Merge branch 'main' into tool-use

application/api/answer/routes.py

@@ -18,7 +18,7 @@ from application.error import bad_request
 from application.extensions import api
 from application.llm.llm_creator import LLMCreator
 from application.retriever.retriever_creator import RetrieverCreator
-from application.utils import check_required_fields
+from application.utils import check_required_fields, limit_chat_history
 
 logger = logging.getLogger(__name__)
 
@@ -118,8 +118,31 @@ def is_azure_configured():
     )
 
 
-def save_conversation(conversation_id, question, response, source_log_docs, llm):
-    if conversation_id is not None and conversation_id != "None":
+def save_conversation(conversation_id, question, response, source_log_docs, llm,index=None):
+    if conversation_id is not None and index is not None:
+        conversations_collection.update_one(
+            {"_id": ObjectId(conversation_id), f"queries.{index}": {"$exists": True}},
+            {
+                "$set": {
+                    f"queries.{index}.prompt": question,
+                    f"queries.{index}.response": response,
+                    f"queries.{index}.sources": source_log_docs,
+                }
+            }
+        )
+        ##remove following queries from the array
+        conversations_collection.update_one(
+            {"_id": ObjectId(conversation_id), f"queries.{index}": {"$exists": True}},
+            {
+                "$push":{
+                    "queries":{
+                        "$each":[],
+                        "$slice":index+1
+                    }
+                }
+            }
+        )
+    elif conversation_id is not None and conversation_id != "None":
         conversations_collection.update_one(
             {"_id": ObjectId(conversation_id)},
             {
@@ -141,17 +164,17 @@ def save_conversation(conversation_id, question, response, source_log_docs, llm)
                 "role": "assistant",
                 "content": "Summarise following conversation in no more than 3 "
                 "words, respond ONLY with the summary, use the same "
-                "language as the system \n\nUser: "
-                + question
-                + "\n\n"
-                + "AI: "
-                + response,
+                "language as the system",
             },
             {
                 "role": "user",
                 "content": "Summarise following conversation in no more than 3 words, "
                 "respond ONLY with the summary, use the same language as the "
-                "system",
+                "system \n\nUser: "
+                + question
+                + "\n\n"
+                + "AI: "
+                + response,
             },
         ]
 
@@ -186,7 +209,7 @@ def get_prompt(prompt_id):
 
 
 def complete_stream(
-    question, retriever, conversation_id, user_api_key, isNoneDoc=False
+    question, retriever, conversation_id, user_api_key, isNoneDoc=False,index=None
 ):
 
     try:
@@ -217,7 +240,7 @@ def complete_stream(
         )
         if user_api_key is None:
             conversation_id = save_conversation(
-                conversation_id, question, response_full, source_log_docs, llm
+                conversation_id, question, response_full, source_log_docs, llm,index
             )
             # send data.type = "end" to indicate that the stream has ended as json
             data = json.dumps({"type": "id", "id": str(conversation_id)})
@@ -282,6 +305,9 @@ class Stream(Resource):
             "isNoneDoc": fields.Boolean(
                 required=False, description="Flag indicating if no document is used"
             ),
+            "index":fields.Integer(
+                required=False, description="The position where query is to be updated"
+            ),
         },
     )
 
@@ -290,23 +316,23 @@ class Stream(Resource):
     def post(self):
         data = request.get_json()
         required_fields = ["question"]
-
+        if "index" in data:
+            required_fields = ["question","conversation_id"]
         missing_fields = check_required_fields(data, required_fields)
         if missing_fields:
             return missing_fields
 
         try:
             question = data["question"]
-            history = data.get("history", [])
-            history = json.loads(history)
+            history = limit_chat_history(json.loads(data.get("history", [])), gpt_model=gpt_model)
             conversation_id = data.get("conversation_id")
             prompt_id = data.get("prompt_id", "default")
             
-
+            index=data.get("index",None)
             chunks = int(data.get("chunks", 2))
             token_limit = data.get("token_limit", settings.DEFAULT_MAX_HISTORY)
             retriever_name = data.get("retriever", "classic")
-
+            
             if "api_key" in data:
                 data_key = get_data_from_api_key(data["api_key"])
                 chunks = int(data_key.get("chunks", 2))
@@ -343,7 +369,7 @@ class Stream(Resource):
                 gpt_model=gpt_model,
                 user_api_key=user_api_key,
             )
-
+            
             return Response(
                 complete_stream(
                     question=question,
@@ -351,6 +377,7 @@ class Stream(Resource):
                     conversation_id=conversation_id,
                     user_api_key=user_api_key,
                     isNoneDoc=data.get("isNoneDoc"),
+                    index=index,
                 ),
                 mimetype="text/event-stream",
             )
@@ -428,7 +455,7 @@ class Answer(Resource):
 
         try:
             question = data["question"]
-            history = data.get("history", [])
+            history = limit_chat_history(json.loads(data.get("history", [])), gpt_model=gpt_model)
             conversation_id = data.get("conversation_id")
             prompt_id = data.get("prompt_id", "default")
             chunks = int(data.get("chunks", 2))