added support for cohere north mini

embd_res/klite.embd

@@ -3562,7 +3562,7 @@ Current version indicated by LITEVER below.
 	// whitelisted auto selected horde model names
 	const defaultmodels = ["gpt4all","supercot","pygmalion-6","pygmalion-v8","pygmalion-2","hermes","airoboros","chrono","wizard","mantis","vicuna","manticore","alpaca","myth","xwin","spicyboros","mlewd","mxlewd","westlake","anubis","skyfall","llama2","llama3","llama-2","llama-3-","llama-3.","mistral","maid","mixtral","estopia","fighter","fimbul","euryale","nemo","gemma","lunaris","stheno","magnum","cydonia","qwen2.5-32b","behemoth","exaone","glm4","glm-4","tutu","deepseek","tlacuilo","rocinante","-14B","-32B","-27B","-35B"];
 	const ignoredmodels = ["tinyllama","debug-","-1b","-270m"]; //blacklisted model names
-	const hardcoded_think_closers = ["</think>","<channel|>"];
+	const hardcoded_think_closers = ["</think>","<channel|>","</seed:think>","<|END_THINKING|>"];
 
 	const instructstartplaceholder = "\n{{[INPUT]}}\n";
 	const instructendplaceholder = "\n{{[OUTPUT]}}\n";

kcpp_adapters/AutoGuess.json

@@ -201,7 +201,7 @@
     }
 }, {
     "search": ["<|START_OF_TURN_TOKEN|>"],
-    "name": "Cohere (Aya Expanse 32B based)",
+    "name": "Cohere",
     "adapter": {
         "system_start": "<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>",
         "system_end": "<|END_OF_TURN_TOKEN|>",
@@ -312,6 +312,17 @@
         "assistant_end": "\n",
         "assistant_gen": "<|begin_assistant|>\nWe can respond now.\n[BEGIN FINAL RESPONSE]\n"
     }
+}, {
+    "search": ["<|developer_end|>", "<|assistant_start|>","<|system_start|>"],
+    "name": "Apertus",
+    "adapter": {
+        "system_start": "<|system_start|>",
+        "system_end": "<|system_end|>",
+        "user_start": "<|user_start|>",
+        "user_end": "<|user_end|>",
+        "assistant_start": "<|assistant_start|>",
+        "assistant_end": "<|assistant_end|>"
+    }
 }, {
     "search": ["[e~[","]~b]user"],
     "name": "MiniMax",

koboldcpp.py

@@ -194,6 +194,7 @@ tool_call_pairs = [ #third element is optional str to match in chat template bef
     ("<|end|><|start|>assistant<|channel|>commentary to=", "", None, False), #gpt-oss
     ("<|tool_call_start|>", "<|tool_call_end|>", "CONTINUE_FINAL_MESSAGE_TAG", True), #lfm2.5
     ("<tool_calls>", "</tool_calls>", "[BEGIN FINAL RESPONSE]", True), #apriel
+    ("<|START_ACTION|>", "<|END_ACTION|>", "<|START_OF_TURN_TOKEN|>", True), #cohere
 ]
 deprecated_keys = {
     "hordeconfig",
@@ -3578,21 +3579,47 @@ def toolcall_to_normalized_json(text,start_tag,end_tag,required_match_txt): #con
         except Exception:
             return text
 
+    def parse_cohere2moe(text: str) -> str:
+        text = text.strip()
+        try:
+            calls = json.loads(text)
+        except Exception:
+            return text
+        if isinstance(calls, dict):
+            calls = [calls]
+        if not isinstance(calls, list):
+            return text
+        results = []
+        for call in calls:
+            if not isinstance(call, dict):
+                continue
+            fn_name = call.get("tool_name") or call.get("name")
+            args = call.get("parameters", call.get("arguments", {}))
+            if not fn_name:
+                continue
+            results.append({"name": fn_name,"arguments": args if isinstance(args, dict) else {}})
+        if not results:
+            return text
+        return json.dumps(results) if len(results) > 1 else json.dumps(results[0])
+
     # gemma4 takes precedence, since it can contain valid json fragments
     if end_tag=="<tool_call|>":
         return parse_gemma4(text)
 
+    if start_tag=="<|tool_call_start|>" and end_tag=="<|tool_call_end|>" and cached_chat_template and (required_match_txt is None or required_match_txt in cached_chat_template):
+        return parse_lfm25(text)
+
+    if start_tag=="<|START_ACTION|>" and end_tag=="<|END_ACTION|>" and cached_chat_template and (required_match_txt is None or required_match_txt in cached_chat_template):
+        return parse_cohere2moe(text)
+
+    if start_tag=="<tool_calls>" and end_tag=="</tool_calls>" and cached_chat_template and (required_match_txt is None or required_match_txt in cached_chat_template):
+        return extract_json_from_string(text, True) #apriel is json
+
     #if we are already valid JSON, return
     check_ok = extract_json_from_string(text, True)
     if check_ok and len(check_ok)>0:
         return text #is valid JSON or parsable
 
-    if start_tag=="<|tool_call_start|>" and end_tag=="<|tool_call_end|>" and cached_chat_template and (required_match_txt is None or required_match_txt in cached_chat_template):
-        return parse_lfm25(text)
-
-    if start_tag=="<tool_calls>" and end_tag=="</tool_calls>" and cached_chat_template and (required_match_txt is None or required_match_txt in cached_chat_template):
-        return extract_json_from_string(text, True) #apriel is json
-
     if "<arg_key>" in text and "<arg_value>" in text: # handle glm with args
         return parse_glm(text)
 
@@ -3655,14 +3682,14 @@ def format_jinja(messages_orig, tools, chat_template_kwargs=None):
             print(f"Warning: Jinja template raised an exception: {msg}")
             return ""
         global cached_chat_template
-        from jinja2.ext import Extension
+        from jinja2.ext import Extension, loopcontrols
         class IgnoreGenerationTags(Extension):
             tags = {"generation"}
             def parse(self, parser):
                 parser.stream.skip(1)
                 return parser.parse_statements( ("name:endgeneration",), drop_needle=True)
         from jinja2.sandbox import ImmutableSandboxedEnvironment
-        jinja_env = ImmutableSandboxedEnvironment(trim_blocks=True, lstrip_blocks=True,  extensions=[IgnoreGenerationTags])
+        jinja_env = ImmutableSandboxedEnvironment(trim_blocks=True, lstrip_blocks=True,  extensions=[IgnoreGenerationTags,loopcontrols])
         # sanitize messages to remove none types
         messages = json.loads(json.dumps(messages_orig))
         for m in messages:

src/llama-vocab.cpp

@@ -3052,20 +3052,18 @@ void llama_vocab::impl::load(llama_model_loader & ml, const LLM_KV & kv) {
                 attr = LLAMA_TOKEN_ATTR_USER_DEFINED;
             }
 
-            //kcpp hack render these
-            if (t.first == "<|tool_call_start|>" || t.first == "<|tool_call_end|>") {
+            //kcpp hack: render these special tokens
+            if (t.first == "<|tool_call_start|>" || t.first == "<|tool_call_end|>"
+                || t.first=="<|START_THINKING|>" || t.first=="<|END_THINKING|>"
+                || t.first=="<|START_ACTION|>" || t.first=="<|END_ACTION|>"
+                || t.first == "[THINK]" || t.first == "[/THINK]"
+                || t.first == "<think>" || t.first == "</think>"
+                || t.first == "[CALL_ID]" || t.first == "[TOOL_CONTENT]" || t.first == "[TOOL_CALLS]" || t.first == "[ARGS]") {
                 LLAMA_LOG_WARN("%s: setting token '%s' (%d) attribute to USER_DEFINED (%u), old attributes: %u\n",
                         __func__, t.first.c_str(), t.second, LLAMA_TOKEN_ATTR_USER_DEFINED, attr);
-
                 attr = LLAMA_TOKEN_ATTR_USER_DEFINED;
             }
 
-            if (t.first == "[THINK]" || t.first == "[/THINK]" || t.first == "<think>" || t.first == "</think>" ||
-                t.first == "[CALL_ID]" || t.first == "[TOOL_CONTENT]" || t.first == "[TOOL_CALLS]" || t.first == "[ARGS]") {
-                LLAMA_LOG_WARN("%s: setting token '%s' (%d) attribute to USER_DEFINED (%u), old attributes: %u\n",
-                               __func__, t.first.c_str(), t.second, LLAMA_TOKEN_ATTR_USER_DEFINED, attr);
-                attr = LLAMA_TOKEN_ATTR_USER_DEFINED;
-            }
         }
 
         // sanity checks