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skills/pi-pathfinder/assets/README.md

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+# Assets
+
+Bundled resources for pi-pathfinder skill
+
+- [ ] example_plugin_analysis.json: Example JSON output from the plugin_analyzer.py script, showcasing the structure and content of the plugin analysis.
+- [ ] skill_adaptation_template.py: Template for adapting skills from one plugin to another, including placeholders for input parameters, output variables, and adaptation logic.
+- [ ] plugin_selection_rules.yaml: YAML file containing rules for selecting the best plugin for a given task, based on keywords, capabilities, and user preferences.

skills/pi-pathfinder/assets/example_plugin_analysis.json

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+{
+  "_comment": "Example JSON output for plugin analysis by PI Pathfinder",
+  "query": "Summarize the key findings from the latest IPCC report on climate change and suggest potential mitigation strategies.",
+  "selected_plugin": {
+    "name": "Research Assistant",
+    "description": "A powerful research tool for accessing and summarizing information from various online sources.",
+    "capabilities": [
+      "Web scraping",
+      "Document summarization",
+      "Academic paper retrieval",
+      "Fact checking",
+      "Trend analysis"
+    ],
+    "reasoning": "This plugin is best suited for the task because it can access the IPCC report online, summarize its findings, and identify relevant mitigation strategies from reputable sources.",
+    "confidence_score": 0.95
+  },
+  "extracted_skills": [
+    {
+      "skill_name": "Document Summarization",
+      "skill_description": "Condenses large documents into concise summaries highlighting key information.",
+      "parameters": {
+        "document_url": "URL of the IPCC report",
+        "summary_length": "medium",
+        "focus_areas": ["key findings", "mitigation strategies"]
+      },
+      "implementation_details": "Utilizes advanced NLP techniques to identify and extract the most important information, including sentence scoring and topic modeling.",
+      "success_probability": 0.9
+    },
+    {
+      "skill_name": "Web Scraping",
+      "skill_description": "Extracts data from web pages, including text, tables, and images.",
+      "parameters": {
+        "url": "URL of the IPCC report website",
+        "elements_to_extract": ["text", "tables"]
+      },
+      "implementation_details": "Uses a robust web scraping library to handle various website structures and anti-scraping measures.",
+      "success_probability": 0.98
+    }
+  ],
+  "execution_plan": [
+    {
+      "step": 1,
+      "action": "Use Web Scraping to extract the text content from the IPCC report webpage.",
+      "plugin_skill": "Web Scraping",
+      "expected_outcome": "Successful extraction of the IPCC report text."
+    },
+    {
+      "step": 2,
+      "action": "Use Document Summarization to generate a summary of the extracted text, focusing on key findings and mitigation strategies.",
+      "plugin_skill": "Document Summarization",
+      "expected_outcome": "A concise summary of the IPCC report's key findings and mitigation strategies."
+    },
+     {
+      "step": 3,
+      "action": "Return the generated summary to the user.",
+      "plugin_skill": null,
+      "expected_outcome": "User receives a helpful summary of the IPCC report."
+    }
+  ],
+  "alternative_plugins": [
+    {
+      "name": "Web Search",
+      "description": "Performs web searches and retrieves relevant snippets.",
+      "suitability_score": 0.7,
+      "reason": "Useful for finding general information, but less effective for in-depth document analysis."
+    },
+    {
+      "name": "Document Reader",
+      "description": "Reads and analyzes local documents.",
+      "suitability_score": 0.3,
+      "reason": "Not applicable as the IPCC report is likely online."
+    }
+  ],
+  "overall_assessment": {
+    "success_likelihood": 0.9,
+    "potential_issues": [
+      "Website may have anti-scraping measures.",
+      "Summarization may miss subtle nuances in the report."
+    ],
+    "recommendations": "Review the generated summary for accuracy and consult the original report for a complete understanding."
+  }
+}

skills/pi-pathfinder/assets/plugin_selection_rules.yaml

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+# plugin_selection_rules.yaml
+# Configuration file for PI Pathfinder plugin selection logic.
+
+# Global settings for plugin selection behavior.
+global:
+  # Default preference for prioritizing plugins: "speed", "accuracy", "cost"
+  default_priority: "accuracy"
+  # Maximum number of plugins to consider for a given task.
+  max_plugins_considered: 10
+  # Minimum relevance score for a plugin to be considered. (0.0 - 1.0)
+  minimum_relevance_score: 0.2
+  # Enable/Disable verbose logging for debugging.
+  verbose_logging: false
+
+# Rules for selecting plugins based on keywords and task descriptions.
+keyword_rules:
+  # Define keywords and their associated plugin preferences.
+  # The higher the weight, the more preferred the plugin is for that keyword.
+  - keywords: ["image", "generate", "picture", "visual"]
+    plugin_preferences:
+      "DALL-E": 0.9  # Example: Prefer DALL-E for image generation
+      "Stable Diffusion": 0.8
+      "REPLACE_ME_IMAGE_PLUGIN": 0.5
+  - keywords: ["translate", "language", "multilingual"]
+    plugin_preferences:
+      "Google Translate": 0.95
+      "DeepL Translator": 0.9
+      "REPLACE_ME_TRANSLATION_PLUGIN": 0.6
+  - keywords: ["code", "programming", "algorithm", "debug"]
+    plugin_preferences:
+      "Code Interpreter": 0.9
+      "GitHub Copilot": 0.85
+      "REPLACE_ME_CODE_PLUGIN": 0.7
+  - keywords: ["data analysis", "statistics", "spreadsheet"]
+    plugin_preferences:
+      "Wolfram Alpha": 0.9
+      "Excel Online": 0.8
+      "REPLACE_ME_DATA_PLUGIN": 0.6
+
+# Rules for selecting plugins based on their stated capabilities.
+capability_rules:
+  # Define capability patterns and their associated plugin preferences.
+  # These rules are based on the plugin's description and advertised skills.
+  - capability_pattern: "Generates realistic images from text prompts."
+    plugin_preferences:
+      "DALL-E": 1.0
+      "Stable Diffusion": 0.9
+  - capability_pattern: "Translates text between multiple languages."
+    plugin_preferences:
+      "Google Translate": 1.0
+      "DeepL Translator": 0.95
+  - capability_pattern: "Executes code and analyzes data."
+    plugin_preferences:
+      "Code Interpreter": 1.0
+      "Wolfram Alpha": 0.8
+
+# Rules for handling user preferences.
+user_preferences:
+  # Default user preferences (can be overridden by user-specific settings).
+  defaults:
+    priority: "accuracy"  # Default priority: "speed", "accuracy", "cost"
+    preferred_plugins: [] # List of plugins the user prefers (e.g., ["DALL-E", "Google Translate"])
+    excluded_plugins: []  # List of plugins the user wants to avoid (e.g., ["Expensive Plugin"])
+
+  # Example: User-specific preferences (loaded from a user profile, for example).
+  user_id_123:
+    priority: "speed"
+    preferred_plugins: ["Google Translate"]
+    excluded_plugins: ["REPLACE_ME_EXPENSIVE_PLUGIN"]
+
+# Fallback plugin to use if no other plugin matches the criteria.
+fallback_plugin: "Web Search"
+
+# Advanced configuration (for expert users only).
+advanced:
+  # Weighting factors for combining different rule types.
+  keyword_weight: 0.6
+  capability_weight: 0.4
+  user_preference_weight: 0.2
+
+  # Threshold for considering a plugin "suitable" after applying all rules.
+  suitability_threshold: 0.7
+
+  # Plugin specific configurations (example).
+  plugin_configurations:
+    "DALL-E":
+      api_key: "REPLACE_ME_DALL_E_API_KEY"
+      image_size: "1024x1024"
+    "Google Translate":
+      target_language: "en" # Default target language

skills/pi-pathfinder/assets/skill_adaptation_template.py

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+#!/usr/bin/env python3
+
+"""
+Template for adapting skills from one plugin to another.
+
+This module provides a template for adapting skills from a source plugin
+to a target plugin. It includes placeholders for input parameters,
+output variables, and adaptation logic.
+
+"""
+
+import logging
+
+# Configure logging
+logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
+
+
+def adapt_skill(source_plugin_skills, target_plugin_requirements, user_query):
+    """
+    Adapt skills from the source plugin to meet the target plugin's requirements.
+
+    Args:
+        source_plugin_skills (dict): A dictionary representing the skills
+                                      provided by the source plugin.
+        target_plugin_requirements (dict): A dictionary representing the
+                                            requirements of the target plugin.
+        user_query (str): The original user query.
+
+    Returns:
+        dict: A dictionary containing the adapted input parameters for the
+              target plugin.  Returns None if adaptation is not possible.
+
+    Raises:
+        TypeError: If input types are incorrect.
+        ValueError: If input values are invalid.
+        Exception: For any other unexpected error during adaptation.
+    """
+
+    try:
+        if not isinstance(source_plugin_skills, dict):
+            raise TypeError("source_plugin_skills must be a dictionary.")
+        if not isinstance(target_plugin_requirements, dict):
+            raise TypeError("target_plugin_requirements must be a dictionary.")
+        if not isinstance(user_query, str):
+            raise TypeError("user_query must be a string.")
+
+        # Example adaptation logic (replace with your actual adaptation)
+        adapted_input = {}
+
+        # Check if the target plugin requires a 'text' input and adapt from user query
+        if "text" in target_plugin_requirements:
+            adapted_input["text"] = user_query
+
+        # Check if the source plugin can provide a 'summary' and the target plugin requires it
+        if "summary" in target_plugin_requirements and "summarize" in source_plugin_skills:
+            # Assuming source_plugin_skills["summarize"] is a function that returns a summary
+            # This is a placeholder, replace with actual logic using the source plugin's skills
+            try:
+                # Placeholder:  Replace with actual call to source plugin's skill
+                # summary = source_plugin_skills["summarize"](user_query)
+                summary = "This is a placeholder summary." # Simulate a summary
+                adapted_input["summary"] = summary
+            except Exception as e:
+                logging.error(f"Error summarizing using source plugin: {e}")
+                return None  # Adaptation failed
+
+        # Check if adaptation logic was successful
+        if not adapted_input:
+            logging.warning("No adaptation logic applied. Adaptation may not be effective.")
+
+        return adapted_input
+
+    except TypeError as e:
+        logging.error(f"Type error during skill adaptation: {e}")
+        raise
+    except ValueError as e:
+        logging.error(f"Value error during skill adaptation: {e}")
+        raise
+    except Exception as e:
+        logging.exception("Unexpected error during skill adaptation.")
+        raise
+
+
+def post_process_output(target_plugin_output):
+    """
+    Post-processes the output from the target plugin.
+
+    Args:
+        target_plugin_output (any): The raw output from the target plugin.
+
+    Returns:
+        str: A human-readable string representing the processed output.
+
+    Raises:
+        TypeError: If input type is incorrect.
+        Exception: For any other error during post-processing.
+    """
+    try:
+        if target_plugin_output is None:
+            return "No output from target plugin."
+
+        # Simple example: Convert to string
+        processed_output = str(target_plugin_output)
+
+        return processed_output
+
+    except TypeError as e:
+        logging.error(f"Type error during output post-processing: {e}")
+        raise
+    except Exception as e:
+        logging.exception("Unexpected error during output post-processing.")
+        raise
+
+
+if __name__ == "__main__":
+    # Example Usage
+    source_plugin_skills = {
+        "summarize": lambda x: f"Summary of: {x}"  # Placeholder summarize function
+    }
+    target_plugin_requirements = {
+        "text": "string",
+        "summary": "string"
+    }
+    user_query = "This is a long document that needs to be summarized."
+
+    try:
+        adapted_input = adapt_skill(source_plugin_skills, target_plugin_requirements, user_query)
+
+        if adapted_input:
+            print("Adapted Input:", adapted_input)
+
+            # Simulate target plugin output
+            target_plugin_output = f"Target plugin processed: {adapted_input}"
+
+            processed_output = post_process_output(target_plugin_output)
+            print("Processed Output:", processed_output)
+        else:
+            print("Skill adaptation failed.")
+
+    except Exception as e:
+        print(f"An error occurred: {e}")