Merge pull request #1552 from didiforgithub/main

Fix JSON Load Error & Fix Claude Token Calculate Error.

examples/aflow/optimize.py

@@ -72,7 +72,12 @@ def parse_args():
     parser.add_argument("--max_rounds", type=int, default=20, help="Max iteration rounds")
     parser.add_argument("--check_convergence", type=bool, default=True, help="Whether to enable early stop")
     parser.add_argument("--validation_rounds", type=int, default=5, help="Validation rounds")
-    parser.add_argument("--if_first_optimize", type=bool, default=True, help="Whether it's the first optimization")
+    parser.add_argument(
+        "--if_first_optimize",
+        type=lambda x: x.lower() == "true",
+        default=True,
+        help="Whether to download dataset for the first time",
+    )
     return parser.parse_args()
 
 

metagpt/ext/aflow/scripts/optimizer_utils/data_utils.py

@@ -18,7 +18,11 @@ class DataUtils:
     def load_results(self, path: str) -> list:
         result_path = os.path.join(path, "results.json")
         if os.path.exists(result_path):
-            return read_json_file(result_path, encoding="utf-8")
+            with open(result_path, "r") as json_file:
+                try:
+                    return json.load(json_file)
+                except json.JSONDecodeError:
+                    return []
         return []
 
     def get_top_rounds(self, sample: int, path=None, mode="Graph"):

metagpt/utils/token_counter.py

@@ -10,6 +10,7 @@ ref3: https://github.com/Significant-Gravitas/Auto-GPT/blob/master/autogpt/llm/t
 ref4: https://github.com/hwchase17/langchain/blob/master/langchain/chat_models/openai.py
 ref5: https://ai.google.dev/models/gemini
 """
+import anthropic
 import tiktoken
 from openai.types import CompletionUsage
 from openai.types.chat import ChatCompletionChunk
@@ -377,6 +378,10 @@ SPARK_TOKENS = {
 
 def count_input_tokens(messages, model="gpt-3.5-turbo-0125"):
     """Return the number of tokens used by a list of messages."""
+    if "claude" in model:
+        vo = anthropic.Client()
+        num_tokens = vo.count_tokens(str(messages))
+        return num_tokens
     try:
         encoding = tiktoken.encoding_for_model(model)
     except KeyError:
@@ -463,6 +468,10 @@ def count_output_tokens(string: str, model: str) -> int:
     Returns:
         int: The number of tokens in the text string.
     """
+    if "claude" in model:
+        vo = anthropic.Client()
+        num_tokens = vo.count_tokens(string)
+        return num_tokens
     try:
         encoding = tiktoken.encoding_for_model(model)
     except KeyError: