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fix: defensive parsing

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oskar 2026-07-13 18:32:38 +07:00
parent 709e53c02d
commit 6bd0219c75
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1 changed files with 19 additions and 12 deletions
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31
.github/workflows/auto_update_price_and_context_window_file.py vendored
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@ -85,24 +85,31 @@ def transform_openrouter_data(data):
def transform_vercel_ai_gateway_data(data):
transformed = {}
for row in data:
obj = {
"max_tokens": row["context_window"],
"input_cost_per_token": float(row["pricing"]["input"]),
"output_cost_per_token": float(row["pricing"]["output"]),
'max_output_tokens': row['max_tokens'],
'max_input_tokens': row["context_window"],
}
obj = {}
if "context_window" in row:
obj['max_tokens'] = row["context_window"]
obj['max_input_tokens'] = row["context_window"]
if "pricing" in row:
if "input" in row["pricing"] and row["pricing"]["input"] is not None:
obj['input_cost_per_token'] = float(row["pricing"]["input"])
if "output" in row["pricing"] and row["pricing"]["output"] is not None:
obj['output_cost_per_token'] = float(row["pricing"]["output"])
if "max_tokens" in row:
obj['max_output_tokens'] = row['max_tokens']
# Handle cache pricing if available
if "pricing" in row:
if "input_cache_read" in row["pricing"] and row["pricing"]["input_cache_read"] is not None:
obj['cache_read_input_token_cost'] = float(f"{float(row['pricing']['input_cache_read']):e}")
if "input_cache_write" in row["pricing"] and row["pricing"]["input_cache_write"] is not None:
obj['cache_creation_input_token_cost'] = float(f"{float(row['pricing']['input_cache_write']):e}")
mode = "embedding" if "embedding" in row["id"].lower() else "chat"
obj.update({"litellm_provider": "vercel_ai_gateway", "mode": mode})
transformed[f'vercel_ai_gateway/{row["id"]}'] = obj
@ -133,17 +140,17 @@ def main():
# Load local data from file
local_data = load_local_data(local_file_path)
# Fetch OpenRouter data
openrouter_data = asyncio.run(fetch_data(openrouter_url))
# Transform the fetched OpenRouter data
openrouter_data = transform_openrouter_data(openrouter_data)
# Fetch Vercel AI Gateway data
vercel_data = asyncio.run(fetch_data(vercel_ai_gateway_url))
# Transform the fetched Vercel AI Gateway data
vercel_data = transform_vercel_ai_gateway_data(vercel_data)
# Combine both datasets
all_remote_data = {**openrouter_data, **vercel_data}