lines = readFileSync(this.sessionFile, "utf8").trim().split("\n");
for (const line of lines) {
try {
const entry = JSON.parse(line);
if (entry.type === "message") {
messages.push(entry.message);
}
} catch {
// Skip malformed lines
}
}
return messages;
}
getSessionId(): string {
return this.sessionId;
}
getSessionFile(): string {
return this.sessionFile;
}
}

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import type { AgentTool } from "@mariozechner/pi-ai";
import { Type } from "@sinclair/typebox";
import { exec } from "child_process";
import { promisify } from "util";
const execAsync = promisify(exec);
const bashSchema = Type.Object({
command: Type.String({ description: "Bash command to execute" }),
});
export const bashTool: AgentTool<typeof bashSchema> = {
name: "bash",
label: "bash",
description:
"Execute a bash command in the current working directory. Returns stdout and stderr. Commands run with a 30 second timeout.",
parameters: bashSchema,
execute: async (_toolCallId: string, { command }: { command: string }) => {
try {
const { stdout, stderr } = await execAsync(command, {
timeout: 30000,
maxBuffer: 10 * 1024 * 1024, // 10MB
});
let output = "";
if (stdout) output += stdout;
if (stderr) output += stderr ? `\nSTDERR:\n${stderr}` : "";
return { output: output || "(no output)", details: undefined };
} catch (error: any) {
return {
output: `Error executing command: ${error.message}\nSTDOUT: ${error.stdout || ""}\nSTDERR: ${error.stderr || ""}`,
details: undefined,
};
}
},
};

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import type { AgentTool } from "@mariozechner/pi-ai";
import { Type } from "@sinclair/typebox";
import { existsSync, readFileSync, writeFileSync } from "fs";
import { resolve } from "path";
const editSchema = Type.Object({
path: Type.String({ description: "Path to the file to edit (relative or absolute)" }),
oldText: Type.String({ description: "Exact text to find and replace (must match exactly)" }),
newText: Type.String({ description: "New text to replace the old text with" }),
});
export const editTool: AgentTool<typeof editSchema> = {
name: "edit",
label: "edit",
description:
"Edit a file by replacing exact text. The oldText must match exactly (including whitespace). Use this for precise, surgical edits.",
parameters: editSchema,
execute: async (
_toolCallId: string,
{ path, oldText, newText }: { path: string; oldText: string; newText: string },
) => {
try {
const absolutePath = resolve(path);
if (!existsSync(absolutePath)) {
return { output: `Error: File not found: ${path}`, details: undefined };
}
const content = readFileSync(absolutePath, "utf-8");
// Check if old text exists
if (!content.includes(oldText)) {
return {
output: `Error: Could not find the exact text in ${path}. The old text must match exactly including all whitespace and newlines.`,
details: undefined,
};
}
// Count occurrences
const occurrences = content.split(oldText).length - 1;
if (occurrences > 1) {
return {
output: `Error: Found ${occurrences} occurrences of the text in ${path}. The text must be unique. Please provide more context to make it unique.`,
details: undefined,
};
}
// Perform replacement
const newContent = content.replace(oldText, newText);
writeFileSync(absolutePath, newContent, "utf-8");
return {
output: `Successfully replaced text in ${path}. Changed ${oldText.length} characters to ${newText.length} characters.`,
details: undefined,
};
} catch (error: any) {
return { output: `Error editing file: ${error.message}`, details: undefined };
}
},
};

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export { bashTool } from "./bash.js";
export { editTool } from "./edit.js";
export { readTool } from "./read.js";
export { writeTool } from "./write.js";
import { bashTool } from "./bash.js";
import { editTool } from "./edit.js";
import { readTool } from "./read.js";
import { writeTool } from "./write.js";
export const codingTools = [readTool, bashTool, editTool, writeTool];

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import type { AgentTool } from "@mariozechner/pi-ai";
import { Type } from "@sinclair/typebox";
import { existsSync, readFileSync } from "fs";
import { resolve } from "path";
const readSchema = Type.Object({
path: Type.String({ description: "Path to the file to read (relative or absolute)" }),
});
export const readTool: AgentTool<typeof readSchema> = {
name: "read",
label: "read",
description: "Read the contents of a file. Returns the full file content as text.",
parameters: readSchema,
execute: async (_toolCallId: string, { path }: { path: string }) => {
try {
const absolutePath = resolve(path);
if (!existsSync(absolutePath)) {
return { output: `Error: File not found: ${path}`, details: undefined };
}
const content = readFileSync(absolutePath, "utf-8");
return { output: content, details: undefined };
} catch (error: any) {
return { output: `Error reading file: ${error.message}`, details: undefined };
}
},
};

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import type { AgentTool } from "@mariozechner/pi-ai";
import { Type } from "@sinclair/typebox";
import { mkdirSync, writeFileSync } from "fs";
import { dirname, resolve } from "path";
const writeSchema = Type.Object({
path: Type.String({ description: "Path to the file to write (relative or absolute)" }),
content: Type.String({ description: "Content to write to the file" }),
});
export const writeTool: AgentTool<typeof writeSchema> = {
name: "write",
label: "write",
description:
"Write content to a file. Creates the file if it doesn't exist, overwrites if it does. Automatically creates parent directories.",
parameters: writeSchema,
execute: async (_toolCallId: string, { path, content }: { path: string; content: string }) => {
try {
const absolutePath = resolve(path);
const dir = dirname(absolutePath);
// Create parent directories if needed
mkdirSync(dir, { recursive: true });
writeFileSync(absolutePath, content, "utf-8");
return { output: `Successfully wrote ${content.length} bytes to ${path}`, details: undefined };
} catch (error: any) {
return { output: `Error writing file: ${error.message}`, details: undefined };
}
},
};

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import { mkdirSync, rmSync, writeFileSync } from "fs";
import { tmpdir } from "os";
import { join } from "path";
import { afterEach, beforeEach, describe, expect, it } from "vitest";
import { bashTool } from "../src/tools/bash.js";
import { editTool } from "../src/tools/edit.js";
import { readTool } from "../src/tools/read.js";
import { writeTool } from "../src/tools/write.js";
describe("Coding Agent Tools", () => {
let testDir: string;
beforeEach(() => {
// Create a unique temporary directory for each test
testDir = join(tmpdir(), `coding-agent-test-${Date.now()}`);
mkdirSync(testDir, { recursive: true });
});
afterEach(() => {
// Clean up test directory
rmSync(testDir, { recursive: true, force: true });
});
describe("read tool", () => {
it("should read file contents", async () => {
const testFile = join(testDir, "test.txt");
const content = "Hello, world!";
writeFileSync(testFile, content);
const result = await readTool.execute("test-call-1", { path: testFile });
expect(result.output).toBe(content);
expect(result.details).toBeUndefined();
});
it("should handle non-existent files", async () => {
const testFile = join(testDir, "nonexistent.txt");
const result = await readTool.execute("test-call-2", { path: testFile });
expect(result.output).toContain("Error");
expect(result.output).toContain("File not found");
});
});
describe("write tool", () => {
it("should write file contents", async () => {
const testFile = join(testDir, "write-test.txt");
const content = "Test content";
const result = await writeTool.execute("test-call-3", { path: testFile, content });
expect(result.output).toContain("Successfully wrote");
expect(result.output).toContain(testFile);
expect(result.details).toBeUndefined();
});
it("should create parent directories", async () => {
const testFile = join(testDir, "nested", "dir", "test.txt");
const content = "Nested content";
const result = await writeTool.execute("test-call-4", { path: testFile, content });
expect(result.output).toContain("Successfully wrote");
});
});
describe("edit tool", () => {
it("should replace text in file", async () => {
const testFile = join(testDir, "edit-test.txt");
const originalContent = "Hello, world!";
writeFileSync(testFile, originalContent);
const result = await editTool.execute("test-call-5", {
path: testFile,
oldText: "world",
newText: "testing",
});
expect(result.output).toContain("Successfully replaced");
expect(result.details).toBeUndefined();
});
it("should fail if text not found", async () => {
const testFile = join(testDir, "edit-test.txt");
const originalContent = "Hello, world!";
writeFileSync(testFile, originalContent);
const result = await editTool.execute("test-call-6", {
path: testFile,
oldText: "nonexistent",
newText: "testing",
});
expect(result.output).toContain("Could not find the exact text");
});
it("should fail if text appears multiple times", async () => {
const testFile = join(testDir, "edit-test.txt");
const originalContent = "foo foo foo";
writeFileSync(testFile, originalContent);
const result = await editTool.execute("test-call-7", {
path: testFile,
oldText: "foo",
newText: "bar",
});
expect(result.output).toContain("Found 3 occurrences");
});
});
describe("bash tool", () => {
it("should execute simple commands", async () => {
const result = await bashTool.execute("test-call-8", { command: "echo 'test output'" });
expect(result.output).toContain("test output");
expect(result.details).toBeUndefined();
});
it("should handle command errors", async () => {
const result = await bashTool.execute("test-call-9", { command: "exit 1" });
expect(result.output).toContain("Command failed");
});
it("should respect timeout", async () => {
const result = await bashTool.execute("test-call-10", { command: "sleep 35" });
expect(result.output).toContain("Command failed");
}, 35000);
});
});

View file

@ -0,0 +1,9 @@
{
"extends": "../../tsconfig.base.json",
"compilerOptions": {
"outDir": "./dist",
"rootDir": "./src"
},
"include": ["src/**/*.ts"],
"exclude": ["node_modules", "dist", "**/*.d.ts", "src/**/*.d.ts"]
}

View file

@ -0,0 +1,9 @@
import { defineConfig } from 'vitest/config';
export default defineConfig({
test: {
globals: true,
environment: 'node',
testTimeout: 30000, // 30 seconds for API calls
}
});

View file

@ -34,7 +34,7 @@
"node": ">=20.0.0"
},
"dependencies": {
"@mariozechner/pi-agent": "^0.5.44",
"@mariozechner/pi-agent-old": "^0.5.44",
"chalk": "^5.5.0"
},
"devDependencies": {}

View file

@ -1,4 +1,4 @@
import { main as agentMain } from "@mariozechner/pi-agent";
import { main as agentMain } from "@mariozechner/pi-agent-old";
import chalk from "chalk";
import { getActivePod, loadConfig } from "../config.js";

View file

@ -9,6 +9,7 @@ import {
type AppMessage,
AppStorage,
ChatPanel,
createJavaScriptReplTool,
IndexedDBStorageBackend,
// PersistentStorageDialog, // TODO: Fix - currently broken
ProviderKeysStore,
@ -197,6 +198,12 @@ Feel free to use these tools when needed to provide accurate and helpful respons
await chatPanel.setAgent(agent, {
onApiKeyRequired: async (provider: string) => {
return await ApiKeyPromptDialog.prompt(provider);
},
toolsFactory: (agent, agentInterface, artifactsPanel, runtimeProvidersFactory) => {
// Create javascript_repl tool with access to attachments + artifacts
const replTool = createJavaScriptReplTool();
replTool.runtimeProvidersFactory = runtimeProvidersFactory;
return [replTool];
}
});
};

View file

@ -9,7 +9,6 @@ import { ArtifactsRuntimeProvider } from "./components/sandbox/ArtifactsRuntimeP
import { AttachmentsRuntimeProvider } from "./components/sandbox/AttachmentsRuntimeProvider.js";
import type { SandboxRuntimeProvider } from "./components/sandbox/SandboxRuntimeProvider.js";
import { ArtifactsPanel, ArtifactsToolRenderer } from "./tools/artifacts/index.js";
import { createJavaScriptReplTool } from "./tools/javascript-repl.js";
import { registerToolRenderer } from "./tools/renderer-registry.js";
import type { Attachment } from "./utils/attachment-utils.js";
import { i18n } from "./utils/i18n.js";
@ -65,6 +64,7 @@ export class ChatPanel extends LitElement {
agent: Agent,
agentInterface: AgentInterface,
artifactsPanel: ArtifactsPanel,
runtimeProvidersFactory: () => SandboxRuntimeProvider[],
) => AgentTool<any>[];
},
) {
@ -80,12 +80,6 @@ export class ChatPanel extends LitElement {
this.agentInterface.onApiKeyRequired = config?.onApiKeyRequired;
this.agentInterface.onBeforeSend = config?.onBeforeSend;
// Create JavaScript REPL tool
const javascriptReplTool = createJavaScriptReplTool();
if (config?.sandboxUrlProvider) {
javascriptReplTool.sandboxUrlProvider = config.sandboxUrlProvider;
}
// Set up artifacts panel
this.artifactsPanel = new ArtifactsPanel();
if (config?.sandboxUrlProvider) {
@ -94,7 +88,7 @@ export class ChatPanel extends LitElement {
// Register the standalone tool renderer (not the panel itself)
registerToolRenderer("artifacts", new ArtifactsToolRenderer(this.artifactsPanel));
// Runtime providers factory
// Runtime providers factory for attachments + artifacts access
const runtimeProvidersFactory = () => {
const attachments: Attachment[] = [];
for (const message of this.agent!.state.messages) {
@ -116,7 +110,6 @@ export class ChatPanel extends LitElement {
return providers;
};
javascriptReplTool.runtimeProvidersFactory = runtimeProvidersFactory;
this.artifactsPanel.runtimeProvidersFactory = runtimeProvidersFactory;
this.artifactsPanel.onArtifactsChange = () => {
@ -141,8 +134,10 @@ export class ChatPanel extends LitElement {
};
// Set tools on the agent
const additionalTools = config?.toolsFactory?.(agent, this.agentInterface, this.artifactsPanel) || [];
const tools = [javascriptReplTool, this.artifactsPanel.tool, ...additionalTools];
// Pass runtimeProvidersFactory so consumers can configure their own REPL tools
const additionalTools =
config?.toolsFactory?.(agent, this.agentInterface, this.artifactsPanel, runtimeProvidersFactory) || [];
const tools = [this.artifactsPanel.tool, ...additionalTools];
this.agent.setTools(tools);
// Reconstruct artifacts from existing messages

View file

@ -1,4 +1,4 @@
import { ARTIFACTS_RUNTIME_PROVIDER_DESCRIPTION } from "../../prompts/tool-prompts.js";
import { ARTIFACTS_RUNTIME_PROVIDER_DESCRIPTION } from "../../prompts/prompts.js";
import type { SandboxRuntimeProvider } from "./SandboxRuntimeProvider.js";
// Define minimal interface for ArtifactsPanel to avoid circular dependencies

View file

@ -1,4 +1,4 @@
import { ATTACHMENTS_RUNTIME_DESCRIPTION } from "../../prompts/tool-prompts.js";
import { ATTACHMENTS_RUNTIME_DESCRIPTION } from "../../prompts/prompts.js";
import type { Attachment } from "../../utils/attachment-utils.js";
import type { SandboxRuntimeProvider } from "./SandboxRuntimeProvider.js";

View file

@ -23,6 +23,10 @@ export class ConsoleRuntimeProvider implements SandboxRuntimeProvider {
return {};
}
getDescription(): string {
return "";
}
getRuntime(): (sandboxId: string) => void {
return (_sandboxId: string) => {
// Store truly original console methods on first wrap only

View file

@ -31,5 +31,5 @@ export interface SandboxRuntimeProvider {
* Optional documentation describing what globals/functions this provider injects.
* This will be appended to tool descriptions dynamically so the LLM knows what's available.
*/
getDescription?(): string;
getDescription(): string;
}

View file

@ -56,8 +56,8 @@ export { ApiKeysTab, ProxyTab, SettingsDialog, SettingsTab } from "./dialogs/Set
// Prompts
export {
ARTIFACTS_RUNTIME_PROVIDER_DESCRIPTION,
DOWNLOADABLE_FILE_RUNTIME_DESCRIPTION,
} from "./prompts/tool-prompts.js";
ATTACHMENTS_RUNTIME_DESCRIPTION,
} from "./prompts/prompts.js";
// Storage
export { AppStorage, getAppStorage, setAppStorage } from "./storage/app-storage.js";
export { IndexedDBStorageBackend } from "./storage/backends/indexeddb-storage-backend.js";

View file

@ -7,7 +7,7 @@
// JavaScript REPL Tool
// ============================================================================
export const JAVASCRIPT_REPL_DESCRIPTION = `# JavaScript REPL
export const JAVASCRIPT_REPL_TOOL_DESCRIPTION = (runtimeProviderDescriptions: string[]) => `# JavaScript REPL
## Purpose
Execute JavaScript code in a sandboxed browser environment with full Web APIs.
@ -16,7 +16,7 @@ Execute JavaScript code in a sandboxed browser environment with full Web APIs.
- Quick calculations or data transformations
- Testing JavaScript code snippets in isolation
- Processing data with libraries (XLSX, CSV, etc.)
- Creating visualizations (charts, graphs)
- Creating artifacts from data
## Environment
- ES2023+ JavaScript (async/await, optional chaining, nullish coalescing, etc.)
@ -54,13 +54,21 @@ console.log('Sum:', sum, 'Average:', avg);
## Important Notes
- Graphics: Use fixed dimensions (800x600), NOT window.innerWidth/Height
- Chart.js: Set options: { responsive: false, animation: false }
- Three.js: renderer.setSize(800, 600) with matching aspect ratio`;
- Three.js: renderer.setSize(800, 600) with matching aspect ratio
## Library functions
You can use the following functions in your code:
${runtimeProviderDescriptions.join("\n\n")}
`;
// ============================================================================
// Artifacts Tool
// ============================================================================
export const ARTIFACTS_BASE_DESCRIPTION = `Creates and manages file artifacts. Each artifact is a file with a filename and content.
export const ARTIFACTS_TOOL_DESCRIPTION = (
runtimeProviderDescriptions: string[],
) => `Creates and manages file artifacts. Each artifact is a file with a filename and content.
CRITICAL - ARTIFACT UPDATE WORKFLOW:
1. Creating new file? Use 'create'
@ -104,33 +112,8 @@ Commands:
ANTI-PATTERNS TO AVOID:
Using 'get' + modifying content + 'rewrite' to change one section
Using createOrUpdateArtifact() in code for manual edits YOU make
Use 'update' command for surgical, targeted modifications`;
Use 'update' command for surgical, targeted modifications
export const ARTIFACTS_RUNTIME_EXAMPLE = `- Example HTML artifact that processes a CSV attachment:
<script>
// List available files
const files = listAttachments();
console.log('Available files:', files);
// Find CSV file
const csvFile = files.find(f => f.mimeType === 'text/csv');
if (csvFile) {
const csvContent = readTextAttachment(csvFile.id);
// Process CSV data...
}
// Display image
const imageFile = files.find(f => f.mimeType.startsWith('image/'));
if (imageFile) {
const bytes = readBinaryAttachment(imageFile.id);
const blob = new Blob([bytes], {type: imageFile.mimeType});
const url = URL.createObjectURL(blob);
document.body.innerHTML = '<img src="' + url + '">';
}
</script>
`;
export const ARTIFACTS_HTML_SECTION = `
For text/html artifacts:
- Must be a single self-contained file
- External scripts: Use CDNs like https://esm.sh, https://unpkg.com, or https://cdnjs.cloudflare.com
@ -166,40 +149,33 @@ CRITICAL REMINDER FOR ALL ARTIFACTS:
- Prefer to update existing files rather than creating new ones
- Keep filenames consistent and descriptive
- Use appropriate file extensions
- Ensure HTML artifacts have a defined background color`;
- Ensure HTML artifacts have a defined background color
/**
* Build complete artifacts description with optional provider docs.
*/
export function buildArtifactsDescription(providerDocs?: string): string {
const runtimeSection = providerDocs
? `
The following functions are available inside your code in HTML artifacts:
For text/html artifacts with runtime capabilities:${providerDocs}
${ARTIFACTS_RUNTIME_EXAMPLE}
`
: "";
return ARTIFACTS_BASE_DESCRIPTION + runtimeSection + ARTIFACTS_HTML_SECTION;
}
${runtimeProviderDescriptions.join("\n\n")}
`;
// ============================================================================
// Artifacts Runtime Provider
// ============================================================================
export const ARTIFACTS_RUNTIME_PROVIDER_DESCRIPTION = `
Artifact Management from within executed code (HTML/JavaScript REPL).
### Artifacts
WHEN TO USE THESE FUNCTIONS:
Programmatically create, read, update, and delete artifact files from your code.
#### When to Use
- Persist data or state between REPL calls
- ONLY when writing code that programmatically generates/transforms data
- Examples: Web scraping results, processed CSV data, generated charts saved as JSON
- The artifact content is CREATED BY THE CODE, not by you directly
DO NOT USE THESE FUNCTIONS FOR:
#### Do NOT Use For
- Summaries or notes YOU write (use artifacts tool instead)
- Content YOU author directly (use artifacts tool instead)
Functions:
#### Functions
- await listArtifacts() - Get list of all artifact filenames, returns string[]
* Example: const files = await listArtifacts(); // ['data.json', 'notes.md']
@ -216,39 +192,75 @@ Functions:
- await deleteArtifact(filename) - Delete an artifact
* Example: await deleteArtifact('temp.json')
Example - Scraping data and saving it:
const response = await fetch('https://api.example.com/data');
const data = await response.json();
await createOrUpdateArtifact('api-results.json', data);
#### Example
Scraping data and saving it:
\`\`\`javascript
const response = await fetch('https://api.example.com/data');
const data = await response.json();
await createOrUpdateArtifact('api-results.json', data);
\`\`\`
Binary data must be converted to a base64 string before passing to createOrUpdateArtifact.
Example:
const blob = await new Promise(resolve => canvas.toBlob(resolve, 'image/png'));
const arrayBuffer = await blob.arrayBuffer();
const base64 = btoa(String.fromCharCode(...new Uint8Array(arrayBuffer)));
await createOrUpdateArtifact('image.png', base64);
Binary data (convert to base64 first):
\`\`\`javascript
const blob = await new Promise(resolve => canvas.toBlob(resolve, 'image/png'));
const arrayBuffer = await blob.arrayBuffer();
const base64 = btoa(String.fromCharCode(...new Uint8Array(arrayBuffer)));
await createOrUpdateArtifact('image.png', base64);
\`\`\`
`;
// ============================================================================
// Downloadable File Runtime Provider
// Attachments Runtime Provider
// ============================================================================
export const DOWNLOADABLE_FILE_RUNTIME_DESCRIPTION = `
Downloadable Files (one-time downloads for the user - YOU cannot read these back):
- await returnDownloadableFile(filename, content, mimeType?) - Create downloadable file (async!)
* Use for: Processed/transformed data, generated images, analysis results
* Important: This creates a download for the user. You will NOT be able to access this file's content later.
* If you need to access the data later, use createArtifact() instead (if available).
* Always use await with returnDownloadableFile
* REQUIRED: For Blob/Uint8Array binary content, you MUST supply a proper MIME type (e.g., "image/png").
If omitted, throws an Error with stack trace pointing to the offending line.
* Strings without a MIME default to text/plain.
* Objects are auto-JSON stringified and default to application/json unless a MIME is provided.
* Canvas images: Use toBlob() with await Promise wrapper
* Examples:
- await returnDownloadableFile('cleaned-data.csv', csvString, 'text/csv')
- await returnDownloadableFile('analysis.json', {results: [...]}, 'application/json')
- await returnDownloadableFile('chart.png', blob, 'image/png')`;
export const ATTACHMENTS_RUNTIME_DESCRIPTION = `
### User Attachments
Read files that the user has uploaded to the conversation.
#### When to Use
- When you need to read or process files the user has uploaded to the conversation
- Examples: CSV data files, JSON datasets, Excel spreadsheets, images, PDFs
#### Do NOT Use For
- Creating new files (use createOrUpdateArtifact instead)
- Modifying existing files (read first, then create artifact with modified version)
#### Functions
- listAttachments() - List all attachments, returns array of {id, fileName, mimeType, size}
* Example: const files = listAttachments(); // [{id: '...', fileName: 'data.xlsx', mimeType: '...', size: 12345}]
- readTextAttachment(attachmentId) - Read attachment as text, returns string
* Use for: CSV, JSON, TXT, XML, and other text-based files
* Example: const csvContent = readTextAttachment(files[0].id);
* Example: const json = JSON.parse(readTextAttachment(jsonFile.id));
- readBinaryAttachment(attachmentId) - Read attachment as binary data, returns Uint8Array
* Use for: Excel (.xlsx), images, PDFs, and other binary files
* Example: const xlsxBytes = readBinaryAttachment(files[0].id);
* Example: const XLSX = await import('https://esm.run/xlsx'); const workbook = XLSX.read(xlsxBytes);
#### Example
Processing CSV attachment:
\`\`\`javascript
const files = listAttachments();
const csvFile = files.find(f => f.fileName.endsWith('.csv'));
const csvData = readTextAttachment(csvFile.id);
const rows = csvData.split('\\n').map(row => row.split(','));
console.log(\`Found \${rows.length} rows\`);
\`\`\`
Processing Excel attachment:
\`\`\`javascript
const XLSX = await import('https://esm.run/xlsx');
const files = listAttachments();
const excelFile = files.find(f => f.fileName.endsWith('.xlsx'));
const bytes = readBinaryAttachment(excelFile.id);
const workbook = XLSX.read(bytes);
const firstSheet = workbook.Sheets[workbook.SheetNames[0]];
const jsonData = XLSX.utils.sheet_to_json(firstSheet);
\`\`\`
`;
// ============================================================================
// Extract Document Tool
@ -273,27 +285,3 @@ Structured plain text with page/sheet/slide delimiters in XML-like format:
- Maximum file size: 50MB
- CORS restrictions may block some URLs - if this happens, the error will guide you to help the user configure a CORS proxy
- Format is automatically detected from file extension and Content-Type header`;
// ============================================================================
// Attachments Runtime Provider
// ============================================================================
export const ATTACHMENTS_RUNTIME_DESCRIPTION = `
User Attachments (files the user added to the conversation):
- listAttachments() - List all attachments, returns array of {id, fileName, mimeType, size}
* Example: const files = listAttachments(); // [{id: '...', fileName: 'data.xlsx', mimeType: '...', size: 12345}]
- readTextAttachment(attachmentId) - Read attachment as text, returns string
* Use for: CSV, JSON, TXT, XML, and other text-based files
* Example: const csvContent = readTextAttachment(files[0].id);
* Example: const json = JSON.parse(readTextAttachment(jsonFile.id));
- readBinaryAttachment(attachmentId) - Read attachment as binary data, returns Uint8Array
* Use for: Excel (.xlsx), images, PDFs, and other binary files
* Example: const xlsxBytes = readBinaryAttachment(files[0].id);
* Example: const XLSX = await import('https://esm.run/xlsx'); const workbook = XLSX.read(xlsxBytes);
Common pattern - Process attachment and create download:
const files = listAttachments();
const csvFile = files.find(f => f.fileName.endsWith('.csv'));
const csvData = readTextAttachment(csvFile.id);
// Process csvData...
await returnDownloadableFile('processed-' + csvFile.fileName, processedData, 'text/csv');`;

View file

@ -8,7 +8,7 @@ import { createRef, type Ref, ref } from "lit/directives/ref.js";
import { X } from "lucide";
import type { ArtifactMessage } from "../../components/Messages.js";
import type { SandboxRuntimeProvider } from "../../components/sandbox/SandboxRuntimeProvider.js";
import { buildArtifactsDescription } from "../../prompts/tool-prompts.js";
import { ARTIFACTS_TOOL_DESCRIPTION } from "../../prompts/prompts.js";
import { i18n } from "../../utils/i18n.js";
import type { ArtifactElement } from "./ArtifactElement.js";
import { DocxArtifact } from "./DocxArtifact.js";
@ -245,14 +245,12 @@ export class ArtifactsPanel extends LitElement {
label: "Artifacts",
name: "artifacts",
get description() {
// Get dynamic provider descriptions
const providers = self.runtimeProvidersFactory?.() || [];
const providerDocs = providers
.map((p) => p.getDescription?.())
.filter(Boolean)
.join("\n");
return buildArtifactsDescription(providerDocs || undefined);
const runtimeProviderDescriptions =
self
.runtimeProvidersFactory?.()
.map((d) => d.getDescription())
.filter((d) => d.trim().length > 0) || [];
return ARTIFACTS_TOOL_DESCRIPTION(runtimeProviderDescriptions);
},
parameters: artifactsParamsSchema,
// Execute mutates our local store and returns a plain output

View file

@ -3,7 +3,7 @@ import type { AgentTool, ToolResultMessage } from "@mariozechner/pi-ai";
import { type Static, Type } from "@sinclair/typebox";
import { createRef, ref } from "lit/directives/ref.js";
import { FileText } from "lucide";
import { EXTRACT_DOCUMENT_DESCRIPTION } from "../prompts/tool-prompts.js";
import { EXTRACT_DOCUMENT_DESCRIPTION } from "../prompts/prompts.js";
import { loadAttachment } from "../utils/attachment-utils.js";
import { registerToolRenderer, renderCollapsibleHeader, renderHeader } from "./renderer-registry.js";
import type { ToolRenderer, ToolRenderResult } from "./types.js";

View file

@ -5,7 +5,7 @@ import { createRef, ref } from "lit/directives/ref.js";
import { Code } from "lucide";
import { type SandboxFile, SandboxIframe, type SandboxResult } from "../components/SandboxedIframe.js";
import type { SandboxRuntimeProvider } from "../components/sandbox/SandboxRuntimeProvider.js";
import { JAVASCRIPT_REPL_DESCRIPTION } from "../prompts/tool-prompts.js";
import { JAVASCRIPT_REPL_TOOL_DESCRIPTION } from "../prompts/prompts.js";
import type { Attachment } from "../utils/attachment-utils.js";
import { registerToolRenderer, renderCollapsibleHeader, renderHeader } from "./renderer-registry.js";
import type { ToolRenderer, ToolRenderResult } from "./types.js";
@ -132,7 +132,13 @@ export function createJavaScriptReplTool(): AgentTool<typeof javascriptReplSchem
name: "javascript_repl",
runtimeProvidersFactory: () => [], // default to empty array
sandboxUrlProvider: undefined, // optional, for browser extensions
description: JAVASCRIPT_REPL_DESCRIPTION,
get description() {
const runtimeProviderDescriptions =
this.runtimeProvidersFactory?.()
.map((d) => d.getDescription())
.filter((d) => d.trim().length > 0) || [];
return JAVASCRIPT_REPL_TOOL_DESCRIPTION(runtimeProviderDescriptions);
},
parameters: javascriptReplSchema,
execute: async function (_toolCallId: string, args: Static<typeof javascriptReplSchema>, signal?: AbortSignal) {
const result = await executeJavaScript(

View file

@ -7,6 +7,8 @@
"@mariozechner/pi-ai": ["./packages/ai/src/index.ts"],
"@mariozechner/pi-web-ui": ["./packages/web-ui/src/index.ts"],
"@mariozechner/pi-agent": ["./packages/agent/src/index.ts"],
"@mariozechner/pi-agent-old": ["./packages/agent-old/src/index.ts"],
"@mariozechner/coding-agent": ["./packages/coding-agent/src/index.ts"],
"@mariozechner/pi": ["./packages/pods/src/index.ts"]
}
},