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fix(friendliai): sync serverless catalog with the models API
The catalog carried only meta-llama-3.1-70b-instruct and meta-llama-3.1-8b-instruct. Both are retired; neither is served by https://api.friendli.ai/serverless/v1/models anymore, so their pricing and 8k context windows were the only FriendliAI data litellm exposed. Every field is taken from that endpoint, which is public and unauthenticated: pricing.input, pricing.output and pricing.input_cache_read map onto the token costs, context_length onto max_input_tokens, max_completion_tokens onto max_output_tokens and max_tokens, and functionality.tool_call, functionality.parallel_tool_call and functionality.structured_output onto the capability flags. Qwen3-235B-A22B-Instruct-2507 reports a deprecation_date of 2026-08-05 and carries it through. tests/test_litellm/test_friendliai_model_metadata.py pins the lineup, asserts the retired keys stay absent, and asserts the root JSON and the bundled backup never drift apart for this provider
This commit is contained in:
robust-WJL
parent
24123269cc
commit
daa43de167
3 changed files with 318 additions and 24 deletions
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@ -17198,30 +17198,116 @@
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"output_cost_per_token": 0.0,
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"source": "https://fireworks.ai/pricing"
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},
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"friendliai/meta-llama-3.1-70b-instruct": {
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"input_cost_per_token": 6e-07,
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"friendliai/LGAI-EXAONE/K-EXAONE-236B-A23B": {
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"cache_read_input_token_cost": 1e-07,
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"input_cost_per_token": 2e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 8192,
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"max_output_tokens": 8192,
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"max_tokens": 8192,
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"max_input_tokens": 262144,
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"max_output_tokens": 262144,
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"max_tokens": 262144,
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"mode": "chat",
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"output_cost_per_token": 6e-07,
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"output_cost_per_token": 8e-07,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/MiniMaxAI/MiniMax-M2.5": {
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"cache_read_input_token_cost": 6e-08,
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"input_cost_per_token": 3e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 196608,
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"max_output_tokens": 196608,
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"max_tokens": 196608,
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"mode": "chat",
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"output_cost_per_token": 1.2e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/Qwen/Qwen3-235B-A22B-Instruct-2507": {
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"deprecation_date": "2026-08-05",
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"input_cost_per_token": 2e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 262144,
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"max_output_tokens": 262144,
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"max_tokens": 262144,
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"mode": "chat",
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"output_cost_per_token": 8e-07,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/meta-llama-3.1-8b-instruct": {
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"input_cost_per_token": 1e-07,
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"friendliai/deepseek-ai/DeepSeek-V3.2": {
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"cache_read_input_token_cost": 2.5e-07,
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"input_cost_per_token": 5e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 8192,
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"max_output_tokens": 8192,
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"max_tokens": 8192,
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"max_input_tokens": 163840,
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"max_output_tokens": 163840,
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"max_tokens": 163840,
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"mode": "chat",
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"output_cost_per_token": 1e-07,
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"output_cost_per_token": 1.5e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/google/gemma-4-31B-it": {
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"input_cost_per_token": 1.4e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 262144,
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"max_output_tokens": 262144,
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"max_tokens": 262144,
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"mode": "chat",
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"output_cost_per_token": 4e-07,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true,
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"supports_vision": true
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},
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"friendliai/zai-org/GLM-5.1": {
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"cache_read_input_token_cost": 2.6e-07,
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"input_cost_per_token": 1.4e-06,
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"litellm_provider": "friendliai",
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"max_input_tokens": 202752,
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"max_output_tokens": 202752,
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"max_tokens": 202752,
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"mode": "chat",
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"output_cost_per_token": 4.4e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/zai-org/GLM-5.2": {
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"cache_read_input_token_cost": 2.6e-07,
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"input_cost_per_token": 1.4e-06,
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"litellm_provider": "friendliai",
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"max_input_tokens": 1048576,
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"max_output_tokens": 1048576,
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"max_tokens": 1048576,
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"mode": "chat",
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"output_cost_per_token": 4.4e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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@ -17198,30 +17198,116 @@
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"output_cost_per_token": 0.0,
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"source": "https://fireworks.ai/pricing"
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},
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"friendliai/meta-llama-3.1-70b-instruct": {
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"input_cost_per_token": 6e-07,
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"friendliai/LGAI-EXAONE/K-EXAONE-236B-A23B": {
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"cache_read_input_token_cost": 1e-07,
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"input_cost_per_token": 2e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 8192,
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"max_output_tokens": 8192,
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"max_tokens": 8192,
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"max_input_tokens": 262144,
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"max_output_tokens": 262144,
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"max_tokens": 262144,
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"mode": "chat",
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"output_cost_per_token": 6e-07,
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"output_cost_per_token": 8e-07,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/MiniMaxAI/MiniMax-M2.5": {
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"cache_read_input_token_cost": 6e-08,
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"input_cost_per_token": 3e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 196608,
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"max_output_tokens": 196608,
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"max_tokens": 196608,
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"mode": "chat",
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"output_cost_per_token": 1.2e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/Qwen/Qwen3-235B-A22B-Instruct-2507": {
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"deprecation_date": "2026-08-05",
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"input_cost_per_token": 2e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 262144,
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"max_output_tokens": 262144,
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"max_tokens": 262144,
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"mode": "chat",
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"output_cost_per_token": 8e-07,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/meta-llama-3.1-8b-instruct": {
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"input_cost_per_token": 1e-07,
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"friendliai/deepseek-ai/DeepSeek-V3.2": {
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"cache_read_input_token_cost": 2.5e-07,
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"input_cost_per_token": 5e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 8192,
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"max_output_tokens": 8192,
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"max_tokens": 8192,
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"max_input_tokens": 163840,
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"max_output_tokens": 163840,
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"max_tokens": 163840,
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"mode": "chat",
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"output_cost_per_token": 1e-07,
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"output_cost_per_token": 1.5e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/google/gemma-4-31B-it": {
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"input_cost_per_token": 1.4e-07,
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"litellm_provider": "friendliai",
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"max_input_tokens": 262144,
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"max_output_tokens": 262144,
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"max_tokens": 262144,
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"mode": "chat",
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"output_cost_per_token": 4e-07,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true,
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"supports_vision": true
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},
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"friendliai/zai-org/GLM-5.1": {
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"cache_read_input_token_cost": 2.6e-07,
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"input_cost_per_token": 1.4e-06,
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"litellm_provider": "friendliai",
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"max_input_tokens": 202752,
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"max_output_tokens": 202752,
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"max_tokens": 202752,
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"mode": "chat",
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"output_cost_per_token": 4.4e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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},
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"friendliai/zai-org/GLM-5.2": {
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"cache_read_input_token_cost": 2.6e-07,
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"input_cost_per_token": 1.4e-06,
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"litellm_provider": "friendliai",
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"max_input_tokens": 1048576,
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"max_output_tokens": 1048576,
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"max_tokens": 1048576,
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"mode": "chat",
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"output_cost_per_token": 4.4e-06,
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"supports_function_calling": true,
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"supports_parallel_function_calling": true,
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"supports_prompt_caching": true,
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"supports_reasoning": true,
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"supports_response_schema": true,
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"supports_system_messages": true,
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"supports_tool_choice": true
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122
tests/test_litellm/test_friendliai_model_metadata.py
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122
tests/test_litellm/test_friendliai_model_metadata.py
Normal file
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@ -0,0 +1,122 @@
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"""Regression tests for the FriendliAI serverless catalog entries.
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The catalog previously carried only ``friendliai/meta-llama-3.1-70b-instruct``
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and ``friendliai/meta-llama-3.1-8b-instruct``, both retired and no longer
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served by ``https://api.friendli.ai/serverless/v1/models``. These tests pin the
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current serverless lineup, assert the retired entries stay gone, and assert the
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root JSON and the bundled backup JSON never drift apart for this provider.
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"""
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import json
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from pathlib import Path
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from typing import Final, NamedTuple
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import pytest
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class FriendliModel(NamedTuple):
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key: str
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input_cost_per_token: float
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output_cost_per_token: float
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cache_read_input_token_cost: float | None
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max_input_tokens: int
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max_output_tokens: int
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EXPECTED_MODELS: Final[tuple[FriendliModel, ...]] = (
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FriendliModel(
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"friendliai/LGAI-EXAONE/K-EXAONE-236B-A23B", 2e-07, 8e-07, 1e-07, 262144, 262144
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),
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FriendliModel(
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"friendliai/MiniMaxAI/MiniMax-M2.5", 3e-07, 1.2e-06, 6e-08, 196608, 196608
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),
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FriendliModel(
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"friendliai/Qwen/Qwen3-235B-A22B-Instruct-2507", 2e-07, 8e-07, None, 262144, 262144
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),
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FriendliModel(
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"friendliai/deepseek-ai/DeepSeek-V3.2", 5e-07, 1.5e-06, 2.5e-07, 163840, 163840
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),
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FriendliModel(
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"friendliai/google/gemma-4-31B-it", 1.4e-07, 4e-07, None, 262144, 262144
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),
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FriendliModel(
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"friendliai/zai-org/GLM-5.1", 1.4e-06, 4.4e-06, 2.6e-07, 202752, 202752
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),
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FriendliModel(
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"friendliai/zai-org/GLM-5.2", 1.4e-06, 4.4e-06, 2.6e-07, 1048576, 1048576
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),
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)
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RETIRED_KEYS: Final[tuple[str, ...]] = (
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"friendliai/meta-llama-3.1-70b-instruct",
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"friendliai/meta-llama-3.1-8b-instruct",
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)
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_REPO_ROOT: Final[Path] = Path(__file__).resolve().parents[2]
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ROOT_PATH: Final[Path] = _REPO_ROOT / "model_prices_and_context_window.json"
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BACKUP_PATH: Final[Path] = (
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_REPO_ROOT / "litellm" / "model_prices_and_context_window_backup.json"
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)
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CATALOG_PATHS: Final[tuple[Path, ...]] = (ROOT_PATH, BACKUP_PATH)
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def _load(path: Path) -> dict[str, dict[str, object]]:
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return json.loads(path.read_text(encoding="utf-8"))
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@pytest.mark.parametrize("path", CATALOG_PATHS, ids=lambda p: p.name)
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@pytest.mark.parametrize("expected", EXPECTED_MODELS, ids=lambda m: m.key)
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def test_serverless_model_pricing_and_context(path: Path, expected: FriendliModel) -> None:
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entry = _load(path).get(expected.key)
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assert entry is not None, f"{expected.key} missing from {path.name}"
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assert entry["litellm_provider"] == "friendliai"
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assert entry["mode"] == "chat"
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assert entry["input_cost_per_token"] == expected.input_cost_per_token
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assert entry["output_cost_per_token"] == expected.output_cost_per_token
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assert entry.get("cache_read_input_token_cost") == expected.cache_read_input_token_cost
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assert entry["max_input_tokens"] == expected.max_input_tokens
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assert entry["max_output_tokens"] == expected.max_output_tokens
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assert entry["max_tokens"] == expected.max_output_tokens
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@pytest.mark.parametrize("path", CATALOG_PATHS, ids=lambda p: p.name)
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@pytest.mark.parametrize("expected", EXPECTED_MODELS, ids=lambda m: m.key)
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def test_serverless_models_advertise_tool_calling(
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path: Path, expected: FriendliModel
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) -> None:
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entry = _load(path)[expected.key]
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assert entry["supports_function_calling"] is True
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assert entry["supports_parallel_function_calling"] is True
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assert entry["supports_response_schema"] is True
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assert entry["supports_tool_choice"] is True
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@pytest.mark.parametrize("path", CATALOG_PATHS, ids=lambda p: p.name)
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@pytest.mark.parametrize("key", RETIRED_KEYS)
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def test_retired_llama_entries_absent(path: Path, key: str) -> None:
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assert key not in _load(path), f"{key} is retired and must not be re-added"
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def test_prompt_caching_flag_tracks_cache_read_cost() -> None:
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catalog = _load(ROOT_PATH)
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for expected in EXPECTED_MODELS:
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entry = catalog[expected.key]
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assert entry.get("supports_prompt_caching", False) is (
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expected.cache_read_input_token_cost is not None
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), f"{expected.key} prompt-caching flag disagrees with cache_read cost"
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def test_deprecating_model_carries_iso_date() -> None:
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entry = _load(ROOT_PATH)["friendliai/Qwen/Qwen3-235B-A22B-Instruct-2507"]
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assert entry["deprecation_date"] == "2026-08-05"
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def test_root_and_backup_agree_on_every_friendliai_entry() -> None:
|
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root = {k: v for k, v in _load(ROOT_PATH).items() if k.startswith("friendliai/")}
|
||||
backup = {k: v for k, v in _load(BACKUP_PATH).items() if k.startswith("friendliai/")}
|
||||
assert root == backup
|
||||
|
||||
|
||||
def test_catalog_covers_exactly_the_expected_lineup() -> None:
|
||||
keys = {k for k in _load(ROOT_PATH) if k.startswith("friendliai/")}
|
||||
assert keys == {m.key for m in EXPECTED_MODELS}
|
||||
Loading…
Add table
Reference in a new issue