(feat:conv history) token limit from settings

application/utils.py

@@ -46,17 +46,37 @@ def check_required_fields(data, required_fields):
 def get_hash(data):
     return hashlib.md5(data.encode()).hexdigest()
 
-def limit_chat_history(history,max_token_limit = 500):
-   
-    cumulative_token_count = 0
+def limit_chat_history(history, max_token_limit=None, gpt_model="docsgpt"):
+    """
+    Limits chat history based on token count.
+    Returns a list of messages that fit within the token limit.
+    """
+    from application.core.settings import settings
+
+    max_token_limit = (
+        max_token_limit
+        if max_token_limit
+        and max_token_limit < settings.MODEL_TOKEN_LIMITS.get(
+            gpt_model, settings.DEFAULT_MAX_HISTORY
+        )
+        else settings.MODEL_TOKEN_LIMITS.get(gpt_model, settings.DEFAULT_MAX_HISTORY)
+    )
+
+    if not history:
+        return []
+        
+    tokens_current_history = 0
     trimmed_history = []
     
-    for i in reversed(history):
-        
-        if("prompt" in i and "response" in i):
-            cumulative_token_count += num_tokens_from_string(i["prompt"] + i["response"])
-            if(cumulative_token_count > max_token_limit):
-                    break
-            trimmed_history.insert(0,i)
-            
-    return trimmed_history
+    for message in reversed(history):
+        if "prompt" in message and "response" in message:
+            tokens_batch = num_tokens_from_string(message["prompt"]) + num_tokens_from_string(
+                message["response"]
+            )
+            if tokens_current_history + tokens_batch < max_token_limit:
+                tokens_current_history += tokens_batch
+                trimmed_history.insert(0, message)
+            else:
+                break
+                
+    return trimmed_history