Adriano/Multi_Swarm_Coevolutive
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

refactor(llm): route all tiers via OpenRouter, drop Anthropic SDK

Browse Source 
Tutti i tier (S/A/B/C/D) ora passano per OpenRouter via OpenAI SDK.
Modelli Anthropic raggiungibili via prefisso `anthropic/...`.

- pyproject: rimosso `anthropic>=0.39` da deps + uv.lock
- config: rimosso `anthropic_api_key` field
- LLMClient: dispatch unico, single client OpenAI con base_url OpenRouter
- defaults S/A/B → `anthropic/claude-{opus-4-7,sonnet-4-6}`
- retry exceptions: solo openai.* (drop anthropic.*)
- test rinominati e adattati: tier S/A/B mockano OpenAI con prefisso `anthropic/`
- rimosso test `tier_S_without_anthropic_key_raises` (non più rilevante)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
This commit is contained in:
AdrianoDev
2026-05-10 09:39:23 +02:00
parent 70b8bc3d6c
commit 4dad8be36b
8 changed files with 84 additions and 177 deletions
Download Patch File Download Diff File Expand all files Collapse all files
.env.example
+6 -7
View File
@@ -4,17 +4,16 @@ CERBERO_TESTNET_TOKEN=
CERBERO_MAINNET_TOKEN=
CERBERO_BOT_TAG=swarm-poc-phase1
# LLM providers
# LLM provider (single endpoint via OpenRouter — supports anthropic/openai/qwen/llama models)
OPENROUTER_API_KEY=
ANTHROPIC_API_KEY=
OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
# LLM models (override Phase 1 defaults if needed)
LLM_MODEL_TIER_S=claude-opus-4-7
LLM_MODEL_TIER_A=claude-sonnet-4-6
LLM_MODEL_TIER_B=claude-sonnet-4-6
# Models per tier (override Phase 1 defaults if needed)
LLM_MODEL_TIER_S=anthropic/claude-opus-4-7
LLM_MODEL_TIER_A=anthropic/claude-sonnet-4-6
LLM_MODEL_TIER_B=anthropic/claude-sonnet-4-6
LLM_MODEL_TIER_C=qwen/qwen-2.5-72b-instruct
LLM_MODEL_TIER_D=meta-llama/llama-3.3-70b-instruct
OPENROUTER_BASE_URL=https://openrouter.ai/api/v1
# Run config
RUN_NAME=phase1-spike-001
pyproject.toml
-1
View File
@@ -13,7 +13,6 @@ dependencies = [
"pydantic-settings>=2.6",
"sqlmodel>=0.0.22",
"sexpdata>=1.0.2",
"anthropic>=0.39",
"openai>=1.55",
"httpx>=0.28",
"requests>=2.32",
scripts/run_phase1.py
-4
View File
@@ -44,10 +44,6 @@ def main() -> None:
llm = LLMClient(
openrouter_api_key=settings.openrouter_api_key.get_secret_value(),
anthropic_api_key=(
settings.anthropic_api_key.get_secret_value()
if settings.anthropic_api_key else None
),
model_tier_s=settings.llm_model_tier_s,
model_tier_a=settings.llm_model_tier_a,
model_tier_b=settings.llm_model_tier_b,
src/multi_swarm/config.py
+3 -4
View File
@@ -24,11 +24,10 @@ class Settings(BaseSettings):
cerbero_bot_tag: str = "swarm-poc-phase1"
openrouter_api_key: SecretStr
anthropic_api_key: SecretStr | None = None
llm_model_tier_s: str = "claude-opus-4-7"
llm_model_tier_a: str = "claude-sonnet-4-6"
llm_model_tier_b: str = "claude-sonnet-4-6"
llm_model_tier_s: str = "anthropic/claude-opus-4-7"
llm_model_tier_a: str = "anthropic/claude-sonnet-4-6"
llm_model_tier_b: str = "anthropic/claude-sonnet-4-6"
llm_model_tier_c: str = "qwen/qwen-2.5-72b-instruct"
llm_model_tier_d: str = "meta-llama/llama-3.3-70b-instruct"
openrouter_base_url: str = "https://openrouter.ai/api/v1"
src/multi_swarm/llm/client.py
+8 -59
View File
@@ -2,9 +2,7 @@ from __future__ import annotations
from dataclasses import dataclass
import anthropic
import openai
from anthropic import Anthropic
from openai import OpenAI
from tenacity import (
retry,
@@ -15,12 +13,12 @@ from tenacity import (
from ..genome.hypothesis import HypothesisAgentGenome, ModelTier
# Modelli configurati per Phase 1
MODEL_TIER_S = "claude-opus-4-7" # via Anthropic
MODEL_TIER_A = "claude-sonnet-4-6" # via Anthropic (premium override)
MODEL_TIER_B = "claude-sonnet-4-6" # via Anthropic
MODEL_TIER_C = "qwen/qwen-2.5-72b-instruct" # via OpenRouter
MODEL_TIER_D = "meta-llama/llama-3.3-70b-instruct" # via OpenRouter
# Modelli configurati per Phase 1 — tutti via OpenRouter
MODEL_TIER_S = "anthropic/claude-opus-4-7"
MODEL_TIER_A = "anthropic/claude-sonnet-4-6"
MODEL_TIER_B = "anthropic/claude-sonnet-4-6"
MODEL_TIER_C = "qwen/qwen-2.5-72b-instruct"
MODEL_TIER_D = "meta-llama/llama-3.3-70b-instruct"
OPENROUTER_BASE_URL = "https://openrouter.ai/api/v1"
# Errori transient: retry. RateLimit/Auth/InvalidRequest: NO retry.
@@ -28,9 +26,6 @@ _RETRYABLE_EXCEPTIONS: tuple[type[BaseException], ...] = (
openai.APIConnectionError,
openai.APITimeoutError,
openai.InternalServerError,
anthropic.APIConnectionError,
anthropic.APITimeoutError,
anthropic.InternalServerError,
)
@@ -44,13 +39,9 @@ class CompletionResult:
class LLMClient:
_ANTHROPIC_TIERS: tuple[ModelTier, ...] = (ModelTier.S, ModelTier.A, ModelTier.B)
_OPENROUTER_TIERS: tuple[ModelTier, ...] = (ModelTier.C, ModelTier.D)
def __init__(
self,
openrouter_api_key: str,
anthropic_api_key: str | None = None,
model_tier_s: str = MODEL_TIER_S,
model_tier_a: str = MODEL_TIER_A,
model_tier_b: str = MODEL_TIER_B,
@@ -71,8 +62,7 @@ class LLMClient:
ModelTier.C: model_tier_c,
ModelTier.D: model_tier_d,
}
self._openrouter = OpenAI(api_key=openrouter_api_key, base_url=openrouter_base_url)
self._anthropic = Anthropic(api_key=anthropic_api_key) if anthropic_api_key else None
self._client = OpenAI(api_key=openrouter_api_key, base_url=openrouter_base_url)
@retry(
stop=stop_after_attempt(3),
@@ -88,19 +78,7 @@ class LLMClient:
max_tokens: int = 2000,
) -> CompletionResult:
model = self._tier_models[genome.model_tier]
if genome.model_tier in self._ANTHROPIC_TIERS:
return self._call_anthropic(genome, system, user, max_tokens, model)
return self._call_openrouter(genome, system, user, max_tokens, model)
def _call_openrouter(
self,
genome: HypothesisAgentGenome,
system: str,
user: str,
max_tokens: int,
model: str,
) -> CompletionResult:
resp = self._openrouter.chat.completions.create(
resp = self._client.chat.completions.create(
model=model,
messages=[
{"role": "system", "content": system},
@@ -119,32 +97,3 @@ class LLMClient:
tier=genome.model_tier,
model=model,
)
def _call_anthropic(
self,
genome: HypothesisAgentGenome,
system: str,
user: str,
max_tokens: int,
model: str,
) -> CompletionResult:
if self._anthropic is None:
raise RuntimeError(
f"ANTHROPIC_API_KEY required for tier {genome.model_tier.value} genomes"
)
msg = self._anthropic.messages.create(
model=model,
system=system,
messages=[{"role": "user", "content": user}],
temperature=genome.temperature,
top_p=genome.top_p,
max_tokens=max_tokens,
)
text = "".join(block.text for block in msg.content if hasattr(block, "text"))
return CompletionResult(
text=text,
input_tokens=msg.usage.input_tokens,
output_tokens=msg.usage.output_tokens,
tier=genome.model_tier,
model=model,
)
tests/unit/test_config.py
+3 -4
View File
@@ -19,7 +19,6 @@ def test_settings_loads_from_env(monkeypatch: pytest.MonkeyPatch) -> None:
monkeypatch.setenv("CERBERO_MAINNET_TOKEN", "tok-main")
monkeypatch.setenv("CERBERO_BOT_TAG", "swarm-poc-phase1")
monkeypatch.setenv("OPENROUTER_API_KEY", "or-key")
monkeypatch.setenv("ANTHROPIC_API_KEY", "an-key")
monkeypatch.setenv("RUN_NAME", "test-run")
s = Settings() # type: ignore[call-arg]
@@ -74,9 +73,9 @@ def test_settings_llm_model_defaults(monkeypatch: pytest.MonkeyPatch) -> None:
s = Settings(_env_file=None) # type: ignore[call-arg]
assert s.llm_model_tier_s == "claude-opus-4-7"
assert s.llm_model_tier_a == "claude-sonnet-4-6"
assert s.llm_model_tier_b == "claude-sonnet-4-6"
assert s.llm_model_tier_s == "anthropic/claude-opus-4-7"
assert s.llm_model_tier_a == "anthropic/claude-sonnet-4-6"
assert s.llm_model_tier_b == "anthropic/claude-sonnet-4-6"
assert s.llm_model_tier_c == "qwen/qwen-2.5-72b-instruct"
assert s.llm_model_tier_d == "meta-llama/llama-3.3-70b-instruct"
assert s.openrouter_base_url == "https://openrouter.ai/api/v1"
tests/unit/test_llm_client.py
+64 -68
View File
@@ -25,7 +25,7 @@ def test_completion_tier_c_uses_openrouter(mocker):
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key=None)
client = LLMClient(openrouter_api_key="or-x")
g = make_genome(ModelTier.C)
out = client.complete(g, system="sys", user="usr")
@@ -37,15 +37,15 @@ def test_completion_tier_c_uses_openrouter(mocker):
fake_openai.chat.completions.create.assert_called_once()
def test_completion_tier_b_uses_anthropic(mocker):
fake_anthropic = mocker.MagicMock()
fake_msg = mocker.MagicMock()
fake_msg.content = [mocker.MagicMock(text="(strategy ...)")]
fake_msg.usage = mocker.MagicMock(input_tokens=80, output_tokens=150)
fake_anthropic.messages.create.return_value = fake_msg
mocker.patch("multi_swarm.llm.client.Anthropic", return_value=fake_anthropic)
def test_completion_tier_b_uses_openrouter_with_anthropic_model(mocker):
fake_openai = mocker.MagicMock()
fake_response = mocker.MagicMock()
fake_response.choices = [mocker.MagicMock(message=mocker.MagicMock(content="(strategy ...)"))]
fake_response.usage = mocker.MagicMock(prompt_tokens=80, completion_tokens=150)
fake_openai.chat.completions.create.return_value = fake_response
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key="an-x")
client = LLMClient(openrouter_api_key="or-x")
g = make_genome(ModelTier.B)
out = client.complete(g, system="sys", user="usr")
@@ -53,6 +53,9 @@ def test_completion_tier_b_uses_anthropic(mocker):
assert out.input_tokens == 80
assert out.output_tokens == 150
assert out.tier == ModelTier.B
call_kwargs = fake_openai.chat.completions.create.call_args.kwargs
assert call_kwargs["model"] == "anthropic/claude-sonnet-4-6"
assert out.model == "anthropic/claude-sonnet-4-6"
@pytest.mark.slow
@@ -66,7 +69,7 @@ def test_completion_retries_on_connection_error(mocker):
)
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key=None)
client = LLMClient(openrouter_api_key="or-x")
g = make_genome(ModelTier.C)
with pytest.raises(openai.APIConnectionError):
@@ -87,7 +90,6 @@ def test_completion_uses_custom_model_tier_c(mocker):
client = LLMClient(
openrouter_api_key="or-x",
anthropic_api_key=None,
model_tier_c="deepseek/deepseek-chat",
)
g = make_genome(ModelTier.C)
@@ -100,63 +102,64 @@ def test_completion_uses_custom_model_tier_c(mocker):
def test_completion_uses_custom_model_tier_b(mocker):
fake_anthropic = mocker.MagicMock()
fake_msg = mocker.MagicMock()
fake_msg.content = [mocker.MagicMock(text="(strategy ...)")]
fake_msg.usage = mocker.MagicMock(input_tokens=10, output_tokens=20)
fake_anthropic.messages.create.return_value = fake_msg
mocker.patch("multi_swarm.llm.client.Anthropic", return_value=fake_anthropic)
fake_openai = mocker.MagicMock()
fake_response = mocker.MagicMock()
fake_response.choices = [
mocker.MagicMock(message=mocker.MagicMock(content="(strategy ...)"))
]
fake_response.usage = mocker.MagicMock(prompt_tokens=10, completion_tokens=20)
fake_openai.chat.completions.create.return_value = fake_response
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(
openrouter_api_key="or-x",
anthropic_api_key="an-x",
model_tier_b="claude-opus-4-7",
model_tier_b="anthropic/claude-opus-4-7",
)
g = make_genome(ModelTier.B)
out = client.complete(g, system="sys", user="usr")
fake_anthropic.messages.create.assert_called_once()
call_kwargs = fake_anthropic.messages.create.call_args.kwargs
assert call_kwargs["model"] == "claude-opus-4-7"
assert out.model == "claude-opus-4-7"
fake_openai.chat.completions.create.assert_called_once()
call_kwargs = fake_openai.chat.completions.create.call_args.kwargs
assert call_kwargs["model"] == "anthropic/claude-opus-4-7"
assert out.model == "anthropic/claude-opus-4-7"
def test_completion_tier_s_uses_anthropic_with_opus(mocker):
fake_anthropic = mocker.MagicMock()
fake_msg = mocker.MagicMock()
fake_msg.content = [mocker.MagicMock(text="(strategy s)")]
fake_msg.usage = mocker.MagicMock(input_tokens=50, output_tokens=100)
fake_anthropic.messages.create.return_value = fake_msg
mocker.patch("multi_swarm.llm.client.Anthropic", return_value=fake_anthropic)
def test_completion_tier_s_uses_openrouter_with_anthropic_model(mocker):
fake_openai = mocker.MagicMock()
fake_response = mocker.MagicMock()
fake_response.choices = [mocker.MagicMock(message=mocker.MagicMock(content="(strategy s)"))]
fake_response.usage = mocker.MagicMock(prompt_tokens=50, completion_tokens=100)
fake_openai.chat.completions.create.return_value = fake_response
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key="an-x")
client = LLMClient(openrouter_api_key="or-x")
g = make_genome(ModelTier.S)
out = client.complete(g, system="sys", user="usr")
fake_anthropic.messages.create.assert_called_once()
call_kwargs = fake_anthropic.messages.create.call_args.kwargs
assert call_kwargs["model"] == "claude-opus-4-7"
fake_openai.chat.completions.create.assert_called_once()
call_kwargs = fake_openai.chat.completions.create.call_args.kwargs
assert call_kwargs["model"] == "anthropic/claude-opus-4-7"
assert out.tier == ModelTier.S
assert out.model == "claude-opus-4-7"
assert out.model == "anthropic/claude-opus-4-7"
def test_completion_tier_a_uses_anthropic_with_sonnet(mocker):
fake_anthropic = mocker.MagicMock()
fake_msg = mocker.MagicMock()
fake_msg.content = [mocker.MagicMock(text="(strategy a)")]
fake_msg.usage = mocker.MagicMock(input_tokens=40, output_tokens=80)
fake_anthropic.messages.create.return_value = fake_msg
mocker.patch("multi_swarm.llm.client.Anthropic", return_value=fake_anthropic)
def test_completion_tier_a_uses_openrouter_with_anthropic_model(mocker):
fake_openai = mocker.MagicMock()
fake_response = mocker.MagicMock()
fake_response.choices = [mocker.MagicMock(message=mocker.MagicMock(content="(strategy a)"))]
fake_response.usage = mocker.MagicMock(prompt_tokens=40, completion_tokens=80)
fake_openai.chat.completions.create.return_value = fake_response
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key="an-x")
client = LLMClient(openrouter_api_key="or-x")
g = make_genome(ModelTier.A)
out = client.complete(g, system="sys", user="usr")
fake_anthropic.messages.create.assert_called_once()
call_kwargs = fake_anthropic.messages.create.call_args.kwargs
assert call_kwargs["model"] == "claude-sonnet-4-6"
fake_openai.chat.completions.create.assert_called_once()
call_kwargs = fake_openai.chat.completions.create.call_args.kwargs
assert call_kwargs["model"] == "anthropic/claude-sonnet-4-6"
assert out.tier == ModelTier.A
assert out.model == "claude-sonnet-4-6"
assert out.model == "anthropic/claude-sonnet-4-6"
def test_completion_tier_d_uses_openrouter_with_llama(mocker):
@@ -169,7 +172,7 @@ def test_completion_tier_d_uses_openrouter_with_llama(mocker):
fake_openai.chat.completions.create.return_value = fake_response
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key=None)
client = LLMClient(openrouter_api_key="or-x")
g = make_genome(ModelTier.D)
out = client.complete(g, system="sys", user="usr")
@@ -181,32 +184,25 @@ def test_completion_tier_d_uses_openrouter_with_llama(mocker):
def test_completion_uses_custom_model_tier_s(mocker):
fake_anthropic = mocker.MagicMock()
fake_msg = mocker.MagicMock()
fake_msg.content = [mocker.MagicMock(text="(strategy custom-s)")]
fake_msg.usage = mocker.MagicMock(input_tokens=10, output_tokens=20)
fake_anthropic.messages.create.return_value = fake_msg
mocker.patch("multi_swarm.llm.client.Anthropic", return_value=fake_anthropic)
fake_openai = mocker.MagicMock()
fake_response = mocker.MagicMock()
fake_response.choices = [
mocker.MagicMock(message=mocker.MagicMock(content="(strategy custom-s)"))
]
fake_response.usage = mocker.MagicMock(prompt_tokens=10, completion_tokens=20)
fake_openai.chat.completions.create.return_value = fake_response
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(
openrouter_api_key="or-x",
anthropic_api_key="an-x",
model_tier_s="claude-future-mega",
model_tier_s="anthropic/claude-future-mega",
)
g = make_genome(ModelTier.S)
out = client.complete(g, system="sys", user="usr")
call_kwargs = fake_anthropic.messages.create.call_args.kwargs
assert call_kwargs["model"] == "claude-future-mega"
assert out.model == "claude-future-mega"
def test_completion_tier_s_without_anthropic_key_raises(mocker):
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=mocker.MagicMock())
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key=None)
g = make_genome(ModelTier.S)
with pytest.raises(RuntimeError, match="tier S"):
client.complete(g, system="sys", user="usr")
call_kwargs = fake_openai.chat.completions.create.call_args.kwargs
assert call_kwargs["model"] == "anthropic/claude-future-mega"
assert out.model == "anthropic/claude-future-mega"
@pytest.mark.slow
@@ -227,7 +223,7 @@ def test_completion_succeeds_after_one_retry(mocker):
]
mocker.patch("multi_swarm.llm.client.OpenAI", return_value=fake_openai)
client = LLMClient(openrouter_api_key="or-x", anthropic_api_key=None)
client = LLMClient(openrouter_api_key="or-x")
g = make_genome(ModelTier.C)
out = client.complete(g, system="sys", user="usr")
uv.lock
Generated
-30
View File
@@ -139,25 +139,6 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
]
[[package]]
name = "anthropic"
version = "0.100.0"
source = { registry = "https://pypi.org/simple" }
dependencies = [
{ name = "anyio" },
{ name = "distro" },
{ name = "docstring-parser" },
{ name = "httpx" },
{ name = "jiter" },
{ name = "pydantic" },
{ name = "sniffio" },
{ name = "typing-extensions" },
]
sdist = { url = "https://files.pythonhosted.org/packages/9c/2d/24caf0ff727cba2ed863925017c8f93463a2ea6224a0efe5626e672bc3d2/anthropic-0.100.0.tar.gz", hash = "sha256:650dee9e023afb16395939ee4104bbc21f966b380210119fb91122c12099c79a", size = 758255, upload-time = "2026-05-06T15:07:13.578Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/5d/a0/c775c59ab9445ecabb57ef3d5c24027de060139189a9e312ef9ef889a665/anthropic-0.100.0-py3-none-any.whl", hash = "sha256:1c15769efa15d8fd5c1ebf900e25c57e3ee540f8554a29aa56e4edefffe2951d", size = 753596, upload-time = "2026-05-06T15:07:12.106Z" },
]
[[package]]
name = "anyio"
version = "4.13.0"
@@ -467,15 +448,6 @@ wheels = [
{ url = "https://files.pythonhosted.org/packages/12/b3/231ffd4ab1fc9d679809f356cebee130ac7daa00d6d6f3206dd4fd137e9e/distro-1.9.0-py3-none-any.whl", hash = "sha256:7bffd925d65168f85027d8da9af6bddab658135b840670a223589bc0c8ef02b2", size = 20277, upload-time = "2023-12-24T09:54:30.421Z" },
]
[[package]]
name = "docstring-parser"
version = "0.18.0"
source = { registry = "https://pypi.org/simple" }
sdist = { url = "https://files.pythonhosted.org/packages/e0/4d/f332313098c1de1b2d2ff91cf2674415cc7cddab2ca1b01ae29774bd5fdf/docstring_parser-0.18.0.tar.gz", hash = "sha256:292510982205c12b1248696f44959db3cdd1740237a968ea1e2e7a900eeb2015", size = 29341, upload-time = "2026-04-14T04:09:19.867Z" }
wheels = [
{ url = "https://files.pythonhosted.org/packages/a7/5f/ed01f9a3cdffbd5a008556fc7b2a08ddb1cc6ace7effa7340604b1d16699/docstring_parser-0.18.0-py3-none-any.whl", hash = "sha256:b3fcbed555c47d8479be0796ef7e19c2670d428d72e96da63f3a40122860374b", size = 22484, upload-time = "2026-04-14T04:09:18.638Z" },
]
[[package]]
name = "frozenlist"
version = "1.8.0"
@@ -887,7 +859,6 @@ name = "multi-swarm"
version = "0.1.0"
source = { editable = "." }
dependencies = [
{ name = "anthropic" },
{ name = "ccxt" },
{ name = "httpx" },
{ name = "numpy" },
@@ -919,7 +890,6 @@ dev = [
[package.metadata]
requires-dist = [
{ name = "anthropic", specifier = ">=0.39" },
{ name = "ccxt", specifier = ">=4.4" },
{ name = "httpx", specifier = ">=0.28" },
{ name = "numpy", specifier = ">=2.1" },