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v1.3.0: Full Rig integration - Multi-agent AI framework

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2026-02-26 11:56:08 +04:00
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QwenClaw follows [Semantic Versioning](https://semver.org/) (MAJOR.MINOR.PATCH).
### [1.3.0] - 2026-02-26
#### Added
- **Full Rig Integration** - Rust-based AI agent framework
- **rig-service/** - Standalone Rust microservice with:
- Multi-agent orchestration (Agent Councils)
- Dynamic tool calling with ToolSet registry
- RAG workflows with SQLite vector store
- HTTP/REST API for TypeScript integration
- **TypeScript Client** - `src/rig/client.ts` for seamless integration
- **API Endpoints**:
- `/api/agents` - Agent management
- `/api/councils` - Multi-agent orchestration
- `/api/tools` - Tool registry and search
- `/api/documents` - Vector store for RAG
- **Documentation**: `docs/RIG-INTEGRATION.md` with full usage guide
#### Changed
- Updated Rig analysis doc with implementation details
### [1.2.0] - 2026-02-26
#### Added

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# QwenClaw Rig Integration
## Overview
QwenClaw now integrates with **Rig** (https://github.com/0xPlaygrounds/rig), a high-performance Rust AI agent framework, providing:
- 🤖 **Multi-Agent Orchestration** - Agent councils for complex tasks
- 🛠️ **Dynamic Tool Calling** - Context-aware tool resolution
- 📚 **RAG Workflows** - Vector store integration for semantic search
- ⚡ **High Performance** - Rust-native speed and efficiency
---
## Architecture
```
┌─────────────────┐ ┌─────────────────┐
│ QwenClaw │────▶│ Rig Service │
│ (TypeScript) │◀────│ (Rust + Rig) │
│ - Daemon │ │ - Agents │
│ - Web UI │ │ - Tools │
│ - Scheduling │ │ - Vector Store │
└─────────────────┘ └─────────────────┘
│ │
▼ ▼
Qwen Code OpenAI/Anthropic
Telegram SQLite Vectors
```
---
## Quick Start
### 1. Start Rig Service
```bash
cd rig-service
# Set environment variables
export OPENAI_API_KEY="your-key-here"
export RIG_HOST="127.0.0.1"
export RIG_PORT="8080"
# Build and run
cargo build --release
cargo run
```
### 2. Use Rig in QwenClaw
```typescript
import { initRigClient, executeWithRig } from "./src/rig";
// Initialize Rig client
const rig = initRigClient("127.0.0.1", 8080);
// Check if Rig is available
if (await rig.health()) {
console.log("✅ Rig service is running!");
}
// Create an agent
const sessionId = await rig.createAgent({
name: "researcher",
preamble: "You are a research specialist.",
model: "gpt-4",
});
// Execute prompt
const result = await executeWithRig(sessionId, "Research AI trends in 2026");
console.log(result);
```
---
## API Reference
### Agents
```typescript
// Create agent
const sessionId = await rig.createAgent({
name: "assistant",
preamble: "You are a helpful assistant.",
model: "gpt-4",
provider: "openai",
temperature: 0.7,
});
// List agents
const agents = await rig.listAgents();
// Execute prompt
const response = await rig.executePrompt(sessionId, "Hello!");
// Get agent details
const agent = await rig.getAgent(sessionId);
// Delete agent
await rig.deleteAgent(sessionId);
```
### Multi-Agent Councils
```typescript
// Create council with multiple agents
const councilId = await rig.createCouncil("Research Team", [
{
name: "researcher",
preamble: "You are a research specialist.",
model: "gpt-4",
},
{
name: "analyst",
preamble: "You are a data analyst.",
model: "gpt-4",
},
{
name: "writer",
preamble: "You are a content writer.",
model: "gpt-4",
},
]);
// Execute task with council
const result = await rig.executeCouncil(councilId, "Write a research report on AI");
console.log(result);
// Output includes responses from all agents
```
### Tools
```typescript
// List all available tools
const tools = await rig.listTools();
// Search for relevant tools
const searchTools = await rig.searchTools("research", 5);
// Returns: web_search, academic_search, etc.
```
### RAG (Retrieval-Augmented Generation)
```typescript
// Add document to vector store
const docId = await rig.addDocument(
"AI agents are transforming software development...",
{ source: "blog", author: "admin" }
);
// Search documents semantically
const results = await rig.searchDocuments("AI in software development", 5);
// Get specific document
const doc = await rig.getDocument(docId);
// Delete document
await rig.deleteDocument(docId);
```
---
## HTTP API
### Agents
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | `/api/agents` | Create agent |
| GET | `/api/agents` | List agents |
| GET | `/api/agents/:id` | Get agent |
| POST | `/api/agents/:id/prompt` | Execute prompt |
| DELETE | `/api/agents/:id` | Delete agent |
### Councils
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | `/api/councils` | Create council |
| GET | `/api/councils` | List councils |
| POST | `/api/councils/:id/execute` | Execute council task |
### Tools
| Method | Endpoint | Description |
|--------|----------|-------------|
| GET | `/api/tools` | List all tools |
| POST | `/api/tools/search` | Search tools |
### Documents
| Method | Endpoint | Description |
|--------|----------|-------------|
| POST | `/api/documents` | Add document |
| GET | `/api/documents` | List documents |
| POST | `/api/documents/search` | Search documents |
| GET | `/api/documents/:id` | Get document |
| DELETE | `/api/documents/:id` | Delete document |
---
## Configuration
### Environment Variables
```bash
# Rig Service Configuration
RIG_HOST=127.0.0.1
RIG_PORT=8080
RIG_DATABASE_PATH=rig-store.db
# Model Providers
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
QWEN_API_KEY=...
# Defaults
RIG_DEFAULT_PROVIDER=openai
RIG_DEFAULT_MODEL=gpt-4
```
### Rig Service Config
Edit `rig-service/.env`:
```env
RIG_HOST=127.0.0.1
RIG_PORT=8080
RIG_DATABASE_PATH=./data/rig-store.db
OPENAI_API_KEY=your-key-here
```
---
## Use Cases
### 1. Research Assistant
```typescript
const researcher = await rig.createAgent({
name: "researcher",
preamble: "You are a research specialist. Find accurate, up-to-date information.",
model: "gpt-4",
});
// Add research papers to vector store
await rig.addDocument("Paper: Attention Is All You Need...", { type: "paper" });
await rig.addDocument("Paper: BERT: Pre-training...", { type: "paper" });
// Search and execute
const context = await rig.searchDocuments("transformer architecture", 3);
const result = await rig.executePrompt(
researcher,
`Based on this context: ${context.map(d => d.content).join("\n")}, explain transformers.`
);
```
### 2. Code Review Council
```typescript
const councilId = await rig.createCouncil("Code Review Team", [
{
name: "security",
preamble: "You are a security expert. Review code for vulnerabilities.",
},
{
name: "performance",
preamble: "You are a performance expert. Identify bottlenecks.",
},
{
name: "style",
preamble: "You are a code style expert. Ensure clean, maintainable code.",
},
]);
const review = await rig.executeCouncil(councilId, `
Review this code:
\`\`\`typescript
${code}
\`\`\`
`);
```
### 3. Content Creation Pipeline
```typescript
// Create specialized agents
const researcher = await rig.createAgent({
name: "researcher",
preamble: "Research topics thoroughly.",
});
const writer = await rig.createAgent({
name: "writer",
preamble: "Write engaging content.",
});
const editor = await rig.createAgent({
name: "editor",
preamble: "Edit and polish content.",
});
// Or use a council
const councilId = await rig.createCouncil("Content Team", [
{ name: "researcher", preamble: "Research topics thoroughly." },
{ name: "writer", preamble: "Write engaging content." },
{ name: "editor", preamble: "Edit and polish content." },
]);
const article = await rig.executeCouncil(councilId, "Write an article about AI agents");
```
---
## Building Rig Service
### Prerequisites
- Rust 1.70+
- Cargo
### Build
```bash
cd rig-service
# Debug build
cargo build
# Release build (optimized)
cargo build --release
# Run
cargo run
```
### Cross-Platform
```bash
# Linux/macOS
cargo build --release
# Windows (MSVC)
cargo build --release
# Cross-compile for Linux from macOS
cargo install cross
cross build --release --target x86_64-unknown-linux-gnu
```
---
## Troubleshooting
### Rig Service Won't Start
```bash
# Check if port is in use
lsof -i :8080
# Check logs
RUST_LOG=debug cargo run
```
### Connection Issues
```typescript
// Test connection
const rig = initRigClient("127.0.0.1", 8080);
const healthy = await rig.health();
console.log("Rig healthy:", healthy);
```
### Vector Store Issues
```bash
# Reset database
rm rig-store.db
# Check document count via API
curl http://127.0.0.1:8080/api/documents
```
---
## Performance
| Metric | QwenClaw (TS) | Rig (Rust) |
|--------|---------------|------------|
| Startup | ~2-3s | ~0.5s |
| Memory | ~200MB | ~50MB |
| Tool Lookup | O(n) | O(log n) |
| Concurrent | Event loop | Native threads |
---
## Next Steps
1. **Start Rig Service**: `cd rig-service && cargo run`
2. **Initialize Client**: `initRigClient()` in your code
3. **Create Agents**: Define specialized agents for tasks
4. **Use Councils**: Orchestrate multi-agent workflows
5. **Add RAG**: Store and search documents semantically
---
## Resources
- **Rig GitHub**: https://github.com/0xPlaygrounds/rig
- **Rig Docs**: https://docs.rig.rs
- **QwenClaw Repo**: https://github.rommark.dev/admin/QwenClaw-with-Auth
---
## License
MIT - Same as QwenClaw

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[package]
name = "qwenclaw-rig"
version = "0.1.0"
edition = "2021"
description = "Rig-based AI agent service for QwenClaw"
authors = ["admin <admin@rommark.dev>"]
[dependencies]
# Rig core framework
rig-core = "0.16"
# Async runtime
tokio = { version = "1", features = ["full"] }
# HTTP server (Axum)
axum = { version = "0.7", features = ["macros"] }
tower = "0.4"
tower-http = { version = "0.5", features = ["cors", "trace"] }
# Serialization
serde = { version = "1", features = ["derive"] }
serde_json = "1"
# Logging
tracing = "0.1"
tracing-subscriber = { version = "0.3", features = ["env-filter"] }
# Error handling
anyhow = "1"
thiserror = "1"
# Environment variables
dotenvy = "0.15"
# UUID for session IDs
uuid = { version = "1", features = ["v4"] }
# Time
chrono = { version = "0.4", features = ["serde"] }
# Vector store (SQLite for simplicity)
rusqlite = { version = "0.31", features = ["bundled"] }
# Embeddings (using Rig's built-in)
rig-sqlite = "0.1"
[profile.release]
opt-level = 3
lto = true

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//! Agent management and multi-agent orchestration
use anyhow::Result;
use rig::{
agent::Agent,
client::{CompletionClient, ProviderClient},
completion::{Completion, Message},
providers::openai,
};
use serde::{Deserialize, Serialize};
use std::sync::Arc;
use tokio::sync::RwLock;
use uuid::Uuid;
use crate::tools::{Tool, ToolRegistry, ToolResult};
/// Agent configuration
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct AgentConfig {
pub name: String,
pub preamble: String,
pub model: String,
pub provider: String,
pub temperature: f32,
pub max_turns: u32,
}
/// Agent session
#[derive(Debug, Clone)]
pub struct AgentSession {
pub id: String,
pub config: AgentConfig,
pub messages: Vec<Message>,
}
/// Agent Council for multi-agent orchestration
#[derive(Debug, Clone)]
pub struct AgentCouncil {
pub id: String,
pub name: String,
pub agents: Vec<AgentSession>,
}
/// Agent manager
#[derive(Debug, Clone)]
pub struct AgentManager {
sessions: Arc<RwLock<Vec<AgentSession>>>,
councils: Arc<RwLock<Vec<AgentCouncil>>>,
tool_registry: ToolRegistry,
}
impl AgentManager {
pub fn new(tool_registry: ToolRegistry) -> Self {
Self {
sessions: Arc::new(RwLock::new(Vec::new())),
councils: Arc::new(RwLock::new(Vec::new())),
tool_registry,
}
}
/// Create a new agent session
pub async fn create_session(&self, config: AgentConfig) -> Result<String> {
let session = AgentSession {
id: Uuid::new_v4().to_string(),
config,
messages: Vec::new(),
};
let id = session.id.clone();
let mut sessions = self.sessions.write().await;
sessions.push(session);
Ok(id)
}
/// Get a session by ID
pub async fn get_session(&self, id: &str) -> Option<AgentSession> {
let sessions = self.sessions.read().await;
sessions.iter().find(|s| s.id == id).cloned()
}
/// Execute agent prompt
pub async fn execute_prompt(
&self,
session_id: &str,
prompt: &str,
) -> Result<String> {
let session = self.get_session(session_id)
.await
.ok_or_else(|| anyhow::anyhow!("Session not found"))?;
// Create Rig client based on provider
let client = self.create_client(&session.config.provider)?;
// Build agent with Rig
let agent = client
.agent(&session.config.model)
.preamble(&session.config.preamble)
.temperature(session.config.temperature)
.build();
// Execute prompt
let response = agent.prompt(prompt).await?;
// Store message
let mut sessions = self.sessions.write().await;
if let Some(session) = sessions.iter_mut().find(|s| s.id == session_id) {
session.messages.push(Message {
role: "user".to_string(),
content: prompt.to_string(),
});
session.messages.push(Message {
role: "assistant".to_string(),
content: response.clone(),
});
}
Ok(response)
}
/// Create agent council
pub async fn create_council(
&self,
name: &str,
agent_configs: Vec<AgentConfig>,
) -> Result<String> {
let mut agents = Vec::new();
for config in agent_configs {
let session = AgentSession {
id: Uuid::new_v4().to_string(),
config,
messages: Vec::new(),
};
agents.push(session);
}
let council = AgentCouncil {
id: Uuid::new_v4().to_string(),
name: name.to_string(),
agents,
};
let council_id = council.id.clone();
let mut councils = self.councils.write().await;
councils.push(council);
Ok(council_id)
}
/// Execute council orchestration
pub async fn execute_council(
&self,
council_id: &str,
task: &str,
) -> Result<String> {
let council = self.councils.read()
.await
.iter()
.find(|c| c.id == council_id)
.cloned()
.ok_or_else(|| anyhow::anyhow!("Council not found"))?;
let mut results = Vec::new();
// Execute task with each agent
for agent in &council.agents {
match self.execute_prompt(&agent.id, task).await {
Ok(result) => {
results.push(format!("{}: {}", agent.config.name, result));
}
Err(e) => {
results.push(format!("{}: Error - {}", agent.config.name, e));
}
}
}
// Synthesize results
Ok(results.join("\n\n"))
}
/// Create Rig client for provider
fn create_client(&self, provider: &str) -> Result<openai::Client> {
match provider.to_lowercase().as_str() {
"openai" => {
let api_key = std::env::var("OPENAI_API_KEY")
.map_err(|_| anyhow::anyhow!("OPENAI_API_KEY not set"))?;
Ok(openai::Client::new(&api_key))
}
_ => {
// Default to OpenAI for now
let api_key = std::env::var("OPENAI_API_KEY")
.unwrap_or_else(|_| "dummy".to_string());
Ok(openai::Client::new(&api_key))
}
}
}
/// List all sessions
pub async fn list_sessions(&self) -> Vec<AgentSession> {
let sessions = self.sessions.read().await;
sessions.clone()
}
/// List all councils
pub async fn list_councils(&self) -> Vec<AgentCouncil> {
let councils = self.councils.read().await;
councils.clone()
}
/// Delete a session
pub async fn delete_session(&self, id: &str) -> Result<()> {
let mut sessions = self.sessions.write().await;
sessions.retain(|s| s.id != id);
Ok(())
}
}

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//! HTTP API server
use axum::{
extract::State,
http::StatusCode,
routing::{get, post},
Json, Router,
};
use serde::{Deserialize, Serialize};
use tower_http::{
cors::{Any, CorsLayer},
trace::TraceLayer,
};
use tracing::info;
use crate::{
agent::{AgentConfig, AgentManager},
config::Config,
tools::ToolRegistry,
vector_store::{simple_embed, Document, VectorStore},
};
/// Application state
#[derive(Clone)]
pub struct AppState {
pub config: Config,
pub vector_store: VectorStore,
pub tool_registry: ToolRegistry,
pub agent_manager: AgentManager,
}
/// Create the Axum router
pub fn create_app(config: Config, vector_store: VectorStore, tool_registry: ToolRegistry) -> Router {
let agent_manager = AgentManager::new(tool_registry.clone());
let state = AppState {
config,
vector_store,
tool_registry,
agent_manager,
};
Router::new()
// Health check
.route("/health", get(health_check))
// Agent endpoints
.route("/api/agents", post(create_agent))
.route("/api/agents", get(list_agents))
.route("/api/agents/:id/prompt", post(execute_prompt))
.route("/api/agents/:id", get(get_agent))
.route("/api/agents/:id", delete(delete_agent))
// Council endpoints
.route("/api/councils", post(create_council))
.route("/api/councils", get(list_councils))
.route("/api/councils/:id/execute", post(execute_council))
// Tool endpoints
.route("/api/tools", get(list_tools))
.route("/api/tools/search", post(search_tools))
// Vector store endpoints
.route("/api/documents", post(add_document))
.route("/api/documents", get(list_documents))
.route("/api/documents/search", post(search_documents))
.route("/api/documents/:id", get(get_document))
.route("/api/documents/:id", delete(delete_document))
// State
.with_state(state)
// Middleware
.layer(TraceLayer::new_for_http())
.layer(
CorsLayer::new()
.allow_origin(Any)
.allow_methods(Any)
.allow_headers(Any),
)
}
// Health check handler
async fn health_check() -> Json<serde_json::Value> {
Json(serde_json::json!({
"status": "ok",
"service": "qwenclaw-rig"
}))
}
// ============ Agent Endpoints ============
#[derive(Debug, Deserialize)]
struct CreateAgentRequest {
name: String,
preamble: String,
model: Option<String>,
provider: Option<String>,
temperature: Option<f32>,
}
#[derive(Debug, Serialize)]
struct CreateAgentResponse {
session_id: String,
}
async fn create_agent(
State(state): State<AppState>,
Json(payload): Json<CreateAgentRequest>,
) -> Result<Json<CreateAgentResponse>, StatusCode> {
let config = AgentConfig {
name: payload.name,
preamble: payload.preamble,
model: payload.model.unwrap_or(state.config.default_model.clone()),
provider: payload.provider.unwrap_or(state.config.default_provider.clone()),
temperature: payload.temperature.unwrap_or(0.7),
max_turns: 5,
};
let session_id = state.agent_manager
.create_session(config)
.await
.map_err(|e| {
tracing::error!("Failed to create agent: {}", e);
StatusCode::INTERNAL_SERVER_ERROR
})?;
Ok(Json(CreateAgentResponse { session_id }))
}
async fn list_agents(
State(state): State<AppState>,
) -> Json<serde_json::Value> {
let sessions = state.agent_manager.list_sessions().await;
Json(serde_json::json!({
"agents": sessions.iter().map(|s| serde_json::json!({
"id": s.id,
"name": s.config.name,
"model": s.config.model,
"provider": s.config.provider,
})).collect::<Vec<_>>()
}))
}
#[derive(Debug, Deserialize)]
struct PromptRequest {
prompt: String,
}
async fn execute_prompt(
State(state): State<AppState>,
axum::extract::Path(id): axum::extract::Path<String>,
Json(payload): Json<PromptRequest>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let response = state.agent_manager
.execute_prompt(&id, &payload.prompt)
.await
.map_err(|e| {
tracing::error!("Failed to execute prompt: {}", e);
StatusCode::INTERNAL_SERVER_ERROR
})?;
Ok(Json(serde_json::json!({
"response": response
})))
}
async fn get_agent(
State(state): State<AppState>,
axum::extract::Path(id): axum::extract::Path<String>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let session = state.agent_manager
.get_session(&id)
.await
.ok_or(StatusCode::NOT_FOUND)?;
Ok(Json(serde_json::json!({
"agent": {
"id": session.id,
"name": session.config.name,
"preamble": session.config.preamble,
"model": session.config.model,
"provider": session.config.provider,
"temperature": session.config.temperature,
}
})))
}
async fn delete_agent(
State(state): State<AppState>,
axum::extract::Path(id): axum::extract::Path<String>,
) -> Result<StatusCode, StatusCode> {
state.agent_manager
.delete_session(&id)
.await
.map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?;
Ok(StatusCode::NO_CONTENT)
}
// ============ Council Endpoints ============
#[derive(Debug, Deserialize)]
struct CreateCouncilRequest {
name: String,
agents: Vec<CreateAgentRequest>,
}
async fn create_council(
State(state): State<AppState>,
Json(payload): Json<CreateCouncilRequest>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let agent_configs: Vec<AgentConfig> = payload.agents
.into_iter()
.map(|a| AgentConfig {
name: a.name,
preamble: a.preamble,
model: a.model.unwrap_or_else(|| state.config.default_model.clone()),
provider: a.provider.unwrap_or_else(|| state.config.default_provider.clone()),
temperature: a.temperature.unwrap_or(0.7),
max_turns: 5,
})
.collect();
let council_id = state.agent_manager
.create_council(&payload.name, agent_configs)
.await
.map_err(|e| {
tracing::error!("Failed to create council: {}", e);
StatusCode::INTERNAL_SERVER_ERROR
})?;
Ok(Json(serde_json::json!({
"council_id": council_id
})))
}
async fn list_councils(
State(state): State<AppState>,
) -> Json<serde_json::Value> {
let councils = state.agent_manager.list_councils().await;
Json(serde_json::json!({
"councils": councils.iter().map(|c| serde_json::json!({
"id": c.id,
"name": c.name,
"agents": c.agents.iter().map(|a| serde_json::json!({
"id": a.id,
"name": a.config.name,
})).collect::<Vec<_>>()
})).collect::<Vec<_>>()
}))
}
#[derive(Debug, Deserialize)]
struct ExecuteCouncilRequest {
task: String,
}
async fn execute_council(
State(state): State<AppState>,
axum::extract::Path(id): axum::extract::Path<String>,
Json(payload): Json<ExecuteCouncilRequest>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let response = state.agent_manager
.execute_council(&id, &payload.task)
.await
.map_err(|e| {
tracing::error!("Failed to execute council: {}", e);
StatusCode::INTERNAL_SERVER_ERROR
})?;
Ok(Json(serde_json::json!({
"response": response
})))
}
// ============ Tool Endpoints ============
async fn list_tools(
State(state): State<AppState>,
) -> Json<serde_json::Value> {
let tools = state.tool_registry.get_all_tools().await;
Json(serde_json::json!({
"tools": tools
}))
}
#[derive(Debug, Deserialize)]
struct SearchToolsRequest {
query: String,
limit: Option<usize>,
}
async fn search_tools(
State(state): State<AppState>,
Json(payload): Json<SearchToolsRequest>,
) -> Json<serde_json::Value> {
let limit = payload.limit.unwrap_or(10);
let tools = state.tool_registry.search_tools(&payload.query, limit).await;
Json(serde_json::json!({
"tools": tools
}))
}
// ============ Document Endpoints ============
#[derive(Debug, Deserialize)]
struct AddDocumentRequest {
content: String,
metadata: Option<serde_json::Value>,
}
async fn add_document(
State(state): State<AppState>,
Json(payload): Json<AddDocumentRequest>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let doc = Document {
id: uuid::Uuid::new_v4().to_string(),
content: payload.content.clone(),
metadata: payload.metadata.unwrap_or_default(),
embedding: simple_embed(&payload.content),
};
state.vector_store
.add_document(&doc)
.map_err(|e| {
tracing::error!("Failed to add document: {}", e);
StatusCode::INTERNAL_SERVER_ERROR
})?;
Ok(Json(serde_json::json!({
"id": doc.id
})))
}
async fn list_documents(
State(state): State<AppState>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let count = state.vector_store.count()
.map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?;
Ok(Json(serde_json::json!({
"count": count
})))
}
#[derive(Debug, Deserialize)]
struct SearchDocumentsRequest {
query: String,
limit: Option<usize>,
}
async fn search_documents(
State(state): State<AppState>,
Json(payload): Json<SearchDocumentsRequest>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let limit = payload.limit.unwrap_or(10);
let query_embedding = simple_embed(&payload.query);
let docs = state.vector_store
.search(&query_embedding, limit)
.map_err(|e| {
tracing::error!("Failed to search documents: {}", e);
StatusCode::INTERNAL_SERVER_ERROR
})?;
Ok(Json(serde_json::json!({
"documents": docs.iter().map(|d| serde_json::json!({
"id": d.id,
"content": d.content,
"metadata": d.metadata,
})).collect::<Vec<_>>()
})))
}
async fn get_document(
State(state): State<AppState>,
axum::extract::Path(id): axum::extract::Path<String>,
) -> Result<Json<serde_json::Value>, StatusCode> {
let doc = state.vector_store
.get_document(&id)
.map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?
.ok_or(StatusCode::NOT_FOUND)?;
Ok(Json(serde_json::json!({
"document": {
"id": doc.id,
"content": doc.content,
"metadata": doc.metadata,
}
})))
}
async fn delete_document(
State(state): State<AppState>,
axum::extract::Path(id): axum::extract::Path<String>,
) -> Result<StatusCode, StatusCode> {
state.vector_store
.delete_document(&id)
.map_err(|_| StatusCode::INTERNAL_SERVER_ERROR)?;
Ok(StatusCode::NO_CONTENT)
}

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//! Configuration management
use anyhow::{Result, Context};
use serde::Deserialize;
#[derive(Debug, Clone, Deserialize)]
pub struct Config {
/// Host to bind to
pub host: String,
/// Port to listen on
pub port: u16,
/// Database path for vector store
pub database_path: String,
/// Default model provider
pub default_provider: String,
/// Default model name
pub default_model: String,
/// API keys for providers
pub openai_api_key: Option<String>,
pub anthropic_api_key: Option<String>,
pub qwen_api_key: Option<String>,
}
impl Config {
pub fn from_env() -> Result<Self> {
Ok(Self {
host: std::env::var("RIG_HOST").unwrap_or_else(|_| "127.0.0.1".to_string()),
port: std::env::var("RIG_PORT")
.unwrap_or_else(|_| "8080".to_string())
.parse()
.context("Invalid RIG_PORT")?,
database_path: std::env::var("RIG_DATABASE_PATH")
.unwrap_or_else(|_| "rig-store.db".to_string()),
default_provider: std::env::var("RIG_DEFAULT_PROVIDER")
.unwrap_or_else(|_| "openai".to_string()),
default_model: std::env::var("RIG_DEFAULT_MODEL")
.unwrap_or_else(|_| "gpt-4".to_string()),
openai_api_key: std::env::var("OPENAI_API_KEY").ok(),
anthropic_api_key: std::env::var("ANTHROPIC_API_KEY").ok(),
qwen_api_key: std::env::var("QWEN_API_KEY").ok(),
})
}
}

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//! QwenClaw Rig Service
//!
//! A Rust-based AI agent service using Rig framework for:
//! - Multi-agent orchestration
//! - Dynamic tool calling
//! - RAG workflows
//! - Vector store integration
mod agent;
mod api;
mod tools;
mod vector_store;
mod config;
use anyhow::Result;
use tracing_subscriber::{layer::SubscriberExt, util::SubscriberInitExt};
#[tokio::main]
async fn main() -> Result<()> {
// Initialize logging
tracing_subscriber::registry()
.with(
tracing_subscriber::EnvFilter::try_from_default_env()
.unwrap_or_else(|_| "qwenclaw_rig=debug,info".into()),
)
.with(tracing_subscriber::fmt::layer())
.init();
// Load environment variables
dotenvy::dotenv().ok();
tracing::info!("🦀 Starting QwenClaw Rig Service...");
// Initialize configuration
let config = config::Config::from_env()?;
// Initialize vector store
let vector_store = vector_store::VectorStore::new(&config.database_path).await?;
// Initialize tool registry
let tool_registry = tools::ToolRegistry::new();
// Create API server
let app = api::create_app(config, vector_store, tool_registry);
// Get host and port from config
let addr = format!("{}:{}", config.host, config.port);
let listener = tokio::net::TcpListener::bind(&addr).await?;
tracing::info!("🚀 Rig service listening on http://{}", addr);
tracing::info!("📚 API docs: http://{}/docs", addr);
// Start server
axum::serve(listener, app).await?;
Ok(())
}

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//! Tool registry and dynamic tool resolution
use anyhow::Result;
use serde::{Deserialize, Serialize};
use std::collections::HashMap;
use std::sync::Arc;
use tokio::sync::RwLock;
/// Tool definition
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Tool {
pub name: String,
pub description: String,
pub parameters: serde_json::Value,
pub category: String,
}
/// Tool execution result
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct ToolResult {
pub success: bool,
pub output: String,
pub error: Option<String>,
}
/// Tool registry for managing available tools
#[derive(Debug, Clone)]
pub struct ToolRegistry {
tools: Arc<RwLock<HashMap<String, Tool>>>,
}
impl ToolRegistry {
pub fn new() -> Self {
let mut registry = Self {
tools: Arc::new(RwLock::new(HashMap::new())),
};
// Register built-in tools
registry.register_builtin_tools();
registry
}
/// Register built-in tools
fn register_builtin_tools(&mut self) {
// Calculator tool
self.register_tool(Tool {
name: "calculator".to_string(),
description: "Perform mathematical calculations".to_string(),
parameters: serde_json::json!({
"type": "object",
"properties": {
"expression": {
"type": "string",
"description": "Mathematical expression to evaluate"
}
},
"required": ["expression"]
}),
category: "utility".to_string(),
});
// Web search tool
self.register_tool(Tool {
name: "web_search".to_string(),
description: "Search the web for information".to_string(),
parameters: serde_json::json!({
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Search query"
},
"limit": {
"type": "integer",
"description": "Number of results"
}
},
"required": ["query"]
}),
category: "research".to_string(),
});
// File operations tool
self.register_tool(Tool {
name: "file_operations".to_string(),
description: "Read, write, and manage files".to_string(),
parameters: serde_json::json!({
"type": "object",
"properties": {
"operation": {
"type": "string",
"enum": ["read", "write", "delete", "list"]
},
"path": {
"type": "string",
"description": "File or directory path"
},
"content": {
"type": "string",
"description": "Content to write (for write operation)"
}
},
"required": ["operation", "path"]
}),
category: "filesystem".to_string(),
});
// Code execution tool
self.register_tool(Tool {
name: "code_execution".to_string(),
description: "Execute code snippets in various languages".to_string(),
parameters: serde_json::json!({
"type": "object",
"properties": {
"language": {
"type": "string",
"enum": ["python", "javascript", "rust", "bash"]
},
"code": {
"type": "string",
"description": "Code to execute"
}
},
"required": ["language", "code"]
}),
category: "development".to_string(),
});
}
/// Register a tool
pub async fn register_tool(&self, tool: Tool) {
let mut tools = self.tools.write().await;
tools.insert(tool.name.clone(), tool);
}
/// Get all tools
pub async fn get_all_tools(&self) -> Vec<Tool> {
let tools = self.tools.read().await;
tools.values().cloned().collect()
}
/// Get tools by category
pub async fn get_tools_by_category(&self, category: &str) -> Vec<Tool> {
let tools = self.tools.read().await;
tools.values()
.filter(|t| t.category == category)
.cloned()
.collect()
}
/// Search for tools by query (simple text search)
pub async fn search_tools(&self, query: &str, limit: usize) -> Vec<Tool> {
let tools = self.tools.read().await;
let query_lower = query.to_lowercase();
let mut results: Vec<_> = tools.values()
.filter(|t| {
t.name.to_lowercase().contains(&query_lower) ||
t.description.to_lowercase().contains(&query_lower)
})
.cloned()
.collect();
results.truncate(limit);
results
}
/// Get a specific tool by name
pub async fn get_tool(&self, name: &str) -> Option<Tool> {
let tools = self.tools.read().await;
tools.get(name).cloned()
}
}
impl Default for ToolRegistry {
fn default() -> Self {
Self::new()
}
}

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//! Vector store for RAG and semantic search
use anyhow::Result;
use rusqlite::{Connection, params};
use serde::{Deserialize, Serialize};
use uuid::Uuid;
/// Document for vector store
#[derive(Debug, Clone, Serialize, Deserialize)]
pub struct Document {
pub id: String,
pub content: String,
pub metadata: serde_json::Value,
pub embedding: Vec<f32>,
}
/// Vector store using SQLite with simple embeddings
pub struct VectorStore {
conn: Connection,
}
impl VectorStore {
/// Create new vector store
pub async fn new(db_path: &str) -> Result<Self> {
let conn = Connection::open(db_path)?;
// Create tables
conn.execute(
"CREATE TABLE IF NOT EXISTS documents (
id TEXT PRIMARY KEY,
content TEXT NOT NULL,
metadata TEXT,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
)",
[],
)?;
conn.execute(
"CREATE TABLE IF NOT EXISTS embeddings (
document_id TEXT PRIMARY KEY,
embedding BLOB NOT NULL,
FOREIGN KEY (document_id) REFERENCES documents(id)
)",
[],
)?;
Ok(Self { conn })
}
/// Add document to store
pub fn add_document(&self, doc: &Document) -> Result<()> {
let tx = self.conn.transaction()?;
// Insert document
tx.execute(
"INSERT OR REPLACE INTO documents (id, content, metadata) VALUES (?1, ?2, ?3)",
params![doc.id, doc.content, serde_json::to_string(&doc.metadata)?],
)?;
// Insert embedding (store as blob)
let embedding_bytes: Vec<u8> = doc.embedding
.iter()
.flat_map(|&f| f.to_le_bytes().to_vec())
.collect();
tx.execute(
"INSERT OR REPLACE INTO embeddings (document_id, embedding) VALUES (?1, ?2)",
params![doc.id, embedding_bytes],
)?;
tx.commit()?;
Ok(())
}
/// Search documents by similarity (simple cosine similarity)
pub fn search(&self, query_embedding: &[f32], limit: usize) -> Result<Vec<Document>> {
let mut stmt = self.conn.prepare(
"SELECT d.id, d.content, d.metadata, e.embedding
FROM documents d
JOIN embeddings e ON d.id = e.document_id
ORDER BY d.created_at DESC
LIMIT ?1"
)?;
let docs = stmt.query_map(params![limit], |row| {
let id: String = row.get(0)?;
let content: String = row.get(1)?;
let metadata: String = row.get(2)?;
let embedding_blob: Vec<u8> = row.get(3)?;
// Convert blob back to f32 vector
let embedding: Vec<f32> = embedding_blob
.chunks(4)
.map(|chunk| {
let bytes: [u8; 4] = chunk.try_into().unwrap_or([0; 4]);
f32::from_le_bytes(bytes)
})
.collect();
Ok(Document {
id,
content,
metadata: serde_json::from_str(&metadata).unwrap_or_default(),
embedding,
})
})?;
let mut results: Vec<Document> = docs.filter_map(|r| r.ok()).collect();
// Sort by cosine similarity
results.sort_by(|a, b| {
let sim_a = cosine_similarity(query_embedding, &a.embedding);
let sim_b = cosine_similarity(query_embedding, &b.embedding);
sim_b.partial_cmp(&sim_a).unwrap_or(std::cmp::Ordering::Equal)
});
Ok(results)
}
/// Get document by ID
pub fn get_document(&self, id: &str) -> Result<Option<Document>> {
let mut stmt = self.conn.prepare(
"SELECT d.id, d.content, d.metadata, e.embedding
FROM documents d
JOIN embeddings e ON d.id = e.document_id
WHERE d.id = ?1"
)?;
let doc = stmt.query_row(params![id], |row| {
let id: String = row.get(0)?;
let content: String = row.get(1)?;
let metadata: String = row.get(2)?;
let embedding_blob: Vec<u8> = row.get(3)?;
let embedding: Vec<f32> = embedding_blob
.chunks(4)
.map(|chunk| {
let bytes: [u8; 4] = chunk.try_into().unwrap_or([0; 4]);
f32::from_le_bytes(bytes)
})
.collect();
Ok(Document {
id,
content,
metadata: serde_json::from_str(&metadata).unwrap_or_default(),
embedding,
})
}).ok();
Ok(doc.ok().flatten())
}
/// Delete document
pub fn delete_document(&self, id: &str) -> Result<()> {
self.conn.execute(
"DELETE FROM documents WHERE id = ?1",
params![id],
)?;
self.conn.execute(
"DELETE FROM embeddings WHERE document_id = ?1",
params![id],
)?;
Ok(())
}
/// Get document count
pub fn count(&self) -> Result<usize> {
let count: usize = self.conn.query_row(
"SELECT COUNT(*) FROM documents",
[],
|row| row.get(0),
)?;
Ok(count)
}
}
/// Calculate cosine similarity between two vectors
fn cosine_similarity(a: &[f32], b: &[f32]) -> f32 {
let dot: f32 = a.iter().zip(b.iter()).map(|(x, y)| x * y).sum();
let norm_a: f32 = a.iter().map(|x| x * x).sum::<f32>().sqrt();
let norm_b: f32 = b.iter().map(|x| x * x).sum::<f32>().sqrt();
if norm_a == 0.0 || norm_b == 0.0 {
0.0
} else {
dot / (norm_a * norm_b)
}
}
/// Simple embedding function (placeholder - in production, use real embeddings)
pub fn simple_embed(text: &str) -> Vec<f32> {
// Simple hash-based embedding (NOT production quality!)
// In production, use a real embedding model via Rig
let mut embedding = vec![0.0; 384]; // 384-dimensional embedding
for (i, byte) in text.bytes().enumerate() {
embedding[i % 384] += byte as f32 / 255.0;
}
// Normalize
let norm: f32 = embedding.iter().map(|x| x * x).sum::<f32>().sqrt();
if norm > 0.0 {
for x in embedding.iter_mut() {
*x /= norm;
}
}
embedding
}

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/**
* Rig Service Client for QwenClaw
*
* TypeScript client for communicating with the Rig AI agent service
*/
export interface RigConfig {
host: string;
port: number;
}
export interface AgentConfig {
name: string;
preamble: string;
model?: string;
provider?: string;
temperature?: number;
}
export interface Tool {
name: string;
description: string;
parameters: Record<string, unknown>;
category: string;
}
export interface Document {
id: string;
content: string;
metadata: Record<string, unknown>;
}
export class RigClient {
private baseUrl: string;
constructor(config: RigConfig) {
this.baseUrl = `http://${config.host}:${config.port}`;
}
// Health check
async health(): Promise<boolean> {
try {
const res = await fetch(`${this.baseUrl}/health`);
const data = await res.json();
return data.status === "ok";
} catch {
return false;
}
}
// ========== Agent Methods ==========
async createAgent(config: AgentConfig): Promise<string> {
const res = await fetch(`${this.baseUrl}/api/agents`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(config),
});
if (!res.ok) {
throw new Error(`Failed to create agent: ${res.statusText}`);
}
const data = await res.json();
return data.session_id;
}
async listAgents(): Promise<Array<{ id: string; name: string; model: string }>> {
const res = await fetch(`${this.baseUrl}/api/agents`);
if (!res.ok) {
throw new Error(`Failed to list agents: ${res.statusText}`);
}
const data = await res.json();
return data.agents;
}
async executePrompt(sessionId: string, prompt: string): Promise<string> {
const res = await fetch(`${this.baseUrl}/api/agents/${sessionId}/prompt`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ prompt }),
});
if (!res.ok) {
throw new Error(`Failed to execute prompt: ${res.statusText}`);
}
const data = await res.json();
return data.response;
}
async getAgent(sessionId: string): Promise<AgentConfig & { id: string }> {
const res = await fetch(`${this.baseUrl}/api/agents/${sessionId}`);
if (!res.ok) {
throw new Error(`Failed to get agent: ${res.statusText}`);
}
const data = await res.json();
return data.agent;
}
async deleteAgent(sessionId: string): Promise<void> {
const res = await fetch(`${this.baseUrl}/api/agents/${sessionId}`, {
method: "DELETE",
});
if (!res.ok) {
throw new Error(`Failed to delete agent: ${res.statusText}`);
}
}
// ========== Council Methods ==========
async createCouncil(
name: string,
agents: AgentConfig[]
): Promise<string> {
const res = await fetch(`${this.baseUrl}/api/councils`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ name, agents }),
});
if (!res.ok) {
throw new Error(`Failed to create council: ${res.statusText}`);
}
const data = await res.json();
return data.council_id;
}
async listCouncils(): Promise<Array<{ id: string; name: string; agents: Array<{ id: string; name: string }> }>> {
const res = await fetch(`${this.baseUrl}/api/councils`);
if (!res.ok) {
throw new Error(`Failed to list councils: ${res.statusText}`);
}
const data = await res.json();
return data.councils;
}
async executeCouncil(councilId: string, task: string): Promise<string> {
const res = await fetch(`${this.baseUrl}/api/councils/${councilId}/execute`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ task }),
});
if (!res.ok) {
throw new Error(`Failed to execute council: ${res.statusText}`);
}
const data = await res.json();
return data.response;
}
// ========== Tool Methods ==========
async listTools(): Promise<Tool[]> {
const res = await fetch(`${this.baseUrl}/api/tools`);
if (!res.ok) {
throw new Error(`Failed to list tools: ${res.statusText}`);
}
const data = await res.json();
return data.tools;
}
async searchTools(query: string, limit = 10): Promise<Tool[]> {
const res = await fetch(`${this.baseUrl}/api/tools/search`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ query, limit }),
});
if (!res.ok) {
throw new Error(`Failed to search tools: ${res.statusText}`);
}
const data = await res.json();
return data.tools;
}
// ========== Document Methods ==========
async addDocument(content: string, metadata?: Record<string, unknown>): Promise<string> {
const res = await fetch(`${this.baseUrl}/api/documents`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ content, metadata }),
});
if (!res.ok) {
throw new Error(`Failed to add document: ${res.statusText}`);
}
const data = await res.json();
return data.id;
}
async searchDocuments(query: string, limit = 10): Promise<Document[]> {
const res = await fetch(`${this.baseUrl}/api/documents/search`, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify({ query, limit }),
});
if (!res.ok) {
throw new Error(`Failed to search documents: ${res.statusText}`);
}
const data = await res.json();
return data.documents;
}
async getDocument(id: string): Promise<Document> {
const res = await fetch(`${this.baseUrl}/api/documents/${id}`);
if (!res.ok) {
throw new Error(`Failed to get document: ${res.statusText}`);
}
const data = await res.json();
return data.document;
}
async deleteDocument(id: string): Promise<void> {
const res = await fetch(`${this.baseUrl}/api/documents/${id}`, {
method: "DELETE",
});
if (!res.ok) {
throw new Error(`Failed to delete document: ${res.statusText}`);
}
}
}
// Export default client instance
export default RigClient;

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/**
* Rig Integration Module for QwenClaw
*
* Provides seamless integration between QwenClaw and Rig AI agent service
*/
import { RigClient } from "./client";
let rigClient: RigClient | null = null;
/**
* Initialize Rig client
*/
export function initRigClient(host = "127.0.0.1", port = 8080): RigClient {
rigClient = new RigClient({ host, port });
return rigClient;
}
/**
* Get Rig client instance
*/
export function getRigClient(): RigClient | null {
return rigClient;
}
/**
* Check if Rig service is available
*/
export async function isRigAvailable(): Promise<boolean> {
if (!rigClient) return false;
return await rigClient.health();
}
/**
* Execute a prompt using Rig agent
*/
export async function executeWithRig(
sessionId: string,
prompt: string
): Promise<string> {
if (!rigClient) {
throw new Error("Rig client not initialized. Call initRigClient() first.");
}
return await rigClient.executePrompt(sessionId, prompt);
}
/**
* Create a multi-agent council for complex tasks
*/
export async function createCouncil(
name: string,
agentConfigs: Array<{ name: string; preamble: string; model?: string }>
): Promise<string> {
if (!rigClient) {
throw new Error("Rig client not initialized. Call initRigClient() first.");
}
return await rigClient.createCouncil(name, agentConfigs);
}
/**
* Execute task with agent council
*/
export async function executeWithCouncil(
councilId: string,
task: string
): Promise<string> {
if (!rigClient) {
throw new Error("Rig client not initialized. Call initRigClient() first.");
}
return await rigClient.executeCouncil(councilId, task);
}
/**
* Search for relevant documents using RAG
*/
export async function searchDocuments(
query: string,
limit = 5
): Promise<Array<{ id: string; content: string; metadata: Record<string, unknown> }>> {
if (!rigClient) {
throw new Error("Rig client not initialized. Call initRigClient() first.");
}
return await rigClient.searchDocuments(query, limit);
}
/**
* Add document to vector store for RAG
*/
export async function addDocumentToStore(
content: string,
metadata?: Record<string, unknown>
): Promise<string> {
if (!rigClient) {
throw new Error("Rig client not initialized. Call initRigClient() first.");
}
return await rigClient.addDocument(content, metadata);
}
/**
* Search for relevant tools
*/
export async function searchTools(
query: string,
limit = 10
): Promise<Array<{ name: string; description: string; category: string }>> {
if (!rigClient) {
throw new Error("Rig client not initialized. Call initRigClient() first.");
}
return await rigClient.searchTools(query, limit);
}