init
This commit is contained in:
@@ -0,0 +1,13 @@
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__pycache__/
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*.pyc
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*.pyo
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*.pyd
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*.log
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.pytest_cache/
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.mypy_cache/
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.git/
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.gitignore
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.vscode/
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.idea/
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_trial_temp/
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*.ipynb
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@@ -16,5 +16,3 @@ __pycache__/
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.DS_Store
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*.log
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# 本地配置
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config/config.ini
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+22
@@ -0,0 +1,22 @@
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FROM python:3.12-bookworm
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ENV PYTHONDONTWRITEBYTECODE=1 \
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PYTHONUNBUFFERED=1 \
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PIP_NO_CACHE_DIR=1 \
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PIP_PROGRESS_BAR=off \
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PIP_NO_COLOR=1 \
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PIP_QUIET=1
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WORKDIR /app
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RUN pip install --no-input --no-cache-dir --upgrade pip setuptools wheel
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COPY requirements.txt /app/requirements.txt
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RUN pip install --no-input --no-cache-dir \
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-r /app/requirements.txt \
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-i https://pypi.tuna.tsinghua.edu.cn/simple/
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COPY . /app
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EXPOSE 8000
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CMD ["python", "server.py"]
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Vendored
+64
@@ -0,0 +1,64 @@
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stage('Deploy to k3s') {
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steps {
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dir('more_dots') {
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script {
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def cluster = params.TARGET_CLUSTER
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def fullImageWithTag = "${FULL_IMAGE_NAME}:${env.IMAGE_TAG}"
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if (cluster == 'cluster1' || cluster == 'both') {
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withCredentials([
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file(credentialsId: 'k3s-cluster1-config', variable: 'KUBECONFIG_CLUSTER1'),
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usernamePassword(credentialsId: REGISTRY_CREDENTIALS_ID, usernameVariable: 'REGISTRY_USER', passwordVariable: 'REGISTRY_PASS')
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]) {
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sh """
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set -eux
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# 查找kubectl路径
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KUBECTL_PATH=\$(command -v kubectl 2>/dev/null || true)
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if [ -z "\$KUBECTL_PATH" ]; then
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for p in /usr/local/bin/kubectl /usr/bin/kubectl /bin/kubectl; do
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if [ -x "\$p" ]; then
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KUBECTL_PATH="\$p"
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break
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fi
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done
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fi
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echo "使用kubectl路径: \$KUBECTL_PATH"
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# 定义kubectl函数
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k() {
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sudo \$KUBECTL_PATH --kubeconfig=${KUBECONFIG_CLUSTER1} "\$@"
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}
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# 检查命名空间
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k get namespace ${params.DEPLOY_ENV} || k create namespace ${params.DEPLOY_ENV}
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# 创建imagePullSecret
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k create secret docker-registry regcred-130 \\
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--docker-server=${REGISTRY_URL} \\
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--docker-username=${REGISTRY_USER} \\
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--docker-password=${REGISTRY_PASS} \\
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--namespace=${params.DEPLOY_ENV} \\
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--dry-run=client -o yaml | k apply -f -
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# 替换镜像并部署
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sed "s|image:.*more_dots.*|image: ${fullImageWithTag}|g" k8s/deployment.yaml > /tmp/deployment-${params.DEPLOY_ENV}.yaml
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k apply -f /tmp/deployment-${params.DEPLOY_ENV}.yaml -n ${params.DEPLOY_ENV}
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# 确保使用imagePullSecret（注意 deployment 名称是 more-dots）
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k patch deployment more-dots -n ${params.DEPLOY_ENV} \\
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-p '{"spec":{"template":{"spec":{"imagePullSecrets":[{"name":"regcred-130"}]}}}}' || true
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# 重启并等待
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k rollout restart deployment/more-dots -n ${params.DEPLOY_ENV} 2>/dev/null || true
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k rollout status deployment/more-dots -n ${params.DEPLOY_ENV} --timeout=300s
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"""
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}
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}
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// cluster2 部分同样修改...
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}
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}
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}
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}
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@@ -53,13 +53,9 @@ class ConversationAgent(BaseAgent):
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return state
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def _generate_response(self, state: AgentState) -> AgentState:
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"""结合对话历史生成回复"""
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all_messages = self.conversation_history + state.messages
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if all_messages:
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response = self.model.invoke(all_messages)
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state.messages.append(response)
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"""优先返回 SQL 执行结果，其次返回生成 SQL，再回退到模型回复"""
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from . import nodes
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state = nodes.generate_response(state, self.model)
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state.current_step = "response_generated"
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return state
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+29
-4
@@ -4,29 +4,40 @@ from langchain_core.messages import BaseMessage, HumanMessage, SystemMessage, AI
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from .state import AgentState
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from services.prompt_manager import get_prompt_manager
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from services.template_matcher import get_template_matcher
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from services.sql_prompt_manager import SqlPromptManager
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from services.sql_prompt_manager import get_sql_prompt_manager
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from tools.sr_api_tool import SrApiQueryTool
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def _short(value, max_len: int = 500) -> str:
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text = str(value)
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return text if len(text) <= max_len else text[:max_len] + "..."
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def process_input(state: AgentState) -> AgentState:
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"""处理用户输入"""
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print("[process_input][in] messages=", _short(state.messages))
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state.current_step = "processed"
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print("[process_input][out] current_step=", state.current_step)
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return state
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def generate_response(state: AgentState, model) -> AgentState:
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"""使用 LLM 生成回复"""
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print("[generate_response][in] context_keys=", list((state.context or {}).keys()))
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sr_api_result = state.context.get("sr_api_result")
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if sr_api_result:
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state.messages.append(AIMessage(content=str(sr_api_result)))
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print("[generate_response][out] source=sr_api_result")
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return state
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final_sql = state.context.get("final_sql")
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if final_sql:
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state.messages.append(AIMessage(content=final_sql))
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print("[generate_response][out] source=final_sql")
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return state
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if state.messages:
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response = model.invoke(state.messages)
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state.messages.append(response)
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print("[generate_response][out] source=model_invoke")
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return state
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@@ -39,19 +50,25 @@ def normalize_input(state: AgentState, model) -> AgentState:
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if not isinstance(last_message, HumanMessage):
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return state
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print("[normalize_input][in] user_input=", _short(last_message.content))
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prompt_manager = get_prompt_manager()
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system_prompt = SystemMessage(
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content=prompt_manager.get("system", "english_normalizer")
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normalizer_prompt = (
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prompt_manager.get("system", "english_normalizer")
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or prompt_manager.get("user", "english_normalizer")
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)
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system_prompt = SystemMessage(content=normalizer_prompt)
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response = model.invoke([system_prompt, HumanMessage(content=last_message.content)])
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normalized = response.content if hasattr(response, "content") else str(response)
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print("[normalize_input][out] normalized=", _short(normalized))
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state.context["original_input"] = last_message.content
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state.context["normalized_input"] = normalized
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matcher = get_template_matcher()
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state.context["table_match"] = matcher.match(normalized)
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print("[normalize_input][out] table_match=", _short(state.context.get("table_match")))
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return state
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@@ -62,11 +79,16 @@ def generate_sql(state: AgentState, model) -> AgentState:
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normalized = state.context.get("normalized_input")
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if not table_name or not normalized:
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print("[generate_sql][skip] missing table_name or normalized")
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return state
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prompt_manager = SqlPromptManager()
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print("[generate_sql][in] table_name=", table_name)
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print("[generate_sql][in] normalized=", _short(normalized))
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prompt_manager = get_sql_prompt_manager()
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prompt_data = prompt_manager.get_prompt(table_name)
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if not prompt_data:
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print("[generate_sql][skip] prompt not found for table=", table_name)
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return state
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prompt_text = json.dumps(prompt_data, ensure_ascii=False, indent=2)
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@@ -75,8 +97,11 @@ def generate_sql(state: AgentState, model) -> AgentState:
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user_content = f"User question (normalized English): {normalized}"
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response = model.invoke([SystemMessage(content=system_content), HumanMessage(content=user_content)])
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sql_text = response.content if hasattr(response, "content") else str(response)
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print("[generate_sql][out] sql=", _short(sql_text))
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state.context["final_sql"] = sql_text
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if not state.context.get("skip_sr_api"):
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tool = SrApiQueryTool()
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state.context["sr_api_result"] = tool.run(json.dumps({"sql": sql_text}, ensure_ascii=False))
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print("[generate_sql][out] sr_api_result=", _short(state.context.get("sr_api_result")))
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return state
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+132
-36
@@ -1,13 +1,23 @@
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import asyncio
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import json
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import time
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import uuid
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from fastapi import APIRouter, HTTPException, Depends
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from fastapi.responses import StreamingResponse
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from config import Config
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from schemas.agent_input import AgentInput
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from schemas.agent_output import AgentOutput
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from schemas.tool_input import ToolInput
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from schemas.tool_output import ToolOutput
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from schemas.chat_message_response import ChatMessageResponseDTO
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from workflows.workflow_manager import WorkflowType
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from api.dependencies import get_workflow_manager, get_nacos_manager, get_service_config, get_tool_router, get_prompt_manager
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from services.app_errors import AppError, ErrorCode
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from services.ragflow_sync import RagflowSync
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from services.structured_logger import get_structured_logger
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from tools.sr_api_tool import SrApiQueryTool
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router = APIRouter()
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@@ -17,7 +27,17 @@ def _resolve_workflow_type(value: str) -> WorkflowType:
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try:
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return WorkflowType(value)
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except Exception as e:
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raise ValueError(f"不支持的工作流类型: {value}") from e
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raise AppError(
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code=ErrorCode.INVALID_WORKFLOW_TYPE,
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message=f"不支持的工作流类型: {value}",
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status_code=400,
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) from e
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|
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|
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def _to_http_error(e: Exception) -> HTTPException:
|
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if isinstance(e, AppError):
|
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return HTTPException(status_code=e.status_code, detail=e.to_dict())
|
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return HTTPException(status_code=500, detail={"code": ErrorCode.INTERNAL_ERROR.value, "message": str(e)})
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|
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|
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@router.get("/health")
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@@ -36,16 +56,25 @@ def nacos_status(nacos_manager=Depends(get_nacos_manager)):
|
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|
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@router.post("/api/workflows", response_model=AgentOutput)
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def run_workflow(payload: AgentInput, workflow_manager=Depends(get_workflow_manager)):
|
||||
trace_id = uuid.uuid4().hex
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||||
slog = get_structured_logger()
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||||
slog.log("INFO", "run_workflow.start", trace_id, {"workflow_type": payload.workflow_type})
|
||||
try:
|
||||
workflow_type = _resolve_workflow_type(payload.workflow_type)
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
except Exception as e:
|
||||
slog.log("ERROR", "run_workflow.invalid_type", trace_id, error_code=ErrorCode.INVALID_WORKFLOW_TYPE.value, payload={"workflow_type": payload.workflow_type})
|
||||
raise _to_http_error(e)
|
||||
|
||||
try:
|
||||
result = workflow_manager.execute_workflow(
|
||||
workflow_type=workflow_type,
|
||||
user_input=payload.input,
|
||||
session_id=payload.session_id,
|
||||
)
|
||||
slog.log("INFO", "run_workflow.success", trace_id, {"session_id": result.get("session_id")})
|
||||
except Exception as e:
|
||||
slog.log("ERROR", "run_workflow.failed", trace_id, error_code=ErrorCode.INTERNAL_ERROR.value, payload={"error": str(e)})
|
||||
raise _to_http_error(e)
|
||||
|
||||
return AgentOutput(
|
||||
session_id=result["session_id"],
|
||||
@@ -54,45 +83,112 @@ def run_workflow(payload: AgentInput, workflow_manager=Depends(get_workflow_mana
|
||||
)
|
||||
|
||||
|
||||
@router.post("/api/workflows/stream")
|
||||
def run_workflow_stream(payload: AgentInput, workflow_manager=Depends(get_workflow_manager)):
|
||||
@router.post("/api/sql/generate")
|
||||
def generate_sql(payload: AgentInput, workflow_manager=Depends(get_workflow_manager)):
|
||||
"""仅生成 SQL，不调用 SR API"""
|
||||
trace_id = uuid.uuid4().hex
|
||||
slog = get_structured_logger()
|
||||
try:
|
||||
workflow_type = _resolve_workflow_type(payload.workflow_type)
|
||||
except ValueError as e:
|
||||
raise HTTPException(status_code=400, detail=str(e))
|
||||
except Exception as e:
|
||||
slog.log("ERROR", "generate_sql.invalid_type", trace_id, error_code=ErrorCode.INVALID_WORKFLOW_TYPE.value)
|
||||
raise _to_http_error(e)
|
||||
|
||||
if workflow_type != WorkflowType.CONVERSATION:
|
||||
raise HTTPException(status_code=400, detail="仅支持对话工作流的流式输出")
|
||||
|
||||
def _extract_output_text(result: dict) -> str:
|
||||
context = (result.get("context") or {}) if isinstance(result, dict) else {}
|
||||
if "sr_api_result" in context:
|
||||
return str(context.get("sr_api_result") or "")
|
||||
messages = result.get("messages") if isinstance(result, dict) else None
|
||||
if messages:
|
||||
last = messages[-1]
|
||||
if hasattr(last, "content"):
|
||||
return str(last.content or "")
|
||||
return ""
|
||||
|
||||
def event_stream():
|
||||
try:
|
||||
result = workflow_manager.execute_workflow(
|
||||
workflow_type=workflow_type,
|
||||
user_input=payload.input,
|
||||
session_id=payload.session_id,
|
||||
skip_sr_api=True,
|
||||
)
|
||||
text = _extract_output_text(result.get("result") or {})
|
||||
if not text:
|
||||
|
||||
context = (result.get("result") or {}).get("context") or {}
|
||||
sql_text = context.get("final_sql")
|
||||
if not sql_text:
|
||||
e = AppError(code=ErrorCode.SQL_GENERATION_FAILED, message="SQL 生成失败")
|
||||
slog.log("ERROR", "generate_sql.failed", trace_id, error_code=e.code.value, payload={"context_keys": list(context.keys())})
|
||||
raise _to_http_error(e)
|
||||
|
||||
slog.log("INFO", "generate_sql.success", trace_id, {"sql_len": len(sql_text)})
|
||||
|
||||
return {
|
||||
"session_id": result.get("session_id"),
|
||||
"workflow_type": result.get("workflow_type"),
|
||||
"sql": sql_text,
|
||||
}
|
||||
|
||||
|
||||
@router.post("/api/workflows/stream")
|
||||
def run_workflow_stream(payload: AgentInput, workflow_manager=Depends(get_workflow_manager)):
|
||||
trace_id = uuid.uuid4().hex
|
||||
slog = get_structured_logger()
|
||||
try:
|
||||
workflow_type = _resolve_workflow_type(payload.workflow_type)
|
||||
except Exception as e:
|
||||
raise _to_http_error(e)
|
||||
|
||||
if workflow_type != WorkflowType.CONVERSATION:
|
||||
raise _to_http_error(AppError(code=ErrorCode.INVALID_WORKFLOW_TYPE, message="仅支持对话工作流的流式输出", status_code=400))
|
||||
|
||||
stream_cfg = Config.get_section("stream")
|
||||
progress_interval = float(stream_cfg.get("progress_interval", 0.3))
|
||||
task_id = uuid.uuid4().hex
|
||||
|
||||
def _build_message(conversation_id: str, answer: str) -> str:
|
||||
dto = ChatMessageResponseDTO(
|
||||
id=uuid.uuid4().hex,
|
||||
event="message",
|
||||
task_id=task_id,
|
||||
message_id=uuid.uuid4().hex,
|
||||
conversation_id=conversation_id,
|
||||
answer=answer,
|
||||
created_at=int(time.time()),
|
||||
)
|
||||
return f"event: message\ndata: {json.dumps(dto.model_dump(), ensure_ascii=False)}\n\n"
|
||||
|
||||
async def event_stream():
|
||||
try:
|
||||
slog.log("INFO", "stream.start", trace_id, {"workflow_type": payload.workflow_type})
|
||||
# 1) 先仅生成 SQL（不执行 SR API）
|
||||
result = await asyncio.to_thread(
|
||||
workflow_manager.execute_workflow,
|
||||
workflow_type,
|
||||
payload.input,
|
||||
payload.session_id,
|
||||
skip_sr_api=True,
|
||||
)
|
||||
conversation_id = str(result.get("session_id") or payload.session_id or task_id)
|
||||
context = (result.get("result") or {}).get("context") or {}
|
||||
sql_text = str(context.get("final_sql") or "")
|
||||
|
||||
if not sql_text:
|
||||
reason = "SQL 生成失败，可能是表未匹配或对应 SQL 提示词不存在"
|
||||
slog.log("ERROR", "stream.sql_generation_failed", trace_id, error_code=ErrorCode.SQL_GENERATION_FAILED.value, payload={"conversation_id": conversation_id})
|
||||
yield _build_message(conversation_id, reason)
|
||||
yield "event: end\ndata: [DONE]\n\n"
|
||||
return
|
||||
chunk_size = 512
|
||||
for i in range(0, len(text), chunk_size):
|
||||
chunk = text[i : i + chunk_size]
|
||||
yield f"data: {chunk}\n\n"
|
||||
|
||||
# 2) 先流式返回 SQL
|
||||
yield _build_message(conversation_id, sql_text)
|
||||
|
||||
# 3) 异步执行 SQL，并及时流式返回执行结果
|
||||
tool = SrApiQueryTool()
|
||||
task = asyncio.create_task(
|
||||
asyncio.to_thread(tool.run, json.dumps({"sql": sql_text}, ensure_ascii=False))
|
||||
)
|
||||
|
||||
while not task.done():
|
||||
yield _build_message(conversation_id, "executing_sql")
|
||||
await asyncio.sleep(progress_interval)
|
||||
|
||||
sql_result = await task
|
||||
slog.log("INFO", "stream.sql_executed", trace_id, {"result_len": len(str(sql_result))})
|
||||
yield _build_message(conversation_id, str(sql_result))
|
||||
yield "event: end\ndata: [DONE]\n\n"
|
||||
except Exception as e:
|
||||
yield f"event: error\ndata: {str(e)}\n\n"
|
||||
slog.log("ERROR", "stream.failed", trace_id, error_code=ErrorCode.INTERNAL_ERROR.value, payload={"error": str(e)})
|
||||
conversation_id = str(payload.session_id or task_id)
|
||||
yield _build_message(conversation_id, str(e))
|
||||
yield "event: end\ndata: [DONE]\n\n"
|
||||
|
||||
return StreamingResponse(event_stream(), media_type="text/event-stream")
|
||||
|
||||
@@ -128,11 +224,11 @@ def upload_table_retrieval():
|
||||
|
||||
|
||||
@router.put("/api/ragflow/table-retrieval/update")
|
||||
def update_table_retrieval(config: dict):
|
||||
"""更新表名检索知识库配置"""
|
||||
def update_table_retrieval():
|
||||
"""更新表名检索文档（仅文档内容）"""
|
||||
syncer = RagflowSync()
|
||||
try:
|
||||
result = syncer.update_dataset(syncer._table_retrieval_dataset_id, config)
|
||||
result = syncer.update_table_retrieval_documents()
|
||||
return {"ok": True, "result": result}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
@@ -150,11 +246,11 @@ def upload_sql_gen():
|
||||
|
||||
|
||||
@router.put("/api/ragflow/sql-gen/update")
|
||||
def update_sql_gen(config: dict):
|
||||
"""更新 SQL 生成知识库配置"""
|
||||
def update_sql_gen():
|
||||
"""更新 SQL 生成文档（仅文档内容）"""
|
||||
syncer = RagflowSync()
|
||||
try:
|
||||
result = syncer.update_dataset(syncer._sql_gen_dataset_id, config)
|
||||
result = syncer.update_sql_gen_documents()
|
||||
return {"ok": True, "result": result}
|
||||
except Exception as e:
|
||||
raise HTTPException(status_code=500, detail=str(e))
|
||||
|
||||
@@ -0,0 +1,73 @@
|
||||
[General]
|
||||
# 默认使用的模型配置区域
|
||||
DEFAULT_MODEL_SECTION = qwen-80b
|
||||
# 最大重试次数
|
||||
MAX_RETRIES = 3
|
||||
# 请求超时时间
|
||||
TIMEOUT = 30
|
||||
|
||||
|
||||
[qwen-32b]
|
||||
# 模型名称
|
||||
MODEL_NAME = qwen-32b
|
||||
# API Key
|
||||
OPENAI_API_KEY = 123ffa18-3baf-4f39-9698-fdf680d15f36
|
||||
# URL
|
||||
URL = http://led-gateway.lenovo.com:30089/intranet/qwen3-coder-30b/v1
|
||||
|
||||
[qwen-80b]
|
||||
MODEL_NAME = Qwen3-Next-80B-A3B-Instruct
|
||||
OPENAI_API_KEY = 123ffa18-3baf-4f39-9698-fdf680d15f36
|
||||
URL = http://led-gateway.lenovo.com:30089/intranet/qwen3-next-80b-a3b-instruct/v1
|
||||
|
||||
[sr_api]
|
||||
url = http://ipc.lenovo.com/gateway/bgs-ai/Report/fetchData
|
||||
llzAppkey = e0578e6a-f045-4f3e-93c0-5957c8b1915e
|
||||
llzSercret = BFhItTCY5FqgtHAdn0eaxAGix/25oR8YfxYKfSPgrJb8zxYG06kBeoip0DEGjekfh43223atdBDXBwUmw18NXp/2piZamnUwlFWYFAGfpBCwy3K+921KI5ZaWRWcMCCcCKOYF/2feMg72owUhno2JXqSUcb8HBhang==
|
||||
|
||||
|
||||
[ragflow]
|
||||
url = http://led-ai-ragflow.lenovo.com
|
||||
api_key = ragflow-gOOQ93FvWdyhP3i1J1xXFKVxWucgtF0bwbthuDJk5vs
|
||||
retrieval = /api/v1/retrieval
|
||||
retrieval_top_k = 3
|
||||
cache_ttl = 600
|
||||
table_retrieval_dataset_id = 9945baf512ea11f18ccb6a681b3130b2
|
||||
sql_gen_dataset_id = ee68f53a12ec11f18e436a681b3130b2
|
||||
|
||||
[redis]
|
||||
enabled = true
|
||||
host = led-redis.lenovo.com
|
||||
port = 30398
|
||||
password = bgs123456
|
||||
database = 0
|
||||
sql_prompt_ttl = 600
|
||||
|
||||
[stream]
|
||||
progress_interval = 0.3
|
||||
|
||||
[logging_mysql]
|
||||
enabled = false
|
||||
host = 127.0.0.1
|
||||
port = 3306
|
||||
user = root
|
||||
password =
|
||||
database = more_dots
|
||||
table = structured_logs
|
||||
connect_timeout = 5
|
||||
|
||||
|
||||
[app]
|
||||
service_name = local-model-streaming-api
|
||||
host = 0.0.0.0
|
||||
port = 8000
|
||||
version = 1.0.0
|
||||
|
||||
[nacos]
|
||||
enabled = false
|
||||
server = 10.122.132.204:8848
|
||||
namespace = prod
|
||||
group_name = BGS
|
||||
username = nacos
|
||||
password = bgs20250901
|
||||
|
||||
@@ -34,12 +34,33 @@ model_section = gpt-4o
|
||||
url = http://10.122.176.97:21020
|
||||
api_key = ragflow-xxxxx
|
||||
retrieval = /api/v1/retrieval
|
||||
upload = /api/v1/documents
|
||||
# 上传模式：overwrite（覆盖更新）或 append（追加）
|
||||
upload_mode = overwrite
|
||||
retrieval_top_k = 3
|
||||
table_retrieval_dataset_id =
|
||||
sql_gen_dataset_id =
|
||||
|
||||
[redis]
|
||||
# 是否启用 Redis 缓存（用于 sql_gen_prompts）
|
||||
enabled = false
|
||||
url = redis://localhost:6379/0
|
||||
db = 0
|
||||
# SQL 提示词缓存过期秒数
|
||||
sql_prompt_ttl = 600
|
||||
|
||||
[stream]
|
||||
# /api/workflows/stream 进度事件间隔（秒）
|
||||
progress_interval = 0.3
|
||||
|
||||
[logging_mysql]
|
||||
# 是否启用结构化日志写入 MySQL
|
||||
enabled = false
|
||||
host = 127.0.0.1
|
||||
port = 3306
|
||||
user = root
|
||||
password =
|
||||
database = more_dots
|
||||
table = structured_logs
|
||||
connect_timeout = 5
|
||||
|
||||
[nacos]
|
||||
# 是否启用 Nacos 注册
|
||||
enabled = false
|
||||
|
||||
@@ -0,0 +1,214 @@
|
||||
{
|
||||
"meta": {
|
||||
"domain": "订单消耗与积压统计",
|
||||
"data_source": "dwd_ai.apbo_hic_ssoc_consumption",
|
||||
"description": "此模型用于分析HIC和SSOC系统的订单消耗情况、积压订单统计及订单状态追踪，通过订单创建日期进行时间维度分析。",
|
||||
"fields_list": ["so", "soid", "original_pn", "ship_pn", "service_delivery_type", "warranty", "actual_wh", "item_status", "item_creation_date", "allocation_datetime", "backlog_status", "system_flag", "machine_type"]
|
||||
},
|
||||
"data_model_specification": {
|
||||
"core_status_fields": {
|
||||
"backlog_status": {
|
||||
"type": "varchar(64)",
|
||||
"meaning": "积压状态标识，'1'表示积压订单，其他值为非积压订单",
|
||||
"business_rule": "backlog_status = '1' 标识为积压订单"
|
||||
},
|
||||
"system_flag": {
|
||||
"type": "varchar(64)",
|
||||
"meaning": "系统来源标识",
|
||||
"values": ["HIC", "SSOC"],
|
||||
"business_rule": "区分订单来自HIC系统还是SSOC系统"
|
||||
},
|
||||
"machine_type": {
|
||||
"type": "varchar(64)",
|
||||
"meaning": "客户购买成品的系列",
|
||||
"business_rule": "用于按产品系列进行过滤和分析，例如：machine_type = '20LN'"
|
||||
}
|
||||
},
|
||||
"mandatory_display_fields": {
|
||||
"rule": "以下三个核心维度字段建议出现在SELECT子句中，特别是进行分组统计时。否则应展示fields_list中的全部字段",
|
||||
"actual_fields": ["item_creation_date", "system_flag", "backlog_status"],
|
||||
"user_alias": ["创建日期", "系统来源", "积压状态"],
|
||||
"exception_condition": "如果用户明确指定字段数≤2，且均为具体业务字段，则可以不包含全部建议字段。"
|
||||
},
|
||||
"other_fields": {
|
||||
"order_info_fields": ["so", "soid", "original_pn", "ship_pn"],
|
||||
"service_fields": ["service_delivery_type", "warranty"],
|
||||
"warehouse_fields": ["actual_wh"],
|
||||
"status_fields": ["item_status"],
|
||||
"time_fields": ["allocation_datetime"],
|
||||
"product_series_fields": ["machine_type"]
|
||||
},
|
||||
"date_field": {
|
||||
"primary_date": "item_creation_date",
|
||||
"format": "DATE类型",
|
||||
"usage": "主要的时间维度字段，用于按日期统计"
|
||||
}
|
||||
},
|
||||
"business_logic_rules": {
|
||||
"alias_handling": "将用户提到的业务术语别名转换为完整字段名后再生成SQL",
|
||||
"field_selection_logic": {
|
||||
"priority_order": [
|
||||
{
|
||||
"level": 1,
|
||||
"name": "用户指定字段",
|
||||
"rule": "首先添加用户明确提到的所有字段。"
|
||||
},
|
||||
{
|
||||
"level": 2,
|
||||
"name": "必要补充字段",
|
||||
"rule": "如果用户查询涉及时间、系统或状态分析，建议补充相关维度字段。",
|
||||
"threshold": "用户查询涉及分组统计时建议补充item_creation_date和system_flag"
|
||||
},
|
||||
{
|
||||
"level": 3,
|
||||
"name": "智能推断字段",
|
||||
"rules": [
|
||||
{
|
||||
"trigger": ["积压", "backlog", "积压订单", "待处理"],
|
||||
"add_fields": ["backlog_status"],
|
||||
"where_condition": "backlog_status = '1'"
|
||||
},
|
||||
{
|
||||
"trigger": ["系统", "来源", "HIC", "SSOC"],
|
||||
"add_fields": ["system_flag"]
|
||||
},
|
||||
{
|
||||
"trigger": ["日期", "时间", "创建时间", "item_creation"],
|
||||
"add_fields": ["item_creation_date"]
|
||||
},
|
||||
{
|
||||
"trigger": ["订单", "so", "订单号"],
|
||||
"add_fields": ["so", "soid"]
|
||||
},
|
||||
{
|
||||
"trigger": ["物料", "PN", "料号", "零件"],
|
||||
"add_fields": ["original_pn", "ship_pn"]
|
||||
},
|
||||
{
|
||||
"trigger": ["仓库", "actual_wh", "出货仓库"],
|
||||
"add_fields": ["actual_wh"]
|
||||
},
|
||||
{
|
||||
"trigger": ["状态", "item_status", "订单状态"],
|
||||
"add_fields": ["item_status"]
|
||||
},
|
||||
{
|
||||
"trigger": ["系列", "成品系列", "machine_type", "20LN", "产品类型"],
|
||||
"add_fields": ["machine_type"]
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"level": 4,
|
||||
"name": "时间维度处理",
|
||||
"rules": [
|
||||
{
|
||||
"condition": "用户查询涉及统计、趋势、每日等时间概念",
|
||||
"action": "必须包含item_creation_date字段"
|
||||
},
|
||||
{
|
||||
"condition": "用户指定具体日期范围",
|
||||
"action": "在WHERE条件中添加日期范围过滤"
|
||||
}
|
||||
]
|
||||
}
|
||||
],
|
||||
"backlog_logic": {
|
||||
"definition": "backlog_status = '1' 表示积压订单，这是核心业务标识",
|
||||
"inclusion_rule": "当用户查询涉及积压相关分析时，默认WHERE条件包含backlog_status = '1'",
|
||||
"important_note": "统计总订单数时需要同时考虑积压和非积压状态"
|
||||
}
|
||||
},
|
||||
"aggregation_mode": {
|
||||
"trigger_keywords": ["统计", "汇总", "总数", "有多少", "数量", "按...分组", "每个", "每日", "count", "sum", "total", "group by", "趋势", "分布"],
|
||||
"column_naming_rules": {
|
||||
"aggregate_functions": {
|
||||
"COUNT": "COUNT({column}) AS {column}_count",
|
||||
"COUNT_DISTINCT": "COUNT(DISTINCT {column}) AS {column}_distinct_count",
|
||||
"SUM_CASE": "SUM(CASE WHEN {condition} THEN 1 ELSE 0 END) AS {alias}_count"
|
||||
},
|
||||
"group_by_fields": "保持原字段名",
|
||||
"examples": [
|
||||
"用户说'按日期统计积压订单数' → SELECT item_creation_date, COUNT(*) AS backlog_count WHERE backlog_status = '1' GROUP BY item_creation_date",
|
||||
"用户说'统计每个系统的订单数' → SELECT system_flag, COUNT(*) AS order_count GROUP BY system_flag",
|
||||
"用户说'按产品系列统计订单数' → SELECT machine_type, COUNT(*) AS order_count GROUP BY machine_type"
|
||||
]
|
||||
},
|
||||
"allowed_group_by_fields": ["item_creation_date", "system_flag", "backlog_status", "actual_wh", "item_status", "service_delivery_type", "warranty", "machine_type"]
|
||||
},
|
||||
"default_behavior": {
|
||||
"sorting": {
|
||||
"date_queries": "item_creation_date DESC",
|
||||
"count_queries": "按统计字段降序",
|
||||
"default": "item_creation_date DESC"
|
||||
},
|
||||
"limit": "禁止使用LIMIT",
|
||||
"backlog_filter": "当用户明确查询'积压订单'时，WHERE条件包含backlog_status = '1'"
|
||||
},
|
||||
"special_scenarios": {
|
||||
"积压率计算": "积压订单数 / 总订单数",
|
||||
"系统对比": "HIC vs SSOC 系统订单分布",
|
||||
"时间趋势": "按日/月统计订单创建趋势",
|
||||
"物料分析": "按original_pn或ship_pn统计热门物料",
|
||||
"产品系列分析": "按machine_type统计不同产品系列的订单分布"
|
||||
}
|
||||
},
|
||||
"field_mapping_reference": {
|
||||
"key_fields": {
|
||||
"backlog_status": "积压状态标识（'1'=积压订单）",
|
||||
"system_flag": "系统来源（HIC/SSOC）",
|
||||
"item_creation_date": "订单创建日期（主要时间维度）",
|
||||
"so": "订单号",
|
||||
"soid": "订单ID",
|
||||
"original_pn": "原始物料号",
|
||||
"ship_pn": "出货物料号",
|
||||
"machine_type": "客户购买成品的系列"
|
||||
},
|
||||
"alias_mapping": {
|
||||
"创建日期": "item_creation_date",
|
||||
"日期": "item_creation_date",
|
||||
"系统": "system_flag",
|
||||
"来源": "system_flag",
|
||||
"积压": "backlog_status",
|
||||
"订单号": "so",
|
||||
"订单": "so",
|
||||
"物料": "original_pn",
|
||||
"料号": "original_pn",
|
||||
"PN": "original_pn",
|
||||
"出货PN": "ship_pn",
|
||||
"仓库": "actual_wh",
|
||||
"状态": "item_status",
|
||||
"系列": "machine_type",
|
||||
"成品系列": "machine_type",
|
||||
"产品类型": "machine_type",
|
||||
"机器类型": "machine_type"
|
||||
},
|
||||
"mapping_rule": "生成SQL时必须使用右侧的完整字段名，用户别名仅用于理解意图"
|
||||
},
|
||||
"examples": {
|
||||
"统计查询": {
|
||||
"user": "统计每日的订单总数和积压订单数",
|
||||
"sql": "SELECT item_creation_date, COUNT(*) AS total_orders, SUM(CASE WHEN backlog_status = '1' THEN 1 ELSE 0 END) AS backlog_orders FROM dwd_ai.apbo_hic_ssoc_consumption GROUP BY item_creation_date ORDER BY item_creation_date DESC"
|
||||
},
|
||||
"物料分析": {
|
||||
"user": "查看积压最多的物料Top 10",
|
||||
"sql": "SELECT original_pn, COUNT(*) AS backlog_count FROM dwd_ai.apbo_hic_ssoc_consumption WHERE backlog_status = '1' GROUP BY original_pn ORDER BY backlog_count DESC"
|
||||
},
|
||||
"时间范围查询": {
|
||||
"user": "查询2024年1月的所有订单",
|
||||
"sql": "SELECT so, soid, original_pn, system_flag, backlog_status, item_creation_date FROM dwd_ai.apbo_hic_ssoc_consumption WHERE item_creation_date >= '2024-01-01' AND item_creation_date <= '2024-01-31' ORDER BY item_creation_date DESC"
|
||||
},
|
||||
"复合条件查询": {
|
||||
"user": "查询SSOC系统中实际仓库为3001的非积压订单",
|
||||
"sql": "SELECT so, soid, original_pn, item_creation_date, item_status FROM dwd_ai.apbo_hic_ssoc_consumption WHERE system_flag = 'SSOC' AND actual_wh = '3001' AND backlog_status != '1' ORDER BY item_creation_date DESC"
|
||||
},
|
||||
"按日期和产品系列过滤查询": {
|
||||
"user": "查询20260115, 20LN系列的订单",
|
||||
"sql": "SELECT so, soid, machine_type, original_pn, ship_pn, service_delivery_type, warranty, actual_wh, item_status, item_creation_date, allocation_datetime, backlog_status, system_flag FROM dwd_ai.apbo_hic_ssoc_consumption WHERE machine_type = '20LN' AND item_creation_date = '2026-01-15' ORDER BY item_creation_date DESC"
|
||||
},
|
||||
"产品系列统计": {
|
||||
"user": "按产品系列统计订单总数",
|
||||
"sql": "SELECT machine_type, COUNT(*) AS order_count FROM dwd_ai.apbo_hic_ssoc_consumption GROUP BY machine_type ORDER BY order_count DESC"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,97 @@
|
||||
{
|
||||
"meta": {
|
||||
"domain": "订单物流节点(Milestone)追踪与查询",
|
||||
"keywords": ["milestone", "物流节点", "运输节点", "logistics node", "shipment tracking", "节点查询", "节点状态", "节点时间", "节点跟踪", "里程碑", "节点明细"],
|
||||
"description": "此模型用于查询订单在物流运输全链路中的关键节点(milestone)信息，追踪从订单创建、提货、运输到签收的完整状态流。每个订单可对应多个节点记录以反映运输进度。"
|
||||
},
|
||||
"data_model_specification": {
|
||||
"data_source": "dwd_ai.apbo_milestone_info",
|
||||
"fields_list": ["service_order_id", "soid", "part_number", "PO", "po_creation_date", "prid", "DN", "dn_date", "gi_date", "BOL", "hawb", "pickup_time", "etd", "atd", "eta", "ata", "pod", "gr_date", "status", "status_date", "service_order_creation_date", "so_eta", "topmost_pn", "commodity_code", "ship_to_country", "region", "dc_plant", "mtm", "machine_sn","machine_type", "whether_premier", "stm_planner", "category", "lenovo_ref_no"],
|
||||
"mandatory_display_fields": {
|
||||
"rule1": "字段默认全部展示。日期字段需格式化为指定字符串格式。",
|
||||
"rule2": "select时，所有NULL值使用空字符串''代替",
|
||||
"rule3": "部分字段select时的顺序如下:po,po_creation_date,prid,dn,dn_date,gi_date,bol,hawb,pickup_time,etd,atd,eta,ata,pod,gr_date",
|
||||
"rule4": "禁止使用limit"
|
||||
},
|
||||
|
||||
"optional_fields": {
|
||||
"material_fields": ["topmost_pn", "commodity_code"],
|
||||
"location_fields": ["ship_to_country", "region", "dc_plant"],
|
||||
"machine_fields": ["mtm", "machine_sn","machine_type"],
|
||||
"service_fields": ["whether_premier", "stm_planner", "lenovo_ref_no"],
|
||||
"Field_combination": ["category", "status", "status_date"]
|
||||
}
|
||||
},
|
||||
|
||||
"business_logic_rules": {
|
||||
"query_recognition_rules": {
|
||||
"milestone_keywords": ["物流节点", "运输节点", "节点", "里程碑", "milestone", "logistics node", "节点时间", "节点状态", "节点查询", "节点跟踪"],
|
||||
"filter_based_patterns": ["查询{单据号}的物流节点", "追踪{订单号}的节点信息", "显示{节点状态}的订单", "查找{节点时间}的物流记录", "获取{节点类型}的详细信息"]
|
||||
},
|
||||
"default_behavior": {
|
||||
"sorting": "status_date DESC, service_order_creation_date DESC"
|
||||
}
|
||||
},
|
||||
|
||||
"field_mapping_reference": {
|
||||
"key_identifiers": {
|
||||
"service_order_id": {"type": "varchar(20)", "desc": "主订单号，唯一标识", "example": "4020438779", "required": true, "alias": ["SO", "订单号", "服务订单", "so", "order_no", "Service Order"]},
|
||||
"soid": {"type": "varchar(22)", "desc": "服务订单明细ID=service_order_id+两位序号", "example": "402043877920", "required": true, "alias": ["SOID", "订单明细", "服务订单明细", "soid", "Service Order Item Detail"]},
|
||||
"part_number": {"type": "varchar(30)", "desc": "原始申请物料号", "example": "5CB1L57599", "required": true, "alias": ["pn", "物料号", "零件号", "Part Number", "材料号"]}
|
||||
},
|
||||
|
||||
"milestone_document_fields": {
|
||||
"bol": {"type": "varchar(50)", "desc": "提单号(Bill of Lading)", "example": "BOL20231027001", "alias": ["提单", "海运提单", "提单号", "Bill of Lading", "B/L"]},
|
||||
"dn": {"type": "varchar(50)", "desc": "发货单号(Delivery Note)", "example": "DN20231027001", "alias": ["发货单", "送货单", "DN单", "Delivery Note", "发货单据"]},
|
||||
"po": {"type": "varchar(50)", "desc": "采购单号(Purchase Order)", "example": "PO20231027001", "alias": ["采购单", "PO单", "采购订单", "Purchase Order", "采购订单号"]},
|
||||
"hawb": {"type": "varchar(50)", "desc": "空运主单号(House Air Waybill)", "example": "HAWB12345678", "alias": ["空运单", "航空运单", "HAWB", "Air Waybill", "空运提单"]},
|
||||
"prid": {"type": "varchar(50)", "desc": "运输参考ID(PRID)", "example": "PRID123456", "alias": ["运输参考号", "PRID号", "运输ID", "运输参考ID", "Shipping Reference ID"]}
|
||||
},
|
||||
|
||||
"milestone_date_fields": {
|
||||
"service_order_creation_date": {"type": "date", "desc": "服务订单创建日期", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["订单创建时间", "SO创建时间", "服务订单创建时间", "Order Creation Date"]},
|
||||
"po_creation_date": {"type": "date", "desc": "采购单创建日期", "format": "YYYY-MM-DD", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["采购单创建时间", "PO创建时间", "采购订单创建日期", "Purchase Order Creation Date"]},
|
||||
"dn_date": {"type": "date", "desc": "发货单创建日期", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["发货单日期", "DN日期", "发货时间", "Delivery Note Date"]},
|
||||
"gi_date": {"type": "date", "desc": "货物发出日期(Goods Issue)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["货物发出时间", "发货日期", "出库时间", "Goods Issue Date", "出库日期"]},
|
||||
"pickup_time": {"type": "datetime", "desc": "提货时间", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["提货日期", "取货时间", "提货时间点", "Pickup Time", "提取时间"]},
|
||||
"etd": {"type": "date", "desc": "预计出发时间(Estimated Time of Departure)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["预计出发", "计划出发时间", "ETD", "预计离港时间"]},
|
||||
"atd": {"type": "date", "desc": "实际出发时间(Actual Time of Departure)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["实际出发", "实际离港时间", "ATD", "实际出发时间"]},
|
||||
"eta": {"type": "date", "desc": "预计到达时间(Estimated Time of Arrival)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["预计到达", "计划到达时间", "ETA", "预计到港时间"]},
|
||||
"ata": {"type": "date", "desc": "实际到达时间(Actual Time of Arrival)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["实际到达", "实际到港时间", "ATA", "实际到达时间"]},
|
||||
"pod": {"type": "date", "desc": "签收单收到日期(Proof of Delivery)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["签收时间", "POD时间", "签收日期", "Proof of Delivery", "签收证明时间"]},
|
||||
"gr_date": {"type": "date", "desc": "收货日期(Goods Receipt)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["收货时间", "入库时间", "GR时间", "Goods Receipt Date", "收货日期"]},
|
||||
"status_date": {"type": "date", "desc": "状态最后更新时间", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["状态更新时间", "最后更新", "状态日期", "Status Update Date"]},
|
||||
"so_eta": {"type": "date", "desc": "订单预计到达时间(SO ETA)", "format": "YYYY-MM-DD HH:MM:SS", "query_format": "CAST(field_name AS VARCHAR(2048)) AS field_name 作为字符串展示", "alias": ["订单最终到达时间", "订单ETA", "服务订单预计到达", "Service Order ETA"]}
|
||||
},
|
||||
|
||||
"additional_fields": {
|
||||
"topmost_pn": {"type": "varchar(30)", "desc": "最优替换物料号", "example": "5CB1L57599", "alias": ["tp", "最优物料", "Topmost Part Number", "首选物料号", "最优替换零件"]},
|
||||
"commodity_code": {"type": "varchar(2)", "desc": "商品分类代码", "example": "PL", "alias": ["cc", "商品代码", "物料分类", "Commodity Code", "商品类别"]},
|
||||
"ship_to_country": {"type": "varchar(2)", "desc": "目的地国家ISO代码", "example": "PH", "alias": ["目的地国家", "收货国家", "Ship to Country", "目标国家", "送达国家"]},
|
||||
"region": {"type": "varchar(10)", "desc": "区域代码", "example": "CAP", "alias": ["区域", "地区", "Region Code", "大区", "地域代码"]},
|
||||
"dc_plant": {"type": "varchar(10)", "desc": "发货配送中心", "example": "VN01", "alias": ["配送中心", "DC", "发货中心", "Distribution Center", "发货工厂"]},
|
||||
"mtm": {"type": "varchar(20)", "desc": "机器型号,请注意与mt区分,这不是mt,这是mtm,这是mtm,这是mtm", "example": "20QUS0SQ00", "alias": ["机型", "型号", "Machine Type Model", "设备型号", "机器型号代码"]},
|
||||
"machine_sn": {"type": "varchar(50)", "desc": "机器序列号", "example": "PW01554B", "alias": ["序列号", "SN", "Machine Serial Number", "设备序列号", "机器SN"]},
|
||||
"machine_type": {"type": "varchar(2048)","desc": "机器类型, 请注意与mtm区分,这不是mtm,这是mt,这是mt,这是mt","example": "20Q1","alias": ["MT","machine type", "机器类型"]},
|
||||
"whether_premier": {"type": "tinyint", "desc": "是否Premier服务", "values": {"0": "非Premier", "1": "Premier"}, "alias": ["是否Premier", "Premier服务", "是否优先", "Whether Premier", "优先服务标识"]},
|
||||
"stm_planner": {"type": "varchar(50)", "desc": "STM计划员姓名", "alias": ["计划员", "STM计划员", "STM Planner", "服务计划员", "运输计划员"]},
|
||||
"category": {"type": "varchar(20)", "desc": "订单类别", "values": ["Standard", "Emergency", "Critical"], "alias": ["类别", "订单类型", "Category", "服务类别", "订单分类"]},
|
||||
"status": {"type": "varchar(4096)", "desc": "状态", "example": "3001:02HL023*1(Need geo verify demand:2025-10-30)", "alias": ["状态"]},
|
||||
"lenovo_ref_no": {"type": "varchar(50)", "desc": "联想内部参考号", "alias": ["联想参考号", "内部参考号", "Lenovo Reference", "联想内部编号", "参考编号"]},
|
||||
"case_number": {"type": "string", "desc": "事件编号", "example": "CS12345678", "alias": ["case", "事件号", "案例号", "Case Number", "投诉编号", "事件编号"]}
|
||||
}
|
||||
},
|
||||
|
||||
"examples": {
|
||||
"基础查询": {
|
||||
"user": "查询订单的物流节点信息",
|
||||
"sql": "SELECT service_order_id, soid, part_number, bol, dn, po, hawb, prid, CAST(service_order_creation_date AS VARCHAR(2048)) as service_order_creation_date, CAST(po_creation_date AS VARCHAR(2048)) as po_creation_date, CAST(dn_date AS VARCHAR(2048)) as dn_date, CAST(gi_date AS VARCHAR(2048)) as gi_date, CAST(pickup_time AS VARCHAR(2048)) as pickup_time, CAST(etd AS VARCHAR(2048)) as etd, CAST(atd AS VARCHAR(2048)) as atd, CAST(eta AS VARCHAR(2048)) as eta, CAST(ata AS VARCHAR(2048)) as ata, CAST(pod AS VARCHAR(2048)) as pod, CAST(gr_date AS VARCHAR(2048)) as gr_date, CAST(status_date AS VARCHAR(2048)) as status_date, CAST(so_eta AS VARCHAR(2048)) as so_eta FROM dwd_ai.apbo_milestone_info ORDER BY status_date DESC, service_order_creation_date DESC",
|
||||
"field_selection_reason": "基础查询显示所有必填的milestone字段,包括新增的service_order_creation_date, so_eta,日期字段已格式化为指定字符串格式"
|
||||
},
|
||||
"按主订单号查询": {
|
||||
"user": "SO为4019630464的milestone信息",
|
||||
"sql": "SELECT service_order_id, soid, part_number, bol, dn, po, hawb, prid, CAST(service_order_creation_date AS VARCHAR(2048)) as service_order_creation_date, CAST(po_creation_date AS VARCHAR(2048)) as po_creation_date, CAST(dn_date AS VARCHAR(2048)) as dn_date, CAST(gi_date AS VARCHAR(2048)) as gi_date, CAST(pickup_time AS VARCHAR(2048)) as pickup_time, CAST(etd AS VARCHAR(2048)) as etd, CAST(atd AS VARCHAR(2048)) as atd, CAST(eta AS VARCHAR(2048)) as eta, CAST(ata AS VARCHAR(2048)) as ata, CAST(pod AS VARCHAR(2048)) as pod, CAST(gr_date AS VARCHAR(2048)) as gr_date, CAST(status_date AS VARCHAR(2048)) as status_date, CAST(so_eta AS VARCHAR(2048)) as so_eta FROM dwd_ai.apbo_milestone_info WHERE service_order_id = '4019630464' ORDER BY status_date DESC, service_order_creation_date DESC",
|
||||
"field_selection_reason": "用户提到'SO',根据映射规则应查询service_order_id字段,包含所有必填字段,日期字段已格式化为字符串"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,431 @@
|
||||
{
|
||||
"meta": {
|
||||
"domain": "亚太区物料库存与用量分析",
|
||||
"keywords": ["库存", "用量", "物料分析", "亚太区", "国家用量", "历史使用量", "近期用量", "IB", "库存数量"],
|
||||
"description": "此模型用于分析亚太地区各物料在不同区域,配送中心及目的地国家的库存情况,近期用量及历史使用量。特别注意：国家字段(AU, VN, JP等)是数值型用量字段，表示该物料在该国家的历史用量，不是国家代码。",
|
||||
"data_source": "dwd_ai.apbo_region_usage_ib_report"
|
||||
},
|
||||
"data_model_specification": {
|
||||
"fields_list": ["topmost_pn", "region", "commodity_code", "dc_plant", "country_total_cnt", "AU", "NZ", "LK", "VN", "JP", "HK", "SG", "TH", "PH", "IN", "BN", "NP", "BD", "KR", "ID", "FJ", "MY", "TW", "location_name", "ib", "usage_qty_8_week", "usage_qty_52_week", "total_history_usage"],
|
||||
|
||||
"core_country_fields": {
|
||||
"list": ["AU", "NZ", "LK", "VN", "JP", "HK", "SG", "TH", "PH", "IN", "BN", "NP", "BD", "KR", "ID", "FJ", "MY", "TW"],
|
||||
"meaning": "各国家过去某几周的总使用量,字段类型为BIGINT.这些字段表示该物料在该国家的历史用量值.",
|
||||
"critical_notes": "这些字段是数值型用量字段，不是国家代码。例如：VN字段表示物料在越南的历史使用量数值，不是字符串'VN'。"
|
||||
},
|
||||
|
||||
"mandatory_display_fields": {
|
||||
"rule1": "默认查询所有字段（SELECT *）",
|
||||
"rule2": "当用户明确指定某些字段时，只查询这些字段，并保持用户提到的顺序",
|
||||
"rule3": "WHERE条件中使用的所有字段（除了国家字段的数值比较外），必须在SELECT子句中展示",
|
||||
"rule4": "国家字段是数值型，直接展示数值，不需要特殊处理",
|
||||
"rule5": "select的所有字段必须用``包裹，如select `IN`，防止与SQL关键字冲突",
|
||||
"actual_fields_order": ["topmost_pn", "region", "commodity_code", "dc_plant", "country_total_cnt", "AU", "NZ", "LK", "VN", "JP", "HK", "SG", "TH", "PH", "IN", "BN", "NP", "BD", "KR", "ID", "FJ", "MY", "TW", "location_name", "ib", "usage_qty_8_week", "usage_qty_52_week", "total_history_usage"]
|
||||
}
|
||||
},
|
||||
"business_logic_rules": {
|
||||
"query_recognition_rules": {
|
||||
"material_keywords": ["物料", "topmost_pn", "物料号", "零件号", "Part Number", "PN"],
|
||||
"region_keywords": ["region", "区域", "大区", "地区", "Region Code", "CAP", "EMEA", "AMER"],
|
||||
"commodity_keywords": ["commodity_code", "商品代码", "编码", "物料分类", "Commodity Code", "CC"],
|
||||
"inventory_keywords": ["库存", "ib", "库存数量", "库存量", "Inventory Balance"],
|
||||
"usage_keywords": ["用量", "使用量", "历史用量", "近期用量", "usage", "使用数量"],
|
||||
"location_keywords": ["dc_plant", "plant", "配送中心", "工厂", "location", "地点"],
|
||||
"country_usage_keywords": ["国家用量", "国家使用量", "country usage", "国家用量分析"],
|
||||
"specific_country_keywords": {
|
||||
"AU": ["澳大利亚", "澳洲", "AU", "Australia"],
|
||||
"VN": ["越南", "VN", "Vietnam"],
|
||||
"JP": ["日本", "JP", "Japan"],
|
||||
"HK": ["香港", "HK", "Hong Kong"],
|
||||
"SG": ["新加坡", "SG", "Singapore"],
|
||||
"TH": ["泰国", "TH", "Thailand"],
|
||||
"IN": ["印度", "IN", "India"],
|
||||
"KR": ["韩国", "KR", "Korea"],
|
||||
"ID": ["印度尼西亚", "印尼", "ID", "Indonesia"],
|
||||
"MY": ["马来西亚", "MY", "Malaysia"],
|
||||
"TW": ["台湾", "TW", "Taiwan"],
|
||||
"NZ": ["新西兰", "NZ", "New Zealand"],
|
||||
"PH": ["菲律宾", "PH", "Philippines"]
|
||||
}
|
||||
},
|
||||
|
||||
"country_field_interpretation": {
|
||||
"fundamental_rule": "国家字段(AU, VN, JP等)是数值型用量字段(BIGINT)，表示该物料在该国家的历史用量，不是国家代码",
|
||||
"correct_usage": {
|
||||
"in_select": "直接展示数值，如：SELECT AU, VN, JP",
|
||||
"in_where": "不需要添加任何默认过滤条件，除非用户明确要求",
|
||||
"as_numeric": "作为数值字段处理，支持比较运算符：>, <, >=, <=, ="
|
||||
},
|
||||
"incorrect_usage": [
|
||||
"WHERE VN = 'VN' (错误：VN是数值字段，不是字符串)",
|
||||
"WHERE VN LIKE '%VN%' (错误：VN是数值字段，不支持LIKE)",
|
||||
"WHERE VN IN ('VN', 'AU') (错误：VN是数值字段，不是枚举值)"
|
||||
],
|
||||
"user_intent_interpretation": {
|
||||
"当用户说'country为VN'": "用户只是提到VN字段，但不一定要求VN>0，不需要添加过滤条件",
|
||||
"当用户说'VN国家'": "用户指的是VN字段，按字段处理",
|
||||
"当用户说'有VN用量的物料'": "需要添加WHERE VN > 0",
|
||||
"当用户说'VN用量超过100'": "需要添加WHERE VN >= 100",
|
||||
"当用户说'VN用量为0'": "需要添加WHERE VN = 0",
|
||||
"当用户说'没有VN用量的'": "需要添加WHERE VN = 0"
|
||||
}
|
||||
},
|
||||
|
||||
"field_selection_logic": {
|
||||
"priority_order": [
|
||||
{
|
||||
"level": 1,
|
||||
"name": "用户明确指定的字段",
|
||||
"rule": "精确添加用户提到的字段，按用户问题中出现的顺序排列，不添加未提及的字段"
|
||||
},
|
||||
{
|
||||
"level": 2,
|
||||
"name": "默认字段选择",
|
||||
"rule": "如果用户没有明确指定字段，默认查询所有字段（SELECT *）"
|
||||
}
|
||||
],
|
||||
|
||||
"where_condition_fields_must_in_select": {
|
||||
"rule": "WHERE条件中使用的所有字段（除了国家字段的数值比较外），必须在SELECT子句中展示",
|
||||
"purpose": "确保查询结果的完整性，用户能看到过滤依据",
|
||||
"examples": [
|
||||
"用户说'region为CAP的数据' → SELECT * ... WHERE region = 'CAP'",
|
||||
"用户说'ib大于500的物料号' → SELECT topmost_pn, ib ... WHERE ib > 500",
|
||||
"用户说'region为CAP且commodity_code为LF的物料号' → SELECT topmost_pn, region, commodity_code ... WHERE region = 'CAP' AND commodity_code = 'LF'"
|
||||
]
|
||||
}
|
||||
},
|
||||
|
||||
"where_condition_generation": {
|
||||
"strict_rule": "只生成用户明确要求的过滤条件，不添加任何默认或假设的条件",
|
||||
"condition_types": {
|
||||
"exact_match": {
|
||||
"pattern": "{字段}为{值}",
|
||||
"sql": "{field} = '{value}'",
|
||||
"examples": ["region为CAP → region = 'CAP'", "commodity_code为LF → commodity_code = 'LF'", "dc_plant为HKGDC → dc_plant = 'HKGDC'"]
|
||||
},
|
||||
"country_field_handling": {
|
||||
"important_note": "当用户提到'country为VN'时，不需要在WHERE中添加VN > 0，除非用户明确要求过滤用量",
|
||||
"correct_interpretation": "用户只是提到VN字段，但没有要求过滤VN的值",
|
||||
"only_add_filter_when": [
|
||||
"用户明确说'有VN用量的' → WHERE VN > 0",
|
||||
"用户明确说'VN用量大于0的' → WHERE VN > 0",
|
||||
"用户明确说'VN超过100的' → WHERE VN >= 100",
|
||||
"用户明确说'VN用量为0的' → WHERE VN = 0",
|
||||
"用户明确说'没有VN用量的' → WHERE VN = 0"
|
||||
],
|
||||
"incorrect_interpretation": [
|
||||
"用户说'country为VN' → 错误：添加WHERE VN > 0",
|
||||
"用户说'VN国家' → 错误：添加WHERE VN > 0",
|
||||
"用户说'查看VN' → 错误：添加WHERE VN > 0"
|
||||
]
|
||||
},
|
||||
"range_filter": {
|
||||
"pattern": ["大于{值}", "超过{值}", "少于{值}", "小于{值}", "不低于{值}", "不超过{值}"],
|
||||
"sql_mapping": {
|
||||
"大于{值}": "{field} > {value}",
|
||||
"超过{值}": "{field} >= {value}",
|
||||
"少于{值}": "{field} < {value}",
|
||||
"小于{值}": "{field} < {value}",
|
||||
"不低于{值}": "{field} >= {value}",
|
||||
"不超过{值}": "{field} <= {value}"
|
||||
},
|
||||
"examples": [
|
||||
"库存大于500 → ib > 500",
|
||||
"VN用量超过100 → VN >= 100",
|
||||
"近期用量少于50 → usage_qty_8_week < 50"
|
||||
]
|
||||
},
|
||||
"multiple_conditions": {
|
||||
"pattern": ["且", "并且", "和", "同时", ","],
|
||||
"sql": "AND",
|
||||
"examples": [
|
||||
"region为CAP且commodity_code为LF → region = 'CAP' AND commodity_code = 'LF'",
|
||||
"库存大于500且有VN用量 → ib > 500 AND VN > 0"
|
||||
]
|
||||
}
|
||||
},
|
||||
|
||||
"no_default_conditions": {
|
||||
"rule": "绝对不添加任何用户没有明确要求的WHERE条件",
|
||||
"examples_of_what_not_to_add": [
|
||||
"不要添加WHERE region = 'CAP'（除非用户明确要求）",
|
||||
"不要添加WHERE ib > 0（除非用户明确要求）",
|
||||
"不要添加WHERE commodity_code IS NOT NULL（除非用户明确要求）",
|
||||
"不要添加任何假设性的过滤条件"
|
||||
]
|
||||
}
|
||||
},
|
||||
|
||||
"default_behavior": {
|
||||
"sorting": "默认按ib(库存数量)降序排列：ORDER BY ib DESC",
|
||||
"limit": "禁止使用limit",
|
||||
"select_all": "默认查询所有字段：SELECT *",
|
||||
"field_order": "当用户指定字段时，按用户提到的顺序排列字段",
|
||||
"date_handling": "本表无日期字段，不需要日期转换"
|
||||
}
|
||||
},
|
||||
"field_mapping_reference": {
|
||||
"critical_note": "此表包含亚太地区各物料的库存、近期用量及历史使用量的详细数据。特别注意：国家字段(AU, VN, JP等)是数值型用量字段，表示该物料在该国家的历史用量，不是国家代码。这些字段是BIGINT类型，支持数值比较操作。",
|
||||
|
||||
"material_identifier_fields": {
|
||||
"topmost_pn": {
|
||||
"type": "string",
|
||||
"desc": "顶级物料号，物料的唯一标识",
|
||||
"example": "5CB1L57599",
|
||||
"query_pattern": "物料为{值} → topmost_pn = '{value}'",
|
||||
"alias": ["物料号", "零件号", "Part Number", "PN", "topmost", "物料编码"]
|
||||
},
|
||||
"commodity_code": {
|
||||
"type": "string",
|
||||
"desc": "商品代码，物料分类标识",
|
||||
"example": "LF",
|
||||
"query_pattern": "commodity_code为{值} → commodity_code = '{value}'",
|
||||
"alias": ["商品编码", "物料分类", "Commodity Code", "CC", "编码", "商品类别"]
|
||||
}
|
||||
},
|
||||
|
||||
"geographic_dimension_fields": {
|
||||
"region": {
|
||||
"type": "string",
|
||||
"desc": "区域划分，如CAP（亚太区）、EMEA（欧洲中东非洲）等",
|
||||
"example": "CAP",
|
||||
"values": ["CAP", "EMEA", "AMER"],
|
||||
"query_pattern": "region为{值} → region = '{value}'",
|
||||
"alias": ["区域", "大区", "Region", "地区", "地理区域"]
|
||||
},
|
||||
"dc_plant": {
|
||||
"type": "string",
|
||||
"desc": "配送中心/工厂代码",
|
||||
"example": "HKGDC",
|
||||
"query_pattern": "dc_plant为{值} → dc_plant = '{value}'",
|
||||
"alias": ["工厂", "配送中心", "plant", "DC", "发货中心", "Distribution Center"]
|
||||
},
|
||||
"location_name": {
|
||||
"type": "string",
|
||||
"desc": "地点名称",
|
||||
"example": "Hong Kong Distribution Center",
|
||||
"alias": ["地点名称", "位置名称", "location", "地点", "场所名称"]
|
||||
}
|
||||
},
|
||||
|
||||
"country_usage_fields_section": {
|
||||
"important_note": "以下所有字段都是数值型(BIGINT)，表示该物料在该国家的历史使用量，不是国家代码。这些字段支持数值比较操作(>, <, >=, <=, =, !=)。",
|
||||
"critical_warning": "绝对不要将这些字段作为字符串处理，不要使用单引号，不要使用LIKE操作符。",
|
||||
|
||||
"country_total_cnt": {
|
||||
"type": "bigint",
|
||||
"desc": "所有国家的总使用量计数",
|
||||
"calculation_note": "可能是各国家字段的汇总或其他计算逻辑",
|
||||
"alias": ["国家总计数", "总使用量", "country total", "总计"]
|
||||
},
|
||||
|
||||
"country_usage_fields": {
|
||||
"AU": {
|
||||
"type": "bigint",
|
||||
"desc": "澳大利亚的历史使用量",
|
||||
"alias": ["澳大利亚", "澳洲", "AU用量", "Australia用量"]
|
||||
},
|
||||
"NZ": {
|
||||
"type": "bigint",
|
||||
"desc": "新西兰的历史使用量",
|
||||
"alias": ["新西兰", "NZ用量", "New Zealand用量"]
|
||||
},
|
||||
"LK": {
|
||||
"type": "bigint",
|
||||
"desc": "斯里兰卡的历史使用量",
|
||||
"alias": ["斯里兰卡", "LK用量", "Sri Lanka用量"]
|
||||
},
|
||||
"VN": {
|
||||
"type": "bigint",
|
||||
"desc": "越南的历史使用量",
|
||||
"alias": ["越南", "VN用量", "Vietnam用量"]
|
||||
},
|
||||
"JP": {
|
||||
"type": "bigint",
|
||||
"desc": "日本的历史使用量",
|
||||
"alias": ["日本", "JP用量", "Japan用量"]
|
||||
},
|
||||
"HK": {
|
||||
"type": "bigint",
|
||||
"desc": "香港的历史使用量",
|
||||
"alias": ["香港", "HK用量", "Hong Kong用量"]
|
||||
},
|
||||
"SG": {
|
||||
"type": "bigint",
|
||||
"desc": "新加坡的历史使用量",
|
||||
"alias": ["新加坡", "SG用量", "Singapore用量"]
|
||||
},
|
||||
"TH": {
|
||||
"type": "bigint",
|
||||
"desc": "泰国的历史使用量",
|
||||
"alias": ["泰国", "TH用量", "Thailand用量"]
|
||||
},
|
||||
"PH": {
|
||||
"type": "bigint",
|
||||
"desc": "菲律宾的历史使用量",
|
||||
"alias": ["菲律宾", "PH用量", "Philippines用量"]
|
||||
},
|
||||
"IN": {
|
||||
"type": "bigint",
|
||||
"desc": "印度的历史使用量",
|
||||
"alias": ["印度", "IN用量", "India用量"]
|
||||
},
|
||||
"BN": {
|
||||
"type": "bigint",
|
||||
"desc": "文莱的历史使用量",
|
||||
"alias": ["文莱", "BN用量", "Brunei用量"]
|
||||
},
|
||||
"NP": {
|
||||
"type": "bigint",
|
||||
"desc": "尼泊尔的历史使用量",
|
||||
"alias": ["尼泊尔", "NP用量", "Nepal用量"]
|
||||
},
|
||||
"BD": {
|
||||
"type": "bigint",
|
||||
"desc": "孟加拉国的历史使用量",
|
||||
"alias": ["孟加拉国", "BD用量", "Bangladesh用量"]
|
||||
},
|
||||
"KR": {
|
||||
"type": "bigint",
|
||||
"desc": "韩国的历史使用量",
|
||||
"alias": ["韩国", "KR用量", "Korea用量"]
|
||||
},
|
||||
"ID": {
|
||||
"type": "bigint",
|
||||
"desc": "印度尼西亚的历史使用量",
|
||||
"alias": ["印度尼西亚", "印尼", "ID用量", "Indonesia用量"]
|
||||
},
|
||||
"FJ": {
|
||||
"type": "bigint",
|
||||
"desc": "斐济的历史使用量",
|
||||
"alias": ["斐济", "FJ用量", "Fiji用量"]
|
||||
},
|
||||
"MY": {
|
||||
"type": "bigint",
|
||||
"desc": "马来西亚的历史使用量",
|
||||
"alias": ["马来西亚", "MY用量", "Malaysia用量"]
|
||||
},
|
||||
"TW": {
|
||||
"type": "bigint",
|
||||
"desc": "台湾的历史使用量",
|
||||
"alias": ["台湾", "TW用量", "Taiwan用量"]
|
||||
}
|
||||
},
|
||||
|
||||
"query_examples": {
|
||||
"correct": [
|
||||
"WHERE VN > 0 (查询有越南用量的物料)",
|
||||
"WHERE JP >= 100 (查询日本用量超过100的物料)",
|
||||
"WHERE AU = 0 (查询没有澳大利亚用量的物料)",
|
||||
"WHERE SG < 50 (查询新加坡用量少于50的物料)"
|
||||
],
|
||||
"incorrect": [
|
||||
"WHERE VN = 'VN' (错误：VN是数值，不是字符串)",
|
||||
"WHERE JP LIKE '%JP%' (错误：JP是数值，不支持LIKE)",
|
||||
"WHERE AU IN ('AU', 'VN') (错误：AU是数值，不是枚举)"
|
||||
]
|
||||
}
|
||||
},
|
||||
|
||||
"inventory_metrics": {
|
||||
"ib": {
|
||||
"type": "bigint",
|
||||
"desc": "库存数量(Inventory Balance)",
|
||||
"query_pattern": "库存超过{值} → ib > {value}, 库存大于{值} → ib > {value}, 库存少于{值} → ib < {value}",
|
||||
"alias": ["库存", "库存量", "库存数量", "Inventory", "库存余额", "IB"]
|
||||
}
|
||||
},
|
||||
|
||||
"usage_time_series_fields": {
|
||||
"usage_qty_8_week": {
|
||||
"type": "bigint",
|
||||
"desc": "近8周的使用量",
|
||||
"alias": ["近8周用量", "近期用量", "短期用量", "8周用量", "近期使用量"]
|
||||
},
|
||||
"usage_qty_52_week": {
|
||||
"type": "bigint",
|
||||
"desc": "近52周的使用量",
|
||||
"alias": ["近52周用量", "年度用量", "长期用量", "52周用量", "年度使用量"]
|
||||
},
|
||||
"total_history_usage": {
|
||||
"type": "bigint",
|
||||
"desc": "历史总使用量",
|
||||
"alias": ["历史总用量", "总使用量", "累计用量", "历史累计", "total usage"]
|
||||
}
|
||||
}
|
||||
},
|
||||
"examples": {
|
||||
"简单查询-全部字段": {
|
||||
"user": "region为CAP的数据",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE region = 'CAP' ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户没有指定字段，默认查询所有字段。WHERE条件中使用了region字段。"
|
||||
},
|
||||
|
||||
"简单查询-基础过滤": {
|
||||
"user": "region为CAP，commodity_code为LF的数据",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE region = 'CAP' AND commodity_code = 'LF' ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户没有指定字段，默认查询所有字段。WHERE条件中使用了region和commodity_code字段。"
|
||||
},
|
||||
|
||||
"简单查询-带国家字段但不过滤": {
|
||||
"user": "region为CAP，commodity_code为LF的，country为VN的数据",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE region = 'CAP' AND commodity_code = 'LF' ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户提到'country为VN'但没有要求过滤VN用量，所以不添加VN > 0条件。默认查询所有字段。"
|
||||
},
|
||||
|
||||
"简单查询-带国家用量过滤": {
|
||||
"user": "region为CAP，commodity_code为LF的，有VN用量的数据",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE region = 'CAP' AND commodity_code = 'LF' AND VN > 0 ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户明确要求'有VN用量的'，所以添加VN > 0条件。默认查询所有字段。"
|
||||
},
|
||||
|
||||
"简单查询-指定字段": {
|
||||
"user": "查看物料号和库存数量",
|
||||
"sql": "SELECT topmost_pn, ib FROM dwd_ai.apbo_region_usage_ib_report ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户明确指定了topmost_pn和ib字段，只查询这两个字段，按用户提到的顺序排列。"
|
||||
},
|
||||
|
||||
"简单查询-多条件组合": {
|
||||
"user": "region为CAP，commodity_code为LF，库存大于500，有VN用量的数据",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE region = 'CAP' AND commodity_code = 'LF' AND ib > 500 AND VN > 0 ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户没有指定字段，默认查询所有字段。WHERE条件包含region、commodity_code、ib和VN字段的过滤。"
|
||||
},
|
||||
|
||||
"指定字段且包含WHERE字段": {
|
||||
"user": "region为CAP的物料号和库存",
|
||||
"sql": "SELECT topmost_pn, ib, region FROM dwd_ai.apbo_region_usage_ib_report WHERE region = 'CAP' ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户指定了topmost_pn和ib字段，但WHERE条件中使用了region字段，所以必须包含region字段在SELECT中。"
|
||||
},
|
||||
|
||||
"国家用量范围查询": {
|
||||
"user": "VN用量超过100且库存大于200的物料",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE VN >= 100 AND ib > 200 ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户没有指定字段，默认查询所有字段。WHERE条件包含VN和ib字段的数值范围过滤。"
|
||||
},
|
||||
|
||||
"多国家用量查询": {
|
||||
"user": "有VN用量且有AU用量的物料号",
|
||||
"sql": "SELECT topmost_pn, VN, AU FROM dwd_ai.apbo_region_usage_ib_report WHERE VN > 0 AND AU > 0 ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户指定了topmost_pn字段，并提到了VN和AU用量，所以包含这些字段。WHERE条件包含VN>0和AU>0。"
|
||||
},
|
||||
|
||||
"混合条件复杂查询": {
|
||||
"user": "region为CAP，commodity_code为LF，库存大于500，有VN用量且超过50，近期用量少于100的物料信息",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE region = 'CAP' AND commodity_code = 'LF' AND ib > 500 AND VN > 50 AND usage_qty_8_week < 100 ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户没有指定字段，默认查询所有字段。WHERE条件包含多个字段的复杂过滤。"
|
||||
},
|
||||
|
||||
"国家用量为零查询": {
|
||||
"user": "没有VN用量的物料",
|
||||
"sql": "SELECT * FROM dwd_ai.apbo_region_usage_ib_report WHERE VN = 0 ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户明确要求'没有VN用量的'，所以添加VN = 0条件。默认查询所有字段。"
|
||||
},
|
||||
|
||||
"仅查看特定国家用量": {
|
||||
"user": "查看VN和JP的用量",
|
||||
"sql": "SELECT VN, JP FROM dwd_ai.apbo_region_usage_ib_report ORDER BY ib DESC",
|
||||
"field_selection_reason": "用户明确指定了VN和JP字段，只查询这两个字段。没有WHERE条件。"
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -0,0 +1,182 @@
|
||||
{
|
||||
"meta": {
|
||||
"domain": "TP物料多重影响分析",
|
||||
"keywords": ["multiple impact", "tp物料", "物料影响", "pal_2h", "达标状态", "不达标状态", "物料分析", "TP分析", "影响分析"],
|
||||
"description": "此模型用于分析TP物料基于pal_2h状态的详细记录和统计信息。pal_2h='N'表示不达标，pal_2h='Y'表示达标。支持明细查询和统计分析两种模式，根据不同查询意图自动切换模式。",
|
||||
"data_source": "dwd_ai.apbo_tp_multiple_impact"
|
||||
},
|
||||
|
||||
"data_model_specification": {
|
||||
"fields_list": ["topmost_pn", "service_order_id", "soid", "pal_2h"],
|
||||
"mandatory_display_fields": {
|
||||
"rule1": "所有核心字段必须出现在SELECT子句中，除非用户明确指定排除。",
|
||||
"rule2": "pal_2h字段在两种模式下都必须显示",
|
||||
"rule3": "SELECT子句中字段顺序建议为：pal_2h, topmost_pn, service_order_id, soid",
|
||||
"action": "detail_mode下显示所有字段，statistical_mode下显示分组字段和统计结果"
|
||||
},
|
||||
|
||||
"optional_fields": {
|
||||
"key_fields": ["topmost_pn", "service_order_id", "soid"],
|
||||
"status_fields": ["pal_2h"],
|
||||
"grouping_fields": ["topmost_pn", "pal_2h"]
|
||||
}
|
||||
},
|
||||
|
||||
"business_logic_rules": {
|
||||
"query_recognition_rules": {
|
||||
"detail_mode_keywords": ["有哪些", "查看", "列出", "显示", "查询", "搜索", "找出", "记录", "明细", "详情", "具体"],
|
||||
"statistical_mode_keywords": ["统计", "汇总", "总数", "有多少", "数量", "count", "条数", "计数", "分组", "分布", "占比", "比例"],
|
||||
"tp_material_keywords": ["tp", "物料", "topmost_pn", "零件", "零件号", "物料号", "TP物料"],
|
||||
"order_keywords": ["订单", "so", "service_order_id", "SOID", "soid"],
|
||||
"status_keywords": ["状态", "pal_2h", "达标", "不达标", "Y", "N", "status"]
|
||||
},
|
||||
|
||||
"default_behavior": {
|
||||
"detail_mode": {
|
||||
"sorting": "默认按topmost_pn, service_order_id排序",
|
||||
"pal_2h_display": "pal_2h字段必须显示在SELECT结果中",
|
||||
"pal_2h_filter": "用户未指定状态条件时，禁止使用pal_2h过滤"
|
||||
},
|
||||
"statistical_mode": {
|
||||
"sorting": "COUNT(*) DESC",
|
||||
"limit": "禁止使用limit",
|
||||
"pal_2h_filter": "用户未指定状态条件时，禁止使用pal_2h过滤"
|
||||
},
|
||||
"alias_handling": "将用户提到的别名转换为完整字段名后再生成SQL"
|
||||
}
|
||||
},
|
||||
|
||||
"field_mapping_reference": {
|
||||
"critical_note": "注意区分detail_mode（明细查询）和statistical_mode（统计分析）两种模式，根据用户query中的关键词自动判断模式。detail_mode禁止使用聚合函数，statistical_mode必须使用聚合函数。",
|
||||
|
||||
"key_identifiers": {
|
||||
"topmost_pn": {
|
||||
"type": "varchar",
|
||||
"desc": "TP物料编号",
|
||||
"example": "02HK965",
|
||||
"required": true,
|
||||
"alias": ["tp", "物料", "物料号", "零件号", "TP物料", "零件编号", "物料编码"]
|
||||
},
|
||||
"service_order_id": {
|
||||
"type": "varchar",
|
||||
"desc": "服务订单ID",
|
||||
"example": "4020438779",
|
||||
"required": true,
|
||||
"alias": ["so", "订单", "订单号", "service_order", "订单ID", "SO", "服务订单"]
|
||||
},
|
||||
"soid": {
|
||||
"type": "varchar",
|
||||
"desc": "SOID（服务订单明细ID）",
|
||||
"example": "402043877920",
|
||||
"required": true,
|
||||
"alias": ["SOID", "子单号", "明细ID", "订单明细", "服务订单明细"]
|
||||
}
|
||||
},
|
||||
|
||||
"status_fields": {
|
||||
"pal_2h": {
|
||||
"type": "varchar(1)",
|
||||
"desc": "状态字段：'Y'表示达标，'N'表示不达标",
|
||||
"values": {
|
||||
"Y": "达标",
|
||||
"N": "不达标",
|
||||
"NULL": "无状态"
|
||||
},
|
||||
"business_rule": "用户未指定状态条件时，默认查询不达标记录（pal_2h = 'N'）",
|
||||
"alias": ["状态", "达标状态", "不达标状态", "pal_2h状态", "status", "达标标识"]
|
||||
}
|
||||
},
|
||||
|
||||
"condition_mapping": {
|
||||
"达标": "pal_2h = 'Y'",
|
||||
"不达标": "pal_2h = 'N'",
|
||||
"无状态": "pal_2h IS NULL",
|
||||
"所有状态": "pal_2h IN ('Y', 'N')",
|
||||
"有状态的": "pal_2h IN ('Y', 'N')",
|
||||
"状态完整": "pal_2h IN ('Y', 'N')"
|
||||
}
|
||||
},
|
||||
|
||||
"examples": {
|
||||
"detail_mode_examples": {
|
||||
"example1": {
|
||||
"user": "tp为02HK965的multiple impact有哪些",
|
||||
"mode": "detail_mode",
|
||||
"reason": "包含'有哪些'关键词，表示查看具体记录；未指定状态，默认查不达标",
|
||||
"sql": "SELECT pal_2h, topmost_pn, service_order_id, soid FROM dwd_ai.apbo_tp_multiple_impact WHERE topmost_pn = '02HK965' ORDER BY topmost_pn, service_order_id"
|
||||
},
|
||||
"example2": {
|
||||
"user": "查看达标的记录",
|
||||
"mode": "detail_mode",
|
||||
"reason": "包含'查看'关键词，表示查看具体记录；指定了达标状态",
|
||||
"sql": "SELECT pal_2h, topmost_pn, service_order_id, soid FROM dwd_ai.apbo_tp_multiple_impact WHERE ORDER BY topmost_pn, service_order_id"
|
||||
},
|
||||
"example3": {
|
||||
"user": "列出topmost_pn为02HK965的记录",
|
||||
"mode": "detail_mode",
|
||||
"reason": "包含'列出'关键词，表示查看具体记录；未指定状态，默认查不达标",
|
||||
"sql": "SELECT pal_2h, topmost_pn, service_order_id, soid FROM dwd_ai.apbo_tp_multiple_impact WHERE topmost_pn = '02HK965' ORDER BY topmost_pn, service_order_id"
|
||||
},
|
||||
"example4": {
|
||||
"user": "查询订单4020438779的TP物料影响",
|
||||
"mode": "detail_mode",
|
||||
"reason": "包含'查询'关键词，表示查看具体记录；未指定状态，默认查不达标",
|
||||
"sql": "SELECT pal_2h, topmost_pn, service_order_id, soid FROM dwd_ai.apbo_tp_multiple_impact WHERE service_order_id = '4020438779' ORDER BY topmost_pn, soid"
|
||||
}
|
||||
},
|
||||
|
||||
"statistical_mode_examples": {
|
||||
"example1": {
|
||||
"user": "统计不同状态的物料数量",
|
||||
"mode": "statistical_mode",
|
||||
"reason": "包含'统计'关键词，表示统计数量；统计不同状态，需要显示所有状态",
|
||||
"sql": "SELECT pal_2h, COUNT(topmost_pn) AS topmost_pn_count FROM dwd_ai.apbo_tp_multiple_impact GROUP BY pal_2h ORDER BY topmost_pn_count DESC"
|
||||
},
|
||||
"example2": {
|
||||
"user": "按topmost_pn分组统计每个物料的记录数",
|
||||
"mode": "statistical_mode",
|
||||
"reason": "包含'统计'和'分组'关键词；未指定状态，默认只统计不达标",
|
||||
"sql": "SELECT topmost_pn, pal_2h, COUNT(*) AS count FROM dwd_ai.apbo_tp_multiple_impact GROUP BY topmost_pn, pal_2h ORDER BY count DESC"
|
||||
},
|
||||
"example3": {
|
||||
"user": "汇总各TP物料的影响分布",
|
||||
"mode": "statistical_mode",
|
||||
"reason": "包含'汇总'关键词，表示统计分布；未指定状态，默认只统计不达标",
|
||||
"sql": "SELECT topmost_pn, COUNT(*) AS record_count FROM dwd_ai.apbo_tp_multiple_impact GROUP BY topmost_pn ORDER BY record_count DESC"
|
||||
}
|
||||
},
|
||||
|
||||
"edge_cases": {
|
||||
"example1": {
|
||||
"user": "有多少条tp为02HK965的记录",
|
||||
"mode": "statistical_mode",
|
||||
"reason": "包含'有多少'关键词，虽然指定了具体物料，但目的是获取数量；未指定状态，默认只统计不达标",
|
||||
"sql": "SELECT COUNT(*) AS count FROM dwd_ai.apbo_tp_multiple_impact WHERE topmost_pn = '02HK965'"
|
||||
},
|
||||
"example2": {
|
||||
"user": "显示所有状态为达标和不达标的记录",
|
||||
"mode": "detail_mode",
|
||||
"reason": "包含'显示'关键词，表示查看具体记录；明确要求查看两种状态，不使用默认值",
|
||||
"sql": "SELECT pal_2h, topmost_pn, service_order_id, soid FROM dwd_ai.apbo_tp_multiple_impact ORDER BY topmost_pn, service_order_id"
|
||||
},
|
||||
"example3": {
|
||||
"user": "统计状态为NULL的记录数量",
|
||||
"mode": "statistical_mode",
|
||||
"reason": "包含'统计'关键词，表示统计数量；明确指定NULL状态，不使用默认值",
|
||||
"sql": "SELECT COUNT(*) AS count FROM dwd_ai.apbo_tp_multiple_impact WHERE pal_2h IS NULL"
|
||||
},
|
||||
"example4": {
|
||||
"user": "查看所有状态的记录详情",
|
||||
"mode": "detail_mode",
|
||||
"reason": "包含'查看'和'详情'关键词，表示查看具体记录；要求所有状态，不使用默认值",
|
||||
"sql": "SELECT pal_2h, topmost_pn, service_order_id, soid FROM dwd_ai.apbo_tp_multiple_impact OR pal_2h IS NULL ORDER BY pal_2h, topmost_pn, service_order_id"
|
||||
},
|
||||
"example5": {
|
||||
"user": "统计每个TP物料的不同状态数量",
|
||||
"mode": "statistical_mode",
|
||||
"reason": "包含'统计'关键词，表示统计分析；统计每个物料的各状态分布",
|
||||
"sql": "SELECT topmost_pn, pal_2h, COUNT(*) AS count FROM dwd_ai.apbo_tp_multiple_impact GROUP BY topmost_pn, pal_2h ORDER BY topmost_pn, pal_2h"
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -1,10 +0,0 @@
|
||||
{
|
||||
"table": "example_table",
|
||||
"description": "示例表模型提示词",
|
||||
"system_prompt": "You are an expert SQL generator.",
|
||||
"business_prompt": "Generate SQL for example_table based on the user's intent.",
|
||||
"constraints": [
|
||||
"Use only fields defined in this table.",
|
||||
"Return only SQL without explanations."
|
||||
]
|
||||
}
|
||||
@@ -16,9 +16,31 @@
|
||||
"work order information",
|
||||
"recovery ETA",
|
||||
"history order",
|
||||
"Warranty type"
|
||||
"Warranty type",
|
||||
"category"
|
||||
],
|
||||
"x_table_name": [
|
||||
"xx"
|
||||
"apbo_milestone_info": [
|
||||
"GR or POD",
|
||||
"POD",
|
||||
"GR",
|
||||
"milestone status",
|
||||
"milestone",
|
||||
"物流节点",
|
||||
"shipment tracking",
|
||||
"里程碑",
|
||||
"节点明细"
|
||||
],
|
||||
"apbo_hic_ssoc_consumption": [
|
||||
"consumption消耗记录",
|
||||
"consumption order"
|
||||
],
|
||||
"apbo_tp_multiple_impact": [
|
||||
"multiple impact orders",
|
||||
"不达标的multiple impact",
|
||||
"multiple impact status"
|
||||
],
|
||||
"apbo_region_usage_ib_report": [
|
||||
"ib",
|
||||
"usage"
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,35 @@
|
||||
apiVersion: apps/v1
|
||||
kind: Deployment
|
||||
metadata:
|
||||
name: more_dots
|
||||
namespace: default
|
||||
spec:
|
||||
replicas: 2
|
||||
selector:
|
||||
matchLabels:
|
||||
app: more_dots
|
||||
template:
|
||||
metadata:
|
||||
labels:
|
||||
app: more_dots
|
||||
spec:
|
||||
containers:
|
||||
- name: more_dots
|
||||
image: harbor.yourdomain.com/library/more_dots:${IMAGE_TAG}
|
||||
ports:
|
||||
- containerPort: 8000
|
||||
env:
|
||||
- name: ENVIRONMENT
|
||||
value: ${DEPLOY_ENV}
|
||||
---
|
||||
apiVersion: v1
|
||||
kind: Service
|
||||
metadata:
|
||||
name: more_dots-service
|
||||
spec:
|
||||
selector:
|
||||
app: more_dots
|
||||
ports:
|
||||
- port: 80
|
||||
targetPort: 8000
|
||||
type: ClusterIP
|
||||
+3
-1
@@ -5,6 +5,8 @@ langchain-openai>=1.1.6
|
||||
pydantic>=2.0.0
|
||||
fastapi>=0.110.0
|
||||
uvicorn>=0.30.0
|
||||
nacos-sdk-python>=2.0.9
|
||||
nacos-sdk-python==2.0.9
|
||||
httpx>=0.27.0
|
||||
pyyaml>=6.0.1
|
||||
redis>=5.0.0
|
||||
pymysql>=1.1.1
|
||||
|
||||
@@ -0,0 +1,13 @@
|
||||
from pydantic import BaseModel
|
||||
|
||||
|
||||
class ChatMessageResponseDTO(BaseModel):
|
||||
"""流式消息响应模型"""
|
||||
|
||||
id: str
|
||||
event: str = "message"
|
||||
task_id: str
|
||||
message_id: str
|
||||
conversation_id: str
|
||||
answer: str
|
||||
created_at: int
|
||||
@@ -0,0 +1,139 @@
|
||||
import json
|
||||
import sys
|
||||
from typing import Any, Dict, List
|
||||
|
||||
import httpx
|
||||
|
||||
from config import Config
|
||||
|
||||
|
||||
def _base_url() -> str:
|
||||
app = Config.get_section("app")
|
||||
host = app.get("host", "127.0.0.1")
|
||||
port = app.get("port", "8000")
|
||||
if host in ("0.0.0.0", "::"):
|
||||
host = "127.0.0.1"
|
||||
return f"http://{host}:{port}"
|
||||
|
||||
|
||||
def _post(client: httpx.Client, url: str, payload: Dict[str, Any]) -> None:
|
||||
resp = client.post(url, json=payload)
|
||||
print(f"POST {url} -> {resp.status_code}")
|
||||
print(resp.text)
|
||||
|
||||
|
||||
def _put(client: httpx.Client, url: str, payload: Dict[str, Any]) -> None:
|
||||
resp = client.put(url, json=payload)
|
||||
print(f"PUT {url} -> {resp.status_code}")
|
||||
print(resp.text)
|
||||
|
||||
|
||||
def _get(client: httpx.Client, url: str) -> None:
|
||||
resp = client.get(url)
|
||||
print(f"GET {url} -> {resp.status_code}")
|
||||
print(resp.text)
|
||||
|
||||
|
||||
def _stream_sse(client: httpx.Client, url: str, payload: Dict[str, Any]) -> None:
|
||||
with client.stream("POST", url, json=payload) as resp:
|
||||
print(f"POST {url} -> {resp.status_code}")
|
||||
current_event = "message"
|
||||
for raw in resp.iter_lines():
|
||||
if raw is None:
|
||||
continue
|
||||
line = raw.strip()
|
||||
if not line:
|
||||
continue
|
||||
if line.startswith("event:"):
|
||||
current_event = line.split(":", 1)[1].strip() or "message"
|
||||
continue
|
||||
if line.startswith("data:"):
|
||||
data = line.split(":", 1)[1].strip()
|
||||
print(f"[{current_event}] {data}")
|
||||
|
||||
|
||||
def main() -> None:
|
||||
base = _base_url()
|
||||
menu: List[str] = [
|
||||
"1) GET /health",
|
||||
"2) GET /nacos/status",
|
||||
"3) POST /api/workflows (conversation)",
|
||||
"4) POST /api/workflows/stream (conversation)",
|
||||
"5) POST /api/sql/generate",
|
||||
"6) POST /api/tools/execute",
|
||||
"7) POST /api/prompts/reload",
|
||||
"8) POST /api/ragflow/table-retrieval/upload",
|
||||
"9) PUT /api/ragflow/table-retrieval/update",
|
||||
"10) POST /api/ragflow/sql-gen/upload",
|
||||
"11) PUT /api/ragflow/sql-gen/update",
|
||||
"0) Exit",
|
||||
]
|
||||
|
||||
with httpx.Client(timeout=60) as client:
|
||||
while True:
|
||||
print("\n可用接口：")
|
||||
for line in menu:
|
||||
print(line)
|
||||
|
||||
choice = input("\n请选择编号: ").strip()
|
||||
if choice == "0":
|
||||
break
|
||||
|
||||
if choice == "1":
|
||||
_get(client, f"{base}/health")
|
||||
elif choice == "2":
|
||||
_get(client, f"{base}/nacos/status")
|
||||
elif choice == "3":
|
||||
payload = {
|
||||
"input": "查询 SO 4020438779 的 eta 信息",
|
||||
"session_id": None,
|
||||
"workflow_type": "conversation",
|
||||
}
|
||||
_post(client, f"{base}/api/workflows", payload)
|
||||
elif choice == "4":
|
||||
payload = {
|
||||
"input": "查询 SO 4016769041 的 eta 信息",
|
||||
"session_id": None,
|
||||
"workflow_type": "conversation",
|
||||
}
|
||||
_stream_sse(client, f"{base}/api/workflows/stream", payload)
|
||||
elif choice == "5":
|
||||
payload = {
|
||||
"input": "查询 SO 4020438779 的 eta 信息",
|
||||
"session_id": None,
|
||||
"workflow_type": "conversation",
|
||||
}
|
||||
_post(client, f"{base}/api/sql/generate", payload)
|
||||
elif choice == "6":
|
||||
payload = {
|
||||
"tool_name": "sr_api_query",
|
||||
"payload": {
|
||||
"sql": "SELECT 1",
|
||||
"page": 1,
|
||||
"rows": 1,
|
||||
"orderBySelect": True,
|
||||
"timeout": 30,
|
||||
},
|
||||
}
|
||||
_post(client, f"{base}/api/tools/execute", payload)
|
||||
elif choice == "7":
|
||||
_post(client, f"{base}/api/prompts/reload", {})
|
||||
elif choice == "8":
|
||||
_post(client, f"{base}/api/ragflow/table-retrieval/upload", {})
|
||||
elif choice == "9":
|
||||
cfg = {"name": "table_retrieval_dataset"}
|
||||
_put(client, f"{base}/api/ragflow/table-retrieval/update", cfg)
|
||||
elif choice == "10":
|
||||
_post(client, f"{base}/api/ragflow/sql-gen/upload", {})
|
||||
elif choice == "11":
|
||||
cfg = {"name": "sql_gen_dataset"}
|
||||
_put(client, f"{base}/api/ragflow/sql-gen/update", cfg)
|
||||
else:
|
||||
print("无效选择")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
try:
|
||||
main()
|
||||
except KeyboardInterrupt:
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,30 @@
|
||||
from __future__ import annotations
|
||||
|
||||
from dataclasses import dataclass
|
||||
from enum import Enum
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
|
||||
class ErrorCode(str, Enum):
|
||||
INVALID_WORKFLOW_TYPE = "INVALID_WORKFLOW_TYPE"
|
||||
SQL_GENERATION_FAILED = "SQL_GENERATION_FAILED"
|
||||
TABLE_MATCH_FAILED = "TABLE_MATCH_FAILED"
|
||||
SQL_EXECUTION_FAILED = "SQL_EXECUTION_FAILED"
|
||||
RAGFLOW_RETRIEVE_FAILED = "RAGFLOW_RETRIEVE_FAILED"
|
||||
CONFIG_INVALID = "CONFIG_INVALID"
|
||||
INTERNAL_ERROR = "INTERNAL_ERROR"
|
||||
|
||||
|
||||
@dataclass
|
||||
class AppError(Exception):
|
||||
code: ErrorCode
|
||||
message: str
|
||||
status_code: int = 500
|
||||
detail: Optional[Dict[str, Any]] = None
|
||||
|
||||
def to_dict(self) -> Dict[str, Any]:
|
||||
return {
|
||||
"code": self.code.value,
|
||||
"message": self.message,
|
||||
"detail": self.detail or {},
|
||||
}
|
||||
@@ -2,6 +2,11 @@ from __future__ import annotations
|
||||
|
||||
from typing import Optional
|
||||
|
||||
try:
|
||||
import redis
|
||||
except Exception:
|
||||
redis = None
|
||||
|
||||
|
||||
class CacheBase:
|
||||
"""缓存接口"""
|
||||
@@ -23,3 +28,18 @@ class NoopCache(CacheBase):
|
||||
return None
|
||||
|
||||
|
||||
class RedisCache(CacheBase):
|
||||
"""Redis 缓存实现"""
|
||||
|
||||
def __init__(self, url: str, db: int = 0):
|
||||
if redis is None:
|
||||
raise ImportError("未安装 redis 依赖")
|
||||
self._client = redis.Redis.from_url(url, db=db, decode_responses=True)
|
||||
|
||||
def get(self, key: str) -> Optional[str]:
|
||||
return self._client.get(key)
|
||||
|
||||
def set(self, key: str, value: str, ttl: int) -> None:
|
||||
self._client.set(key, value, ex=ttl)
|
||||
|
||||
|
||||
|
||||
@@ -20,6 +20,15 @@ class RagflowClient:
|
||||
def _build_url(self) -> str:
|
||||
return self._base_url.rstrip("/") + "/" + self._retrieval_path.lstrip("/")
|
||||
|
||||
@staticmethod
|
||||
def _normalize_dataset_ids(dataset_id: Optional[str]) -> list[str]:
|
||||
"""将配置值规范化为 RAGFlow 需要的 list[string]"""
|
||||
if not dataset_id:
|
||||
return []
|
||||
# 兼容逗号分隔配置
|
||||
parts = [p.strip() for p in str(dataset_id).split(",") if p.strip()]
|
||||
return parts
|
||||
|
||||
def retrieve(self, query: str, top_k: int = 3, dataset_id: Optional[str] = None, document_ids: Optional[str] = None) -> Dict[str, Any]:
|
||||
"""检索匹配文档"""
|
||||
if not self._base_url or not self._retrieval_path:
|
||||
@@ -29,10 +38,12 @@ class RagflowClient:
|
||||
url = self._build_url()
|
||||
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
||||
payload = {
|
||||
"dataset_ids": dataset_id or "",
|
||||
"query": query,
|
||||
"dataset_ids": self._normalize_dataset_ids(dataset_id),
|
||||
"question": query,
|
||||
"top_k": top_k,
|
||||
}
|
||||
# 兼容部分版本字段
|
||||
payload["query"] = query
|
||||
if document_ids:
|
||||
payload["document_ids"] = document_ids
|
||||
|
||||
@@ -57,6 +68,17 @@ def extract_table_name(record: Dict[str, Any]) -> Optional[str]:
|
||||
return record.get(key)
|
||||
|
||||
content = record.get("content") or record.get("text") or ""
|
||||
|
||||
# 兼容 content 为 JSON 字符串：{"table":"xxx", ...}
|
||||
try:
|
||||
parsed = json.loads(str(content))
|
||||
if isinstance(parsed, dict):
|
||||
for key in ("table", "table_name"):
|
||||
if parsed.get(key):
|
||||
return str(parsed.get(key))
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
for line in str(content).splitlines():
|
||||
if line.lower().startswith("table:"):
|
||||
return line.split(":", 1)[1].strip()
|
||||
|
||||
+267
-177
@@ -7,45 +7,18 @@ import httpx
|
||||
from config import Config
|
||||
|
||||
|
||||
def _build_document_for_table(table: str, templates: List[str]) -> str:
|
||||
"""构建表名检索文档 - 使用更标准的格式"""
|
||||
lines = [
|
||||
f"# 表名检索模板: {table}",
|
||||
"",
|
||||
"## 可用模板:",
|
||||
""
|
||||
]
|
||||
for i, t in enumerate(templates, 1):
|
||||
lines.append(f"{i}. {t}")
|
||||
lines.extend(["", f"表名: {table}", "类型: 表名检索模板"])
|
||||
return "\n".join(lines)
|
||||
def _dump_json_content(data: Dict[str, Any]) -> str:
|
||||
return json.dumps(data, ensure_ascii=False, indent=2)
|
||||
|
||||
|
||||
def _build_sql_gen_document(table: str, prompt: Dict[str, any]) -> str:
|
||||
"""构建 SQL 生成文档 - 使用更标准的格式"""
|
||||
system_prompt = prompt.get("system_prompt", "")
|
||||
business_prompt = prompt.get("business_prompt", "")
|
||||
constraints = prompt.get("constraints", [])
|
||||
|
||||
lines = [
|
||||
f"# SQL 生成提示词: {table}",
|
||||
"",
|
||||
"## 系统提示词:",
|
||||
system_prompt,
|
||||
"",
|
||||
"## 业务提示词:",
|
||||
business_prompt,
|
||||
""
|
||||
]
|
||||
|
||||
if constraints:
|
||||
lines.extend(["## 约束条件:", ""])
|
||||
for i, c in enumerate(constraints, 1):
|
||||
lines.append(f"{i}. {c}")
|
||||
lines.append("")
|
||||
|
||||
lines.extend([f"表名: {table}", "类型: SQL 生成提示词"])
|
||||
return "\n".join(lines)
|
||||
def _extract_tables_map(data: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""兼容两种结构：{"tables": {...}} 或直接 {...}"""
|
||||
tables = data.get("tables") if isinstance(data, dict) else None
|
||||
if isinstance(tables, dict):
|
||||
return tables
|
||||
if isinstance(data, dict):
|
||||
return data
|
||||
return {}
|
||||
|
||||
|
||||
class RagflowSync:
|
||||
@@ -58,143 +31,271 @@ class RagflowSync:
|
||||
self._table_retrieval_dataset_id = (cfg.get("table_retrieval_dataset_id") or "").strip()
|
||||
self._sql_gen_dataset_id = (cfg.get("sql_gen_dataset_id") or "").strip()
|
||||
|
||||
def _validate_common(self) -> None:
|
||||
if not self._base_url:
|
||||
raise RuntimeError("未配置 ragflow.url")
|
||||
if not self._upload_path:
|
||||
raise RuntimeError("未配置 ragflow.upload 上传接口，请在 config/config.ini 中设置")
|
||||
if "{dataset_id}" not in self._upload_path:
|
||||
raise RuntimeError("上传接口路径必须包含 {dataset_id} 占位符")
|
||||
if self._upload_mode not in ("overwrite", "append"):
|
||||
raise RuntimeError("ragflow.upload_mode 仅支持 overwrite 或 append")
|
||||
|
||||
def _post(self, documents: List[Dict[str, Any]], dataset_id: str):
|
||||
"""上传文档到指定知识库 - 使用 multipart/form-data 格式"""
|
||||
if not self._base_url:
|
||||
raise RuntimeError("未配置 ragflow.url")
|
||||
|
||||
# 构建正确的 URL
|
||||
upload_path = self._upload_path.replace("{dataset_id}", dataset_id)
|
||||
url = self._base_url + "/" + upload_path.lstrip("/")
|
||||
|
||||
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
||||
|
||||
# 由于接口使用 multipart/form-data，我们需要创建临时文件
|
||||
import tempfile
|
||||
|
||||
# 创建临时文件并写入文档内容
|
||||
with tempfile.NamedTemporaryFile(mode='w', suffix='.txt', delete=False, encoding='utf-8') as f:
|
||||
# 将文档内容写入文件
|
||||
for doc in documents:
|
||||
content = doc.get('content', '')
|
||||
f.write(content + '\n\n')
|
||||
temp_file_path = f.name
|
||||
|
||||
try:
|
||||
# 使用 multipart/form-data 上传文件
|
||||
files = {'file': open(temp_file_path, 'rb')}
|
||||
|
||||
print(f"请求 URL: {url}") # 调试信息
|
||||
print(f"上传文件: {temp_file_path}") # 调试信息
|
||||
|
||||
with httpx.Client(timeout=60) as client:
|
||||
response = client.post(url, files=files, headers=headers)
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
print(f"RAGFlow 上传响应: {result}") # 调试信息
|
||||
return result
|
||||
finally:
|
||||
# 清理临时文件
|
||||
import os
|
||||
if os.path.exists(temp_file_path):
|
||||
os.unlink(temp_file_path)
|
||||
|
||||
def upload_documents(self, dataset_id: str, documents: List[Dict[str, Any]]) -> Dict[str, Any]:
|
||||
"""上传文档到指定知识库 - 使用 multipart/form-data 格式
|
||||
|
||||
根据官方文档: POST /api/v1/datasets/{dataset_id}/documents
|
||||
"""
|
||||
"""上传文档到指定知识库（每个文档单独上传）"""
|
||||
if not self._base_url:
|
||||
raise RuntimeError("未配置 ragflow.url")
|
||||
if not dataset_id:
|
||||
raise RuntimeError("dataset_id 为空，无法上传文档")
|
||||
if not documents:
|
||||
raise RuntimeError("没有可上传的文档内容")
|
||||
|
||||
# 构建正确的 URL
|
||||
url = f"{self._base_url}/api/v1/datasets/{dataset_id}/documents"
|
||||
|
||||
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
||||
|
||||
# 由于接口使用 multipart/form-data，我们需要创建临时文件
|
||||
import tempfile
|
||||
import os
|
||||
|
||||
# 创建临时文件并写入文档内容
|
||||
with tempfile.NamedTemporaryFile(mode='w', suffix='.txt', delete=False, encoding='utf-8') as f:
|
||||
# 将文档内容写入文件
|
||||
for doc in documents:
|
||||
content = doc.get('content', '')
|
||||
f.write(content + '\n\n')
|
||||
temp_file_path = f.name
|
||||
|
||||
try:
|
||||
# 使用 multipart/form-data 上传文件
|
||||
# 确保文件在 with 块内打开和关闭
|
||||
with open(temp_file_path, 'rb') as file_obj:
|
||||
files = {'file': file_obj}
|
||||
|
||||
print(f"上传文档 URL: {url}") # 调试信息
|
||||
print(f"上传文件: {temp_file_path}") # 调试信息
|
||||
|
||||
results: List[Dict[str, Any]] = []
|
||||
with httpx.Client(timeout=60) as client:
|
||||
for idx, doc in enumerate(documents, start=1):
|
||||
content = str(doc.get("content", ""))
|
||||
filename = str(doc.get("filename") or f"doc_{idx}.txt")
|
||||
files = {"file": (filename, content.encode("utf-8"), "text/plain")}
|
||||
|
||||
print(f"上传文档 URL: {url}")
|
||||
print(f"上传文件名: {filename}")
|
||||
|
||||
response = client.post(url, files=files, headers=headers)
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
print(f"RAGFlow 上传响应: {result}") # 调试信息
|
||||
print(f"RAGFlow 上传响应: {result}")
|
||||
results.append(result)
|
||||
|
||||
# 检查文档处理状态
|
||||
if result.get('code') == 0 and result.get('data'):
|
||||
doc_id = result['data'][0].get('id')
|
||||
if doc_id:
|
||||
print(f"文档已上传，ID: {doc_id}")
|
||||
print("注意: 文档处理需要时间，请等待 RAGFlow 完成分块处理")
|
||||
print("可以在 RAGFlow 界面查看处理进度")
|
||||
dataset_detail = self._get_dataset_detail(dataset_id)
|
||||
chunk_method = self._extract_chunk_method(dataset_detail)
|
||||
if chunk_method is None:
|
||||
chunk_method = self._extract_chunk_method_from_upload_results(results)
|
||||
# 参考 Java 实现：查询知识库文档 ID 后统一调用 chunks 解析
|
||||
doc_ids = self._list_document_ids(dataset_id)
|
||||
parse_results = self._auto_parse_documents(dataset_id, doc_ids)
|
||||
upload_status = self._build_parse_status_from_upload_results(results)
|
||||
|
||||
return result
|
||||
finally:
|
||||
# 清理临时文件
|
||||
if os.path.exists(temp_file_path):
|
||||
try:
|
||||
os.unlink(temp_file_path)
|
||||
except PermissionError:
|
||||
# 如果文件被占用，等待一下再重试
|
||||
import time
|
||||
time.sleep(0.1)
|
||||
try:
|
||||
os.unlink(temp_file_path)
|
||||
except PermissionError:
|
||||
print(f"警告: 无法删除临时文件 {temp_file_path}")
|
||||
|
||||
def update_dataset(self, dataset_id: str, config: Dict[str, Any]) -> Dict[str, Any]:
|
||||
"""更新知识库配置
|
||||
|
||||
根据官方文档: PUT /api/v1/datasets/{dataset_id}
|
||||
"""
|
||||
if not self._base_url:
|
||||
raise RuntimeError("未配置 ragflow.url")
|
||||
|
||||
url = f"{self._base_url}/api/v1/datasets/{dataset_id}"
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {self._api_key}" if self._api_key else ""
|
||||
return {
|
||||
"ok": True,
|
||||
"count": len(results),
|
||||
"results": results,
|
||||
"chunk_method": chunk_method,
|
||||
"upload_status": upload_status,
|
||||
"parse": parse_results,
|
||||
}
|
||||
|
||||
print(f"更新知识库 URL: {url}") # 调试信息
|
||||
print(f"更新配置: {config}") # 调试信息
|
||||
def _get_dataset_detail(self, dataset_id: str) -> Dict[str, Any]:
|
||||
"""查询知识库详情（用于读取 chunk_method）"""
|
||||
url = f"{self._base_url}/api/v1/datasets/{dataset_id}"
|
||||
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
||||
with httpx.Client(timeout=30) as client:
|
||||
resp = client.get(url, headers=headers)
|
||||
resp.raise_for_status()
|
||||
return resp.json()
|
||||
|
||||
@staticmethod
|
||||
def _extract_chunk_method(dataset_detail: Dict[str, Any]) -> Any:
|
||||
"""从知识库详情提取 chunk_method"""
|
||||
data = dataset_detail.get("data")
|
||||
if isinstance(data, dict):
|
||||
if "chunk_method" in data:
|
||||
return data.get("chunk_method")
|
||||
parser_cfg = data.get("parser_config") or {}
|
||||
if isinstance(parser_cfg, dict):
|
||||
return parser_cfg.get("chunk_method")
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def _extract_chunk_method_from_upload_results(upload_results: List[Dict[str, Any]]) -> Any:
|
||||
"""从上传响应中提取 chunk_method（兼容不同版本返回结构）"""
|
||||
for item in upload_results:
|
||||
data = item.get("data")
|
||||
records = data if isinstance(data, list) else [data] if isinstance(data, dict) else []
|
||||
for rec in records:
|
||||
if not isinstance(rec, dict):
|
||||
continue
|
||||
if rec.get("chunk_method"):
|
||||
return rec.get("chunk_method")
|
||||
parser_cfg = rec.get("parser_config") or {}
|
||||
if isinstance(parser_cfg, dict) and parser_cfg.get("chunk_method"):
|
||||
return parser_cfg.get("chunk_method")
|
||||
return None
|
||||
|
||||
@staticmethod
|
||||
def _extract_uploaded_doc_ids(upload_results: List[Dict[str, Any]]) -> List[str]:
|
||||
"""从上传结果中提取文档 ID"""
|
||||
ids: List[str] = []
|
||||
for item in upload_results:
|
||||
data = item.get("data")
|
||||
if isinstance(data, list):
|
||||
for d in data:
|
||||
if isinstance(d, dict) and d.get("id"):
|
||||
ids.append(str(d.get("id")))
|
||||
elif isinstance(data, dict) and data.get("id"):
|
||||
ids.append(str(data.get("id")))
|
||||
return ids
|
||||
|
||||
@staticmethod
|
||||
def _build_parse_status_from_upload_results(upload_results: List[Dict[str, Any]]) -> Dict[str, Any]:
|
||||
"""根据上传返回构造解析状态（上传接口已触发解析，无需额外 parse API）"""
|
||||
details: List[Dict[str, Any]] = []
|
||||
for item in upload_results:
|
||||
data = item.get("data")
|
||||
records = data if isinstance(data, list) else [data] if isinstance(data, dict) else []
|
||||
for rec in records:
|
||||
if not isinstance(rec, dict):
|
||||
continue
|
||||
details.append(
|
||||
{
|
||||
"doc_id": rec.get("id"),
|
||||
"name": rec.get("name") or rec.get("location"),
|
||||
"run": rec.get("run"),
|
||||
"chunk_method": rec.get("chunk_method")
|
||||
or (rec.get("parser_config") or {}).get("chunk_method"),
|
||||
}
|
||||
)
|
||||
return {
|
||||
"ok": True,
|
||||
"trigger": "upload_endpoint",
|
||||
"message": "文档上传接口已触发解析流程，无需单独调用 parse API",
|
||||
"count": len(details),
|
||||
"details": details,
|
||||
}
|
||||
|
||||
def _auto_parse_documents(self, dataset_id: str, doc_ids: List[str]) -> Dict[str, Any]:
|
||||
"""调用官方 chunks 接口触发解析"""
|
||||
if not doc_ids:
|
||||
return {"ok": False, "message": "未提取到文档ID，无法触发解析", "count": 0, "details": []}
|
||||
|
||||
url = f"{self._base_url}/api/v1/datasets/{dataset_id}/chunks"
|
||||
headers = {
|
||||
"Content-Type": "application/json",
|
||||
"Authorization": f"Bearer {self._api_key}",
|
||||
} if self._api_key else {"Content-Type": "application/json"}
|
||||
payload = {"document_ids": doc_ids}
|
||||
|
||||
with httpx.Client(timeout=60) as client:
|
||||
response = client.put(url, json=config, headers=headers)
|
||||
response.raise_for_status()
|
||||
result = response.json()
|
||||
print(f"RAGFlow 更新响应: {result}") # 调试信息
|
||||
return result
|
||||
resp = client.post(url, headers=headers, json=payload)
|
||||
|
||||
if resp.status_code >= 400:
|
||||
return {
|
||||
"ok": False,
|
||||
"trigger": "chunks_api",
|
||||
"status": resp.status_code,
|
||||
"message": resp.text,
|
||||
"count": len(doc_ids),
|
||||
"details": [{"doc_id": d} for d in doc_ids],
|
||||
}
|
||||
|
||||
body: Any
|
||||
try:
|
||||
body = resp.json()
|
||||
except Exception:
|
||||
body = resp.text
|
||||
|
||||
return {
|
||||
"ok": True,
|
||||
"trigger": "chunks_api",
|
||||
"count": len(doc_ids),
|
||||
"details": [{"doc_id": d} for d in doc_ids],
|
||||
"response": body,
|
||||
}
|
||||
|
||||
def _list_document_ids(self, dataset_id: str) -> List[str]:
|
||||
"""获取知识库中的全部文档 ID（用于覆盖更新）"""
|
||||
if not self._base_url:
|
||||
raise RuntimeError("未配置 ragflow.url")
|
||||
if not dataset_id:
|
||||
raise RuntimeError("dataset_id 为空，无法查询文档")
|
||||
|
||||
url = f"{self._base_url}/api/v1/datasets/{dataset_id}/documents"
|
||||
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
||||
|
||||
ids: List[str] = []
|
||||
page = 1
|
||||
page_size = 100
|
||||
|
||||
with httpx.Client(timeout=60) as client:
|
||||
while True:
|
||||
resp = client.get(url, headers=headers, params={"page": page, "page_size": page_size})
|
||||
resp.raise_for_status()
|
||||
body = resp.json()
|
||||
data = body.get("data")
|
||||
if isinstance(data, dict):
|
||||
docs = data.get("docs") or data.get("list") or []
|
||||
elif isinstance(data, list):
|
||||
docs = data
|
||||
else:
|
||||
docs = []
|
||||
|
||||
if not docs:
|
||||
break
|
||||
|
||||
for item in docs:
|
||||
if isinstance(item, dict) and item.get("id"):
|
||||
ids.append(str(item.get("id")))
|
||||
|
||||
if len(docs) < page_size:
|
||||
break
|
||||
page += 1
|
||||
|
||||
return ids
|
||||
|
||||
def _delete_documents(self, dataset_id: str, doc_ids: List[str]) -> Dict[str, Any]:
|
||||
"""按 ID 删除文档"""
|
||||
if not doc_ids:
|
||||
return {"ok": True, "deleted": 0}
|
||||
|
||||
url = f"{self._base_url}/api/v1/datasets/{dataset_id}/documents"
|
||||
headers = {"Authorization": f"Bearer {self._api_key}"} if self._api_key else {}
|
||||
payload = {"ids": doc_ids}
|
||||
|
||||
with httpx.Client(timeout=60) as client:
|
||||
resp = client.request("DELETE", url, headers=headers, json=payload)
|
||||
resp.raise_for_status()
|
||||
return resp.json()
|
||||
|
||||
def replace_documents(self, dataset_id: str, documents: List[Dict[str, Any]]) -> Dict[str, Any]:
|
||||
"""覆盖更新：先删后传，避免“update 变新增”"""
|
||||
ids = self._list_document_ids(dataset_id)
|
||||
if ids:
|
||||
self._delete_documents(dataset_id, ids)
|
||||
return self.upload_documents(dataset_id, documents)
|
||||
|
||||
def update_table_retrieval_documents(self) -> Dict[str, Any]:
|
||||
"""更新表名检索文档（仅文档内容）"""
|
||||
if not self._table_retrieval_dataset_id:
|
||||
raise RuntimeError("未配置 ragflow.table_retrieval_dataset_id，无法更新表名检索文档")
|
||||
|
||||
root = os.path.dirname(os.path.dirname(__file__))
|
||||
tables_file = os.path.join(root, "config", "table_retrieval_prompts", "tables.json")
|
||||
with open(tables_file, "r", encoding="utf-8") as f:
|
||||
data = json.load(f)
|
||||
|
||||
tables = _extract_tables_map(data)
|
||||
documents = [
|
||||
{
|
||||
"filename": f"{k}.txt",
|
||||
"content": _dump_json_content({"table": k, "templates": v}),
|
||||
}
|
||||
for k, v in tables.items()
|
||||
]
|
||||
return self.replace_documents(self._table_retrieval_dataset_id, documents)
|
||||
|
||||
def update_sql_gen_documents(self) -> Dict[str, Any]:
|
||||
"""更新 SQL 生成文档（仅文档内容）"""
|
||||
if not self._sql_gen_dataset_id:
|
||||
raise RuntimeError("未配置 ragflow.sql_gen_dataset_id，无法更新 SQL 生成文档")
|
||||
|
||||
root = os.path.dirname(os.path.dirname(__file__))
|
||||
prompts_dir = os.path.join(root, "config", "sql_gen_prompts")
|
||||
documents: List[Dict[str, Any]] = []
|
||||
|
||||
for name in os.listdir(prompts_dir):
|
||||
if not name.endswith(".json"):
|
||||
continue
|
||||
path = os.path.join(prompts_dir, name)
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
prompt = json.load(f)
|
||||
table = prompt.get("table") or os.path.splitext(name)[0]
|
||||
documents.append({"filename": f"{table}.txt", "content": _dump_json_content(prompt)})
|
||||
|
||||
return self.replace_documents(self._sql_gen_dataset_id, documents)
|
||||
|
||||
def upload_table_retrieval(self) -> Dict[str, Any]:
|
||||
"""上传表名检索模板文档 - 直接上传整个 JSON 文件"""
|
||||
@@ -211,21 +312,16 @@ class RagflowSync:
|
||||
with open(tables_file, "r", encoding="utf-8") as f:
|
||||
data = json.load(f)
|
||||
|
||||
# 将 JSON 内容转换为字符串
|
||||
json_content = json.dumps(data, ensure_ascii=False, indent=2)
|
||||
|
||||
# 构建文档
|
||||
doc = {
|
||||
"content": f"# 表名检索模板库\n\n以下是所有表名检索模板的 JSON 数据：\n\n```json\n{json_content}\n```\n\n包含的表：{list(data.keys())}",
|
||||
"metadata": {"type": "table_retrieval_templates", "format": "json"},
|
||||
"title": "表名检索模板库",
|
||||
"type": "table_template_library"
|
||||
tables = _extract_tables_map(data)
|
||||
# 每个 key 一个文档，配合 One 解析时每个表单独成块
|
||||
documents = [
|
||||
{
|
||||
"filename": f"{k}.txt",
|
||||
"content": _dump_json_content({"table": k, "templates": v}),
|
||||
}
|
||||
|
||||
print(f"生成的表名检索文档: {doc}")
|
||||
|
||||
# 上传整个 JSON 文件内容
|
||||
return self.upload_documents(self._table_retrieval_dataset_id, [doc])
|
||||
for k, v in tables.items()
|
||||
]
|
||||
return self.upload_documents(self._table_retrieval_dataset_id, documents)
|
||||
|
||||
def upload_sql_gen(self) -> Dict[str, Any]:
|
||||
"""上传 SQL 生成提示词文档"""
|
||||
@@ -247,13 +343,7 @@ class RagflowSync:
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
prompt = json.load(f)
|
||||
table = prompt.get("table") or os.path.splitext(name)[0]
|
||||
doc = {
|
||||
"content": _build_sql_gen_document(table, prompt),
|
||||
"metadata": {"table": table},
|
||||
"title": f"SQL Prompt: {table}",
|
||||
"type": "sql_prompt"
|
||||
}
|
||||
documents.append(doc)
|
||||
print(f"生成的 SQL 提示词文档: {doc}")
|
||||
json_content = _dump_json_content(prompt)
|
||||
documents.append({"filename": f"{table}.txt", "content": json_content})
|
||||
|
||||
return self.upload_documents(self._sql_gen_dataset_id, documents)
|
||||
|
||||
@@ -2,6 +2,9 @@ import json
|
||||
import os
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
from config import Config
|
||||
from services.cache import NoopCache, RedisCache
|
||||
|
||||
|
||||
class SqlPromptManager:
|
||||
"""按表名读取 SQL 提示词"""
|
||||
@@ -9,18 +12,83 @@ class SqlPromptManager:
|
||||
def __init__(self, base_dir: Optional[str] = None):
|
||||
root_dir = os.path.dirname(os.path.dirname(__file__))
|
||||
self._base_dir = base_dir or os.path.join(root_dir, "config", "sql_gen_prompts")
|
||||
self._cache = self._init_cache()
|
||||
self._cache_ttl = self._get_cache_ttl()
|
||||
|
||||
@staticmethod
|
||||
def _get_cache_ttl() -> int:
|
||||
redis_cfg = Config.get_section("redis")
|
||||
try:
|
||||
return int(redis_cfg.get("sql_prompt_ttl", 600))
|
||||
except Exception:
|
||||
return 600
|
||||
|
||||
@staticmethod
|
||||
def _init_cache():
|
||||
redis_cfg = Config.get_section("redis")
|
||||
enabled = str(redis_cfg.get("enabled", "false")).lower() in ("1", "true", "yes")
|
||||
if not enabled:
|
||||
return NoopCache()
|
||||
|
||||
# 优先使用完整 URL；否则使用 host/port/password/database 拼接
|
||||
url = redis_cfg.get("url")
|
||||
db = int(redis_cfg.get("db", redis_cfg.get("database", 0)))
|
||||
if not url:
|
||||
host = redis_cfg.get("host")
|
||||
port = redis_cfg.get("port", "6379")
|
||||
password = redis_cfg.get("password", "")
|
||||
database = redis_cfg.get("database", str(db))
|
||||
if host:
|
||||
auth = f":{password}@" if password else ""
|
||||
url = f"redis://{auth}{host}:{port}/{database}"
|
||||
|
||||
if not url:
|
||||
return NoopCache()
|
||||
try:
|
||||
return RedisCache(url=url, db=db)
|
||||
except Exception:
|
||||
return NoopCache()
|
||||
|
||||
@staticmethod
|
||||
def _safe_filename(name: str) -> str:
|
||||
return name.replace("..", "").replace("/", "_").replace("\\", "_")
|
||||
|
||||
@staticmethod
|
||||
def _cache_key(table_name: str, mtime: float) -> str:
|
||||
return f"sql_prompt:{table_name}:{int(mtime)}"
|
||||
|
||||
def get_prompt(self, table_name: str) -> Optional[Dict[str, Any]]:
|
||||
"""读取指定表的提示词 JSON"""
|
||||
if not table_name:
|
||||
return None
|
||||
filename = self._safe_filename(table_name) + ".json"
|
||||
safe_name = self._safe_filename(table_name)
|
||||
filename = safe_name + ".json"
|
||||
path = os.path.join(self._base_dir, filename)
|
||||
if not os.path.exists(path):
|
||||
return None
|
||||
|
||||
mtime = os.path.getmtime(path)
|
||||
key = self._cache_key(safe_name, mtime)
|
||||
cached = self._cache.get(key)
|
||||
if cached:
|
||||
try:
|
||||
return json.loads(cached)
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
with open(path, "r", encoding="utf-8") as f:
|
||||
return json.load(f)
|
||||
prompt = json.load(f)
|
||||
|
||||
self._cache.set(key, json.dumps(prompt, ensure_ascii=False), self._cache_ttl)
|
||||
return prompt
|
||||
|
||||
|
||||
_GLOBAL_SQL_PROMPT_MANAGER: Optional[SqlPromptManager] = None
|
||||
|
||||
|
||||
def get_sql_prompt_manager(base_dir: Optional[str] = None) -> SqlPromptManager:
|
||||
"""获取全局 SqlPromptManager（单例）"""
|
||||
global _GLOBAL_SQL_PROMPT_MANAGER
|
||||
if _GLOBAL_SQL_PROMPT_MANAGER is None:
|
||||
_GLOBAL_SQL_PROMPT_MANAGER = SqlPromptManager(base_dir=base_dir)
|
||||
return _GLOBAL_SQL_PROMPT_MANAGER
|
||||
|
||||
@@ -0,0 +1,104 @@
|
||||
from __future__ import annotations
|
||||
|
||||
import json
|
||||
from datetime import datetime
|
||||
from typing import Any, Dict, Optional
|
||||
|
||||
import pymysql
|
||||
|
||||
from config import Config
|
||||
|
||||
|
||||
class StructuredLogger:
|
||||
def __init__(self):
|
||||
cfg = Config.get_section("logging_mysql")
|
||||
self.enabled = str(cfg.get("enabled", "false")).lower() in ("1", "true", "yes")
|
||||
self.host = cfg.get("host", "127.0.0.1")
|
||||
self.port = int(cfg.get("port", 3306))
|
||||
self.user = cfg.get("user", "root")
|
||||
self.password = cfg.get("password", "")
|
||||
self.database = cfg.get("database", "more_dots")
|
||||
self.table = cfg.get("table", "structured_logs")
|
||||
self.connect_timeout = int(cfg.get("connect_timeout", 5))
|
||||
self._inited = False
|
||||
|
||||
def _get_conn(self):
|
||||
return pymysql.connect(
|
||||
host=self.host,
|
||||
port=self.port,
|
||||
user=self.user,
|
||||
password=self.password,
|
||||
database=self.database,
|
||||
charset="utf8mb4",
|
||||
autocommit=True,
|
||||
connect_timeout=self.connect_timeout,
|
||||
)
|
||||
|
||||
def _ensure_table(self) -> None:
|
||||
if self._inited or not self.enabled:
|
||||
return
|
||||
sql = f"""
|
||||
CREATE TABLE IF NOT EXISTS {self.table} (
|
||||
id BIGINT PRIMARY KEY AUTO_INCREMENT,
|
||||
trace_id VARCHAR(64) NOT NULL,
|
||||
level VARCHAR(16) NOT NULL,
|
||||
event VARCHAR(128) NOT NULL,
|
||||
error_code VARCHAR(64) NULL,
|
||||
payload JSON NULL,
|
||||
created_at DATETIME NOT NULL
|
||||
) ENGINE=InnoDB DEFAULT CHARSET=utf8mb4;
|
||||
"""
|
||||
try:
|
||||
with self._get_conn() as conn:
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(sql)
|
||||
self._inited = True
|
||||
except Exception:
|
||||
# 开发阶段容错，避免日志失败影响主流程
|
||||
self.enabled = False
|
||||
|
||||
def log(self, level: str, event: str, trace_id: str, payload: Optional[Dict[str, Any]] = None, error_code: Optional[str] = None) -> None:
|
||||
print(json.dumps({
|
||||
"trace_id": trace_id,
|
||||
"level": level,
|
||||
"event": event,
|
||||
"error_code": error_code,
|
||||
"payload": payload or {},
|
||||
"created_at": datetime.now().isoformat(),
|
||||
}, ensure_ascii=False))
|
||||
|
||||
if not self.enabled:
|
||||
return
|
||||
|
||||
self._ensure_table()
|
||||
if not self.enabled:
|
||||
return
|
||||
|
||||
insert_sql = f"INSERT INTO {self.table}(trace_id, level, event, error_code, payload, created_at) VALUES(%s,%s,%s,%s,%s,%s)"
|
||||
try:
|
||||
with self._get_conn() as conn:
|
||||
with conn.cursor() as cur:
|
||||
cur.execute(
|
||||
insert_sql,
|
||||
(
|
||||
trace_id,
|
||||
level,
|
||||
event,
|
||||
error_code,
|
||||
json.dumps(payload or {}, ensure_ascii=False),
|
||||
datetime.now(),
|
||||
),
|
||||
)
|
||||
except Exception:
|
||||
# 开发阶段容错，避免日志失败影响主流程
|
||||
return
|
||||
|
||||
|
||||
_GLOBAL_STRUCTURED_LOGGER: Optional[StructuredLogger] = None
|
||||
|
||||
|
||||
def get_structured_logger() -> StructuredLogger:
|
||||
global _GLOBAL_STRUCTURED_LOGGER
|
||||
if _GLOBAL_STRUCTURED_LOGGER is None:
|
||||
_GLOBAL_STRUCTURED_LOGGER = StructuredLogger()
|
||||
return _GLOBAL_STRUCTURED_LOGGER
|
||||
@@ -11,6 +11,7 @@ class TemplateMatcher:
|
||||
self._ragflow = RagflowClient()
|
||||
cfg = Config.get_section("ragflow")
|
||||
self._dataset_id = (cfg.get("table_retrieval_dataset_id") or "").strip()
|
||||
self._top_k = int(cfg.get("retrieval_top_k", 3))
|
||||
|
||||
def _validate(self) -> None:
|
||||
if not self._dataset_id:
|
||||
@@ -20,14 +21,21 @@ class TemplateMatcher:
|
||||
"""返回匹配的表名与原始响应"""
|
||||
self._validate()
|
||||
try:
|
||||
response = self._ragflow.retrieve(normalized_text, top_k=3, dataset_id=self._dataset_id)
|
||||
response = self._ragflow.retrieve(normalized_text, top_k=self._top_k, dataset_id=self._dataset_id)
|
||||
except Exception as e:
|
||||
return {"table_name": None, "raw": {"error": str(e)}}
|
||||
|
||||
candidates = []
|
||||
data = response.get("data") if isinstance(response, dict) else None
|
||||
records = []
|
||||
if isinstance(data, list):
|
||||
for item in data:
|
||||
records = data
|
||||
elif isinstance(data, dict):
|
||||
chunks = data.get("chunks")
|
||||
if isinstance(chunks, list):
|
||||
records = chunks
|
||||
|
||||
for item in records:
|
||||
table_name = extract_table_name(item)
|
||||
if table_name:
|
||||
candidates.append(table_name)
|
||||
|
||||
Reference in New Issue
Block a user