A flow language for botrun
Project description
botrun_flow_lang v1.0
開發環境安裝
- 使用 Python 3.11.9
- 安裝 uv 來管理 python 套件
- 安裝 uv 可以參考: 官方文件
- 第一次使用在 /project_folder/ 下執行
uv sync- 之後如果需要新增/刪除套件,需要執行
uv add xxx,uv remove xxx
要進行本地端 fastapi 的開發
uvicorn botrun_flow_lang.main:app --reload --host 0.0.0.0 --port 8080
- 可以執行的 curl,可以參考
botrun_flow_lang/tests/api_functional_tests.py
開發規範
- 修改
CHANGELOG.md - release 修改
pyproject.toml
(備份用)如果要進行 agent 的開發
- 先安裝 langgraph cli
- uncomment
botrun_flow_lang/langgraph_agents/agents/langgraph_react_agent.py的最後面幾行 - 在 project 目錄下執行
langgraph dev
以下是部署參考用,先保留
部署時會輸出可用的 requirements.txt
uv export --format requirements-txt --output-file requirements.txt --no-hashes
建立 firestore 的 index (以下以 dev 為例),實際部署的程式寫在 botrun_chat_deploy
gcloud firestore indexes composite create \
--collection-group=botrun-hatch-dev-hatch \
--field-config=field-path=user_id,order=ascending \
--field-config=field-path=name,order=ascending \
--field-config=field-path=__name__,order=ascending \
--project=scoop-386004
# 為AsyncFirestoreCheckpointer建立索引
gcloud firestore indexes composite create \
--collection-group=botrun-flow-lang-dev-checkpointer \
--field-config=field-path=checkpoint_ns,order=ascending \
--field-config=field-path=thread_id,order=ascending \
--field-config=field-path=timestamp,order=descending \
--field-config=field-path=__name__,order=descending \
--project=scoop-386004
打包 dev
gcloud builds submit --config cloudbuild_fastapi_dev.yaml --project=scoop-386004
deploy cloud run, dev 的版本
gcloud run deploy botrun-flow-lang-fastapi-dev \
--image asia-east1-docker.pkg.dev/scoop-386004/botrun-flow-lang/botrun-flow-lang-fastapi-dev \
--port 8080 \
--platform managed \
--allow-unauthenticated \
--project=scoop-386004 \
--region=asia-east1 \
--cpu 2 \
--memory 8Gi \
--min-instances 0 \
--max-instances 5 \
--timeout 3600s \
--concurrency 300 \
--cpu-boost \
建立 staging 的 index
gcloud firestore indexes composite create \
--collection-group=botrun-hatch-hatch \
--field-config=field-path=user_id,order=ascending \
--field-config=field-path=name,order=ascending \
--field-config=field-path=__name__,order=ascending \
--project=scoop-386004
打包 Cloud Run, staging 的版本
gcloud builds submit --config cloudbuild_fastapi.yaml --project=scoop-386004
佈署 cloud run, staging 的版本
gcloud run deploy botrun-flow-lang-fastapi \
--image asia-east1-docker.pkg.dev/scoop-386004/botrun-flow-lang/botrun-flow-lang-fastapi \
--port 8080 \
--platform managed \
--allow-unauthenticated \
--project=scoop-386004 \
--region=asia-east1 \
--cpu 2 \
--memory 8Gi \
--min-instances 0 \
--max-instances 5 \
--timeout 3600s \
--concurrency 300 \
--cpu-boost \
為了要減少冷啟動的時間,每十分鐘呼叫一次 heartbeat (為了省錢已移除,目前留著備份)
gcloud scheduler jobs create http botrun-flow-lang-heartbeat-job-$ENV \
--schedule "*/10 * * * *" \
--time-zone "Asia/Taipei" \
--uri "https://botrun-flow-lang-fastapi-$ENV-36186877499.asia-east1.run.app/heartbeat" \
--http-method GET \
--location "asia-east1" \
--project "scoop-386004"
測試 scheduler
gcloud scheduler jobs run botrun-flow-lang-heartbeat-job-$ENV --location "asia-east1" --project "scoop-386004"
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