busya
b190414747
T055: APIClient tombstone in network.py T056: AsyncSupersetClient @DEPRECATED marker T057: _llm_http.py + preview_llm_client.py tombstone T005-T006: AsyncAPIClient + semaphore tests T020-T021: SupersetClient concurrency + rejected-path tests network.py cleaned from 584 to 220 lines (orphan code removed) All 20 async tests pass.
224 lines
9.1 KiB
Python
224 lines
9.1 KiB
Python
# #region LLMHttpLegacy [Tombstone] [TYPE Module] [SEMANTICS translate, llm, http, deprecated]
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# @BRIEF Legacy synchronous LLM HTTP client — DEPRECATED.
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# @DEPRECATED 2026-06-04 — replaced by _llm_async_http.py (httpx.AsyncClient)
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# @REPLACED_BY -> [LLMHttpClient]
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# The async equivalent is in _llm_async_http.py
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# structured output fallback. Extracted from _llm_call.py for INV_7 compliance.
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# @LAYER Infrastructure
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# @RELATION DEPENDS_ON -> [EXT:requests]
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# @PRE Valid API endpoint, key, model, and prompt.
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# @POST Returns (response text, finish_reason) tuple.
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# @SIDE_EFFECT HTTP POST to LLM API with optional retry on 429.
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# @RATIONALE Extracted from LLMTranslationService (793 lines) to keep module under INV_7 limit.
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# @REJECTED Single HTTP client class — kept as module-level functions for stateless reusability.
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import os
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import time
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from typing import Any
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from ...core.logger import logger
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# #region _get_verify [C:1] [TYPE Function] [SEMANTICS translate, ssl, verify]
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# @BRIEF Resolve SSL verification path from LLM_SSL_VERIFY env var.
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# @RATIONALE Используем capath=/etc/ssl/certs/ вместо cafile, потому что
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# OpenSSL 3.x не использует intermediate CA сертификаты из cafile для
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# построения цепочки (verify code 20). capath с хеш-симлинками работает
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# корректно (verify code 0).
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# @REJECTED cafile отвергнут — OpenSSL 3.x не использует intermediate CA
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# из единого bundle-файла. Только capath с хеш-симлинками даёт code 0.
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# @POST Returns path to /etc/ssl/certs/ when enabled, False when disabled.
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def _get_verify() -> str | bool:
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raw = os.getenv("LLM_SSL_VERIFY", "true").strip().lower()
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if raw in ("false", "0", "no", "off"):
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return False
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return "/etc/ssl/certs/"
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# #endregion _get_verify
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# #region call_openai_compatible [C:3] [TYPE Function] [SEMANTICS translate, llm, http, openai]
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# @BRIEF Call OpenAI-compatible API with rate-limit handling and structured output fallback.
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# @PRE Valid API endpoint, key, model, and prompt.
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# @POST Returns (response text, finish_reason).
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# @SIDE_EFFECT HTTP POST to LLM API.
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def call_openai_compatible(
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base_url: str,
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api_key: str,
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model: str,
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prompt: str,
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provider_type: str = "openai",
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max_tokens: int = 8192,
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disable_reasoning: bool = False,
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) -> tuple[str, str | None]:
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"""Call OpenAI-compatible API for batch translation."""
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if not base_url:
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raise ValueError("LLM provider has no base_url configured")
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url = f"{base_url.rstrip('/')}/chat/completions"
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headers = {
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"Authorization": f"Bearer {api_key}",
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"Content-Type": "application/json",
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}
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system_content = (
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"You are a database content translation assistant. "
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"Translate the provided text accurately, preserving data semantics. "
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"Respond directly with ONLY the JSON result. "
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"Do NOT include any reasoning, thinking, chain-of-thought, analysis, "
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"or explanation. Output ONLY valid JSON."
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)
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payload: dict[str, Any] = {
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"model": model,
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"messages": [
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{"role": "system", "content": system_content},
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{"role": "user", "content": prompt},
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],
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"temperature": 0.1,
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"max_tokens": max_tokens,
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}
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if provider_type in ("openai", "openai_compatible", "kilo", "openrouter", "litellm"):
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if not disable_reasoning:
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payload["response_format"] = {"type": "json_object"}
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if disable_reasoning:
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if provider_type not in ("kilo", "openrouter", "litellm"):
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payload["reasoning_effort"] = "none"
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payload["max_tokens"] = max_tokens
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logger.reason(
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f"LLM request url={base_url} model={payload.get('model')} "
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f"provider_type={provider_type} "
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f"response_format={'yes' if 'response_format' in payload else 'no'} "
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f"prompt_len={len(prompt)}"
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)
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response, response_text = _do_http_request(url, headers, payload)
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_handle_response_format_fallback(response, response_text, payload, url, headers)
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if not response.ok:
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logger.explore(
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f"LLM API error status={response.status_code} "
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f"model={payload.get('model')} "
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f"body={response_text[:2000]}"
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)
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response.raise_for_status()
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data = response.json()
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choices = data.get("choices", [])
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if not choices:
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logger.explore("LLM returned no choices", extra={
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"src": "executor", "response_keys": list(data.keys()),
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"response_preview": str(data)[:2000],
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})
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raise ValueError("LLM returned no choices")
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try:
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finish_reason = choices[0].get("finish_reason") or "none"
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msg = choices[0].get("message") or {}
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except (TypeError, AttributeError) as e:
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logger.explore("TypeError processing LLM response choices", extra={
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"src": "executor_diag", "error": str(e),
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"choices_0_type": type(choices[0]).__name__ if choices else "N/A",
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"choices_0_repr": repr(choices[0])[:2000] if choices else "N/A",
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"data_type": type(data).__name__, "data_preview": str(data)[:2000],
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})
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raise ValueError(f"LLM response processing failed: {e}")
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# Log provider token usage for batch sizing calibration
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usage = data.get("usage") or {}
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if usage:
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logger.reason(
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"LLM provider usage",
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{
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"prompt_tokens": usage.get("prompt_tokens"),
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"completion_tokens": usage.get("completion_tokens"),
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"total_tokens": usage.get("total_tokens"),
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"finish_reason": finish_reason,
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"max_tokens_sent": max_tokens,
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"chars_sent": len(prompt),
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},
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)
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refusal = msg.get("refusal") if isinstance(msg, dict) else None
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if refusal:
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logger.explore("LLM refused to respond", extra={
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"src": "executor", "refusal": str(refusal)[:500], "finish_reason": finish_reason,
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})
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raise ValueError(f"LLM refused to respond: {refusal}")
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content = msg.get("content") if isinstance(msg, dict) else ""
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if not content and isinstance(msg, dict):
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content = msg.get("content") or ""
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logger.reason(
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f"LLM response finish_reason={finish_reason} content_len={len(content)} "
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f"msg_keys={list(msg.keys()) if isinstance(msg, dict) else []}"
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)
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if not content:
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logger.explore("LLM returned empty content", extra={
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"src": "executor", "finish_reason": finish_reason,
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"msg_keys": list(msg.keys()) if isinstance(msg, dict) else [],
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"response_preview": str(data)[:2000],
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})
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raise ValueError("LLM returned empty content")
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return content, finish_reason
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# #endregion call_openai_compatible
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# #region _do_http_request [C:1] [TYPE Function]
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def _do_http_request(url: str, headers: dict, payload: dict) -> tuple[Any, str]:
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"""Make HTTP POST with rate-limit (429) retry handling."""
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import requests as http_requests
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_max_retry_429 = 3
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_retry_count_429 = 0
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while _retry_count_429 < _max_retry_429:
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response = http_requests.post(url, headers=headers, json=payload, timeout=180, verify=_get_verify())
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response_text = response.text
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if response.status_code == 429:
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_retry_count_429 += 1
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retry_after = response.headers.get("Retry-After")
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if retry_after:
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try:
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wait = int(retry_after)
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except (ValueError, TypeError):
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wait = 2 ** _retry_count_429
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else:
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wait = 2 ** _retry_count_429
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logger.explore(f"Rate limited (429), retry {_retry_count_429}/{_max_retry_429} after {wait}s",
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extra={"src": "executor", "retry_after": retry_after, "wait": wait})
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time.sleep(wait)
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if _retry_count_429 >= _max_retry_429:
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break
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else:
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break
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return response, response_text
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# #endregion _do_http_request
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# #region _handle_response_format_fallback [C:1] [TYPE Function]
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def _handle_response_format_fallback(
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response: Any, response_text: str, payload: dict, url: str, headers: dict,
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) -> None:
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"""Handle 400 errors from structured_outputs not being supported."""
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import requests as http_requests
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_patterns = ("response_format", "structured_outputs", "structured", "json_object")
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if (
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not response.ok
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and response.status_code == 400
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and any(p in (response_text or "").lower() for p in _patterns)
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):
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logger.explore("Structured outputs not supported, retrying without response_format",
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extra={"src": "executor"})
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payload.pop("response_format", None)
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new_response = http_requests.post(url, headers=headers, json=payload, timeout=180, verify=_get_verify())
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response.status_code = new_response.status_code
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response._content = new_response.content
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response.encoding = new_response.encoding
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response.headers = new_response.headers
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# #endregion _handle_response_format_fallback
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# #endregion LLMHttpClient
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