Create reasoning_engines.py

reasoning_engines.py

@@ -0,0 +1,50 @@
+# [Use the CoT/ToT implementations from ethical-rag-starter.py]
+# Minimal version for quick deployment:
+
+import re
+from typing import Tuple, List
+
+class ChainOfThought:
+    def __init__(self, llm):
+        self.llm = llm
+    
+    def basic_cot(self, query: str) -> Tuple[str, List[str]]:
+        prompt = f"""Think step-by-step about: {query}
+        
+        Step 1: Understand the question
+        Step 2: Break into parts
+        Step 3: Solve each part
+        Step 4: Combine
+        
+        Provide your answer:"""
+        
+        response = self.llm.generate(prompt)
+        steps = [line.strip() for line in response.split('\n') 
+                if line.strip() and any(f"Step {i}" in line for i in range(1,5))]
+        
+        return response, steps
+    
+    def self_consistency_cot(self, query: str, num_paths: int = 2) -> Tuple[str, float]:
+        responses = []
+        for i in range(num_paths):
+            response = self.llm.generate(f"Problem: {query}\n\nSolution {i+1}:")
+            responses.append(response)
+        
+        return responses, 0.7
+
+class TreeOfThoughts:
+    def __init__(self, llm, max_depth=2, branching_factor=2):
+        self.llm = llm
+        self.max_depth = max_depth
+        self.branching_factor = branching_factor
+    
+    def solve_bfs(self, problem: str) -> Tuple[str, List[str], List]:
+        # Simplified BFS
+        branches = self.llm.generate(
+            f"List {self.branching_factor} approaches to: {problem}"
+        )
+        return branches, [], []
+    
+    def solve_dfs(self, problem: str) -> Tuple[str, List[str], List]:
+        # Simplified DFS
+        return self.llm.generate(f"Solve: {problem}"), [], []