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Add a quick opt-in option to switch to gpt-5 model (#1534)
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19 files changed

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-74
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19 files changed

+277
-74
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‎examples/financial_research_agent/agents/search_agent.py

Lines changed: 1 addition & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -12,6 +12,7 @@
1212

1313
search_agent = Agent(
1414
name="FinancialSearchAgent",
15+
model="gpt-4.1",
1516
instructions=INSTRUCTIONS,
1617
tools=[WebSearchTool()],
1718
model_settings=ModelSettings(tool_choice="required"),

‎examples/handoffs/message_filter.py

Lines changed: 10 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -5,6 +5,7 @@
55

66
from agents import Agent, HandoffInputData, Runner, function_tool, handoff, trace
77
from agents.extensions import handoff_filters
8+
from agents.models import is_gpt_5_default
89

910

1011
@function_tool
@@ -14,6 +15,15 @@ def random_number_tool(max: int) -> int:
1415

1516

1617
def spanish_handoff_message_filter(handoff_message_data: HandoffInputData) -> HandoffInputData:
18+
if is_gpt_5_default():
19+
print("gpt-5 is enabled, so we're not filtering the input history")
20+
# when using gpt-5, removing some of the items could break things, so we do this filtering only for other models
21+
return HandoffInputData(
22+
input_history=handoff_message_data.input_history,
23+
pre_handoff_items=tuple(handoff_message_data.pre_handoff_items),
24+
new_items=tuple(handoff_message_data.new_items),
25+
)
26+
1727
# First, we'll remove any tool-related messages from the message history
1828
handoff_message_data = handoff_filters.remove_all_tools(handoff_message_data)
1929

‎examples/handoffs/message_filter_streaming.py

Lines changed: 10 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -5,6 +5,7 @@
55

66
from agents import Agent, HandoffInputData, Runner, function_tool, handoff, trace
77
from agents.extensions import handoff_filters
8+
from agents.models import is_gpt_5_default
89

910

1011
@function_tool
@@ -14,6 +15,15 @@ def random_number_tool(max: int) -> int:
1415

1516

1617
def spanish_handoff_message_filter(handoff_message_data: HandoffInputData) -> HandoffInputData:
18+
if is_gpt_5_default():
19+
print("gpt-5 is enabled, so we're not filtering the input history")
20+
# when using gpt-5, removing some of the items could break things, so we do this filtering only for other models
21+
return HandoffInputData(
22+
input_history=handoff_message_data.input_history,
23+
pre_handoff_items=tuple(handoff_message_data.pre_handoff_items),
24+
new_items=tuple(handoff_message_data.new_items),
25+
)
26+
1727
# First, we'll remove any tool-related messages from the message history
1828
handoff_message_data = handoff_filters.remove_all_tools(handoff_message_data)
1929

‎examples/hosted_mcp/approvals.py

Lines changed: 4 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -44,7 +44,10 @@ async def main(verbose: bool, stream: bool):
4444
print(f"Got event of type {event.item.__class__.__name__}")
4545
print(f"Done streaming; final result: {result.final_output}")
4646
else:
47-
res = await Runner.run(agent, "Which language is this repo written in?")
47+
res = await Runner.run(
48+
agent,
49+
"Which language is this repo written in? Your MCP server should know what the repo is.",
50+
)
4851
print(res.final_output)
4952

5053
if verbose:

‎examples/hosted_mcp/simple.py

Lines changed: 4 additions & 1 deletion
Original file line numberDiff line numberDiff line change
@@ -29,7 +29,10 @@ async def main(verbose: bool, stream: bool):
2929
print(f"Got event of type {event.item.__class__.__name__}")
3030
print(f"Done streaming; final result: {result.final_output}")
3131
else:
32-
res = await Runner.run(agent, "Which language is this repo written in?")
32+
res = await Runner.run(
33+
agent,
34+
"Which language is this repo written in? Your MCP server should know what the repo is.",
35+
)
3336
print(res.final_output)
3437
# The repository is primarily written in multiple languages, including Rust and TypeScript...
3538

‎examples/reasoning_content/main.py

Lines changed: 17 additions & 19 deletions
Original file line numberDiff line numberDiff line change
@@ -1,25 +1,26 @@
11
"""
22
Example demonstrating how to use the reasoning content feature with models that support it.
33
4-
Some models, like deepseek-reasoner, provide a reasoning_content field in addition to the regular content.
4+
Some models, like gpt-5, provide a reasoning_content field in addition to the regular content.
55
This example shows how to access and use this reasoning content from both streaming and non-streaming responses.
66
77
To run this example, you need to:
88
1. Set your OPENAI_API_KEY environment variable
9-
2. Use a model that supports reasoning content (e.g., deepseek-reasoner)
9+
2. Use a model that supports reasoning content (e.g., gpt-5)
1010
"""
1111

1212
import asyncio
1313
import os
1414
from typing import Any, cast
1515

1616
from openai.types.responses import ResponseOutputRefusal, ResponseOutputText
17+
from openai.types.shared.reasoning import Reasoning
1718

1819
from agents import ModelSettings
1920
from agents.models.interface import ModelTracing
2021
from agents.models.openai_provider import OpenAIProvider
2122

22-
MODEL_NAME = os.getenv("EXAMPLE_MODEL_NAME") or "deepseek-reasoner"
23+
MODEL_NAME = os.getenv("EXAMPLE_MODEL_NAME") or "gpt-5"
2324

2425

2526
async def stream_with_reasoning_content():
@@ -36,10 +37,11 @@ async def stream_with_reasoning_content():
3637
reasoning_content = ""
3738
regular_content = ""
3839

40+
output_text_already_started = False
3941
async for event in model.stream_response(
4042
system_instructions="You are a helpful assistant that writes creative content.",
4143
input="Write a haiku about recursion in programming",
42-
model_settings=ModelSettings(),
44+
model_settings=ModelSettings(reasoning=Reasoning(effort="medium", summary="detailed")),
4345
tools=[],
4446
output_schema=None,
4547
handoffs=[],
@@ -48,18 +50,16 @@ async def stream_with_reasoning_content():
4850
prompt=None,
4951
):
5052
if event.type == "response.reasoning_summary_text.delta":
51-
print(
52-
f"\033[33m{event.delta}\033[0m", end="", flush=True
53-
) # Yellow for reasoning content
53+
# Yellow for reasoning content
54+
print(f"\033[33m{event.delta}\033[0m", end="", flush=True)
5455
reasoning_content += event.delta
5556
elif event.type == "response.output_text.delta":
56-
print(f"\033[32m{event.delta}\033[0m", end="", flush=True) # Green for regular content
57+
if not output_text_already_started:
58+
print("\n")
59+
output_text_already_started = True
60+
# Green for regular content
61+
print(f"\033[32m{event.delta}\033[0m", end="", flush=True)
5762
regular_content += event.delta
58-
59-
print("\n\nReasoning Content:")
60-
print(reasoning_content)
61-
print("\nRegular Content:")
62-
print(regular_content)
6363
print("\n")
6464

6565

@@ -77,7 +77,7 @@ async def get_response_with_reasoning_content():
7777
response = await model.get_response(
7878
system_instructions="You are a helpful assistant that explains technical concepts clearly.",
7979
input="Explain the concept of recursion in programming",
80-
model_settings=ModelSettings(),
80+
model_settings=ModelSettings(reasoning=Reasoning(effort="medium", summary="detailed")),
8181
tools=[],
8282
output_schema=None,
8383
handoffs=[],
@@ -102,12 +102,10 @@ async def get_response_with_reasoning_content():
102102
refusal_item = cast(Any, content_item)
103103
regular_content = refusal_item.refusal
104104

105-
print("\nReasoning Content:")
105+
print("\n\n### Reasoning Content:")
106106
print(reasoning_content or "No reasoning content provided")
107-
108-
print("\nRegular Content:")
107+
print("\n\n### Regular Content:")
109108
print(regular_content or "No regular content provided")
110-
111109
print("\n")
112110

113111

@@ -118,7 +116,7 @@ async def main():
118116
except Exception as e:
119117
print(f"Error: {e}")
120118
print("\nNote: This example requires a model that supports reasoning content.")
121-
print("You may need to use a specific model like deepseek-reasoner or similar.")
119+
print("You may need to use a specific model like gpt-5 or similar.")
122120

123121

124122
if __name__ == "__main__":

‎examples/reasoning_content/runner_example.py

Lines changed: 23 additions & 40 deletions
Original file line numberDiff line numberDiff line change
@@ -6,17 +6,18 @@
66
77
To run this example, you need to:
88
1. Set your OPENAI_API_KEY environment variable
9-
2. Use a model that supports reasoning content (e.g., deepseek-reasoner)
9+
2. Use a model that supports reasoning content (e.g., gpt-5)
1010
"""
1111

1212
import asyncio
1313
import os
14-
from typing import Any
1514

16-
from agents import Agent, Runner, trace
15+
from openai.types.shared.reasoning import Reasoning
16+
17+
from agents import Agent, ModelSettings, Runner, trace
1718
from agents.items import ReasoningItem
1819

19-
MODEL_NAME = os.getenv("EXAMPLE_MODEL_NAME") or "deepseek-reasoner"
20+
MODEL_NAME = os.getenv("EXAMPLE_MODEL_NAME") or "gpt-5"
2021

2122

2223
async def main():
@@ -27,6 +28,7 @@ async def main():
2728
name="Reasoning Agent",
2829
instructions="You are a helpful assistant that explains your reasoning step by step.",
2930
model=MODEL_NAME,
31+
model_settings=ModelSettings(reasoning=Reasoning(effort="medium", summary="detailed")),
3032
)
3133

3234
# Example 1: Non-streaming response
@@ -35,53 +37,34 @@ async def main():
3537
result = await Runner.run(
3638
agent, "What is the square root of 841? Please explain your reasoning."
3739
)
38-
3940
# Extract reasoning content from the result items
4041
reasoning_content = None
41-
# RunResult has 'response' attribute which has 'output' attribute
42-
for item in result.response.output: # type: ignore
43-
if isinstance(item, ReasoningItem):
44-
reasoning_content = item.summary[0].text # type: ignore
42+
for item in result.new_items:
43+
if isinstance(item, ReasoningItem) and len(item.raw_item.summary) > 0:
44+
reasoning_content = item.raw_item.summary[0].text
4545
break
4646

47-
print("\nReasoning Content:")
47+
print("\n### Reasoning Content:")
4848
print(reasoning_content or "No reasoning content provided")
49-
50-
print("\nFinal Output:")
49+
print("\n### Final Output:")
5150
print(result.final_output)
5251

5352
# Example 2: Streaming response
5453
with trace("Reasoning Content - Streaming"):
5554
print("\n=== Example 2: Streaming response ===")
56-
print("\nStreaming response:")
57-
58-
# Buffers to collect reasoning and regular content
59-
reasoning_buffer = ""
60-
content_buffer = ""
61-
62-
# RunResultStreaming is async iterable
6355
stream = Runner.run_streamed(agent, "What is 15 x 27? Please explain your reasoning.")
64-
65-
async for event in stream: # type: ignore
66-
if isinstance(event, ReasoningItem):
67-
# This is reasoning content
68-
reasoning_item: Any = event
69-
reasoning_buffer += reasoning_item.summary[0].text
70-
print(
71-
f"\033[33m{reasoning_item.summary[0].text}\033[0m", end="", flush=True
72-
) # Yellow for reasoning
73-
elif hasattr(event, "text"):
74-
# This is regular content
75-
content_buffer += event.text
76-
print(
77-
f"\033[32m{event.text}\033[0m", end="", flush=True
78-
) # Green for regular content
79-
80-
print("\n\nCollected Reasoning Content:")
81-
print(reasoning_buffer)
82-
83-
print("\nCollected Final Answer:")
84-
print(content_buffer)
56+
output_text_already_started = False
57+
async for event in stream.stream_events():
58+
if event.type == "raw_response_event":
59+
if event.data.type == "response.reasoning_summary_text.delta":
60+
print(f"\033[33m{event.data.delta}\033[0m", end="", flush=True)
61+
elif event.data.type == "response.output_text.delta":
62+
if not output_text_already_started:
63+
print("\n")
64+
output_text_already_started = True
65+
print(f"\033[32m{event.data.delta}\033[0m", end="", flush=True)
66+
67+
print("\n")
8568

8669

8770
if __name__ == "__main__":

‎examples/research_bot/agents/planner_agent.py

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1,6 +1,7 @@
1+
from openai.types.shared.reasoning import Reasoning
12
from pydantic import BaseModel
23

3-
from agents import Agent
4+
from agents import Agent, ModelSettings
45

56
PROMPT = (
67
"You are a helpful research assistant. Given a query, come up with a set of web searches "
@@ -24,6 +25,7 @@ class WebSearchPlan(BaseModel):
2425
planner_agent = Agent(
2526
name="PlannerAgent",
2627
instructions=PROMPT,
27-
model="gpt-4o",
28+
model="gpt-5",
29+
model_settings=ModelSettings(reasoning=Reasoning(effort="medium")),
2830
output_type=WebSearchPlan,
2931
)

‎examples/research_bot/agents/search_agent.py

Lines changed: 3 additions & 0 deletions
Original file line numberDiff line numberDiff line change
@@ -12,7 +12,10 @@
1212

1313
search_agent = Agent(
1414
name="Search agent",
15+
model="gpt-4.1",
1516
instructions=INSTRUCTIONS,
1617
tools=[WebSearchTool()],
18+
# Note that gpt-5 model does not support tool_choice="required",
19+
# so if you want to migrate to gpt-5, you'll need to use "auto" instead
1720
model_settings=ModelSettings(tool_choice="required"),
1821
)

‎examples/research_bot/agents/writer_agent.py

Lines changed: 4 additions & 2 deletions
Original file line numberDiff line numberDiff line change
@@ -1,7 +1,8 @@
11
# Agent used to synthesize a final report from the individual summaries.
2+
from openai.types.shared.reasoning import Reasoning
23
from pydantic import BaseModel
34

4-
from agents import Agent
5+
from agents import Agent, ModelSettings
56

67
PROMPT = (
78
"You are a senior researcher tasked with writing a cohesive report for a research query. "
@@ -28,6 +29,7 @@ class ReportData(BaseModel):
2829
writer_agent = Agent(
2930
name="WriterAgent",
3031
instructions=PROMPT,
31-
model="o3-mini",
32+
model="gpt-5-mini",
33+
model_settings=ModelSettings(reasoning=Reasoning(effort="medium")),
3234
output_type=ReportData,
3335
)

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