feat: 新增 oss 与智普图片解析功能
This commit is contained in:
parent
89b02c4c93
commit
cb80d5cee7
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@ -35,8 +35,12 @@ from pathlib import Path
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sys.path.append(str(Path(__file__).parent.parent))
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from models.chat_models import ChatRequest, ModelInfo
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from utils.helpers import (extract_delta_content, format_api_response,
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generate_unique_id, get_current_timestamp)
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from utils.helpers import (
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extract_delta_content,
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format_api_response,
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generate_unique_id,
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get_current_timestamp,
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)
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from utils.logger import log_error, log_exception, log_info
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# 模拟数据库 - 实际应用中应使用持久化存储
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@ -1030,13 +1034,18 @@ async def upload_file_handler(file: UploadFile = File(...)):
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unique_filename = f"{int(datetime.utcnow().timestamp())}_{generate_unique_id()}{file_extension}"
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file_path = upload_dir / unique_filename
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# 保存文件
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# 保存文件到本地（临时缓存）
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content = await file.read()
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with open(file_path, "wb") as f:
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content = await file.read()
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f.write(content)
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# 文件关闭后再上传到 OSS
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from utils.oss_uploader import upload_file as oss_upload
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oss_result = oss_upload(str(file_path))
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file_url = oss_result["url"]
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# 返回文件信息
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file_url = f"http://localhost:8000/uploads/{unique_filename}"
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result = {
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"url": file_url,
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"name": file.filename,
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@ -9,3 +9,5 @@ typing-extensions==4.12.2
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# 路线二：阿里云文档智能解析（doc/docx/pdf）
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llama-index-core>=0.10.0
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llama-index-readers-dashscope>=0.1.0
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# 阿里云 OSS 上传
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alibabacloud-oss-v2
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@ -47,7 +47,7 @@ def get_client():
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# ── 模型映射 ──────────────────────────────────────────────────────────
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DEFAULT_TEXT_MODEL = "glm-4.5-Air" # glm-4.6 文本统一模型
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DEFAULT_VISION_MODEL = "glm-4.5-Air"
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DEFAULT_VISION_MODEL = "glm-4.6v"
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MODEL_MAP = {
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"qwen-max": "glm-4.5-Air",
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@ -61,7 +61,12 @@ MODEL_MAP = {
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def resolve_model(model: str, has_vision: bool = False) -> str:
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if model.startswith("glm"):
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return model
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return MODEL_MAP.get(model, DEFAULT_TEXT_MODEL)
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mapped = MODEL_MAP.get(model, DEFAULT_TEXT_MODEL)
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# 当消息包含图片时，强制使用视觉模型
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if has_vision and mapped != DEFAULT_VISION_MODEL:
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print(f"[GLM] 检测到图片，模型从 {mapped} 切换为 {DEFAULT_VISION_MODEL}")
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return DEFAULT_VISION_MODEL
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return mapped
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# ── 文件上传（含 file_id 缓存）───────────────────────────────────────
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@ -249,6 +254,44 @@ async def glm_stream_generator(
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f"[GLM] 流式请求：model={actual_model} vision={has_vision} "
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f"web_search={web_search} thinking={deep_thinking}"
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)
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# ── 调试：打印发送给 GLM 的完整消息结构 ──
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for i, msg in enumerate(glm_msgs):
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role = msg.get("role", "?")
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content = msg.get("content", "")
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if isinstance(content, list):
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for j, part in enumerate(content):
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if not isinstance(part, dict):
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print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {type(part).__name__}")
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continue
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part_type = part.get("type", "?")
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if part_type == "image_url":
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img_val = part.get("image_url", "")
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img_url = (
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img_val.get("url", "")
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if isinstance(img_val, dict)
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else str(img_val)
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)
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display = img_url[:120] + "..." if len(img_url) > 120 else img_url
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print(
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f"[GLM-DEBUG] msg[{i}].content[{j}]: type=image_url, url={display}"
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)
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elif part_type == "text":
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preview = (part.get("text", "") or "")[:100]
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print(
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f"[GLM-DEBUG] msg[{i}].content[{j}]: type=text, text={preview}"
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)
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else:
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print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {part}")
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else:
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print(f"[GLM-DEBUG] msg[{i}]: role={role}, content={str(content)[:150]}")
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if extra_kwargs:
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print(f"[GLM-DEBUG] extra_kwargs={extra_kwargs}")
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# 原始 JSON 转储（用于排查结构问题）
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import json as _json
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print(
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f"[GLM-RAW] messages={_json.dumps(glm_msgs, ensure_ascii=False, default=str)[:2000]}"
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)
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chunk_queue: queue.Queue = queue.Queue(maxsize=128)
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@ -367,6 +410,44 @@ def glm_chat_sync(
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client = get_client()
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print(f"[GLM] 非流式请求：model={actual_model}")
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# ── 调试：打印发送给 GLM 的完整消息结构 ──
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for i, msg in enumerate(glm_msgs):
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role = msg.get("role", "?")
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content = msg.get("content", "")
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if isinstance(content, list):
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for j, part in enumerate(content):
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if not isinstance(part, dict):
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print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {type(part).__name__}")
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continue
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part_type = part.get("type", "?")
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if part_type == "image_url":
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img_val = part.get("image_url", "")
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img_url = (
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img_val.get("url", "")
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if isinstance(img_val, dict)
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else str(img_val)
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)
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display = img_url[:120] + "..." if len(img_url) > 120 else img_url
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print(
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f"[GLM-DEBUG] msg[{i}].content[{j}]: type=image_url, url={display}"
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)
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elif part_type == "text":
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preview = (part.get("text", "") or "")[:100]
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print(
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f"[GLM-DEBUG] msg[{i}].content[{j}]: type=text, text={preview}"
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)
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else:
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print(f"[GLM-DEBUG] msg[{i}].content[{j}]: {part}")
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else:
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print(f"[GLM-DEBUG] msg[{i}]: role={role}, content={str(content)[:150]}")
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if extra_kwargs:
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print(f"[GLM-DEBUG] extra_kwargs={extra_kwargs}")
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# 原始 JSON 转储（用于排查结构问题）
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import json as _json
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print(
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f"[GLM-RAW] messages={_json.dumps(glm_msgs, ensure_ascii=False, default=str)[:2000]}"
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)
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resp = client.chat.completions.create(
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model=actual_model,
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messages=glm_msgs,
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@ -0,0 +1,227 @@
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"""
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阿里云 OSS 简单上传工具
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参考文档: https://help.aliyun.com/zh/oss/user-guide/simple-upload
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支持:
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- 上传本地文件
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- 上传字节数据 / 字符串
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- 上传文件流（file-like object）
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- 自动根据文件后缀生成 OSS 对象路径
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- 返回可公开访问的 URL（需确保 Bucket 已开启公共读或已配置签名）
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前置条件:
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1. pip install alibabacloud-oss-v2
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2. 在 .env 中配置以下变量:
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OSS_ACCESS_KEY_ID=<你的 AccessKey ID>
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OSS_ACCESS_KEY_SECRET=<你的 AccessKey Secret>
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OSS_BUCKET_NAME=<存储空间名称>
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OSS_ENDPOINT=<Endpoint，如 https://oss-cn-hangzhou.aliyuncs.com>
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OSS_REGION=<地域，如 cn-hangzhou>
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OSS_URL_PREFIX=<可选，自定义域名前缀，如 https://cdn.example.com>
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"""
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import os
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import uuid
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import mimetypes
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from datetime import datetime
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from pathlib import Path
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from typing import Optional, Union, BinaryIO
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import alibabacloud_oss_v2 as oss
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from dotenv import load_dotenv
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# ── 加载环境变量 ──────────────────────────────────────────────
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load_dotenv()
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# AccessKey 从系统环境变量读取（~/.bashrc 中 export 设置）
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OSS_ACCESS_KEY_ID = os.environ.get("OSS_ACCESS_KEY_ID", "")
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OSS_ACCESS_KEY_SECRET = os.environ.get("OSS_ACCESS_KEY_SECRET", "")
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# 以下配置从 .env 文件读取
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OSS_BUCKET_NAME = os.getenv("OSS_BUCKET_NAME", "")
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OSS_ENDPOINT = os.getenv("OSS_ENDPOINT", "")
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OSS_REGION = os.getenv("OSS_REGION", "")
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# 可选：自定义域名前缀，用于拼接返回的公开 URL
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OSS_URL_PREFIX = os.getenv("OSS_URL_PREFIX", "")
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def _get_client() -> oss.Client:
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"""创建并返回 OSS 客户端实例"""
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credentials_provider = oss.credentials.StaticCredentialsProvider(
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access_key_id=OSS_ACCESS_KEY_ID,
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access_key_secret=OSS_ACCESS_KEY_SECRET,
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)
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cfg = oss.config.load_default()
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cfg.credentials_provider = credentials_provider
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cfg.region = OSS_REGION
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cfg.endpoint = OSS_ENDPOINT
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return oss.Client(cfg)
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def _generate_object_key(filename: str, prefix: str = "uploads") -> str:
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"""
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根据文件名生成唯一的 OSS 对象 Key
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格式: {prefix}/{日期}/{uuid}_{原始文件名}
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"""
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date_str = datetime.now().strftime("%Y%m%d")
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unique_id = uuid.uuid4().hex[:8]
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safe_name = Path(filename).name # 只取文件名，去掉路径
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return f"{prefix}/{date_str}/{unique_id}_{safe_name}"
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def _build_url(object_key: str) -> str:
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"""根据对象 Key 构建可访问的 URL"""
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if OSS_URL_PREFIX:
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return f"{OSS_URL_PREFIX.rstrip('/')}/{object_key}"
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# 默认使用 Bucket 域名拼接
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endpoint = OSS_ENDPOINT.replace("https://", "").replace("http://", "")
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return f"https://{OSS_BUCKET_NAME}.{endpoint}/{object_key}"
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def upload_file(
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file_path: str,
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object_key: Optional[str] = None,
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prefix: str = "uploads",
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) -> dict:
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"""
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上传本地文件到 OSS
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参数:
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file_path: 本地文件的绝对路径
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object_key: 自定义 OSS 对象名称，为 None 则自动生成
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prefix: 对象 Key 的前缀目录
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返回:
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包含上传结果的字典:
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{
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"url": "文件访问地址",
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"object_key": "OSS 对象路径",
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"etag": "ETag",
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"status_code": 200,
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}
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"""
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if not os.path.isfile(file_path):
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raise FileNotFoundError(f"文件不存在: {file_path}")
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filename = os.path.basename(file_path)
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if object_key is None:
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object_key = _generate_object_key(filename, prefix)
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# 检测文件类型，设置 Content-Type
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content_type, _ = mimetypes.guess_type(file_path)
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client = _get_client()
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result = client.put_object_from_file(
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oss.PutObjectRequest(
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bucket=OSS_BUCKET_NAME,
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key=object_key,
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content_type=content_type,
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),
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file_path,
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)
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return {
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"url": _build_url(object_key),
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"object_key": object_key,
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"etag": result.etag,
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"status_code": result.status_code,
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}
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def upload_bytes(
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data: Union[bytes, str],
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filename: str,
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object_key: Optional[str] = None,
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prefix: str = "uploads",
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content_type: Optional[str] = None,
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) -> dict:
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"""
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上传字节数据或字符串到 OSS
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参数:
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data: 要上传的数据（bytes 或 str）
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filename: 用于生成 Key 的文件名（如 "report.txt"）
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object_key: 自定义 OSS 对象名称，为 None 则自动生成
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prefix: 对象 Key 的前缀目录
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content_type: 自定义 Content-Type
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返回:
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包含上传结果的字典
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"""
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if isinstance(data, str):
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data = data.encode("utf-8")
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if object_key is None:
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object_key = _generate_object_key(filename, prefix)
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if content_type is None:
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content_type, _ = mimetypes.guess_type(filename)
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client = _get_client()
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result = client.put_object(
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oss.PutObjectRequest(
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bucket=OSS_BUCKET_NAME,
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key=object_key,
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body=data,
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content_type=content_type,
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)
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)
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return {
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"url": _build_url(object_key),
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"object_key": object_key,
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"etag": result.etag,
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"status_code": result.status_code,
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}
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def upload_fileobj(
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fileobj: BinaryIO,
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filename: str,
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object_key: Optional[str] = None,
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prefix: str = "uploads",
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content_type: Optional[str] = None,
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) -> dict:
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"""
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上传文件流（file-like object）到 OSS
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参数:
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fileobj: 文件流对象（如 open(path, 'rb') 或 FastAPI 的 UploadFile.file）
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filename: 用于生成 Key 的文件名
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object_key: 自定义 OSS 对象名称，为 None 则自动生成
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prefix: 对象 Key 的前缀目录
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content_type: 自定义 Content-Type
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返回:
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包含上传结果的字典
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"""
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data = fileobj.read()
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return upload_bytes(
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data=data,
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filename=filename,
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object_key=object_key,
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prefix=prefix,
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content_type=content_type,
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)
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# ────────────────────────────────────────────────────────────────
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# 命令行入口：python -m utils.oss_uploader --file <路径>
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# ────────────────────────────────────────────────────────────────
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser(description="阿里云 OSS 简单上传工具")
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parser.add_argument("--file", required=True, help="要上传的本地文件路径")
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parser.add_argument("--key", default=None, help="自定义 OSS 对象路径（可选）")
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parser.add_argument(
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"--prefix", default="uploads", help="对象 Key 前缀（默认: uploads）"
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)
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args = parser.parse_args()
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result = upload_file(args.file, object_key=args.key, prefix=args.prefix)
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print("✅ 上传成功!")
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print(f" 访问地址: {result['url']}")
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print(f" 对象路径: {result['object_key']}")
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print(f" ETag: {result['etag']}")
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print(f" 状态码: {result['status_code']}")
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@ -0,0 +1,89 @@
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"""
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测试脚本：上传文件到 OSS → 获取 URL → 发送给 GLM 进行识别
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用法:
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cd server
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source ~/.bashrc && source .venv/bin/activate
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python -m utils.test_oss_glm --file <本地文件路径> [--prompt "描述一下这张图片"]
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"""
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import argparse
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import sys
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from pathlib import Path
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# 确保 server 目录在 sys.path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from utils.oss_uploader import upload_file
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from utils.glm_adapter import glm_chat_sync
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def main():
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parser = argparse.ArgumentParser(description="上传文件到 OSS 并让 GLM 读取")
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parser.add_argument("--file", required=True, help="要上传的本地文件路径")
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parser.add_argument(
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"--prompt", default="请描述一下这张图片的内容", help="发给 GLM 的提示词"
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)
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parser.add_argument(
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"--model", default="glm-4.6v", help="GLM 模型名称（默认: glm-4.6v）"
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)
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args = parser.parse_args()
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# ── 第一步：上传文件到 OSS ────────────────────────────────
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file_path = args.file
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if not Path(file_path).exists():
|
||||
print(f"❌ 文件不存在: {file_path}")
|
||||
sys.exit(1)
|
||||
|
||||
print(f"📤 正在上传文件: {file_path}")
|
||||
oss_result = upload_file(file_path)
|
||||
file_url = oss_result["url"]
|
||||
print(f"✅ 上传成功!")
|
||||
print(f" URL: {file_url}")
|
||||
print()
|
||||
|
||||
# ── 第二步：构建消息，把 URL 发给 GLM ──────────────────────
|
||||
messages = [
|
||||
{
|
||||
"role": "user",
|
||||
"content": [
|
||||
{
|
||||
"type": "image_url",
|
||||
"image_url": {"url": file_url},
|
||||
},
|
||||
{
|
||||
"type": "text",
|
||||
"text": args.prompt,
|
||||
},
|
||||
],
|
||||
}
|
||||
]
|
||||
|
||||
print(f"🤖 正在请求 GLM ({args.model}) 识别图片...")
|
||||
print(f" 提示词: {args.prompt}")
|
||||
print()
|
||||
|
||||
result = glm_chat_sync(
|
||||
messages=messages,
|
||||
model=args.model,
|
||||
temperature=0.7,
|
||||
max_tokens=2048,
|
||||
)
|
||||
|
||||
print("─" * 60)
|
||||
print("📝 GLM 回复:")
|
||||
print("─" * 60)
|
||||
print(result["content"])
|
||||
print("─" * 60)
|
||||
|
||||
if result.get("usage"):
|
||||
usage = result["usage"]
|
||||
print(
|
||||
f"\n📊 Token 用量: 输入 {usage['promptTokens']} | "
|
||||
f"输出 {usage['completionTokens']} | "
|
||||
f"总计 {usage['totalTokens']}"
|
||||
)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
Loading…
Reference in New Issue