Add Ollama native tool calling workaround section

README.md

@@ -222,6 +222,136 @@ ollama run hf.co/Ex0bit/Elbaz-Prime-Intellect-3_Prism_Abliterated
 
 > **Note:** The `hf.co/` prefix is required to pull from Hugging Face. Requires Ollama 0.3.0+.
 
+<details>
+<summary><strong>🔧 Native Tool Calling with Ollama's `tools` API</strong></summary>
+
+> **Issue:** INTELLECT-3 outputs tool calls in XML format (`<function=name><parameter=key>value</parameter></function>`), but Ollama's parser expects JSON format inside `<tool_call>` tags. This causes Ollama's `tool_calls` field to remain empty even when the model outputs valid tool calls.
+
+**Workaround:** Create a custom model with a template that instructs the model to use JSON format:
+
+1. Create a file called `Modelfile.glm`:
+
+```
+FROM hf.co/Ex0bit/Elbaz-Prime-Intellect-3_Prism_Abliterated
+
+# INTELLECT-3 Prism with GLM-style Tool Template
+# Uses JSON tool call format that works with Ollama's parser
+
+TEMPLATE """
+{{- /* System message at the beginning, if there is .System or .Tools */ -}}
+{{- if or .System .Tools }}
+<|im_start|>system
+{{- if .System }}
+{{ .System }}
+{{- end }}
+{{- if .Tools }}
+
+You are a helpful assistant with the ability to call tools.
+
+**Available tools:**
+{{ range .Tools }}
+{{ . }}
+{{ end }}
+
+**Tool call format:**
+<tool_call>
+{"name": "tool_name", "parameters": {"param1": "value1", "param2": "value2"}}
+</tool_call>
+
+Important:
+- You MUST use JSON format inside <tool_call> tags
+- Do your reasoning first, then output the tool call
+- If no tool is needed, answer normally
+{{- end }}
+<|im_end|>
+{{- end }}
+
+{{- /* Processing messages */ -}}
+{{- range $i, $_ := .Messages }}
+{{- $last := eq (len (slice $.Messages $i)) 1 }}
+
+{{- /* User messages */ -}}
+{{- if eq .Role "user" }}
+<|im_start|>user
+{{ .Content }}<|im_end|>
+{{- /* Start model turn if this is the last message */ -}}
+{{ if $last }}<|im_start|>assistant
+{{ end }}
+
+{{- /* Assistant messages */ -}}
+{{- else if eq .Role "assistant" }}
+<|im_start|>assistant
+{{- if .ToolCalls }}
+<tool_call>
+{{- range .ToolCalls }}
+{"name": "{{ .Function.Name }}", "parameters": {{ .Function.Arguments }}}
+{{- end }}
+</tool_call>
+{{- else }}
+{{ .Content }}
+{{- end }}
+{{- /* End turn if this is not the last message */ -}}
+{{- if not $last }}<|im_end|>
+{{ end }}
+
+{{- /* Tool results */ -}}
+{{- else if eq .Role "tool" }}
+<|im_start|>user
+<tool_response>
+{{ .Content }}
+</tool_response><|im_end|>
+{{- /* Start model turn if this is the last message */ -}}
+{{ if $last }}<|im_start|>assistant
+{{ end }}
+{{- end }}
+{{- end }}
+"""
+
+PARAMETER stop <|im_start|>
+PARAMETER stop <|im_end|>
+PARAMETER temperature 0.6
+PARAMETER num_ctx 32768
+```
+
+2. Create and run the model:
+
+```bash
+ollama create elbaz-prism-glm -f Modelfile.glm
+ollama run elbaz-prism-glm
+```
+
+3. Use with Ollama's native `tools` API:
+
+```python
+import ollama
+
+response = ollama.chat(
+    model='elbaz-prism-glm',
+    messages=[{'role': 'user', 'content': 'What time is it in Tokyo?'}],
+    tools=[{
+        'type': 'function',
+        'function': {
+            'name': 'get_time',
+            'description': 'Get current time in a timezone',
+            'parameters': {
+                'type': 'object',
+                'properties': {
+                    'timezone': {'type': 'string', 'description': 'Timezone like Asia/Tokyo'}
+                }
+            }
+        }
+    }]
+)
+
+# tool_calls field will now be properly populated!
+print(response['message'].get('tool_calls'))
+```
+
+This workaround ensures Ollama's parser correctly populates the `tool_calls` field in API responses.
+
+</details>
+
+
 ### Using with LM Studio
 
 1. Download the GGUF file and place it in your LM Studio models directory