diff --git a/rag/llm/chat_model.py b/rag/llm/chat_model.py
index f00915dd2..46ea7b14e 100644
--- a/rag/llm/chat_model.py
+++ b/rag/llm/chat_model.py
@@ -179,7 +179,41 @@ class Base(ABC):
         except Exception:
             pass
         return 0
+        
+    def _calculate_dynamic_ctx(self, history):
+        """Calculate dynamic context window size"""
+        def count_tokens(text):
+            """Calculate token count for text"""
+            # Simple calculation: 1 token per ASCII character
+            # 2 tokens for non-ASCII characters (Chinese, Japanese, Korean, etc.)
+            total = 0
+            for char in text:
+                if ord(char) < 128:  # ASCII characters
+                    total += 1
+                else:  # Non-ASCII characters (Chinese, Japanese, Korean, etc.)
+                    total += 2
+            return total
 
+        # Calculate total tokens for all messages
+        total_tokens = 0
+        for message in history:
+            content = message.get("content", "")
+            # Calculate content tokens
+            content_tokens = count_tokens(content)
+            # Add role marker token overhead
+            role_tokens = 4
+            total_tokens += content_tokens + role_tokens
+
+        # Apply 1.2x buffer ratio
+        total_tokens_with_buffer = int(total_tokens * 1.2)
+            
+        if total_tokens_with_buffer <= 8192:
+            ctx_size = 8192
+        else:
+            ctx_multiplier = (total_tokens_with_buffer // 8192) + 1
+            ctx_size = ctx_multiplier * 8192
+        
+        return ctx_size
 
 class GptTurbo(Base):
     def __init__(self, key, model_name="gpt-3.5-turbo", base_url="https://api.openai.com/v1"):
@@ -469,7 +503,7 @@ class ZhipuChat(Base):
 
 class OllamaChat(Base):
     def __init__(self, key, model_name, **kwargs):
-        self.client = Client(host=kwargs["base_url"]) if not key or key == "x" else Client(host=kwargs["base_url"], headers={"Authorization": f"Bear {key}"})
+        self.client = Client(host=kwargs["base_url"]) if not key or key == "x" else Client(host=kwargs["base_url"], headers={"Authorization": f"Bearer {key}"})
         self.model_name = model_name
 
     def chat(self, system, history, gen_conf):
@@ -478,7 +512,12 @@ class OllamaChat(Base):
         if "max_tokens" in gen_conf:
             del gen_conf["max_tokens"]
         try:
-            options = {"num_ctx": 32768}
+            # Calculate context size
+            ctx_size = self._calculate_dynamic_ctx(history)
+            
+            options = {
+                "num_ctx": ctx_size
+            }
             if "temperature" in gen_conf:
                 options["temperature"] = gen_conf["temperature"]
             if "max_tokens" in gen_conf:
@@ -489,9 +528,11 @@ class OllamaChat(Base):
                 options["presence_penalty"] = gen_conf["presence_penalty"]
             if "frequency_penalty" in gen_conf:
                 options["frequency_penalty"] = gen_conf["frequency_penalty"]
-            response = self.client.chat(model=self.model_name, messages=history, options=options, keep_alive=-1)
+
+            response = self.client.chat(model=self.model_name, messages=history, options=options, keep_alive=10)
             ans = response["message"]["content"].strip()
-            return ans, response.get("eval_count", 0) + response.get("prompt_eval_count", 0)
+            token_count = response.get("eval_count", 0) + response.get("prompt_eval_count", 0)
+            return ans, token_count
         except Exception as e:
             return "**ERROR**: " + str(e), 0
 
@@ -500,28 +541,38 @@ class OllamaChat(Base):
             history.insert(0, {"role": "system", "content": system})
         if "max_tokens" in gen_conf:
             del gen_conf["max_tokens"]
-        options = {}
-        if "temperature" in gen_conf:
-            options["temperature"] = gen_conf["temperature"]
-        if "max_tokens" in gen_conf:
-            options["num_predict"] = gen_conf["max_tokens"]
-        if "top_p" in gen_conf:
-            options["top_p"] = gen_conf["top_p"]
-        if "presence_penalty" in gen_conf:
-            options["presence_penalty"] = gen_conf["presence_penalty"]
-        if "frequency_penalty" in gen_conf:
-            options["frequency_penalty"] = gen_conf["frequency_penalty"]
-        ans = ""
         try:
-            response = self.client.chat(model=self.model_name, messages=history, stream=True, options=options, keep_alive=-1)
-            for resp in response:
-                if resp["done"]:
-                    yield resp.get("prompt_eval_count", 0) + resp.get("eval_count", 0)
-                ans = resp["message"]["content"]
-                yield ans
+            # Calculate context size
+            ctx_size = self._calculate_dynamic_ctx(history)
+            options = {
+                "num_ctx": ctx_size
+            }
+            if "temperature" in gen_conf:
+                options["temperature"] = gen_conf["temperature"]
+            if "max_tokens" in gen_conf:
+                options["num_predict"] = gen_conf["max_tokens"]
+            if "top_p" in gen_conf:
+                options["top_p"] = gen_conf["top_p"]
+            if "presence_penalty" in gen_conf:
+                options["presence_penalty"] = gen_conf["presence_penalty"]
+            if "frequency_penalty" in gen_conf:
+                options["frequency_penalty"] = gen_conf["frequency_penalty"]
+
+            ans = ""
+            try:
+                response = self.client.chat(model=self.model_name, messages=history, stream=True, options=options, keep_alive=10 )
+                for resp in response:
+                    if resp["done"]:
+                        token_count = resp.get("prompt_eval_count", 0) + resp.get("eval_count", 0)
+                        yield token_count
+                    ans = resp["message"]["content"]
+                    yield ans
+            except Exception as e:
+                yield ans + "\n**ERROR**: " + str(e)
+            yield 0
         except Exception as e:
-            yield ans + "\n**ERROR**: " + str(e)
-        yield 0
+            yield "**ERROR**: " + str(e)
+            yield 0
 
 
 class LocalAIChat(Base):