updated readme, handle unsupported OAI tools

README.md

@@ -6,7 +6,7 @@ Inspired by **KoboldAI** and built on **llama.cpp**
 
 One executable file, no installation required. Ready-to-run downloads are available for Windows, Linux, and macOS.
 
-**[Download KoboldCpp](https://github.com/LostRuins/koboldcpp/releases/latest) | [Documentation and FAQ](https://github.com/LostRuins/koboldcpp/wiki) | [API reference](https://lite.koboldai.net/koboldcpp_api) | [Discord community](https://koboldai.org/discord)**
+**[Download KoboldCpp](https://github.com/LostRuins/koboldcpp/releases/latest) | [Quick Start](#quick-start) | [Documentation and FAQ](https://github.com/LostRuins/koboldcpp/wiki) | [API reference](https://lite.koboldai.net/koboldcpp_api) | [Discord community](https://koboldai.org/discord)**
 
 ![Integrated Web UI](media/preview.png)
 ![Roleplay Chat Mode](media/preview2.png)
@@ -99,8 +99,11 @@ KoboldCpp also retains backward compatibility with legacy GGML `.bin` models, th
 - Lightweight and Fast: [Gemma3-4B](https://huggingface.co/ggml-org/gemma-3-4b-it-GGUF/resolve/main/gemma-3-4b-it-Q4_K_M.gguf)
   - Add [optional Gemma3-4B MMproj file](https://huggingface.co/koboldcpp/mmproj/resolve/main/gemma3-4b-mmproj-q8.gguf) for vision recognition capabilities.
 - Image Generation: [PicX Real](https://huggingface.co/koboldcpp/imgmodel/resolve/main/picx_real_q5_1.gguf)
-- Speech Recognition: [Whisper models for Speech-To-Text](https://huggingface.co/koboldcpp/whisper/tree/main)
-- Text-To-Speech: [TTS models for Narration](https://huggingface.co/koboldcpp/tts/tree/main)
+  - Or browse [More image generation models](https://huggingface.co/koboldcpp/imgmodel/tree/main)
+- Speech Recognition: [Whisper Base](https://huggingface.co/koboldcpp/whisper/resolve/main/whisper-base.en-q5_1.bin)
+  - Or browse [More Whisper models for Speech-To-Text](https://huggingface.co/koboldcpp/whisper/tree/main)
+- Text-To-Speech: [Kokoro TTS](https://huggingface.co/koboldcpp/tts/resolve/main/Kokoro_no_espeak_Q4.gguf)
+  - Or browse [More TTS models for Narration](https://huggingface.co/koboldcpp/tts/tree/main)
 - This is just a list for noobs to get started! There are hundreds more GGUFs out there!
 - [More newbie templates](https://huggingface.co/koboldcpp/newbie-templates) - Contains premade KoboldCpp quick launch templates curated for newbies.
 - [More popular templates](https://huggingface.co/koboldcpp/popular-templates) - Contains premade KoboldCpp quick launch templates curated for popularity.

koboldcpp.py

@@ -4301,6 +4301,9 @@ def remove_outer_tags(inputstr):
 def normalize_anthropic_tools_input(tools): #Convert Anthropic-format tool definitions to OpenAI format.
     normalized = []
     for tool in tools:
+        if not isinstance(tool, dict):
+            print(f"Dropped unsupported tool: {tool}")
+            continue
         if tool.get("type") == "function" and "function" in tool: # Already in OpenAI format — leave it alone
             normalized.append(tool)
             continue
@@ -4316,6 +4319,22 @@ def normalize_anthropic_tools_input(tools): #Convert Anthropic-format tool defin
         # normalized.append(tool)
     return normalized
 
+def normalize_openai_tools_input(tools):
+    """Keep only function tools that KoboldCpp can execute."""
+    normalized = []
+    if not isinstance(tools, list):
+        print(f"Dropped unsupported tools value: {tools}")
+        return normalized
+    for tool in tools:
+        function = tool.get("function") if isinstance(tool, dict) else None
+        if isinstance(tool, dict) and tool.get("type") == "function" and isinstance(function, dict) and function.get("name"):
+            normalized.append(tool)
+        else:
+            # OpenAI built-in tools (for example web_search) require provider-side
+            # implementations and cannot be exposed to the local model as functions.
+            print(f"Dropped unsupported tool: {tool}")
+    return normalized
+
 def normalize_tool_call_resp(obj): # Normalize various tool call formats to OpenAI format
     if "type" in obj and "function" in obj: # Already in OpenAI format
         return obj
@@ -4634,16 +4653,28 @@ def determine_tool_json_to_use(genparams, curr_ctx, assistant_message_start, is_
 def compress_tools_array(tools_array):
     tools_array_filtered = []
     for tool_dict in tools_array:
+        if not isinstance(tool_dict, dict):
+            continue
         tool_data = tool_dict
         if 'function' in tool_dict:
             tool_data = tool_dict['function']
+        if not isinstance(tool_data, dict) or not tool_data.get("name"):
+            continue
         tool_props = {}
         params = tool_data.get("parameters", {})
+        if not isinstance(params, dict):
+            params = {}
         props = params.get("properties", {})
+        if not isinstance(props, dict):
+            props = {}
         for prop_name, prop_data in props.items():
+            if not isinstance(prop_data, dict):
+                continue
             prop_type = prop_data.get("type")
             if prop_type is None and "anyOf" in prop_data:
                 for option in prop_data["anyOf"]:
+                    if not isinstance(option, dict):
+                        continue
                     option_type = option.get("type")
                     if option_type and option_type != "null":
                         prop_type = option_type
@@ -4652,7 +4683,7 @@ def compress_tools_array(tools_array):
                 prop_type = "string"
             tool_props[prop_name] = prop_type
         tools_array_filtered.append({
-            "name": tool_data['name'],
+            "name": tool_data["name"],
             "description": tool_data.get("description", ""),
             "properties": tool_props
         })
@@ -4806,6 +4837,8 @@ ws ::= | " " | "\n" [ \t]{0,20}
         genparams["mirostat"] = genparams.get('mirostat_mode', 0)
 
         if api_format==4 or api_format==7: #handle ollama chat here too
+            if genparams.get("tools"):
+                genparams["tools"] = normalize_openai_tools_input(genparams["tools"])
             # translate openai chat completion messages format into one big string.
             messages_array = genparams.get('messages', [])
             messages_string = adapter_obj.get("chat_start", "")