update parsing

src/llm/chat.py

@@ -15,6 +15,7 @@ You SHOULD NOT include any other text in the response.
 
 Here is a list of functions in JSON format that you can invoke.\n\n{functions}\n""".format(functions=FUNCTION_SCHEMA)
 
+
 device = "cuda" if torch.cuda.is_available() else "cpu"
 
 class FunctionCallingChat:
@@ -42,21 +43,24 @@ class FunctionCallingChat:
 
         output = self.model.generate(tokenized, generation_config=generation_cfg)
         raw    = self.tokenizer.decode(output[0], skip_special_tokens=True)
-        tool_calls_str = raw.split("assistant")[-1]
+        tool_calls_lst_str = raw.split("assistant")[-1]     
 
         try:
-            calls = ast.literal_eval(tool_calls_str)
-        except Exception as e:
-            calls = []
-            print(f"Error parsing tool calls: {e}", file=sys.stderr)
-
-        if calls == []:
-            return {"raw_tool_call": tool_calls_str, "results": "No function call detected."}
-        else:
-            results = []
-            for call in calls:
-                fn_name  = call.func.id
-                kwargs   = {kw.arg: ast.literal_eval(kw.value) for kw in call.keywords}
-                results.append(TOOLS[fn_name](**kwargs))
-
-            return {"raw_tool_call": tool_calls_str, "results": results}
+            tree       = ast.parse(tool_calls_lst_str, mode="eval")
+            call_nodes = tree.body.elts      
+        except SyntaxError:
+
+            return {"raw_tool_call": tool_calls_lst_str,
+                    "results": "Cannot parse the function call."}
+
+        tool_calls_result = []
+        for call in call_nodes:
+            function_name = call.func.id
+            parameters = {kw.arg: ast.literal_eval(kw.value)
+                        for kw in call.keywords}
+
+            result = TOOLS[function_name](**parameters)
+            tool_calls_result.append(result)
+
+        return {"raw_tool_call": tool_calls_lst_str,
+                "results": tool_calls_result}