tools calling functions compatibility

README.md

@@ -49,7 +49,7 @@ python3 main.py
 Available options:
 
 ```bash
-python3 main.py --server [local|remote] --model [model_name] --number [count|all] --verbose --plot-only --no-plot --file [results_file]
+python3 main.py --server [local|remote] --model [model_name] --number [count|all] --verbose --plot-only --no-plot --file [results_file] --funcall [model_name|all]
  ```
 
 ## Arguments:
@@ -61,6 +61,7 @@ python3 main.py --server [local|remote] --model [model_name] --number [count|all
 - --plot-only : Skip benchmarking and just generate graphs from existing results
 - --no-plot : Run benchmarking without plotting graphs at the end
 - --file : Specify a benchmark results file to use for plotting (only with --plot-only)
+- --funcall : Check function calling (tools) compatibility of models. Specify a model name or "all" for all models
 
 ## Supported Tests
 The tool currently tests models on these coding challenges:
@@ -198,6 +199,37 @@ The tool generates several output files in the `benchmark_results` directory:
    - High-resolution (300 DPI) visualization of model performance
    - Shows token processing speed, success rates, and duration ranges
 
+## Function Calling (Tools) Compatibility
+
+The tool now includes a feature to check which Ollama models support function calling (tools). This is useful for identifying models that can be used with applications requiring function calling capabilities.
+
+```bash
+# Check all models for function calling compatibility
+python3 main.py --funcall all
+
+# Check a specific model
+python3 main.py --funcall mistral:7b
+```
+
+Example output:
+
+```
+Tools Compatibility Report
+===================================================================
+Model                                             Tools Support
+-------------------------------------------------------------------
+qwen2.5:14b                                       ✅ Supported
+phi4-mini:latest                                  ✅ Supported
+phi4:latest                                       ❌ Not Supported
+mistral:7b                                        ✅ Supported
+llama3.2:3b                                       ✅ Supported
+llama3.2:1b-instruct-q4_K_M                       ✅ Supported
+gemma3:12b                                        ❌ Not Supported
+===================================================================
+```
+
+During benchmarking, the tool will now also display whether each model supports function calling before running the tests.
+
 ## Recent Updates
 
 ### March 2025 Updates

main.py

@@ -14,6 +14,7 @@ import matplotlib.pyplot as plt
 from together import Together
 from cpuinfo import get_cpu_info
 import subprocess
+from tools import get_tools_compatible_models, print_tools_compatibility_table
 
 
 # ANSI color codes
@@ -473,6 +474,15 @@ def run_model_benchmark(model: str, server_url: str, num_runs: int = 4) -> Dict:
     """
     Run multiple benchmarks for a model and calculate average metrics.
     """
+    # Check function calling (tools) compatibility
+    from tools import test_model_tools_support
+    supports_tools, error = test_model_tools_support(model)
+    if supports_tools:
+        print(f"\n{SUCCESS}Function Calling (Tools): ✅ Supported{ENDC}")
+    else:
+        error_msg = f" ({error})" if error else ""
+        print(f"\n{ERROR}Function Calling (Tools): ❌ Not Supported{error_msg}{ENDC}")
+    
     metrics = []
     
     for i in range(num_runs):
@@ -987,6 +997,8 @@ def main():
                       help='Run benchmarking without plotting graphs at the end')
     parser.add_argument('--file', type=str, 
                       help='Specify a benchmark results file to use for plotting (only with --plot-only)')
+    parser.add_argument('--funcall', type=str, nargs='?', const='all',
+                      help='Check function calling (tools) compatibility of models. Specify a model name or "all" for all models')
     args = parser.parse_args()
     
     # Set global verbose flag
@@ -998,6 +1010,28 @@ def main():
         print(f"{INFO}Running in plot-only mode...{ENDC}")
         plot_benchmark_results(args.file)
         return
+        
+    # Handle function calling compatibility check mode
+    if args.funcall is not None:
+        server_url = SERVERS[args.server]
+        print(f"{INFO}Checking function calling (tools) compatibility...{ENDC}")
+        
+        if args.funcall.lower() == 'all':
+            # Check all available models
+            compatibility = get_tools_compatible_models(server_url=server_url)
+            print_tools_compatibility_table(compatibility)
+        else:
+            # Check specific model
+            model_name = args.funcall
+            print(f"{INFO}Checking function calling compatibility for {model_name}...{ENDC}")
+            supports_tools, error = get_tools_compatible_models(model=model_name)
+            
+            if supports_tools:
+                print(f"{SUCCESS}✅ {model_name}: Supports function calling (tools){ENDC}")
+            else:
+                error_msg = f" ({error})" if error else ""
+                print(f"{ERROR}❌ {model_name}: Does not support function calling (tools){error_msg}{ENDC}")
+        return
     
     server_url = SERVERS[args.server]
     

models.py

@@ -48,14 +48,14 @@ def get_model_details(model_name):
         print(f"An error occurred: {e}")
         return None
 
-# List all available models using the Ollama Python library
-models = get_available_models(server_url)
-print("Available Models:")
-for model_name in models:
-    print(model_name)
-    details = get_model_details(model_name)
-
-    # Display detailed information about the model
-    if details:
-        print("\nModel Details:")
-        print(json.dumps(details, indent=4))
+# This code is commented out to prevent automatic execution when imported
+# models = get_available_models(server_url)
+# print("Available Models:")
+# for model_name in models:
+#     print(model_name)
+#     details = get_model_details(model_name)
+#
+#     # Display detailed information about the model
+#     if details:
+#         print("\nModel Details:")
+#         print(json.dumps(details, indent=4))