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Merge pull request #65 from njfio/agentic-transformation
🔐 Advanced Security + Self-Reflection System + Complete Test Resolution
2 parents 15cb046 + b3f3a95 commit a4153b9

37 files changed

+5660
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lines changed

Cargo.toml

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@@ -30,6 +30,7 @@ chrono = { workspace = true, features = ["serde"] }
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uuid = { workspace = true, features = ["v4", "serde"] }
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serde_json = { workspace = true }
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tempfile = { workspace = true }
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async-trait.workspace = true
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crossterm = "0.27"
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rand = "0.8"
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@@ -58,6 +59,8 @@ tracing-subscriber = "~0.3.18"
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tracing = "~0.1.40"
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# Async runtime - pin to specific minor version for stability
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tokio = { version = "1.40.0", features = ["macros", "rt-multi-thread", "net", "fs", "io-util", "time", "sync"] }
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# Async trait support
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async-trait = "0.1.83"
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# Error handling - allow minor updates within 1.x
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anyhow = { version = "~1.0.89" }
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# Enum utilities - allow minor updates within 0.26.x
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regex = "~1.10.6"
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# YAML serialization - allow minor updates within 0.9.x
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serde_yaml = "~0.9.34"
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# Async traits - allow minor updates within 0.1.x
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async-trait = "~0.1.83"
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# Logging facade - allow minor updates within 0.4.x
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log = "~0.4.22"
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# Unicode text processing - allow minor updates within 1.x
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sled = "0.34.7"
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# Cryptographic hashing - allow minor updates within 0.10.x
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sha2 = "~0.10.8"
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# Ed25519 digital signatures - pin to exact version for security
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ed25519-dalek = "2.1.1"
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# MCP protocol implementation - pin to exact version for stability
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rmcp = { version = "0.1.0", features = ["server", "client", "transport-async-rw", "transport-io", "transport-child-process"] }
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README.md

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@@ -27,6 +27,8 @@ A modern, secure, and modular Rust-based command-line interface for interacting
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- **Workflow Engine**: DAG-based execution with proper timing and retry logic
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- **String Replace Editor**: Surgical file editing with comprehensive test coverage
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- **MCP Integration**: Full Model Context Protocol client and server support
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- **Self-Reflection Engine**: Advanced learning and strategy adjustment capabilities
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- **State Management**: Execution context persistence with checkpoint/restore functionality
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### 📊 **Quality & Testing**
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@@ -62,6 +64,15 @@ A modern, secure, and modular Rust-based command-line interface for interacting
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- **Memory System**: SQLite-based persistent memory with performance optimization
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- **Security Sandboxing**: Rate limiting, input validation, and secure execution environment
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### 🧠 **Self-Reflection & Learning System**
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- **Multi-Type Reflection**: Routine, triggered, deep, meta, and crisis reflection modes
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- **Strategy Adjustment**: Automatic strategy optimization based on performance analysis
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- **Learning Retention**: Experience-based learning with configurable retention periods
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- **Pattern Recognition**: Success and failure pattern identification and application
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- **Performance Metrics**: Comprehensive performance tracking and confidence assessment
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- **State Persistence**: Execution context and learning experience persistence
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### 🔒 **Security & Quality Features**
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- **Comprehensive Input Validation**: Protection against injection attacks and malicious input
@@ -114,14 +125,18 @@ fluent openai "Complex analysis task" --cache
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#### Agent Commands
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```bash
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# Interactive agent session
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fluent agent --interactive
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# Interactive agent session (requires API keys)
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fluent openai agent
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# Agentic mode with specific goal
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fluent agent --agentic --goal "Build a simple web server" --max-iterations 10
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# Agentic mode with specific goal (requires API keys)
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fluent openai --agentic --goal "Build a simple web server" --max-iterations 10 --enable-tools
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# Agent with tools enabled
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fluent agent --tools --config agent_config.json
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# Agent with MCP capabilities (requires API keys)
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fluent agent-mcp --engine openai --task "Analyze codebase" --mcp-servers "filesystem:mcp-server-filesystem"
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# Note: Set appropriate API keys before running:
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# export OPENAI_API_KEY="your-api-key-here"
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# export ANTHROPIC_API_KEY="your-api-key-here"
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```
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#### Pipeline Commands
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prompt: "Analyze this code and suggest improvements: {{previous_output}}"
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```
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### Self-Reflection Configuration
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Configure the agent's self-reflection and learning capabilities:
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```yaml
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# reflection_config.yaml
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reflection:
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reflection_frequency: 5 # Reflect every 5 iterations
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deep_reflection_frequency: 20 # Deep reflection every 20 reflections
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learning_retention_days: 30 # Keep learning experiences for 30 days
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confidence_threshold: 0.6 # Trigger reflection if confidence < 0.6
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performance_threshold: 0.7 # Trigger adjustment if performance < 0.7
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enable_meta_reflection: true # Enable reflection on reflection process
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strategy_adjustment_sensitivity: 0.8 # How readily to adjust strategy (0.0-1.0)
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state_management:
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state_directory: "./agent_state" # Directory for state persistence
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auto_save_enabled: true # Enable automatic state saving
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auto_save_interval_seconds: 30 # Save state every 30 seconds
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max_checkpoints: 50 # Maximum checkpoints to retain
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backup_retention_days: 7 # Keep backups for 7 days
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```
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### Agent Configuration
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Complete agent configuration with all capabilities:
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```yaml
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# agent_config.yaml
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agent:
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max_iterations: 20
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enable_tools: true
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memory_enabled: true
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reflection_enabled: true
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reasoning:
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engine: "openai"
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model: "gpt-4"
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temperature: 0.7
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tools:
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string_replace_editor:
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allowed_paths: ["./src", "./docs", "./examples"]
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create_backups: true
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case_sensitive: false
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max_file_size: 10485760 # 10MB
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filesystem:
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allowed_paths: ["./"]
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max_file_size: 10485760
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shell:
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allowed_commands: ["cargo", "git", "ls", "cat"]
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timeout_seconds: 30
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```
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## 🤖 Experimental Features
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### Agent Mode
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Interactive agent sessions with basic memory and tool access:
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```bash
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# Start an interactive agent session
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# Start an interactive agent session (requires OPENAI_API_KEY)
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fluent openai agent
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# Agent with specific goal (experimental)
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# Agent with specific goal (requires OPENAI_API_KEY)
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fluent openai --agentic --goal "Analyze project structure" --enable-tools
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```
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- **Advanced Tool System**: ✅ Production-ready file operations and code analysis
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- **String Replace Editor**: ✅ Surgical file editing with precision targeting
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- **Memory System**: ✅ SQLite-based persistent memory with optimization
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- **Self-Reflection Engine**: ✅ Advanced learning and strategy adjustment
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- **State Management**: ✅ Execution context persistence with checkpoint/restore
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### Planned Features
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- Enhanced agent capabilities
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- Enhanced multi-modal capabilities
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- Expanded tool ecosystem
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- Advanced MCP client/server features
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- Improved memory and learning systems
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- Advanced workflow orchestration
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- Real-time collaboration features
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- Plugin system for custom tools
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## 🧪 Development
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# Run integration tests
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cargo test --test integration
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# Run reflection system tests
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cargo test -p fluent-agent reflection
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```
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### Running Examples
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```bash
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# Run the self-reflection and strategy adjustment demo
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cargo run --example reflection_demo
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# Run the state management demo
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cargo run --example state_management_demo
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# Run the string replace editor demo
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cargo run --example string_replace_demo
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# Run other available examples
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cargo run --example real_agentic_demo
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cargo run --example working_agentic_demo
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```
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### Quality Assurance Tools

agent_config.json

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{
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"agent": {
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"reasoning_engine": "sonnet3.5",
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"action_engine": "gpt-4o",
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"reflection_engine": "gemini-flash",
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"reasoning_engine": "anthropic",
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"action_engine": "anthropic",
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"reflection_engine": "anthropic",
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"memory_database": "sqlite://./agent_memory.db",
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"tools": {
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"file_operations": true,
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"cargo clippy"
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]
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},
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"config_path": "./config.json",
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"config_path": "./anthropic_config.json",
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"max_iterations": 50,
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"timeout_seconds": 1800
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}

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