Update README.md

README.md

@@ -58,6 +58,10 @@ print(tokenizer.decode(response, skip_special_tokens=True))
 ```
 
 ### Function Calling
+Function calling requires two step inferences, below is the example:
+
+## Step 1:
+
 ```python
 functions_metadata = [
     {
@@ -81,9 +85,41 @@ functions_metadata = [
     }
 ]
 
+messages = [
+    { "role": "system", "content": f"""You are a helpful assistant with access to the following functions: \n {str(functions_metadata)}\n\nTo use these functions respond with:\n<functioncall> {{ "name": "function_name", "arguments": {{ "arg_1": "value_1", "arg_1": "value_1", ... }} }} </functioncall>\n\nEdge cases you must handle:\n - If there are no functions that match the user request, you will respond politely that you cannot help."""},
+    { "role": "user", "content": "What is the temperature in Tokyo right now?"}
+]
+
+input_ids = tokenizer.apply_chat_template(
+    messages,
+    add_generation_prompt=True,
+    return_tensors="pt"
+).to(model.device)
+
+terminators = [
+    tokenizer.eos_token_id,
+    tokenizer.convert_tokens_to_ids("<|eot_id|>")
+]
+
+outputs = model.generate(
+    input_ids,
+    max_new_tokens=256,
+    eos_token_id=terminators,
+    do_sample=True,
+    temperature=0.6,
+    top_p=0.9,
+)
+response = outputs[0][input_ids.shape[-1]:]
+print(tokenizer.decode(response, skip_special_tokens=True))
+# >> <functioncall> {"name": "get_temperature", "arguments": '{"city": "Tokyo"}'} </functioncall>"""}
+```
+## Step 2:
+
+```python
 messages = [
     { "role": "system", "content": f"""You are a helpful assistant with access to the following functions: \n {str(functions_metadata)}\n\nTo use these functions respond with:\n<functioncall> {{ "name": "function_name", "arguments": {{ "arg_1": "value_1", "arg_1": "value_1", ... }} }} </functioncall>\n\nEdge cases you must handle:\n - If there are no functions that match the user request, you will respond politely that you cannot help."""},
     { "role": "user", "content": "What is the temperature in Tokyo right now?"},
+    // You will get the previous prediction, extract it will the tag <functioncall>, execute it and append it to the messages like below:
     { "role": "assistant", "content": """<functioncall> {"name": "get_temperature", "arguments": '{"city": "Tokyo"}'} </functioncall>"""},    
     { "role": "user", "content": """<function_response> {"temperature":30 C} </function_response>"""}
 ]