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https://github.com/Significant-Gravitas/AutoGPT.git
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feat(platform): add copilot/autopilot cost tracking via token_tracking.py
Copilot uses OpenRouter via a separate code path (not through the block executor). This integrates PlatformCostLog into the shared persist_and_record_usage() function which is called by both SDK and baseline copilot paths, capturing: - Every LLM turn (main conversation, title gen, context compression) - Tokens (prompt + completion + cache) - Actual USD cost when available (SDK path provides cost_usd) - Session ID for correlation
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@@ -4,12 +4,15 @@ Both the baseline (OpenRouter) and SDK (Anthropic) service layers need to:
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1. Append a ``Usage`` record to the session.
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2. Log the turn's token counts.
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3. Record weighted usage in Redis for rate-limiting.
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4. Write a PlatformCostLog entry for admin cost tracking.
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This module extracts that common logic so both paths stay in sync.
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"""
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import logging
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from backend.data.platform_cost import PlatformCostEntry, log_platform_cost_safe
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from .model import ChatSession, Usage
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from .rate_limit import record_token_usage
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@@ -95,4 +98,45 @@ async def persist_and_record_usage(
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except Exception as usage_err:
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logger.warning(f"{log_prefix} Failed to record token usage: {usage_err}")
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# Log to PlatformCostLog for admin cost dashboard
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if user_id and total_tokens > 0:
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cost_float = None
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if cost_usd is not None:
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try:
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cost_float = float(cost_usd)
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except (ValueError, TypeError):
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pass
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cost_microdollars = int(cost_float * 1_000_000) if cost_float else None
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session_id = session.session_id if session else None
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if cost_float is not None:
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tracking_type = "cost_usd"
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tracking_amount = cost_float
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else:
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tracking_type = "tokens"
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tracking_amount = total_tokens
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await log_platform_cost_safe(
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PlatformCostEntry(
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user_id=user_id,
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graph_exec_id=session_id,
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block_id="copilot",
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block_name=f"copilot:{log_prefix.strip(' []')}".rstrip(":"),
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provider="open_router",
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credential_id="copilot_system",
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cost_microdollars=cost_microdollars,
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input_tokens=prompt_tokens,
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output_tokens=completion_tokens,
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model=None,
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metadata={
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"tracking_type": tracking_type,
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"tracking_amount": tracking_amount,
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"cache_read_tokens": cache_read_tokens,
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"cache_creation_tokens": cache_creation_tokens,
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"source": "copilot",
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},
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)
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)
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return total_tokens
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