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feat: run benchmark on gpt-4o & llama 3.1 (#497)

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* Run benchmark on gpt-4o & llama 3.1

* update link
This commit is contained in:
you-n-g
2024-11-26 12:02:09 +08:00
committed by GitHub
parent d54e14f1d9
commit c3f78f8bce
7 changed files with 389 additions and 64 deletions
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rdagent/components/coder/factor_coder/evolving_strategy.py
+14 -8
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@@ -158,14 +158,20 @@ class FactorMultiProcessEvolvingStrategy(MultiProcessEvolvingStrategy):
queried_similar_successful_knowledge_to_render = queried_similar_successful_knowledge_to_render[:-1]
elif len(queried_similar_error_knowledge_to_render) > 0:
queried_similar_error_knowledge_to_render = queried_similar_error_knowledge_to_render[:-1]
code = json.loads(
APIBackend(
use_chat_cache=FACTOR_COSTEER_SETTINGS.coder_use_cache
).build_messages_and_create_chat_completion(
user_prompt=user_prompt, system_prompt=system_prompt, json_mode=True
)
)["code"]
return code
for _ in range(10):
try:
code = json.loads(
APIBackend(
use_chat_cache=FACTOR_COSTEER_SETTINGS.coder_use_cache
).build_messages_and_create_chat_completion(
user_prompt=user_prompt, system_prompt=system_prompt, json_mode=True
)
)["code"]
return code
except json.decoder.JSONDecodeError:
pass
else:
return "" # return empty code if failed to get code after 10 attempts
def assign_code_list_to_evo(self, code_list, evo):
for index in range(len(evo.sub_tasks)):