feat: integrate llm-connect FR-1/FR-3/FR-4 into IHF bridge
FR-3 (async_execute_prompt): CollectiveProposals now invokes all agents
concurrently via callAgentsBatch → single bridge subprocess with
asyncio.gather. Latency scales with slowest agent, not sum.
FR-4 (BudgetTracker): AgentDelegations passes tokenBudget to bridge;
llm-connect enforces it natively via BudgetTracker in RunConfig.
BudgetExceededError is a first-class BridgeError variant with total/
consumed/requested fields surfaced to the operator.
FR-1 (LLMServer passthrough): bridge accepts optional serverUrl field;
if present, calls POST {serverUrl}/execute instead of spawning a new
adapter. Infrastructure ready for hot-agent pre-warming (no schema
change required).
AgentBridge.hs: adds callAgentsBatch, callAgentWithBudget,
BudgetExceededError constructor, bridgeErrorMessage helper, defaultRequest,
requestToJson. All controllers updated to use bridgeErrorMessage.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
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7 changed files with 350 additions and 75 deletions
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@ -1,11 +1,10 @@
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#!/usr/bin/env python3
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"""
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IHF llm-connect bridge — Phase 11 AI Federation (IHUB-WP-0012)
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Updated to use llm-connect FR-1 (server passthrough), FR-3 (async batch),
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FR-4 (BudgetTracker).
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Usage:
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echo '{"provider":"openrouter","model":"...","prompt":"..."}' | python3 scripts/llm_bridge.py
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Input JSON fields:
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SINGLE REQUEST — stdin JSON fields:
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provider — openrouter | gemini | openai | claude-code (default: openrouter)
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model — model name string (provider-specific)
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prompt — the user prompt
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@ -13,54 +12,211 @@ Input JSON fields:
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api_key — optional; falls back to llm-connect env-var resolution
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maxTokens — max completion tokens (default: 2000)
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temperature — sampling temperature (default: 0.7)
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budgetTotal — optional int; if set, a BudgetTracker is created with this cap
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budgetSpent — optional int; tokens already consumed (for delegation chains)
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serverUrl — optional str; if set, POST to {serverUrl}/execute instead of
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spawning a local adapter (FR-1 server passthrough)
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Output JSON (stdout, exit 0 on success):
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BATCH REQUEST — stdin JSON with "batch" key:
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batch — list of single-request objects (see above)
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All top-level fields (except batch) are ignored.
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Output JSON — single request (stdout, exit 0 on success):
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content — generated text
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model — model name actually used
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tokensIn — prompt token count
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tokensOut — completion token count
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finishReason — stop reason string
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budgetSpent — cumulative tokens consumed from BudgetTracker after this call
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Error JSON (stdout, exit 1 on LLMError):
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Output JSON — batch request (stdout, exit 0 even on partial failure):
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results — list of {content, model, tokensIn, tokensOut, finishReason}
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OR {error, errorType} per item
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Error JSON (stdout, exit 1 on LLMError for single request):
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error — error message
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errorType — exception class name
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budgetTotal — present only for LLMBudgetExceededError
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budgetSpent — present only for LLMBudgetExceededError
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budgetRequested — present only for LLMBudgetExceededError
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"""
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import sys
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import json
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import os
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import asyncio
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from typing import Any
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sys.path.insert(0, os.path.expanduser("~/llm-connect"))
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from llm_connect import create_adapter, RunConfig
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from llm_connect.exceptions import LLMError
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from llm_connect import create_adapter, RunConfig, BudgetTracker
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from llm_connect.exceptions import LLMError, LLMBudgetExceededError
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def main() -> None:
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req = json.load(sys.stdin)
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# ---------------------------------------------------------------------------
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# Adapter / server call
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def _make_config(req: dict, tracker: BudgetTracker | None) -> RunConfig:
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return RunConfig(
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model_name=req.get("model", ""),
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temperature=req.get("temperature", 0.7),
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max_tokens=req.get("maxTokens", 2000),
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budget_tracker=tracker,
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)
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def _call_server(server_url: str, req: dict, config: RunConfig) -> dict:
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"""Call a running LLMServer via HTTP POST /execute (FR-1)."""
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import urllib.request
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payload = json.dumps({
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"prompt": req["prompt"],
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"config": config.to_dict(),
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}).encode()
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http_req = urllib.request.Request(
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f"{server_url.rstrip('/')}/execute",
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data=payload,
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headers={"Content-Type": "application/json"},
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method="POST",
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)
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with urllib.request.urlopen(http_req, timeout=config.timeout_seconds) as resp:
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return json.loads(resp.read())
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def _execute_single(req: dict) -> dict:
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"""Execute one request dict, return a result or error dict."""
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# Build optional BudgetTracker (FR-4)
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tracker: BudgetTracker | None = None
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if "budgetTotal" in req:
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tracker = BudgetTracker(total=int(req["budgetTotal"]))
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already_spent = int(req.get("budgetSpent", 0))
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if already_spent > 0:
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tracker.consume(already_spent)
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config = _make_config(req, tracker)
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try:
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server_url = req.get("serverUrl")
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if server_url:
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# FR-1: delegate to running LLMServer
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raw = _call_server(server_url, req, config)
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spent = tracker.spent if tracker else 0
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return {
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"content": raw.get("content", ""),
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"model": raw.get("model", ""),
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"tokensIn": raw.get("usage", {}).get("prompt_tokens", 0),
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"tokensOut": raw.get("usage", {}).get("completion_tokens", 0),
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"finishReason": raw.get("finish_reason", "stop"),
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"budgetSpent": spent,
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}
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adapter = create_adapter(
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provider=req.get("provider", "openrouter"),
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model=req.get("model"),
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api_key=req.get("api_key"),
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system_prompt=req.get("systemPrompt"),
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)
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config = RunConfig(
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model_name=req.get("model", ""),
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temperature=req.get("temperature", 0.7),
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max_tokens=req.get("maxTokens", 2000),
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)
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resp = adapter.execute_prompt(req["prompt"], config)
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print(json.dumps({
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"content": resp.content,
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"model": resp.model,
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"tokensIn": resp.usage.get("prompt_tokens", 0),
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"tokensOut": resp.usage.get("completion_tokens", 0),
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spent = tracker.spent if tracker else 0
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return {
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"content": resp.content,
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"model": resp.model,
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"tokensIn": resp.usage.get("prompt_tokens", 0),
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"tokensOut": resp.usage.get("completion_tokens", 0),
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"finishReason": resp.finish_reason,
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}))
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"budgetSpent": spent,
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}
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except LLMBudgetExceededError as e:
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return {
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"error": str(e),
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"errorType": "LLMBudgetExceededError",
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"budgetTotal": e.total,
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"budgetSpent": e.spent,
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"budgetRequested": e.requested,
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}
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except LLMError as e:
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json.dump({"error": str(e), "errorType": type(e).__name__}, sys.stdout)
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return {"error": str(e), "errorType": type(e).__name__}
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# ---------------------------------------------------------------------------
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# Async batch execution (FR-3)
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async def _execute_all_async(requests: list[dict]) -> list[dict]:
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"""Run all requests concurrently via async_execute_prompt (FR-3)."""
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async def _one(req: dict) -> dict:
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tracker: BudgetTracker | None = None
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if "budgetTotal" in req:
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tracker = BudgetTracker(total=int(req["budgetTotal"]))
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already_spent = int(req.get("budgetSpent", 0))
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if already_spent > 0:
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tracker.consume(already_spent)
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config = _make_config(req, tracker)
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try:
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server_url = req.get("serverUrl")
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if server_url:
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# Server calls are already non-blocking HTTP; run in executor
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loop = asyncio.get_running_loop()
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raw = await loop.run_in_executor(
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None, lambda: _call_server(server_url, req, config)
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)
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spent = tracker.spent if tracker else 0
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return {
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"content": raw.get("content", ""),
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"model": raw.get("model", ""),
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"tokensIn": raw.get("usage", {}).get("prompt_tokens", 0),
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"tokensOut": raw.get("usage", {}).get("completion_tokens", 0),
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"finishReason": raw.get("finish_reason", "stop"),
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"budgetSpent": spent,
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}
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adapter = create_adapter(
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provider=req.get("provider", "openrouter"),
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model=req.get("model"),
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api_key=req.get("api_key"),
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system_prompt=req.get("systemPrompt"),
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)
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resp = await adapter.async_execute_prompt(req["prompt"], config)
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spent = tracker.spent if tracker else 0
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return {
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"content": resp.content,
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"model": resp.model,
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"tokensIn": resp.usage.get("prompt_tokens", 0),
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"tokensOut": resp.usage.get("completion_tokens", 0),
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"finishReason": resp.finish_reason,
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"budgetSpent": spent,
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}
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except LLMBudgetExceededError as e:
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return {
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"error": str(e),
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"errorType": "LLMBudgetExceededError",
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"budgetTotal": e.total,
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"budgetSpent": e.spent,
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"budgetRequested": e.requested,
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}
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except LLMError as e:
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return {"error": str(e), "errorType": type(e).__name__}
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return await asyncio.gather(*[_one(r) for r in requests])
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# ---------------------------------------------------------------------------
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# Entry point
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def main() -> None:
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req = json.load(sys.stdin)
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if "batch" in req:
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# Batch mode: run all requests concurrently (FR-3)
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results = asyncio.run(_execute_all_async(req["batch"]))
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print(json.dumps({"results": results}))
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return
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# Single request
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result = _execute_single(req)
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if "error" in result:
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json.dump(result, sys.stdout)
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sys.exit(1)
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print(json.dumps(result))
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if __name__ == "__main__":
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