update hyperparameters

cookbook/step_agent/examples.py

@@ -202,7 +202,7 @@ def example_4_custom_configuration():
         "summarizer": {
             "backend": "step",
             "enable_step_segmentation": True,
-            "enable_similarity_search": True,
+            "enable_similar_comparison": True,
             "enable_experience_validation": True,
             "max_retries": 5
         }
@@ -222,7 +222,7 @@ def example_4_custom_configuration():
         "summarizer": {
             "backend": "step",
             "enable_step_segmentation": False,
-            "enable_similarity_search": False,
+            "enable_similar_comparison": False,
             "enable_experience_validation": False,
             "max_retries": 1
         }

cookbook/step_agent/readme.md

@@ -12,17 +12,16 @@ This system provides advanced step-level experience extraction and context gener
 ## Key Features
 
 ### StepSummarizer Features
-- **Step-level experience extraction** from successful and failed trajectories
-- **Comparative analysis** between success and failure cases
 - **Trajectory segmentation** into meaningful step sequences
+- **Step-level experience extraction** from successful and failed trajectories
+- **Similarity-based comparison** for finding related experiences and compare between success and failure cases
 - **Experience validation** for quality assurance
-- **Similarity-based comparison** for finding related experiences
 
 ### StepContextGenerator Features
-- **Hybrid retrieval** combining vector search with LLM reranking
-- **Context rewriting** to make experiences more relevant to current tasks
 - **Score-based filtering** for quality control
-- **Configurable retrieval parameters** for different use cases
+- **Llm reranking** for reranking after recalling
+- **Context rewriting** to make experiences more relevant to current tasks
+- **Hybrid retrieval** combining vector search with LLM reranking
 
 ## Configuration Options
 

cookbook/step_agent/run.sh

@@ -5,7 +5,7 @@
 
 # StepSummarizer Parameters
 # enable_step_segmentation: Segment trajectories into meaningful step sequences
-# enable_similarity_search: Compare similar sequences between success/failure
+# enable_similar_comparison: Compare similar sequences between success/failure
 # enable_experience_validation: Validate experience quality before storage
 
 # StepContextGenerator Parameters
@@ -22,6 +22,6 @@ python -m experiencemaker.em_service \
     --vector_store='{"backend": "local_file", "store_dir": "./step_experiences/"}' \
     --agent_wrapper='{"backend": "simple"}' \
     --context_generator='{"backend": "step", "enable_llm_rerank": true, "enable_context_rewrite": true, "enable_score_filter": false, "vector_retrieve_top_k": 15, "final_top_k": 5, "min_score_threshold": 0.3}' \
-    --summarizer='{"backend": "step", "enable_step_segmentation": false, "enable_similarity_search": false, "enable_experience_validation": true, "max_retries": 3}'
+    --summarizer='{"backend": "step", "enable_step_segmentation": false, "enable_similar_comparison": false, "enable_experience_validation": true, "max_retries": 3}'
 
 echo "Step Experience Service started on port 8001"

experiencemaker/module/summarizer/step_summarizer.py

@@ -24,7 +24,7 @@ class StepSummarizer(BaseSummarizer, PromptMixin):
 
     # Feature switches - can be configured via startup parameters
     enable_step_segmentation: bool = Field(default=False, description="Enable trajectory segmentation into steps")
-    enable_similarity_search: bool = Field(default=False, description="Enable similarity search for comparison")
+    enable_similar_comparison: bool = Field(default=False, description="Enable similarity search for comparison")
     enable_experience_validation: bool = Field(default=True, description="Enable experience validation")
 
     # LLM retries
@@ -56,7 +56,7 @@ class StepSummarizer(BaseSummarizer, PromptMixin):
             all_experiences.extend(failure_experiences)
 
         # Comparative analysis (if similarity search is enabled)
-        if success_trajectories and failure_trajectories and self.enable_similarity_search:
+        if success_trajectories and failure_trajectories and self.enable_similar_comparison:
             comparative_experiences = self._extract_step_experiences_from_comparison(
                 success_trajectories, failure_trajectories, workspace_id, **kwargs
             )
@@ -345,7 +345,7 @@ class StepSummarizer(BaseSummarizer, PromptMixin):
     def _find_similar_step_sequences(self, success_trajectories: List[Trajectory],
                                      failure_trajectories: List[Trajectory]) -> List[Tuple]:
         """Use embedding model to find similar step sequences for comparison"""
-        if not self.enable_similarity_search:
+        if not self.enable_similar_comparison:
             return []
 
         try: