diff --git a/.env.template b/.env.template index 453e2c6d3..792a0c49b 100644 --- a/.env.template +++ b/.env.template @@ -241,10 +241,8 @@ TONGYI_PROXY_API_KEY={your-tongyi-sk} #BAICHUAN_PROXY_API_SECRET={your-baichuan-sct} # Xunfei Spark -#XUNFEI_SPARK_API_VERSION={version} -#XUNFEI_SPARK_APPID={your_app_id} -#XUNFEI_SPARK_API_KEY={your_api_key} -#XUNFEI_SPARK_API_SECRET={your_api_secret} +#XUNFEI_SPARK_API_PASSWORD={your_api_password} +#XUNFEI_SPARK_API_MODEL={version} ## Yi Proxyllm, https://platform.lingyiwanwu.com/docs #YI_MODEL_VERSION=yi-34b-chat-0205 diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml index eb82f70f8..3ca80641c 100644 --- a/.pre-commit-config.yaml +++ b/.pre-commit-config.yaml @@ -1,41 +1,41 @@ -# Please run command `pre-commit install` to install pre-commit hook -repos: - - repo: local - hooks: - - id: python-fmt - name: Python Format - entry: make fmt-check - language: system - exclude: '^dbgpt/app/static/|^web/' - types: [python] - stages: [commit] - pass_filenames: false - args: [] - - id: python-test - name: Python Unit Test - entry: make test - language: system - exclude: '^dbgpt/app/static/|^web/' - types: [python] - stages: [commit] - pass_filenames: false - args: [] - - id: python-test-doc - name: Python Doc Test - entry: make test-doc - language: system - exclude: '^dbgpt/app/static/|^web/' - types: [python] - stages: [commit] - pass_filenames: false - args: [] - - id: python-lint-mypy - name: Python Lint mypy - entry: make mypy - language: system - exclude: '^dbgpt/app/static/|^web/' - types: [python] - stages: [commit] - pass_filenames: false - args: [] - +# Please run command `pre-commit install` to install pre-commit hook +repos: + - repo: local + hooks: + - id: python-fmt + name: Python Format + entry: make fmt-check + language: system + exclude: '^dbgpt/app/static/|^web/' + types: [python] + stages: [commit] + pass_filenames: false + args: [] + - id: python-test + name: Python Unit Test + entry: make test + language: system + exclude: '^dbgpt/app/static/|^web/' + types: [python] + stages: [commit] + pass_filenames: false + args: [] + - id: python-test-doc + name: Python Doc Test + entry: make test-doc + language: system + exclude: '^dbgpt/app/static/|^web/' + types: [python] + stages: [commit] + pass_filenames: false + args: [] + - id: python-lint-mypy + name: Python Lint mypy + entry: make mypy + language: system + exclude: '^dbgpt/app/static/|^web/' + types: [python] + stages: [commit] + pass_filenames: false + args: [] + diff --git a/dbgpt/_private/config.py b/dbgpt/_private/config.py index 99eb0e2eb..d567d8be8 100644 --- a/dbgpt/_private/config.py +++ b/dbgpt/_private/config.py @@ -78,17 +78,13 @@ class Config(metaclass=Singleton): ) # xunfei spark - self.spark_api_version = os.getenv("XUNFEI_SPARK_API_VERSION") - self.spark_proxy_api_key = os.getenv("XUNFEI_SPARK_API_KEY") - self.spark_proxy_api_secret = os.getenv("XUNFEI_SPARK_API_SECRET") - self.spark_proxy_api_appid = os.getenv("XUNFEI_SPARK_APPID") - if self.spark_proxy_api_key and self.spark_proxy_api_secret: - os.environ["spark_proxyllm_proxy_api_key"] = self.spark_proxy_api_key - os.environ["spark_proxyllm_proxy_api_secret"] = self.spark_proxy_api_secret - os.environ["spark_proxyllm_proxyllm_backend"] = self.spark_api_version or "" - os.environ["spark_proxyllm_proxy_api_app_id"] = ( - self.spark_proxy_api_appid or "" - ) + self.spark_proxy_api_password = os.getenv("XUNFEI_SPARK_API_PASSWORD") + self.spark_proxy_api_model = os.getenv("XUNFEI_SPARK_API_MODEL") + if self.spark_proxy_api_model and self.spark_proxy_api_password: + os.environ[ + "spark_proxyllm_proxy_api_password" + ] = self.spark_proxy_api_password + os.environ["spark_proxyllm_proxy_api_model"] = self.spark_proxy_api_model # baichuan proxy self.bc_proxy_api_key = os.getenv("BAICHUAN_PROXY_API_KEY") diff --git a/dbgpt/agent/core/plan/awel/agent_operator.py b/dbgpt/agent/core/plan/awel/agent_operator.py index 8a68d307a..22568c07a 100644 --- a/dbgpt/agent/core/plan/awel/agent_operator.py +++ b/dbgpt/agent/core/plan/awel/agent_operator.py @@ -291,6 +291,7 @@ class AWELAgentOperator( prompt_template = None if self.awel_agent.agent_prompt: from dbgpt.serve.prompt.api.endpoints import get_service + prompt_service = get_service() prompt_template = prompt_service.get_template( self.awel_agent.agent_prompt.code diff --git a/dbgpt/agent/core/plan/awel/agent_operator_resource.py b/dbgpt/agent/core/plan/awel/agent_operator_resource.py index bbdbbfa68..36b2dede0 100644 --- a/dbgpt/agent/core/plan/awel/agent_operator_resource.py +++ b/dbgpt/agent/core/plan/awel/agent_operator_resource.py @@ -12,6 +12,7 @@ from dbgpt.core.awel.flow import ( ResourceCategory, register_resource, ) + from ....resource.base import AgentResource, ResourceType from ....resource.manage import get_resource_manager from ....util.llm.llm import LLMConfig, LLMStrategyType @@ -20,6 +21,7 @@ from ...agent_manage import get_agent_manager def _agent_resource_prompt_values() -> List[OptionValue]: from dbgpt.serve.prompt.api.endpoints import get_service + prompt_service = get_service() prompts = prompt_service.get_target_prompt() return [ diff --git a/dbgpt/app/knowledge/api.py b/dbgpt/app/knowledge/api.py index 9e00db3ec..8dad87459 100644 --- a/dbgpt/app/knowledge/api.py +++ b/dbgpt/app/knowledge/api.py @@ -2,10 +2,10 @@ import logging import os import shutil import tempfile -from typing import List from pathlib import Path +from typing import List -from fastapi import APIRouter, Depends, File, Form, UploadFile, HTTPException +from fastapi import APIRouter, Depends, File, Form, HTTPException, UploadFile from dbgpt._private.config import Config from dbgpt.app.knowledge.request.request import ( @@ -333,70 +333,72 @@ def document_delete(space_name: str, query_request: DocumentQueryRequest): @router.post("/knowledge/{space_name}/document/upload") async def document_upload( - space_name: str, - doc_name: str = Form(...), - doc_type: str = Form(...), - doc_file: UploadFile = File(...), + space_name: str, + doc_name: str = Form(...), + doc_type: str = Form(...), + doc_file: UploadFile = File(...), ): - print(f"/document/upload params: {space_name}") - try: - if doc_file: - # Sanitize inputs to prevent path traversal - safe_space_name = os.path.basename(space_name) - safe_filename = os.path.basename(doc_file.filename) + print(f"/document/upload params: {space_name}") + try: + if doc_file: + # Sanitize inputs to prevent path traversal + safe_space_name = os.path.basename(space_name) + safe_filename = os.path.basename(doc_file.filename) - # Create absolute paths and verify they are within allowed directory - upload_dir = os.path.abspath(os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, safe_space_name)) - target_path = os.path.abspath(os.path.join(upload_dir, safe_filename)) + # Create absolute paths and verify they are within allowed directory + upload_dir = os.path.abspath( + os.path.join(KNOWLEDGE_UPLOAD_ROOT_PATH, safe_space_name) + ) + target_path = os.path.abspath(os.path.join(upload_dir, safe_filename)) - if not os.path.abspath(KNOWLEDGE_UPLOAD_ROOT_PATH) in target_path: - raise HTTPException(status_code=400, detail="Invalid path detected") + if not os.path.abspath(KNOWLEDGE_UPLOAD_ROOT_PATH) in target_path: + raise HTTPException(status_code=400, detail="Invalid path detected") - if not os.path.exists(upload_dir): - os.makedirs(upload_dir) + if not os.path.exists(upload_dir): + os.makedirs(upload_dir) - # Create temp file - tmp_fd, tmp_path = tempfile.mkstemp(dir=upload_dir) - - try: - with os.fdopen(tmp_fd, "wb") as tmp: - tmp.write(await doc_file.read()) - - shutil.move(tmp_path, target_path) + # Create temp file + tmp_fd, tmp_path = tempfile.mkstemp(dir=upload_dir) - request = KnowledgeDocumentRequest() - request.doc_name = doc_name - request.doc_type = doc_type - request.content = target_path + try: + with os.fdopen(tmp_fd, "wb") as tmp: + tmp.write(await doc_file.read()) - space_res = knowledge_space_service.get_knowledge_space( - KnowledgeSpaceRequest(name=safe_space_name) - ) - if len(space_res) == 0: - # create default space - if "default" != safe_space_name: - raise Exception(f"you have not create your knowledge space.") - knowledge_space_service.create_knowledge_space( - KnowledgeSpaceRequest( - name=safe_space_name, - desc="first db-gpt rag application", - owner="dbgpt", - ) - ) - return Result.succ( - knowledge_space_service.create_knowledge_document( - space=safe_space_name, request=request - ) - ) - except Exception as e: - # Clean up temp file if anything goes wrong - if os.path.exists(tmp_path): - os.unlink(tmp_path) - raise e + shutil.move(tmp_path, target_path) - return Result.failed(code="E000X", msg=f"doc_file is None") - except Exception as e: - return Result.failed(code="E000X", msg=f"document add error {e}") + request = KnowledgeDocumentRequest() + request.doc_name = doc_name + request.doc_type = doc_type + request.content = target_path + + space_res = knowledge_space_service.get_knowledge_space( + KnowledgeSpaceRequest(name=safe_space_name) + ) + if len(space_res) == 0: + # create default space + if "default" != safe_space_name: + raise Exception(f"you have not create your knowledge space.") + knowledge_space_service.create_knowledge_space( + KnowledgeSpaceRequest( + name=safe_space_name, + desc="first db-gpt rag application", + owner="dbgpt", + ) + ) + return Result.succ( + knowledge_space_service.create_knowledge_document( + space=safe_space_name, request=request + ) + ) + except Exception as e: + # Clean up temp file if anything goes wrong + if os.path.exists(tmp_path): + os.unlink(tmp_path) + raise e + + return Result.failed(code="E000X", msg=f"doc_file is None") + except Exception as e: + return Result.failed(code="E000X", msg=f"document add error {e}") @router.post("/knowledge/{space_name}/document/sync") diff --git a/dbgpt/app/scene/base_chat.py b/dbgpt/app/scene/base_chat.py index f686c0cc8..d1fc27334 100644 --- a/dbgpt/app/scene/base_chat.py +++ b/dbgpt/app/scene/base_chat.py @@ -232,7 +232,8 @@ class BaseChat(ABC): ) node = AppChatComposerOperator( model=self.llm_model, - temperature=float(self.prompt_template.temperature), + temperature=self._chat_param.get("temperature") + or float(self.prompt_template.temperature), max_new_tokens=int(self.prompt_template.max_new_tokens), prompt=self.prompt_template.prompt, message_version=self._message_version, diff --git a/dbgpt/model/proxy/llms/spark.py b/dbgpt/model/proxy/llms/spark.py index adbb647eb..cd71f74d1 100644 --- a/dbgpt/model/proxy/llms/spark.py +++ b/dbgpt/model/proxy/llms/spark.py @@ -1,21 +1,13 @@ -import base64 -import hashlib -import hmac import json import os from concurrent.futures import Executor -from datetime import datetime -from time import mktime -from typing import Iterator, Optional -from urllib.parse import urlencode, urlparse +from typing import AsyncIterator, Optional from dbgpt.core import MessageConverter, ModelOutput, ModelRequest, ModelRequestContext from dbgpt.model.parameter import ProxyModelParameters from dbgpt.model.proxy.base import ProxyLLMClient from dbgpt.model.proxy.llms.proxy_model import ProxyModel -SPARK_DEFAULT_API_VERSION = "v3" - def getlength(text): length = 0 @@ -49,7 +41,7 @@ def spark_generate_stream( max_new_tokens=params.get("max_new_tokens"), stop=params.get("stop"), ) - for r in client.sync_generate_stream(request): + for r in client.generate_stream(request): yield r @@ -74,120 +66,57 @@ def get_response(request_url, data): yield result -class SparkAPI: - def __init__( - self, appid: str, api_key: str, api_secret: str, spark_url: str - ) -> None: - self.appid = appid - self.api_key = api_key - self.api_secret = api_secret - self.host = urlparse(spark_url).netloc - self.path = urlparse(spark_url).path +def extract_content(line: str): + if not line.strip(): + return line + if line.startswith("data: "): + json_str = line[len("data: ") :] + else: + raise ValueError("Error line content ") - self.spark_url = spark_url + try: + data = json.loads(json_str) + if data == "[DONE]": + return "" - def gen_url(self): - from wsgiref.handlers import format_date_time - - # 生成RFC1123格式的时间戳 - now = datetime.now() - date = format_date_time(mktime(now.timetuple())) - - # 拼接字符串 - signature_origin = "host: " + self.host + "\n" - signature_origin += "date: " + date + "\n" - signature_origin += "GET " + self.path + " HTTP/1.1" - - # 进行hmac-sha256进行加密 - signature_sha = hmac.new( - self.api_secret.encode("utf-8"), - signature_origin.encode("utf-8"), - digestmod=hashlib.sha256, - ).digest() - - signature_sha_base64 = base64.b64encode(signature_sha).decode(encoding="utf-8") - - authorization_origin = f'api_key="{self.api_key}", algorithm="hmac-sha256", headers="host date request-line", signature="{signature_sha_base64}"' - - authorization = base64.b64encode(authorization_origin.encode("utf-8")).decode( - encoding="utf-8" - ) - - # 将请求的鉴权参数组合为字典 - v = {"authorization": authorization, "date": date, "host": self.host} - # 拼接鉴权参数，生成url - url = self.spark_url + "?" + urlencode(v) - # 此处打印出建立连接时候的url,参考本demo的时候可取消上方打印的注释，比对相同参数时生成的url与自己代码生成的url是否一致 - return url + choices = data.get("choices", []) + if choices and isinstance(choices, list): + delta = choices[0].get("delta", {}) + content = delta.get("content", "") + return content + else: + raise ValueError("Error line content ") + except json.JSONDecodeError: + return "" class SparkLLMClient(ProxyLLMClient): def __init__( self, model: Optional[str] = None, - app_id: Optional[str] = None, - api_key: Optional[str] = None, - api_secret: Optional[str] = None, - api_base: Optional[str] = None, - api_domain: Optional[str] = None, - model_version: Optional[str] = None, model_alias: Optional[str] = "spark_proxyllm", context_length: Optional[int] = 4096, executor: Optional[Executor] = None, ): """ - Tips: 星火大模型API当前有Lite、Pro、Pro-128K、Max、Max-32K和4.0 Ultra六个版本，各版本独立计量tokens。 - 传输协议 ：ws(s),为提高安全性，强烈推荐wss - - Spark4.0 Ultra 请求地址，对应的domain参数为4.0Ultra： - wss://spark-api.xf-yun.com/v4.0/chat - + 星火大模型API当前有Lite、Pro、Pro-128K、Max、Max-32K和4.0 Ultra六个版本 + Spark4.0 Ultra 请求地址，对应的domain参数为4.0Ultra Spark Max-32K请求地址，对应的domain参数为max-32k - wss://spark-api.xf-yun.com/chat/max-32k - Spark Max请求地址，对应的domain参数为generalv3.5 - wss://spark-api.xf-yun.com/v3.5/chat - Spark Pro-128K请求地址，对应的domain参数为pro-128k： - wss://spark-api.xf-yun.com/chat/pro-128k - Spark Pro请求地址，对应的domain参数为generalv3： - wss://spark-api.xf-yun.com/v3.1/chat - Spark Lite请求地址，对应的domain参数为lite： - wss://spark-api.xf-yun.com/v1.1/chat + https://www.xfyun.cn/doc/spark/HTTP%E8%B0%83%E7%94%A8%E6%96%87%E6%A1%A3.html#_3-%E8%AF%B7%E6%B1%82%E8%AF%B4%E6%98%8E """ - if not model_version: - model_version = model or os.getenv("XUNFEI_SPARK_API_VERSION") - if not api_base: - if model_version == SPARK_DEFAULT_API_VERSION: - api_base = "ws://spark-api.xf-yun.com/v3.1/chat" - domain = "generalv3" - elif model_version == "v4.0": - api_base = "ws://spark-api.xf-yun.com/v4.0/chat" - domain = "4.0Ultra" - elif model_version == "v3.5": - api_base = "ws://spark-api.xf-yun.com/v3.5/chat" - domain = "generalv3.5" - else: - api_base = "ws://spark-api.xf-yun.com/v1.1/chat" - domain = "lite" - if not api_domain: - api_domain = domain - self._model = model - self._model_version = model_version - self._api_base = api_base - self._domain = api_domain - self._app_id = app_id or os.getenv("XUNFEI_SPARK_APPID") - self._api_secret = api_secret or os.getenv("XUNFEI_SPARK_API_SECRET") - self._api_key = api_key or os.getenv("XUNFEI_SPARK_API_KEY") - - if not self._app_id: - raise ValueError("app_id can't be empty") - if not self._api_key: - raise ValueError("api_key can't be empty") - if not self._api_secret: - raise ValueError("api_secret can't be empty") + self._model = model or os.getenv("XUNFEI_SPARK_API_MODEL") + self._api_base = os.getenv("PROXY_SERVER_URL") + self._api_password = os.getenv("XUNFEI_SPARK_API_PASSWORD") + if not self._model: + raise ValueError("model can't be empty") + if not self._api_base: + raise ValueError("api_base can't be empty") + if not self._api_password: + raise ValueError("api_password can't be empty") super().__init__( model_names=[model, model_alias], @@ -203,10 +132,6 @@ class SparkLLMClient(ProxyLLMClient): ) -> "SparkLLMClient": return cls( model=model_params.proxyllm_backend, - app_id=model_params.proxy_api_app_id, - api_key=model_params.proxy_api_key, - api_secret=model_params.proxy_api_secret, - api_base=model_params.proxy_api_base, model_alias=model_params.model_name, context_length=model_params.max_context_size, executor=default_executor, @@ -216,35 +141,45 @@ class SparkLLMClient(ProxyLLMClient): def default_model(self) -> str: return self._model - def sync_generate_stream( + def generate_stream( self, request: ModelRequest, message_converter: Optional[MessageConverter] = None, - ) -> Iterator[ModelOutput]: + ) -> AsyncIterator[ModelOutput]: + """ + reference: + https://www.xfyun.cn/doc/spark/HTTP%E8%B0%83%E7%94%A8%E6%96%87%E6%A1%A3.html#_3-%E8%AF%B7%E6%B1%82%E8%AF%B4%E6%98%8E + """ request = self.local_covert_message(request, message_converter) messages = request.to_common_messages(support_system_role=False) - request_id = request.context.request_id or "1" - data = { - "header": {"app_id": self._app_id, "uid": request_id}, - "parameter": { - "chat": { - "domain": self._domain, - "random_threshold": 0.5, - "max_tokens": request.max_new_tokens, - "auditing": "default", - "temperature": request.temperature, - } - }, - "payload": {"message": {"text": messages}}, - } - - spark_api = SparkAPI( - self._app_id, self._api_key, self._api_secret, self._api_base - ) - request_url = spark_api.gen_url() try: - for text in get_response(request_url, data): - yield ModelOutput(text=text, error_code=0) + import requests + except ImportError as e: + raise ValueError( + "Could not import python package: requests " + "Please install requests by command `pip install requests" + ) from e + + data = { + "model": self._model, # 指定请求的模型 + "messages": messages, + "temperature": request.temperature, + "stream": True, + } + header = { + "Authorization": f"Bearer {self._api_password}" # 注意此处替换自己的APIPassword + } + response = requests.post(self._api_base, headers=header, json=data, stream=True) + # 流式响应解析示例 + response.encoding = "utf-8" + try: + content = "" + # data: {"code":0,"message":"Success","sid":"cha000bf865@dx19307263c06b894532","id":"cha000bf865@dx19307263c06b894532","created":1730991766,"choices":[{"delta":{"role":"assistant","content":"你好"},"index":0}]} + # data: [DONE] + for line in response.iter_lines(decode_unicode=True): + print("llm out:", line) + content = content + extract_content(line) + yield ModelOutput(text=content, error_code=0) except Exception as e: return ModelOutput( text=f"**LLMServer Generate Error, Please CheckErrorInfo.**: {e}", diff --git a/dbgpt/storage/vector_store/milvus_store.py b/dbgpt/storage/vector_store/milvus_store.py index 3763f14f8..b71832268 100644 --- a/dbgpt/storage/vector_store/milvus_store.py +++ b/dbgpt/storage/vector_store/milvus_store.py @@ -457,9 +457,7 @@ class MilvusStore(VectorStoreBase): self.vector_field = x.name # convert to milvus expr filter. milvus_filter_expr = self.convert_metadata_filters(filters) if filters else None - _, docs_and_scores = self._search( - query=text, k=topk, expr=milvus_filter_expr - ) + _, docs_and_scores = self._search(query=text, k=topk, expr=milvus_filter_expr) if any(score < 0.0 or score > 1.0 for _, score, id in docs_and_scores): logger.warning( "similarity score need between" f" 0 and 1, got {docs_and_scores}"