Predict F1 Race Winners with OpenAI GPT-4o, Historical Data & Slack Alerts — n8n 워크플로

높음 복잡도⏰ 예약27개의 노드🏷️ Miscellaneous작성자: Cheng Siong Chin

개요

How It Works Every day at 8 AM, the workflow automatically retrieves the latest F1 data—including driver standings, qualifying results, race schedules, and circuit information. All sources are merged into a unified dataset, and driver performance metrics are computed using historical trends. An AI agent, enhanced with vectorized race history, evaluates patterns and generates race-winner predictions. When the confidence score exceeds the defined threshold, the system pushes an automated Slack ale

사용된 노드

Google SheetsHTTP RequestPostgresSlackCodeAI AgentEmbeddings OpenAIOpenAI Chat ModelRecursive Character Text SplitterCode ToolSimple Vector StoreDefault Data Loader

워크플로 미리보기

How It Works
Every day at 8 AM, the workflow automatically retrieves
Setup Steps
1. Update the workflow configuration with: `newsApiUrl`
2. Connect PostgreSQL using the schema:
prediction_date, pre
Use Cases
Applicable for sports analytics dashboards, betting pla
Customization
Extend by adding constructor predictions (modify AI pro
Benefits
Saves time by automating data collection, improves accu
Data Collection
Retrieves live F1 standings, historical results, qualif
Why: Fresh, multi-source data is vital. Standings show
Data Processing
Merges data and calculates 8 driver metrics, including
Why: Metrics reveal patterns raw data
AI Prediction
A LangChain agent (GPT-4o) analyzes the dataset with hi
Why: AI synthesizes complex data at s
Confidence Validation
Compares scores against a 0.75 threshold; high-confiden
Why: Reduces alert fatigue and ensures only reliable in
Driver Performance Metrics
Calculates 8 advanced metrics (podium rate, consistency
Historical Data Vectorization Pipeline
Transforms 3 years of F1 historical data into searchabl
docmodelembedtoolembedtooltooltool
⚡
S
Schedule Trigger
W
Workflow Configuration
Fetch Current F1 Season …
Fetch Driver Standings
Fetch Constructor Standi…
Merge F1 Data
F1 Prediction Agent
OpenAI Chat Model
R
Real-Time F1 News Tool
W
Weather Data Tool
F
Format Prediction Output
Fetch Historical Race Re…
Fetch Qualifying Results
Fetch Circuit Information
Historical Data Vector S…
OpenAI Embeddings
Document Loader
Recursive Text Splitter
Historical Data Retrieva…
Calculate Driver Perform…
C
Check Prediction Confide…
Store Prediction in Data…
Send High Confidence Alert
Log to Prediction Tracker
A
Aggregate Historical Data
Statistical Analysis Tool
OpenAI Embeddings1
27 nodes30 edges

작동 원리

  1. 1

    트리거

    워크플로는 예약 트리거로 시작합니다, 정해진 일정에 따라 실행.

  2. 2

    처리

    데이터가 27개의 노드를 통해 흐릅니다, connecting agent, aggregate, code.

  3. 3

    출력

    워크플로가 자동화를 완료하고 구성된 대상에 결과를 전달합니다.

노드 세부 정보 (27)

GO

Google Sheets

googleSheets

#1
HT

HTTP Request

httpRequest

#2
PO

Postgres

postgres

#3
SL

Slack

slack

#4
CO

Code

code

#5
AI

AI Agent

n8n-nodes-langchain.agent

#6
EM

Embeddings OpenAI

n8n-nodes-langchain.embeddingsOpenAi

#7
OP

OpenAI Chat Model

n8n-nodes-langchain.lmChatOpenAi

#8
RE

Recursive Character Text Splitter

n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter

#9
CO

Code Tool

n8n-nodes-langchain.toolCode

#10
SI

Simple Vector Store

n8n-nodes-langchain.vectorStoreInMemory

#11
DE

Default Data Loader

n8n-nodes-langchain.documentDefaultDataLoader

#12

이 워크플로 가져오는 방법

  1. 1오른쪽의 JSON 다운로드 버튼을 클릭하여 워크플로 파일을 저장합니다.
  2. 2n8n 인스턴스를 열고 워크플로 → 새로 만들기 → 파일에서 가져오기로 이동합니다.
  3. 3다운로드된 predict-f1-race-winners-with-openai-gpt-4o-historical-data-slack-alerts 파일을 선택하고 가져오기를 클릭합니다.
  4. 4각 서비스 노드에 대한 자격 증명（API 키, OAuth 등）을 설정합니다.
  5. 5워크플로 테스트를 클릭하여 모든 것이 작동하는지 확인한 후 활성화합니다.

또는 n8n → JSON에서 가져오기에 직접 붙여넣기:

{ "name": "Predict F1 Race Winners with OpenAI GPT-4o, Historical Data & Slack Alerts", "nodes": [...], ...}

통합

agentaggregatecodedocumentdefaultdataloaderembeddingsopenaigooglesheetshttprequesthttprequesttooliflmchatopenaipostgresscheduletriggersetslacktextsplitterrecursivecharactertextsplittertoolcodevectorstoreinmemory

이 워크플로 가져오기

한 번의 클릭으로 다운로드 및 가져오기

JSON 다운로드n8n.io에서 보기
노드27
복잡도high
트리거scheduled
카테고리Miscellaneous

제작자

Cheng Siong Chin

Cheng Siong Chin

@cschin

태그

agentaggregatecodedocumentdefaultdataloaderembeddingsopenaigooglesheetshttprequesthttprequesttooliflmchatopenai
⚡

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