Merge pull request #30 from Andrei-Constantin-Programmer/revert-28-IBM-21-Explainer_Agent

Revert "Ibm 21 explainer agent"

Author: avimallick

AntiPattern_Remediator/main.py

@@ -1,7 +1,9 @@
+
 """
 Main entry point - Legacy Code Migration Tool
 """
 from config.settings import initialize_settings
+# from scripts import seed_database
 from dotenv import load_dotenv
 load_dotenv()
 from colorama import Fore, Style
@@ -10,35 +12,11 @@
 from full_repo_workflow import run_full_repo_workflow
 
 
-
-def main():
-    """Main function: Run antipattern analysis"""
-
-    # Let user select provider
-    print("Available providers: 1) ollama  2) ibm  3) vllm")
-    choice = input("Select provider (1-3): ").strip()
-
-    provider_map = {"1": "ollama", "2": "ibm", "3": "vllm"}
-    provider = provider_map.get(choice, "ollama")  # default to ollama
-
-    # Let us choose which DB to interact with
-    print("Choose your trove: 1) ChromaDB (VectorDB) 2) TinyDB (DocumentDB)")
-    db_choice = input("Choose 1 or 2: ").strip()
-
-    # Initialize global settings with selected provider
-    settings = initialize_settings(provider)
-    print(Fore.GREEN + f"Using {settings.LLM_PROVIDER} with model {settings.LLM_MODEL}" + Style.RESET_ALL)
-
-    # Temporary Lazy Imports
-    from src.core.graph import CreateGraph
-    from src.data.database import VectorDBManager, TinyDBManager
-    from src.core.prompt import PromptManager
-    from scripts import seed_database
-
-    # Initialize PromptManager
-    print("Initializing PromptManager...")
-    prompt_manager = PromptManager()
-
+def run_code_snippet_workflow(settings, db_manager, prompt_manager, langgraph):
+    """Run the original workflow with a hardcoded Java code snippet."""
+    print(Fore.BLUE + "\n=== Code Snippet Analysis Workflow ===" + Style.RESET_ALL)
+    print("Analyzing the provided Java code snippet...")
+    
     # Example Java code
     legacy_code = """
     public class ApplicationManager {
@@ -77,8 +55,7 @@ def main():
         }
     }
     """
-
-    # Initial workflow state
+    
     initial_state = {
         "code": legacy_code,
         "context": None,
@@ -89,13 +66,59 @@ def main():
         "code_review_results": None,
         "code_review_times": 0,
         "msgs": [],
-        "answer": None,
-
-        # ExplainerAgent fields
-        "explanation_response_raw": None,
-        "explanation_json": None,
+        "answer": None
     }
 
+    final_state = langgraph.invoke(initial_state)
+
+    print(Fore.GREEN + f"\nAnalysis Complete!" + Style.RESET_ALL)
+    print(f"Final state keys: {list(final_state.keys())}")
+    print(f"Context retrieved: {'Yes' if final_state.get('context') else 'No'}")
+    print(f"Analysis completed: {'Yes' if final_state.get('antipatterns_scanner_results') else 'No'}")
+    print(f"Refactored code: {'Yes' if final_state.get('refactored_code') else 'No'}")
+    print(f"Code review results: {final_state.get('code_review_times')}")
+
+
+def main():
+    """Main function: Choose between code snippet analysis or full repository run"""
+
+    print(Fore.BLUE + "=== AntiPattern Remediator Tool ===" + Style.RESET_ALL)
+    print("Choose your analysis mode:")
+    print("1) Code Snippet Analysis - Analyze a sample Java code snippet")
+    print("2) Full Repository Run - Process files with 100% test coverage from JaCoCo results")
+    
+    # Let user choose analysis mode
+    mode_choice = input("\nSelect mode (1-2): ").strip()
+    
+    if mode_choice not in ["1", "2"]:
+        print(Fore.RED + "Invalid choice. Defaulting to Code Snippet Analysis." + Style.RESET_ALL)
+        mode_choice = "1"
+    
+    # Let user select provider
+    print("\nAvailable providers: 1) ollama  2) ibm  3) vllm")
+    choice = input("Select provider (1-3): ").strip()
+
+    provider_map = {"1": "ollama", "2": "ibm", "3": "vllm"}
+    provider = provider_map.get(choice, "ollama")  # default to ollama
+
+    # Let us choose which DB to interact with
+    print("Choose your trove: 1) ChromaDB (VectorDB) 2) TinyDB (DocumentDB)")
+    db_choice = input("Choose 1 or 2: ").strip()
+
+    # Initialize global settings with selected provider
+    settings = initialize_settings(provider)
+    print(Fore.GREEN + f"Using {settings.LLM_PROVIDER} with model {settings.LLM_MODEL}" + Style.RESET_ALL)
+
+    # Temporary Lazy Imports
+    from src.core.graph import CreateGraph
+    from src.data.database import VectorDBManager, TinyDBManager
+    from src.core.prompt import PromptManager
+    from scripts import seed_database
+
+    # Initialize PromptManager
+    print("Initializing PromptManager...")
+    prompt_manager = PromptManager()
+
     # Setup Database
     if db_choice == "2":
         print("Seeding TinyDB with AntiPattern Dataset")
@@ -110,22 +133,11 @@ def main():
     retriever = db_manager.as_retriever()
     langgraph = CreateGraph(db_manager, prompt_manager, retriever=retriever).workflow
 
-    # Final results summary
-    print(Fore.GREEN + f"\nAnalysis Complete!" + Style.RESET_ALL)
-    print(f"Final state keys: {list(final_state.keys())}")
-    print(f"Context retrieved: {'Yes' if final_state.get('context') else 'No'}")
-    print(f"Analysis completed: {'Yes' if final_state.get('antipatterns_scanner_results') else 'No'}")
-    print(f"Refactored code: {'Yes' if final_state.get('refactored_code') else 'No'}")
-    print(f"Code review results: {final_state.get('code_review_times')}")
-
-    # Show explanation from ExplainerAgent
-    if final_state.get("explanation_json"):
-        import json
-        print(Fore.CYAN + "\n=== Explanation (JSON) ===" + Style.RESET_ALL)
-        print(json.dumps(final_state["explanation_json"], indent=2, ensure_ascii=False))
+    # Run the selected workflow
+    if mode_choice == "1":
+        run_code_snippet_workflow(settings, db_manager, prompt_manager, langgraph)
     else:
-        print(Fore.RED + "\nNo explanation was generated." + Style.RESET_ALL)
-
+        run_full_repo_workflow(settings, db_manager, prompt_manager, langgraph)
 
 if __name__ == "__main__":
     main()

AntiPattern_Remediator/src/core/agents/__init__.py

@@ -7,12 +7,10 @@
 from .refactor_strategist import RefactorStrategist
 from .code_transformer import CodeTransformer
 from .code_reviewer import CodeReviewerAgent
-from .explainer import ExplainerAgent
 
 __all__ = [
     "AntipatternScanner", 
     "RefactorStrategist",
     "CodeTransformer",
-    "CodeReviewerAgent",
-    "ExplainerAgent"
+    "CodeReviewerAgent"
 ]

AntiPattern_Remediator/src/core/agents/explainer.py

@@ -14,7 +14,6 @@
 from ..agents import RefactorStrategist
 from ..agents import CodeTransformer
 from ..agents import CodeReviewerAgent
-from ..agents import ExplainerAgent
 
 # Imports for LangSmith tracing
 import os
@@ -63,7 +62,7 @@ def __init__(self, db_manager, prompt_manager: PromptManager, retriever=None, ll
         self.prompt_manager = prompt_manager
         self.conditional_edges = ConditionalEdges()
 
-        # assign the instance attribute before use
+        # ✅ assign the instance attribute before use
         self.retriever = retriever or self.db_manager.as_retriever()
 
         retriever_tool = create_retriever_tool(
@@ -79,13 +78,13 @@ def __init__(self, db_manager, prompt_manager: PromptManager, retriever=None, ll
             "strategist": RefactorStrategist(self.llm, self.prompt_manager, retriever=self.retriever),
             "transformer": CodeTransformer(self.llm, self.prompt_manager),
             "reviewer": CodeReviewerAgent(self.llm, self.prompt_manager),
-            "explainer": ExplainerAgent(self.llm, self.prompt_manager)
         }
 
         # Build the LangGraph workflow
         self.workflow = self._build_graph()
 
     def _build_graph(self):
+        """Build LangGraph workflow"""
         graph = StateGraph(AgentState)
 
         # Scanner: retrieve + analyze
@@ -105,10 +104,6 @@ def _build_graph(self):
         graph.add_node("review_code", self.agents["reviewer"].review_code)
         graph.add_node("display_code_review_results", self.agents["reviewer"].display_code_review_results)
 
-        # Explainer: final storytelling
-        graph.add_node("explain_antipattern", self.agents["explainer"].explain_antipattern)
-        graph.add_node("display_explanation", self.agents["explainer"].display_explanation)
-
         # Topology
         graph.set_entry_point("retrieve_context")
         graph.add_edge("retrieve_context", "analyze_antipatterns")
@@ -128,8 +123,6 @@ def _build_graph(self):
             },
         )
 
-        graph.add_edge("display_code_review_results", "explain_antipattern")
-        graph.add_edge("explain_antipattern", "display_explanation")
-        graph.add_edge("display_explanation", END)
+        graph.add_edge("display_code_review_results", END)
 
         return graph.compile()