mirror of
https://github.com/BerriAI/litellm.git
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add estimate_cost endpoint
This commit is contained in:
Ishaan Jaffer
parent
165d5f3af1
commit
77ecb8eaff
3 changed files with 193 additions and 2 deletions
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@ -11640,6 +11640,7 @@
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"supports_tool_choice": true
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},
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"gemini-1.5-flash": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_audio_per_second": 2e-06,
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"input_cost_per_audio_per_second_above_128k_tokens": 4e-06,
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"input_cost_per_character": 1.875e-08,
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@ -11744,6 +11745,7 @@
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"supports_vision": true
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},
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"gemini-1.5-flash-exp-0827": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_audio_per_second": 2e-06,
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"input_cost_per_audio_per_second_above_128k_tokens": 4e-06,
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"input_cost_per_character": 1.875e-08,
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@ -11778,6 +11780,7 @@
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"supports_vision": true
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},
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"gemini-1.5-flash-preview-0514": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_audio_per_second": 2e-06,
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"input_cost_per_audio_per_second_above_128k_tokens": 4e-06,
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"input_cost_per_character": 1.875e-08,
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@ -11811,6 +11814,7 @@
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"supports_vision": true
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},
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"gemini-1.5-pro": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_audio_per_second": 3.125e-05,
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"input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05,
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"input_cost_per_character": 3.125e-07,
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@ -11898,6 +11902,7 @@
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"supports_vision": true
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},
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"gemini-1.5-pro-preview-0215": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_audio_per_second": 3.125e-05,
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"input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05,
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"input_cost_per_character": 3.125e-07,
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@ -11925,6 +11930,7 @@
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"supports_tool_choice": true
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},
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"gemini-1.5-pro-preview-0409": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_audio_per_second": 3.125e-05,
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"input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05,
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"input_cost_per_character": 3.125e-07,
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@ -11951,6 +11957,7 @@
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"supports_tool_choice": true
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},
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"gemini-1.5-pro-preview-0514": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_audio_per_second": 3.125e-05,
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"input_cost_per_audio_per_second_above_128k_tokens": 6.25e-05,
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"input_cost_per_character": 3.125e-07,
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@ -12222,6 +12229,7 @@
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"tpm": 250000
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},
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"gemini-2.0-flash-preview-image-generation": {
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"deprecation_date": "2025-11-14",
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"cache_read_input_token_cost": 2.5e-08,
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"input_cost_per_audio_token": 7e-07,
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"input_cost_per_token": 1e-07,
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@ -12260,6 +12268,7 @@
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"supports_web_search": true
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},
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"gemini-2.0-flash-thinking-exp": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 0.0,
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"input_cost_per_audio_per_second": 0,
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"input_cost_per_audio_per_second_above_128k_tokens": 0,
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@ -12308,6 +12317,7 @@
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"supports_web_search": true
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},
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"gemini-2.0-flash-thinking-exp-01-21": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 0.0,
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"input_cost_per_audio_per_second": 0,
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"input_cost_per_audio_per_second_above_128k_tokens": 0,
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@ -12494,6 +12504,7 @@
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"tpm": 8000000
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},
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"gemini-2.5-flash-image-preview": {
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"deprecation_date": "2026-01-15",
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"cache_read_input_token_cost": 7.5e-08,
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"input_cost_per_audio_token": 1e-06,
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"input_cost_per_token": 3e-07,
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@ -12804,6 +12815,7 @@
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"tpm": 8000000
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},
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"gemini-2.5-flash-lite-preview-06-17": {
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"deprecation_date": "2025-11-18",
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"cache_read_input_token_cost": 2.5e-08,
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"input_cost_per_audio_token": 5e-07,
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"input_cost_per_token": 1e-07,
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@ -12893,6 +12905,7 @@
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"supports_web_search": true
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},
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"gemini-2.5-flash-preview-05-20": {
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"deprecation_date": "2025-11-18",
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"cache_read_input_token_cost": 7.5e-08,
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"input_cost_per_audio_token": 1e-06,
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"input_cost_per_token": 3e-07,
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@ -13164,6 +13177,7 @@
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"supports_web_search": true
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},
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"gemini-2.5-pro-preview-03-25": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 3.125e-07,
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"input_cost_per_audio_token": 1.25e-06,
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"input_cost_per_token": 1.25e-06,
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@ -13209,6 +13223,7 @@
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"supports_web_search": true
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},
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"gemini-2.5-pro-preview-05-06": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 3.125e-07,
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"input_cost_per_audio_token": 1.25e-06,
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"input_cost_per_token": 1.25e-06,
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@ -13424,6 +13439,7 @@
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"tpm": 10000000
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},
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"gemini/gemini-1.5-flash": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 7.5e-08,
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"input_cost_per_token_above_128k_tokens": 1.5e-07,
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"litellm_provider": "gemini",
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@ -13507,6 +13523,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-flash-8b": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 0,
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"input_cost_per_token_above_128k_tokens": 0,
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"litellm_provider": "gemini",
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@ -13533,6 +13550,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-flash-8b-exp-0827": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 0,
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"input_cost_per_token_above_128k_tokens": 0,
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"litellm_provider": "gemini",
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@ -13558,6 +13576,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-flash-8b-exp-0924": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 0,
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"input_cost_per_token_above_128k_tokens": 0,
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"litellm_provider": "gemini",
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@ -13584,6 +13603,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-flash-exp-0827": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 0,
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"input_cost_per_token_above_128k_tokens": 0,
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"litellm_provider": "gemini",
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@ -13609,6 +13629,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-flash-latest": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 7.5e-08,
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"input_cost_per_token_above_128k_tokens": 1.5e-07,
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"litellm_provider": "gemini",
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@ -13635,6 +13656,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-pro": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 3.5e-06,
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"input_cost_per_token_above_128k_tokens": 7e-06,
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"litellm_provider": "gemini",
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@ -13696,6 +13718,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-pro-exp-0801": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 3.5e-06,
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"input_cost_per_token_above_128k_tokens": 7e-06,
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"litellm_provider": "gemini",
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@ -13715,6 +13738,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-pro-exp-0827": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 0,
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"input_cost_per_token_above_128k_tokens": 0,
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"litellm_provider": "gemini",
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@ -13734,6 +13758,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-1.5-pro-latest": {
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"deprecation_date": "2025-09-29",
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"input_cost_per_token": 3.5e-06,
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"input_cost_per_token_above_128k_tokens": 7e-06,
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"litellm_provider": "gemini",
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@ -13916,6 +13941,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-2.0-flash-lite-preview-02-05": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 1.875e-08,
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"input_cost_per_audio_token": 7.5e-08,
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"input_cost_per_token": 7.5e-08,
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@ -13953,6 +13979,7 @@
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"tpm": 10000000
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},
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"gemini/gemini-2.0-flash-live-001": {
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"deprecation_date": "2025-12-09",
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"cache_read_input_token_cost": 7.5e-08,
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"input_cost_per_audio_token": 2.1e-06,
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"input_cost_per_image": 2.1e-06,
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@ -14001,6 +14028,7 @@
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"tpm": 250000
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},
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"gemini/gemini-2.0-flash-preview-image-generation": {
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"deprecation_date": "2025-11-14",
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"cache_read_input_token_cost": 2.5e-08,
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"input_cost_per_audio_token": 7e-07,
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"input_cost_per_token": 1e-07,
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@ -14040,6 +14068,7 @@
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"tpm": 10000000
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},
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"gemini/gemini-2.0-flash-thinking-exp": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 0.0,
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"input_cost_per_audio_per_second": 0,
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"input_cost_per_audio_per_second_above_128k_tokens": 0,
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@ -14089,6 +14118,7 @@
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"tpm": 4000000
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},
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"gemini/gemini-2.0-flash-thinking-exp-01-21": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 0.0,
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"input_cost_per_audio_per_second": 0,
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"input_cost_per_audio_per_second_above_128k_tokens": 0,
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@ -14277,6 +14307,7 @@
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"tpm": 8000000
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},
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"gemini/gemini-2.5-flash-image-preview": {
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"deprecation_date": "2026-01-15",
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"cache_read_input_token_cost": 7.5e-08,
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"input_cost_per_audio_token": 1e-06,
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"input_cost_per_token": 3e-07,
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@ -14597,6 +14628,7 @@
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"tpm": 250000
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},
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"gemini/gemini-2.5-flash-lite-preview-06-17": {
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"deprecation_date": "2025-11-18",
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"cache_read_input_token_cost": 2.5e-08,
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"input_cost_per_audio_token": 5e-07,
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"input_cost_per_token": 1e-07,
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@ -14688,6 +14720,7 @@
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"tpm": 250000
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},
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"gemini/gemini-2.5-flash-preview-05-20": {
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"deprecation_date": "2025-11-18",
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"cache_read_input_token_cost": 7.5e-08,
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"input_cost_per_audio_token": 1e-06,
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"input_cost_per_token": 3e-07,
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@ -15034,6 +15067,7 @@
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"tpm": 250000
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},
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"gemini/gemini-2.5-pro-preview-03-25": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 3.125e-07,
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"input_cost_per_audio_token": 7e-07,
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"input_cost_per_token": 1.25e-06,
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@ -15074,6 +15108,7 @@
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"tpm": 10000000
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},
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"gemini/gemini-2.5-pro-preview-05-06": {
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"deprecation_date": "2025-12-02",
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"cache_read_input_token_cost": 3.125e-07,
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"input_cost_per_audio_token": 7e-07,
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"input_cost_per_token": 1.25e-06,
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@ -15349,6 +15384,7 @@
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"source": "https://cloud.google.com/vertex-ai/generative-ai/pricing"
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},
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"gemini/imagen-3.0-generate-002": {
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"deprecation_date": "2025-11-10",
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"litellm_provider": "gemini",
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"mode": "image_generation",
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"output_cost_per_image": 0.04,
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@ -15415,6 +15451,7 @@
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]
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},
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"gemini/veo-3.0-fast-generate-preview": {
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"deprecation_date": "2025-11-12",
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"litellm_provider": "gemini",
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"max_input_tokens": 1024,
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"max_tokens": 1024,
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@ -15429,6 +15466,7 @@
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]
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},
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"gemini/veo-3.0-generate-preview": {
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"deprecation_date": "2025-11-12",
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"litellm_provider": "gemini",
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"max_input_tokens": 1024,
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"max_tokens": 1024,
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@ -25126,6 +25164,7 @@
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"source": "https://docs.mistral.ai/capabilities/code_generation/"
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},
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"text-embedding-004": {
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"deprecation_date": "2026-01-14",
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"input_cost_per_character": 2.5e-08,
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"input_cost_per_token": 1e-07,
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"litellm_provider": "vertex_ai-embedding-models",
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@ -27896,6 +27935,7 @@
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"source": "https://cloud.google.com/vertex-ai/generative-ai/pricing"
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},
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"vertex_ai/imagen-3.0-generate-002": {
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"deprecation_date": "2025-11-10",
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"litellm_provider": "vertex_ai-image-models",
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"mode": "image_generation",
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"output_cost_per_image": 0.04,
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@ -28406,6 +28446,7 @@
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]
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},
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"vertex_ai/veo-3.0-fast-generate-preview": {
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"deprecation_date": "2025-11-12",
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"litellm_provider": "vertex_ai-video-models",
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"max_input_tokens": 1024,
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"max_tokens": 1024,
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@ -28420,6 +28461,7 @@
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]
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},
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"vertex_ai/veo-3.0-generate-preview": {
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"deprecation_date": "2025-11-12",
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"litellm_provider": "vertex_ai-video-models",
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"max_input_tokens": 1024,
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"max_tokens": 1024,
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@ -3825,3 +3825,35 @@ class LiteLLM_ManagedVectorStoresTable(LiteLLMPydanticObjectBase):
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class ResponseLiteLLM_ManagedVectorStore(TypedDict, total=False):
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vector_store: LiteLLM_ManagedVectorStoresTable
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class CostEstimateRequest(LiteLLMPydanticObjectBase):
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"""Request body for /cost/estimate endpoint."""
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model: str = Field(description="Model name (from /model_group/info)")
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input_tokens: int = Field(description="Expected input tokens per request", ge=0)
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output_tokens: int = Field(description="Expected output tokens per request", ge=0)
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num_requests: int = Field(default=1, description="Number of requests", ge=1)
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class CostEstimateResponse(LiteLLMPydanticObjectBase):
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"""Response body for /cost/estimate endpoint."""
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model: str
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input_tokens: int
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output_tokens: int
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num_requests: int
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# Per-request costs
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cost_per_request: float = Field(description="Total cost per request (includes margin)")
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input_cost_per_request: float = Field(description="Input token cost per request (before margin)")
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output_cost_per_request: float = Field(description="Output token cost per request (before margin)")
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margin_cost_per_request: float = Field(default=0.0, description="Margin/fee added per request")
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# Total costs (per-request * num_requests)
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total_cost: float = Field(description="Total cost for all requests (includes margin)")
|
||||
total_input_cost: float = Field(description="Total input token cost (before margin)")
|
||||
total_output_cost: float = Field(description="Total output token cost (before margin)")
|
||||
total_margin_cost: float = Field(default=0.0, description="Total margin/fee for all requests")
|
||||
# Pricing info
|
||||
input_cost_per_token: Optional[float] = None
|
||||
output_cost_per_token: Optional[float] = None
|
||||
provider: Optional[str] = None
|
||||
|
|
|
|||
|
|
@ -7,15 +7,22 @@ GET /config/cost_discount_config - Get current cost discount configuration
|
|||
PATCH /config/cost_discount_config - Update cost discount configuration
|
||||
GET /config/cost_margin_config - Get current cost margin configuration
|
||||
PATCH /config/cost_margin_config - Update cost margin configuration
|
||||
POST /cost/estimate - Estimate cost for a given model and token counts
|
||||
"""
|
||||
|
||||
from typing import Dict, Union
|
||||
from typing import Dict, List, Optional, Union
|
||||
|
||||
from fastapi import APIRouter, Depends, HTTPException
|
||||
|
||||
import litellm
|
||||
from litellm._logging import verbose_proxy_logger
|
||||
from litellm.proxy._types import CommonProxyErrors, UserAPIKeyAuth
|
||||
from litellm.cost_calculator import completion_cost
|
||||
from litellm.proxy._types import (
|
||||
CommonProxyErrors,
|
||||
CostEstimateRequest,
|
||||
CostEstimateResponse,
|
||||
UserAPIKeyAuth,
|
||||
)
|
||||
from litellm.proxy.auth.user_api_key_auth import user_api_key_auth
|
||||
from litellm.types.utils import LlmProvidersSet
|
||||
|
||||
|
|
@ -347,3 +354,113 @@ async def update_cost_margin_config(
|
|||
detail={"error": f"Failed to update cost margin config: {str(e)}"}
|
||||
)
|
||||
|
||||
|
||||
@router.post(
|
||||
"/cost/estimate",
|
||||
tags=["Cost Tracking"],
|
||||
dependencies=[Depends(user_api_key_auth)],
|
||||
response_model=CostEstimateResponse,
|
||||
)
|
||||
async def estimate_cost(
|
||||
request: CostEstimateRequest,
|
||||
user_api_key_dict: UserAPIKeyAuth = Depends(user_api_key_auth),
|
||||
) -> CostEstimateResponse:
|
||||
"""
|
||||
Estimate cost for a given model and token counts.
|
||||
|
||||
This endpoint uses the same cost calculation logic as actual requests,
|
||||
including any configured margins and discounts.
|
||||
|
||||
Parameters:
|
||||
- model: Model name from /model_group/info (e.g., "gpt-4", "claude-3-opus")
|
||||
- input_tokens: Expected input tokens per request
|
||||
- output_tokens: Expected output tokens per request
|
||||
- num_requests: Number of requests (default: 1)
|
||||
|
||||
Returns cost breakdown including:
|
||||
- Input token cost
|
||||
- Output token cost
|
||||
- Margin/fee cost
|
||||
- Total cost
|
||||
|
||||
Example:
|
||||
```json
|
||||
{
|
||||
"model": "gpt-4",
|
||||
"input_tokens": 1000,
|
||||
"output_tokens": 500,
|
||||
"num_requests": 100
|
||||
}
|
||||
```
|
||||
"""
|
||||
from litellm.cost_calculator import _apply_cost_margin
|
||||
from litellm.proxy.proxy_server import llm_router
|
||||
from litellm.types.utils import Usage
|
||||
|
||||
if llm_router is None:
|
||||
raise HTTPException(
|
||||
status_code=500,
|
||||
detail={"error": "Router not initialized. No models configured."},
|
||||
)
|
||||
|
||||
# Get model group info from router to resolve pricing
|
||||
model_group_info = llm_router.get_model_group_info(model_group=request.model)
|
||||
|
||||
if model_group_info is None:
|
||||
raise HTTPException(
|
||||
status_code=404,
|
||||
detail={
|
||||
"error": f"Model '{request.model}' not found. Use /model_group/info to see available models."
|
||||
},
|
||||
)
|
||||
|
||||
# Get the provider from the model group
|
||||
providers: List[str] = model_group_info.providers or []
|
||||
custom_llm_provider: Optional[str] = providers[0] if providers else None
|
||||
|
||||
# Get cost per token from model group info
|
||||
input_cost_per_token = model_group_info.input_cost_per_token or 0.0
|
||||
output_cost_per_token = model_group_info.output_cost_per_token or 0.0
|
||||
|
||||
# Calculate base costs (before margin)
|
||||
input_cost = input_cost_per_token * request.input_tokens
|
||||
output_cost = output_cost_per_token * request.output_tokens
|
||||
base_cost = input_cost + output_cost
|
||||
|
||||
# Apply margin using the same function as completion_cost
|
||||
(
|
||||
cost_with_margin,
|
||||
_margin_percent,
|
||||
_margin_fixed_amount,
|
||||
margin_cost,
|
||||
) = _apply_cost_margin(
|
||||
base_cost=base_cost,
|
||||
custom_llm_provider=custom_llm_provider,
|
||||
)
|
||||
|
||||
cost_per_request = cost_with_margin
|
||||
|
||||
# Calculate totals based on number of requests
|
||||
total_cost = cost_per_request * request.num_requests
|
||||
total_input_cost = input_cost * request.num_requests
|
||||
total_output_cost = output_cost * request.num_requests
|
||||
total_margin_cost = margin_cost * request.num_requests
|
||||
|
||||
return CostEstimateResponse(
|
||||
model=request.model,
|
||||
input_tokens=request.input_tokens,
|
||||
output_tokens=request.output_tokens,
|
||||
num_requests=request.num_requests,
|
||||
cost_per_request=cost_per_request,
|
||||
input_cost_per_request=input_cost,
|
||||
output_cost_per_request=output_cost,
|
||||
margin_cost_per_request=margin_cost,
|
||||
total_cost=total_cost,
|
||||
total_input_cost=total_input_cost,
|
||||
total_output_cost=total_output_cost,
|
||||
total_margin_cost=total_margin_cost,
|
||||
input_cost_per_token=input_cost_per_token,
|
||||
output_cost_per_token=output_cost_per_token,
|
||||
provider=custom_llm_provider,
|
||||
)
|
||||
|
||||
|
|
|
|||
Loading…
Add table
Reference in a new issue