add a function call demo

function_call_demo/main.py

@@ -0,0 +1,74 @@
+import json
+import re
+from json import JSONDecodeError
+
+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+
+
+def main():
+    device = "cuda" if torch.cuda.is_available() else "cpu"
+    model_name_or_path = "THUDM/codegeex4-all-9b"
+    tokenizer = AutoTokenizer.from_pretrained(model_name_or_path, trust_remote_code=True)
+    model = AutoModelForCausalLM.from_pretrained(
+        model_name_or_path,
+        torch_dtype=torch.bfloat16,
+        trust_remote_code=True
+    ).to(device).eval()
+
+    tool_content = {
+        "function": [
+            {
+                "name": "weather",
+                "description": "Use for searching weather at a specific location",
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        "location": {
+                            "description": "the location need to check the weather",
+                            "tyoe": "str",
+                        }
+                    },
+                    "required": [
+                        "location"
+                    ]
+                }
+            }
+        ]
+    }
+    response, _ = model.chat(
+        tokenizer,
+        query="Tell me about the weather in Beijing",
+        history=[{"role": "tool", "content": tool_content}],
+        max_new_tokens=1024,
+        temperature=0.1
+    )
+
+    # support parallel calls, thus the result is a list
+    functions = post_process(response)
+    try:
+        return [json.loads(func) for func in functions if func]
+    # get rid of some possible invalid formats
+    except JSONDecodeError:
+        try:
+            return [json.loads(func.replace('(', '[').replace(')', ']')) for func in functions if func]
+        except JSONDecodeError:
+            try:
+                return [json.loads(func.replace("'", '"')) for func in functions if func]
+            except JSONDecodeError as e:
+                return [{"answer": response, "errors": e}]
+
+
+def post_process(text: str) -> list[str]:
+    """
+    Process model's response.
+    In case there are parallel calls, each call is warpped with ```json```.
+    """
+    pattern = r'```json(.*?)```'
+    matches = re.findall(pattern, text, re.DOTALL)
+    return matches
+
+
+if __name__ == '__main__':
+    output = main()
+    print(output)  # [{"name": "weather", "arguments": {"location": "Beijing"}}]