search pipeline updated

RAG/rag_DocumentSearcher.py

@@ -49,12 +49,6 @@ def query_(awsauth,inputs, session_id,search_types):
     url = host+path
     r = requests.get(url, auth=awsauth, json=query_mm, headers=headers)
     response_mm = json.loads(r.text)
-    # response_mm = ospy_client.search(
-    #     body = query_mm,
-    #     index = st.session_state.input_index+"_mm"
-    # )
-
-    
 
     hits = response_mm['hits']['hits']
     context = []
@@ -72,6 +66,24 @@ def query_(awsauth,inputs, session_id,search_types):
     
     searches = ['Keyword','Vector','NeuralSparse']
     equal_weight = (int(100/num_queries) )/100
+    s_pipeline_payload = {}
+    s_pipeline_path = "_search/pipeline/rag-search-pipeline" 
+    if(st.session_state.input_is_rerank):
+        s_pipeline_payload["response_processors"] = [
+                {
+                    "rerank": {
+                    "ml_opensearch": {
+                        "model_id": "eUoo-ZMBTp0efWqBQ-5g"
+                    },
+                    "context": {
+                        "document_fields": [
+                        "processed_element"
+                        ]
+                    }
+                    }
+                }
+                ]
+
     if(num_queries>1):
         for index,search in enumerate(search_types):
             
@@ -81,31 +93,25 @@ def query_(awsauth,inputs, session_id,search_types):
                 weight = 1-sum(weights)
                 
             weights.append(weight)
-        
-        #print(weights) 
-        
-        path = "_search/pipeline/rag-search-pipeline" 
-        url = host + path 
-        s_pipeline_payload = {
-                "description": "Post processor for hybrid search",
-                "phase_results_processors": [
-                {
-                    "normalization-processor": {
-                    "normalization": {
-                        "technique": "min_max"
-                    },
-                    "combination": {
-                        "technique": "arithmetic_mean",
-                        "parameters": {
-                        "weights": weights
+        s_pipeline_payload["phase_results_processors"] = [
+                    {
+                        "normalization-processor": {
+                        "normalization": {
+                            "technique": "min_max"
+                        },
+                        "combination": {
+                            "technique": "arithmetic_mean",
+                            "parameters": {
+                            "weights": weights
+                            }
+                        }
                         }
                     }
-                    }
-                }
-                ]
-            }
-            
-        r = requests.put(url, auth=awsauth, json=s_pipeline_payload, headers=headers)
+                    ]
+                    
+        
+        
+        
     
     SIZE = 5
     
@@ -183,8 +189,10 @@ def query_(awsauth,inputs, session_id,search_types):
         # query_sparse = sparse_["inference_results"][0]["output"][0]["dataAsMap"]["response"][0]
         
     hits = []
-    if(num_queries>1):
-        path = st.session_state.input_index+"/_search?search_pipeline=rag-search-pipeline" 
+    if(num_queries>1 or st.session_state.input_is_rerank): 
+        s_pipeline_url = host + s_pipeline_path 
+        r = requests.put(s_pipeline_url, auth=awsauth, json=s_pipeline_payload, headers=headers)
+        path = st.session_state.input_index+"/_search?search_pipeline=rag-search-pipeline"
     else:
         path = st.session_state.input_index+"/_search"
     url = host+path