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feat: add Friendli serverless models to auto price/context sync
Adds transform_friendli_data() to auto_update_price_and_context_window_file.py and registers https://api.friendli.ai/serverless/v1/models as a sync source. Also adds the current 7 Friendli serverless models to the backup JSON: - friendliai/Qwen/Qwen3-235B-A22B-Instruct-2507 - friendliai/LGAI-EXAONE/K-EXAONE-236B-A23B - friendliai/MiniMaxAI/MiniMax-M2.5 - friendliai/deepseek-ai/DeepSeek-V3.2 - friendliai/zai-org/GLM-5.1 - friendliai/google/gemma-4-31B-it - friendliai/zai-org/GLM-5.2
This commit is contained in:
Lee-Si-Yoon
parent
24123269cc
commit
f13325aca9
2 changed files with 153 additions and 2 deletions
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@ -110,6 +110,61 @@ def transform_vercel_ai_gateway_data(data):
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return transformed
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def transform_friendli_data(data):
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transformed = {}
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for row in data:
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f = row.get("functionality", {}) or {}
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p = row.get("pricing", {}) or {}
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inp = row.get("input_modalities", []) or []
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out = row.get("output_modalities", []) or []
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obj = {
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"max_input_tokens": row.get("context_length"),
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"max_output_tokens": row.get("max_completion_tokens"),
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"max_tokens": row.get("max_completion_tokens") or row.get("context_length"),
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"input_cost_per_token": float(p.get("input", 0)),
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"output_cost_per_token": float(p.get("output", 0)),
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"supports_function_calling": bool(f.get("tool_call")),
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"supports_parallel_function_calling": bool(f.get("parallel_tool_call")),
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"supports_response_schema": bool(f.get("structured_output")),
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"litellm_provider": "friendliai",
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"mode": row.get("mode", "chat"),
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}
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# cache pricing (optional)
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if p.get("input_cache_read") is not None:
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obj["cache_read_input_token_cost"] = float(p["input_cache_read"])
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if p.get("cache_write") is not None:
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obj["cache_creation_input_token_cost"] = float(p["cache_write"])
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# only set these when the API actually returns them — don't overwrite
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# an existing true with false just because the field is absent.
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if f.get("tool_choice") is not None:
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obj["supports_tool_choice"] = bool(f["tool_choice"])
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if f.get("system_messages") is not None:
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obj["supports_system_messages"] = bool(f["system_messages"])
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# reasoning
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if row.get("reasoning"):
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obj["supports_reasoning"] = True
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# deprecation
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if v := row.get("deprecation_date"):
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obj["deprecation_date"] = v[:10]
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# vision modality
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if "image" in inp or "video" in inp:
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obj["supports_vision"] = True
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if inp:
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obj["supported_modalities"] = inp
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if out:
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obj["supported_output_modalities"] = out
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transformed[f'friendliai/{row["id"]}'] = obj
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return transformed
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# Load local data from a specified file
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def load_local_data(file_path):
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try:
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@ -130,6 +185,7 @@ def main():
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local_file_path = "model_prices_and_context_window.json" # Path to the local data file
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openrouter_url = "https://openrouter.ai/api/v1/models" # URL to fetch OpenRouter data
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vercel_ai_gateway_url = "https://ai-gateway.vercel.sh/v1/models" # URL to fetch Vercel AI Gateway data
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friendli_url = "https://api.friendli.ai/serverless/v1/models" # URL to fetch Friendli serverless data
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# Load local data from file
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local_data = load_local_data(local_file_path)
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@ -143,9 +199,14 @@ def main():
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vercel_data = asyncio.run(fetch_data(vercel_ai_gateway_url))
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# Transform the fetched Vercel AI Gateway data
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vercel_data = transform_vercel_ai_gateway_data(vercel_data)
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# Fetch Friendli serverless data
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friendli_data = asyncio.run(fetch_data(friendli_url))
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# Transform the fetched Friendli data
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friendli_data = transform_friendli_data(friendli_data)
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# Combine both datasets
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all_remote_data = {**openrouter_data, **vercel_data}
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# Combine all datasets
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all_remote_data = {**openrouter_data, **vercel_data, **friendli_data}
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# If both local and openrouter data are available, synchronize and save
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if local_data and all_remote_data:
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@ -46194,5 +46194,95 @@
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}
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}
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]
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},
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"friendliai/Qwen/Qwen3-235B-A22B-Instruct-2507": {
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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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"input_cost_per_token": 2e-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_response_schema": true,
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"litellm_provider": "friendliai",
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"mode": "chat",
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"deprecation_date": "2026-08-05"
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},
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"friendliai/LGAI-EXAONE/K-EXAONE-236B-A23B": {
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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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"input_cost_per_token": 2e-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_response_schema": true,
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"litellm_provider": "friendliai",
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"mode": "chat",
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"cache_read_input_token_cost": 1e-07
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},
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"friendliai/MiniMaxAI/MiniMax-M2.5": {
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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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"input_cost_per_token": 3e-07,
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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_response_schema": true,
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"litellm_provider": "friendliai",
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"mode": "chat",
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"cache_read_input_token_cost": 6e-08
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},
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"friendliai/deepseek-ai/DeepSeek-V3.2": {
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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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"input_cost_per_token": 5e-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_response_schema": true,
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"litellm_provider": "friendliai",
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"mode": "chat",
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"cache_read_input_token_cost": 2.5e-07
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},
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"friendliai/zai-org/GLM-5.1": {
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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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"input_cost_per_token": 1.4e-06,
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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_response_schema": true,
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"litellm_provider": "friendliai",
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"mode": "chat",
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"cache_read_input_token_cost": 2.6e-07
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},
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"friendliai/google/gemma-4-31B-it": {
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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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"input_cost_per_token": 1.4e-07,
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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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"litellm_provider": "friendliai",
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"mode": "chat"
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},
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"friendliai/zai-org/GLM-5.2": {
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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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"input_cost_per_token": 1.4e-06,
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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_response_schema": true,
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"litellm_provider": "friendliai",
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"mode": "chat",
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"cache_read_input_token_cost": 2.6e-07
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}
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}
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