o-reasonable - npm Package Compare versions

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0.0.6

0.0.7

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package.json

		{
		"name": "o-reasonable",
		"version": "0.0.6",
		"version": "0.0.7",
		"description": "O-Reasonable is a lightweight reasoning agent designed to mimic logical planning and problem-solving capabilities using cost-effective OpenAI models. It generates step-by-step plans, executes them sequentially, and synthesizes a final answer, making it a practical tool for structured reasoning tasks.",
		@@ -5,0 +5,0 @@ "type": "module",

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README.md

		@@ -61,9 +61,63 @@ # O-Reasonable 🧠
		interface OReasonableConfig {
		model?: string; // OpenAI model to use (default: "gpt-4o-mini")
		apiKey?: string; // Optional API key override
		baseURL?: string; // Custom base URL for OpenAI-compatible APIs
		enableLogs?: boolean; // Enable/disable console logs (default: false)
		model?: string; // OpenAI model to use (default: "gpt-4o-mini")
		apiKey?: string; // Optional API key override
		baseURL?: string; // Custom base URL for OpenAI-compatible APIs
		enableLogs?: boolean; // Enable/disable console logs (default: false)
		enableReflection?: boolean; // Enable step validation and reflection (default: true)
		minConfidence?: number; // Minimum confidence threshold for steps (default: 0.6)
		maxRetries?: number; // Maximum retries for low-confidence steps (default: 1)
		}
		```

		## Enhanced Reasoning Features

		O-Reasonable now includes advanced reasoning capabilities that significantly improve the quality and reliability of the generated responses:

		### 🔍 Step Validation & Reflection
		Each reasoning step is automatically validated for:
		- Confidence: How certain the AI is about the step's accuracy
		- Relevance: How well the step contributes to solving the original task
		- Logical soundness: Whether the reasoning is well-founded

		### 🧠 Smart Context Management
		- Context Summarization: Automatically summarizes previous steps to maintain focus
		- Conversation Threading: Builds coherent conversation history between steps
		- Relevance Filtering: Keeps only the most important information for subsequent steps

		### 🔄 Adaptive Execution
		- Quality Thresholds: Automatically retries steps that don't meet confidence requirements
		- Enhanced Planning: Uses proven reasoning frameworks (analytical, comparative, causal, creative)
		- Self-Evaluation: Reflects on the overall reasoning process quality

		### 📊 Confidence Tracking
		- Individual step confidence scores
		- Overall reasoning confidence
		- Quality metrics for each step

		```typescript
		// Enhanced reasoning with validation
		const result = await runAgent("Analyze the impact of remote work on productivity", {
		enableReflection: true, // Enable step validation and reflection
		minConfidence: 0.7, // Require high confidence (0.0-1.0)
		maxRetries: 2, // Retry low-confidence steps up to 2 times
		enableLogs: true
		});

		// Access enhanced results
		console.log(result.steps); // Array of StepResult objects with confidence scores
		console.log(result.overallConfidence); // Overall reasoning confidence (0.0-1.0)
		console.log(result.reflections); // Self-evaluation of reasoning quality
		```

		### Step Result Structure
		```typescript
		interface StepResult {
		content: string; // The step's reasoning content
		confidence: number; // Confidence score (0.0-1.0)
		relevance: number; // Relevance to original task (0.0-1.0)
		isValid: boolean; // Whether the step passed validation
		reasoning: string; // Explanation of the validation
		}
		```

		## Using OpenAI-Compatible APIs
		@@ -116,12 +170,72 @@

		The `runAgent` function returns a promise that resolves to an `AgentResult`:
		The `runAgent` function returns a promise that resolves to an enhanced `AgentResult`:

		```typescript
		interface AgentResult {
		steps: string[]; // Results from each reasoning step
		finalQuestion: string; // The final question that was asked
		finalAnswer: string; // The synthesized final answer
		steps: StepResult[]; // Enhanced step results with confidence scores
		finalQuestion: string; // The final question that was asked
		finalAnswer: string; // The synthesized final answer
		overallConfidence: number; // Overall confidence in the reasoning (0.0-1.0)
		reflections: string[]; // Self-evaluation and reflection insights
		}
		```

		## Examples

		### Quick Start
		```bash
		# Try the quick example
		node quickstart.js
		```

		### Comprehensive Examples
		```bash
		# Run all examples (JavaScript)
		node example.js

		# Run TypeScript examples (requires ts-node)
		npx ts-node example.ts

		# Try different configurations
		node examples/configurations.js
		```

		### Basic Usage
		```typescript
		import { runAgent } from 'o-reasonable';

		const result = await runAgent("What are the key factors in choosing a programming language?");
		console.log(result.finalAnswer);
		console.log(`Confidence: ${result.overallConfidence.toFixed(2)}`);
		```

		### Advanced Reasoning Configuration
		```typescript
		// High-quality reasoning with strict validation
		const result = await runAgent("Design a sustainable urban transportation system", {
		enableReflection: true,
		minConfidence: 0.8, // Require very high confidence
		maxRetries: 3, // Allow more retries for quality
		enableLogs: true,
		model: "gpt-4"
		});

		// Analyze step quality
		result.steps.forEach((step, i) => {
		console.log(`Step ${i+1}: Confidence ${step.confidence.toFixed(2)}, Relevance ${step.relevance.toFixed(2)}`);
		});
		```

		### Debugging and Analysis
		```typescript
		const result = await runAgent("Solve this complex business problem", {
		enableLogs: true, // See detailed reasoning process
		enableReflection: true // Get self-evaluation insights
		});

		// Review the reasoning process
		console.log("Reflections on reasoning quality:");
		result.reflections.forEach(reflection => console.log(reflection));
		```

		## Development
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dist/index.cjs.js

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dist/index.es.js

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