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Add support for GPT-5 family and recent OpenAI o-series models #238

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Add support for GPT-5 family and recent OpenAI o-series models #238

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68 changes: 57 additions & 11 deletions ai_scientist/llm.py
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Original file line number Diff line number Diff line change
Expand Up @@ -14,25 +14,63 @@
# Anthropic models
"claude-3-5-sonnet-20240620",
"claude-3-5-sonnet-20241022",
# OpenAI models
"gpt-4o-mini",
"gpt-4o-mini-2024-07-18",
# OpenAI GPT-5.4 models
"gpt-5.4",
"gpt-5.4-2026-03-05",
"gpt-5.4-pro",
"gpt-5.4-mini",
"gpt-5.4-mini-2026-03-17",
"gpt-5.4-nano",
"gpt-5.4-nano-2026-03-17",
# OpenAI GPT-5.2 models
"gpt-5.2",
"gpt-5.2-2025-12-11",
"gpt-5.2-pro",
"gpt-5.2-chat-latest",
# OpenAI GPT-5.1 models
"gpt-5.1",
"gpt-5.1-chat-latest",
# OpenAI GPT-5 models
"gpt-5",
"gpt-5-2025-08-07",
"gpt-5-pro",
"gpt-5-mini",
"gpt-5-mini-2025-08-07",
"gpt-5-nano",
"gpt-5-chat-latest",
# OpenAI GPT-4 models
"gpt-4o",
"gpt-4o-2024-05-13",
"gpt-4o-2024-08-06",
"gpt-4o-mini",
"gpt-4o-mini-2024-07-18",
"chatgpt-4o-latest",
"gpt-4.5-preview",
"gpt-4.1",
"gpt-4.1-2025-04-14",
"gpt-4.1-mini",
"gpt-4.1-mini-2025-04-14",
"gpt-4.1-nano",
"gpt-4.1-nano-2025-04-14",
"gpt-4-turbo",
"gpt-4-turbo-2024-04-09",
"gpt-4",
"gpt-4-0613",
"gpt-3.5-turbo",
# OpenAI o-series reasoning models
"o4-mini",
"o4-mini-2025-04-16",
"o3",
"o3-pro",
"o3-pro-2025-06-10",
"o3-mini",
"o3-mini-2025-01-31",
"o1",
"o1-2024-12-17",
"o1-pro",
"o1-preview-2024-09-12",
"o1-mini",
"o1-mini-2024-09-12",
"o3-mini",
"o3-mini-2025-01-31",
# OpenRouter models
"llama3.1-405b",
# Anthropic Claude models via Amazon Bedrock
Expand Down Expand Up @@ -79,18 +117,22 @@ def get_batch_responses_from_llm(

if 'gpt' in model:
new_msg_history = msg_history + [{"role": "user", "content": msg}]
response = client.chat.completions.create(
kwargs = dict(
model=model,
messages=[
{"role": "system", "content": system_message},
*new_msg_history,
],
temperature=temperature,
max_tokens=MAX_NUM_TOKENS,
n=n_responses,
stop=None,
seed=0,
)
if "gpt-5" in model:
kwargs["max_completion_tokens"] = MAX_NUM_TOKENS
else:
kwargs["max_tokens"] = MAX_NUM_TOKENS
response = client.chat.completions.create(**kwargs)
content = [r.message.content for r in response.choices]
new_msg_history = [
new_msg_history + [{"role": "assistant", "content": c}] for c in content
Expand Down Expand Up @@ -185,21 +227,25 @@ def get_response_from_llm(
]
elif 'gpt' in model:
new_msg_history = msg_history + [{"role": "user", "content": msg}]
response = client.chat.completions.create(
kwargs = dict(
model=model,
messages=[
{"role": "system", "content": system_message},
*new_msg_history,
],
temperature=temperature,
max_tokens=MAX_NUM_TOKENS,
n=1,
stop=None,
seed=0,
)
if "gpt-5" in model:
kwargs["max_completion_tokens"] = MAX_NUM_TOKENS
else:
kwargs["max_tokens"] = MAX_NUM_TOKENS
response = client.chat.completions.create(**kwargs)
content = response.choices[0].message.content
new_msg_history = new_msg_history + [{"role": "assistant", "content": content}]
elif "o1" in model or "o3" in model:
elif "o1" in model or "o3" in model or "o4" in model:
new_msg_history = msg_history + [{"role": "user", "content": msg}]
response = client.chat.completions.create(
model=model,
Expand Down Expand Up @@ -326,7 +372,7 @@ def create_client(model):
client_model = model.split("/")[-1]
print(f"Using Vertex AI with model {client_model}.")
return anthropic.AnthropicVertex(), client_model
elif 'gpt' in model or "o1" in model or "o3" in model:
elif 'gpt' in model or "o1" in model or "o3" in model or "o4" in model:
print(f"Using OpenAI API with model {model}.")
return openai.OpenAI(), model
elif model in ["deepseek-chat", "deepseek-reasoner", "deepseek-coder"]:
Expand Down