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test: split provider classification tests (#4392)
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@@ -1,20 +1,18 @@
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"""Provider classification and upstream-error formatting (REAL src.llm_core).
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"""Provider classification from a base URL (REAL src.llm_core).
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ROADMAP "Backend → more tests around ... provider setup" and "Provider
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setup/probing audit for Anthropic, Gemini, Groq, xAI, OpenRouter, OpenAI, and
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DeepSeek". `test_provider_endpoints.py` already pins URL/header *building*; this
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module pins the two pieces of provider setup that decide WHICH provider an
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endpoint is and how its failures are reported to the user:
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endpoint is:
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* `_detect_provider` — host-based provider identification (drives payload
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shape, auth headers, and the /v1 collapse). The look-alike-host and
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domain-in-path cases guard the hostname (not substring) matching.
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* `_provider_label` — the human name shown in degraded-state messages.
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* `_format_upstream_error` — turns a raw upstream HTTP status + body into the
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one-line, provider-aware message the UI shows ("Provider probes" degraded
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reporting in the roadmap).
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* `_uses_max_completion_tokens` — the gpt-5 / o-series quirk that the probe
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and chat payload builders branch on.
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Upstream-error formatting lives in `test_provider_classification_errors.py` and
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the token-param quirk in `test_provider_classification_token_params.py`.
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conftest.py stubs the heavy deps (sqlalchemy, src.database), so importing the
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real module is side-effect free.
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@@ -24,8 +22,6 @@ import pytest
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from src.llm_core import (
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_detect_provider,
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_provider_label,
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_format_upstream_error,
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_uses_max_completion_tokens,
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)
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@@ -108,81 +104,3 @@ class TestProviderLabel:
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@pytest.mark.parametrize("url", ["", None])
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def test_empty_returns_generic(self, url):
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assert _provider_label(url) == "provider"
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# ── _format_upstream_error ──
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# Status + body → one-line provider-aware sentence.
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class TestFormatUpstreamError:
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def test_401_rejects_key_with_provider_and_detail(self):
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msg = _format_upstream_error(
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401, '{"error": {"message": "Invalid API key"}}', "https://api.x.ai/v1"
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)
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assert msg.startswith("xAI rejected the API key")
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assert "Invalid API key" in msg
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assert "re-paste the key" in msg
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def test_403_denies_access(self):
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msg = _format_upstream_error(
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403, '{"error": {"message": "Forbidden"}}', "https://api.openai.com/v1"
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)
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assert "OpenAI denied access (403)" in msg
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assert "Forbidden" in msg
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def test_404_points_at_base_url(self):
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msg = _format_upstream_error(404, "", "https://api.groq.com/openai/v1")
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assert msg == "Groq returned 404 — check the base URL and model name."
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def test_429_rate_limited(self):
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msg = _format_upstream_error(
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429, '{"error": {"message": "slow down"}}', "https://api.anthropic.com"
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)
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assert msg.startswith("Anthropic rate-limited the request (429).")
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assert "slow down" in msg
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def test_5xx_reported_as_outage(self):
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msg = _format_upstream_error(503, "", "https://api.deepseek.com")
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assert msg == "DeepSeek is having an outage (HTTP 503)."
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def test_other_status_passthrough(self):
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msg = _format_upstream_error(418, "", "https://api.openai.com/v1")
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assert msg == "OpenAI returned HTTP 418"
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def test_string_error_field(self):
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msg = _format_upstream_error(401, '{"error": "bad key"}', "https://api.openai.com/v1")
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assert "bad key" in msg
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def test_plain_text_body_used_as_detail(self):
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msg = _format_upstream_error(500, "upstream exploded", "https://api.openai.com/v1")
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assert "OpenAI is having an outage (HTTP 500)." in msg
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assert "upstream exploded" in msg
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def test_bytes_body_is_decoded(self):
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msg = _format_upstream_error(
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401, b'{"error": {"message": "nope"}}', "https://api.openai.com/v1"
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)
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assert "nope" in msg
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def test_unknown_url_falls_back_to_generic_label(self):
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msg = _format_upstream_error(401, "", "")
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assert msg.startswith("provider rejected the API key")
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# ── _uses_max_completion_tokens ──
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# gpt-5 / o-series need `max_completion_tokens`; everything else `max_tokens`.
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class TestUsesMaxCompletionTokens:
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@pytest.mark.parametrize("model", [
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"gpt-5", "gpt-5.2", "gpt-5-mini", "o1", "o1-preview", "o3", "o3-mini",
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"o4-mini", "gpt-4.5", "gpt-4.5-preview", "openrouter/openai/o3",
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])
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def test_requires_max_completion_tokens(self, model):
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assert _uses_max_completion_tokens(model) is True
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@pytest.mark.parametrize("model", [
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# gpt-4o must NOT be confused with the o-series ("o4"/"o1" tokens).
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"gpt-4o", "gpt-4o-mini", "gpt-4.1", "claude-opus-4", "llama-3.3-70b",
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"deepseek-chat", "", None,
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])
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def test_uses_plain_max_tokens(self, model):
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assert _uses_max_completion_tokens(model) is False
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@@ -0,0 +1,71 @@
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"""Upstream-error formatting for provider setup (REAL src.llm_core).
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Split from `test_provider_classification.py` to keep error-message formatting
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separate from provider identification.
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* `_format_upstream_error` — turns a raw upstream HTTP status + body into the
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one-line, provider-aware message the UI shows ("Provider probes" degraded
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reporting in the roadmap).
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conftest.py stubs the heavy deps (sqlalchemy, src.database), so importing the
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real module is side-effect free.
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"""
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from src.llm_core import _format_upstream_error
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# ── _format_upstream_error ──
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# Status + body → one-line provider-aware sentence.
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class TestFormatUpstreamError:
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def test_401_rejects_key_with_provider_and_detail(self):
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msg = _format_upstream_error(
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401, '{"error": {"message": "Invalid API key"}}', "https://api.x.ai/v1"
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)
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assert msg.startswith("xAI rejected the API key")
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assert "Invalid API key" in msg
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assert "re-paste the key" in msg
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def test_403_denies_access(self):
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msg = _format_upstream_error(
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403, '{"error": {"message": "Forbidden"}}', "https://api.openai.com/v1"
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)
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assert "OpenAI denied access (403)" in msg
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assert "Forbidden" in msg
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def test_404_points_at_base_url(self):
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msg = _format_upstream_error(404, "", "https://api.groq.com/openai/v1")
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assert msg == "Groq returned 404 — check the base URL and model name."
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def test_429_rate_limited(self):
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msg = _format_upstream_error(
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429, '{"error": {"message": "slow down"}}', "https://api.anthropic.com"
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)
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assert msg.startswith("Anthropic rate-limited the request (429).")
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assert "slow down" in msg
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def test_5xx_reported_as_outage(self):
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msg = _format_upstream_error(503, "", "https://api.deepseek.com")
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assert msg == "DeepSeek is having an outage (HTTP 503)."
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def test_other_status_passthrough(self):
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msg = _format_upstream_error(418, "", "https://api.openai.com/v1")
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assert msg == "OpenAI returned HTTP 418"
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def test_string_error_field(self):
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msg = _format_upstream_error(401, '{"error": "bad key"}', "https://api.openai.com/v1")
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assert "bad key" in msg
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def test_plain_text_body_used_as_detail(self):
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msg = _format_upstream_error(500, "upstream exploded", "https://api.openai.com/v1")
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assert "OpenAI is having an outage (HTTP 500)." in msg
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assert "upstream exploded" in msg
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def test_bytes_body_is_decoded(self):
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msg = _format_upstream_error(
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401, b'{"error": {"message": "nope"}}', "https://api.openai.com/v1"
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)
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assert "nope" in msg
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def test_unknown_url_falls_back_to_generic_label(self):
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msg = _format_upstream_error(401, "", "")
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assert msg.startswith("provider rejected the API key")
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@@ -0,0 +1,34 @@
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"""Token-parameter selection for provider setup (REAL src.llm_core).
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Split from `test_provider_classification.py` to keep the token-param quirk
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separate from provider identification and error formatting.
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* `_uses_max_completion_tokens` — the gpt-5 / o-series quirk that the probe
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and chat payload builders branch on.
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conftest.py stubs the heavy deps (sqlalchemy, src.database), so importing the
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real module is side-effect free.
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"""
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import pytest
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from src.llm_core import _uses_max_completion_tokens
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# ── _uses_max_completion_tokens ──
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# gpt-5 / o-series need `max_completion_tokens`; everything else `max_tokens`.
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class TestUsesMaxCompletionTokens:
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@pytest.mark.parametrize("model", [
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"gpt-5", "gpt-5.2", "gpt-5-mini", "o1", "o1-preview", "o3", "o3-mini",
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"o4-mini", "gpt-4.5", "gpt-4.5-preview", "openrouter/openai/o3",
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])
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def test_requires_max_completion_tokens(self, model):
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assert _uses_max_completion_tokens(model) is True
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@pytest.mark.parametrize("model", [
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# gpt-4o must NOT be confused with the o-series ("o4"/"o1" tokens).
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"gpt-4o", "gpt-4o-mini", "gpt-4.1", "claude-opus-4", "llama-3.3-70b",
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"deepseek-chat", "", None,
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])
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def test_uses_plain_max_tokens(self, model):
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assert _uses_max_completion_tokens(model) is False
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