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0e1d6bfa79
## Description > **Stacked on #2777.** That PR corrects the built-in table's *values*; this one stops the table being *authoritative*. Both are wanted — the fallback should be right **and** not in charge. Merge #2777 first. You asked whether the token/savings code could be simpler and whether the hardcoding could go. This is the hardcoding half, and the encouraging finding is that **almost none of it needed writing** — the infrastructure already existed and was simply unused. `headroom/pricing/litellm_pricing.py` (300 lines, LiteLLM-backed, with an `ImportError` fallback and gateway-prefix handling) has been in the tree the whole time. `ModelInfo`'s own docstring says: > *"Pricing is fetched dynamically from LiteLLM's database. Use `ModelRegistry.estimate_cost()` to get current pricing."* Yet **zero of the four providers called it** (`grep -c litellm_pricing` → openai 0, anthropic 0, google 0, cohere 0). Each kept a parallel hardcoded table. `_get_pricing` had no LiteLLM lookup at all, unlike `get_context_limit` — which is precisely how it went ~18 months stale and priced `gpt-4.1-nano` **300× over**. ## Changes Made **1. Resolution order now mirrors `get_context_limit`**, so limits and prices can't disagree: ``` explicit user config -> LiteLLM -> built-in table -> family -> unknown default ``` Config beats LiteLLM because a configured price is a decision, not a guess. The table stays because it must: the `litellm` dependency is gated `python_version < '3.14'`, and LiteLLM doesn't know every model. It just isn't in charge, so its drift only reaches installs with no LiteLLM. **2. Gateway-routed names now resolve at all.** `litellm.model_cost` keys the *unwrapped* form, so `bedrock/anthropic.claude-...` missed every candidate and silently took the $2.50/$10.00 unknown default: | model | before | after | |---|---|---| | `bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0` | $2.50 / $10.00 | **$3.00 / $15.00** | | `bedrock/us.anthropic.claude-3-5-sonnet-...-v2:0` | $2.50 / $10.00 | **$3.00 / $15.00** | | `vertex_ai/claude-sonnet-4-5` | $2.50 / $10.00 | **$3.00 / $15.00** | | `groq/llama-3.3-70b-versatile` | $2.50 / $10.00 | **$0.59 / $0.79** | | `gemini-2.5-flash` | $2.50 / $10.00 | **$0.30 / $2.50** | | `deepseek-chat` | $2.50 / $10.00 | **$0.28 / $0.42** | `pricing_lookup_candidates` only ever *prepended* provider prefixes. It now also tries progressively unwrapped forms, derived by splitting on `/` — deliberately **not** another hardcoded gateway-prefix list. A wrong guess costs nothing: each candidate is an exact dict lookup, so it just misses. **3. The staleness warning became meaningful.** It fires only when the fallback table is actually used. Before, it was unconditional — and with `_PRICING_LAST_UPDATED = 2025-01-14` against a 60-day window it had been firing for ~18 months, which trains people to ignore it. **4. `pricing_per_1m` rounds to 6dp.** LiteLLM stores cost *per token*, so `× 1e6` leaves float noise ($0.4/1M arrives as `0.39999999999999997`). ## Type of Change - [x] Bug fix (non-breaking change that fixes an issue) - [x] Code refactoring ## Testing - [x] Unit tests pass (`pytest`) - [x] Linting passes (`ruff check` + `ruff format`) - [x] Type checking passes (`mypy`) - [x] New tests added for new functionality ### Test Output ```text $ pytest tests/test_pricing_from_litellm.py -q 10 passed ``` Full pricing / cost / provider / models / savings / reporting / tokenizer set: ```text $ pytest tests/test_*{pricing,cost,provider,models,savings,utils,reporting,token}*.py -q 3 failed, 1026 passed, 38 skipped pre-existing on main (all three in my recorded baseline): test_bundled_tools_savings.py::test_compressed_payload_preserves_answer_anthropic test_compress_route_tokenizer_by_model.py::...[deepseek/deepseek-v4] (needs transformers) test_compress_route_tokenizer_by_model.py::...[deepseek/deepseek-v4] (needs transformers) ``` Deferring the full sharded run to CI — no maturin/Rust core locally. ### One test of mine changed, and why Three cases in #2777's `test_openai_pricing_resolution.py` failed on exact equality once prices started coming from LiteLLM — `gpt-4.1-mini` arrived as `0.39999999999999997` rather than `0.4`. The values were right; binary floating point isn't exact. Switched those to `pytest.approx(..., abs=0.001)` — money compared to the cent — which passes whether the number comes from LiteLLM or the literal table. ## Deliberately NOT in this PR - **Encodings stay hardcoded.** LiteLLM carries no tiktoken encoding data, and `_lookup_encoding_name`'s `None` return is load-bearing (it's the "not an OpenAI model" signal from #2761). Encodings also track tokenizer generations, not monthly price changes — they aren't the drift problem. - **Anthropic / Cohere / Google providers.** Same shape, same fix, but Anthropic's pricing is a `{input, output, cached_input}` dict rather than a tuple, and its matcher is worse (`if model in known_model or known_model in model` — bidirectional substring). Worth its own PR rather than tripling this diff. - **Context limits.** Already LiteLLM-first; the layering there was correct all along. - `accounts/fireworks/models/kimi-k2` still falls back — LiteLLM genuinely has no entry. The file already shows the pattern for filling such gaps (`_register_minimax_pricing`, `_inject_deepseek_pricing`) if we want it.
87 lines
3.2 KiB
Python
87 lines
3.2 KiB
Python
"""Pricing comes from LiteLLM; the built-in table is only a fallback.
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`_PRICING` used to be authoritative, with no LiteLLM lookup in front of it. That
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is how it went ~18 months stale and priced `gpt-4.1-nano` 300x over. The table is
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still needed -- the `litellm` dependency is gated `python_version < '3.14'`, and
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LiteLLM does not know every model -- but it must not outrank the live source.
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Resolution order (mirroring `get_context_limit`, so limits and prices agree):
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1. explicit user config (`HEADROOM_MODEL_LIMITS` / `models.json`)
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2. LiteLLM
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3. built-in table -> family pattern -> unknown default
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"""
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from __future__ import annotations
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import pytest
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from headroom.pricing.litellm_model_resolution import unwrapped_model_forms
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from headroom.providers.openai import OpenAIProvider
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litellm = pytest.importorskip("litellm")
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def test_unwrapped_model_forms_drops_leading_segments() -> None:
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"""Pure function: no gateway-prefix list to maintain."""
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assert unwrapped_model_forms("bedrock/anthropic.claude-x") == ("anthropic.claude-x",)
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assert unwrapped_model_forms("accounts/fireworks/models/kimi-k2") == (
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"fireworks/models/kimi-k2",
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"models/kimi-k2",
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"kimi-k2",
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)
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assert unwrapped_model_forms("gpt-4o") == ()
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@pytest.mark.parametrize(
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("model", "want_in", "want_out"),
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[
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# Gateway-routed names. litellm.model_cost keys the UNWRAPPED form, so
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# these all returned None (-> $2.50/$10.00 unknown default) before.
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("bedrock/anthropic.claude-3-5-sonnet-20241022-v2:0", 3.00, 15.00),
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("bedrock/us.anthropic.claude-3-5-sonnet-20241022-v2:0", 3.00, 15.00),
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("vertex_ai/claude-sonnet-4-5", 3.00, 15.00),
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("groq/llama-3.3-70b-versatile", 0.59, 0.79),
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# Non-OpenAI models reachable through the OpenAI-compatible passthrough.
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("gemini-2.5-flash", 0.30, 2.50),
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("deepseek-chat", 0.28, 0.42),
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],
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)
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def test_provider_prices_models_its_table_never_covered(
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model: str, want_in: float, want_out: float
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) -> None:
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got_in, got_out = OpenAIProvider()._get_pricing(model)
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assert (round(got_in, 2), round(got_out, 2)) == (want_in, want_out)
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def test_explicit_config_outranks_litellm() -> None:
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"""A configured price is a decision, not a guess."""
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provider = OpenAIProvider()
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provider._pricing_overrides["gpt-4o"] = (99.0, 111.0)
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assert provider._get_pricing("gpt-4o") == (99.0, 111.0)
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def test_falls_back_to_the_builtin_table_without_litellm(monkeypatch: pytest.MonkeyPatch) -> None:
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"""Offline / Python >= 3.14 installs must still get sane numbers.
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Pinned because the fallback is exactly where the table's correctness still
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matters -- it is the only thing those installs see.
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"""
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import headroom.pricing.litellm_pricing as lp
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monkeypatch.setattr(lp, "LITELLM_AVAILABLE", False)
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provider = OpenAIProvider()
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assert provider._get_pricing("gpt-4.1-nano") == (0.10, 0.40)
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assert provider._get_pricing("gpt-4") == (30.00, 60.00)
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assert provider._get_pricing("o3") == (2.00, 8.00)
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def test_unknown_model_still_returns_a_usable_default() -> None:
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"""Never raise, never return None, for a model nobody knows."""
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got = OpenAIProvider()._get_pricing("totally-made-up-model-xyz")
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assert got is not None
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assert got[0] > 0
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