diff --git a/api_llm_generate/api_llm_generate.py b/api_llm_generate/api_llm_generate.py new file mode 100644 index 0000000..db7314a --- /dev/null +++ b/api_llm_generate/api_llm_generate.py @@ -0,0 +1,256 @@ +# -*- coding: utf-8 -*- +import time + +import httpx +import json + + +def fetch_llm_generate_task(odoo_base_url="http://localhost:8069"): + """ + 从 Odoo 接口获取待生成的 LLM 任务数据 + + Args: + odoo_base_url: Odoo 服务地址，默认 http://localhost:8069 + + Returns: + dict or None: 返回获取到的任务数据，包含以下字段： + - id: 记录ID + - final_prompt: 最终提示词 + - system_prompt: 系统提示词 + - user_prompt: 用户提示词 + 如果没有待生成的任务，返回 None + """ + url = f"{odoo_base_url}/api/local-llm-generate/fetch" + + headers = { + "Content-Type": "application/json" + } + + payload = {} + + try: + print(f"[INFO] 正在请求 Odoo 接口: {url}") + response = httpx.post( + url, + headers=headers, + json=payload, + timeout=30 + ) + response.raise_for_status() + + data = response.json() + # print(f"[INFO] 接口返回数据: {json.dumps(data, ensure_ascii=False, indent=2)}") + + # 检查是否返回了 {"data": null}（没有待生成任务） + if isinstance(data, dict) and 'data' in data and data['data'] is None: + print("[INFO] 当前没有待生成的 LLM 任务") + exit(1) + + # 返回获取到的任务数据（包含 id, final_prompt, system_prompt, user_prompt） + if isinstance(data, dict) and 'id' in data: + print(f"[SUCCESS] 获取到任务数据, record_id={data['id']}") + return data + + print(f"[WARNING] 返回数据格式不符合预期: {data}") + return None + + except httpx.TimeoutException: + print("[ERROR] 请求超时") + return None + except httpx.ConnectError as e: + print(f"[ERROR] 连接错误: {e}") + return None + except httpx.HTTPStatusError as e: + print(f"[ERROR] HTTP 错误: {e}") + return None + except Exception as e: + print(f"[ERROR] 发生未知错误: {e}") + return None + + +def call_llm_generate(task_data, max_retries=3): + """ + 调用本地 Ollama LLM 生成内容 + + Args: + task_data: 包含 final_prompt, system_prompt, user_prompt 的字典 + max_retries: 最大重试次数，默认 max_retries 次 + + Returns: + str: 生成的内容，如果失败返回 "failed" + """ + if task_data is None: + print("[ERROR] task_data 为 None，无法调用 LLM") + return "failed" + + # 提取 task_data 中的字段 + final_prompt = task_data.get('final_prompt', '') + system_prompt = task_data.get('system_prompt', '') + user_prompt = task_data.get('user_prompt', '') + record_id = task_data.get('id', 'unknown') + + print(f"[INFO] 开始为 record_id={record_id} 调用本地 Ollama") + + # Ollama API 地址 + ollama_url = "http://localhost:11434/v1/chat/completions" + + # 组装 messages + messages = [] + if system_prompt: + messages.append({"role": "system", "content": system_prompt}) + if final_prompt: + messages.append({"role": "user", "content": final_prompt}) + + # 请求体 + payload = { + "model": "kimi-k2.5:cloud", + "messages": messages, + "stream": False + } + + # 重试机制 + for attempt in range(1, max_retries + 1): + try: + print(f"[INFO] 第 {attempt} 次尝试调用 Ollama...") + + response = httpx.post( + ollama_url, + json=payload, + timeout=600 + ) + response.raise_for_status() + + result = response.json() + + # 提取生成的内容 + if "choices" in result and len(result["choices"]) > 0: + generated_content = result["choices"][0].get("message", {}).get("content", "") + if generated_content: + print(f"[SUCCESS] 第 {attempt} 次尝试成功，生成长度: {len(generated_content)} 字符") + return generated_content + else: + print(f"[WARNING] 第 {attempt} 次尝试返回空内容") + else: + print(f"[WARNING] 第 {attempt} 次尝试返回格式异常: {result}") + + except httpx.TimeoutException: + print(f"[ERROR] 第 {attempt} 次尝试超时") + except httpx.ConnectError as e: + print(f"[ERROR] 第 {attempt} 次尝试连接错误: {e}") + except httpx.HTTPStatusError as e: + print(f"[ERROR] 第 {attempt} 次尝试 HTTP 错误: {e}") + except Exception as e: + print(f"[ERROR] 第 {attempt} 次尝试发生未知错误: {e}") + + # 如果不是最后一次尝试，等待后继续 + if attempt < max_retries: + import time + print(f"[INFO] 等待 2 秒后重试...") + time.sleep(2) + + # 所有重试都失败了 + print(f"[FAILED] 经过 {max_retries} 次尝试后仍然失败") + return "failed" + + +def upload_llm_result(odoo_base_url, upload_data): + """ + 上传 LLM 生成结果到 Odoo + + Args: + odoo_base_url: Odoo 服务地址 + upload_data: 包含以下字段的字典： + - record_id: int, 记录ID + - status: str, "success" 或 "failed" + - result: str, 成功时的生成内容 + - error_message: str, 失败时的错误信息 + + Returns: + bool: 上传成功返回 True，失败返回 False + """ + url = f"{odoo_base_url}/api/alpha-idea/result" + + headers = { + "Content-Type": "application/json" + } + + try: + print(f"[INFO] 正在上传结果到 Odoo: {url}") + print(f"[INFO] 上传数据: {json.dumps(upload_data, ensure_ascii=False)}") + + response = httpx.post( + url, + headers=headers, + json=upload_data, + timeout=30 + ) + response.raise_for_status() + + result = response.json() + print(f"[INFO] 上传结果接口返回: {json.dumps(result, ensure_ascii=False)}") + + # 检查返回结果 + if isinstance(result, dict): + if result.get('status') == 'success' or result.get('success') is True: + print(f"[SUCCESS] 结果上传成功") + return True + + print(f"[WARNING] 结果上传可能失败: {result}") + return False + + except httpx.TimeoutException: + print("[ERROR] 上传结果超时") + return False + except httpx.ConnectError as e: + print(f"[ERROR] 上传结果连接错误: {e}") + return False + except httpx.HTTPStatusError as e: + print(f"[ERROR] 上传结果 HTTP 错误: {e}") + return False + except Exception as e: + print(f"[ERROR] 上传结果发生未知错误: {e}") + return False + + +if __name__ == "__main__": + # 配置 Odoo 服务地址 + ODOO_BASE_URL = "https://quantify.erhe.top" + + print("开始获取 LLM 生成任务...") + + while True: + # 获取任务数据 + task_data = fetch_llm_generate_task(odoo_base_url=ODOO_BASE_URL) + + if not task_data: + break + + llm_generate_result = call_llm_generate(task_data) + + print(llm_generate_result) + + if llm_generate_result != "failed": + print("开始上传 LLM 生成结果...") + upload_data = { + 'record_id': task_data['id'], + 'status': 'success', + 'result': llm_generate_result + } + else: + print("开始上传 LLM 生成结果失败...") + upload_data = { + 'record_id': task_data['id'], + 'status': 'failed', + 'result': '', + 'error_message': 'generate failed' + } + + # 上传结果到 Odoo + upload_success = upload_llm_result(ODOO_BASE_URL, upload_data) + if upload_success: + print("[SUCCESS] 整个流程完成") + else: + print("[FAILED] 结果上传失败") + + time.sleep(60) +