Aryan Mishra commited on
Commit
4347000
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1 Parent(s): 6bf2e25

Remove CI/CD references from docs

Browse files

Deleted the GitHub Actions workflow files and updated the README and project docs to remove outdated CI/CD mentions, keeping the repository documentation aligned with the current deployment and monitoring setup.

.github/workflows/ci.yml DELETED
@@ -1,38 +0,0 @@
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- name: CI
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- on: [push, pull_request]
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- jobs:
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- test:
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- runs-on: ubuntu-latest
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- steps:
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- - uses: actions/checkout@v4
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- - uses: actions/setup-python@v5
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- with: {python-version: "3.11"}
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- - run: pip install -r requirements.txt mypy
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- - run: PYTHONPATH=. pytest tests/ -v --tb=short
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- - run: PYTHONPATH=. python -m mypy src/ --ignore-missing-imports
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-
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- lint:
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- runs-on: ubuntu-latest
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- steps:
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- - uses: actions/checkout@v4
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- - run: pip install ruff black
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- - run: ruff check src/ api/
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- - run: black --check src/ api/
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-
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- build-docker:
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- needs: [test, lint]
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- runs-on: ubuntu-latest
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- steps:
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- - uses: actions/checkout@v4
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- - uses: docker/setup-buildx-action@v3
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- - uses: docker/login-action@v3
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- with:
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- registry: ghcr.io
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- username: ${{github.actor}}
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- password: ${{secrets.GITHUB_TOKEN}}
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- - uses: docker/build-push-action@v5
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- with:
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- context: .
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- file: config/docker/Dockerfile.api.prod
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- push: ${{github.ref == 'refs/heads/main'}}
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- tags: ghcr.io/${{github.repository}}/api:latest
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
.github/workflows/deploy.yml DELETED
@@ -1,29 +0,0 @@
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- name: Deploy
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- on:
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- push:
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- branches: [main]
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- jobs:
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- deploy-api:
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- runs-on: ubuntu-latest
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- steps:
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- - uses: actions/checkout@v4
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- - name: Deploy to Railway
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- run: |
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- npm install -g @railway/cli
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- railway up --service api
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- env:
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- RAILWAY_TOKEN: ${{secrets.RAILWAY_TOKEN}}
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-
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- deploy-dashboard:
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- runs-on: ubuntu-latest
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- steps:
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- - uses: actions/checkout@v4
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- - uses: actions/setup-node@v4
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- with: {node-version: "20"}
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- - run: cd dashboard && npm install && npm run build
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- - uses: amondnet/vercel-action@v25
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- with:
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- vercel-token: ${{secrets.VERCEL_TOKEN}}
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- vercel-org-id: ${{secrets.VERCEL_ORG_ID}}
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- vercel-project-id: ${{secrets.VERCEL_PROJECT_ID}}
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- working-directory: dashboard
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
.github/workflows/drift_check.yml DELETED
@@ -1,20 +0,0 @@
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- name: Weekly Drift Check
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- on:
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- schedule:
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- - cron: "0 9 * * 1" # Every Monday 9am
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- jobs:
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- drift-check:
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- runs-on: ubuntu-latest
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- steps:
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- - uses: actions/checkout@v4
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- - uses: actions/setup-python@v5
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- with: {python-version: "3.11"}
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- - run: pip install -r requirements.txt
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- - run: python scripts/drift_monitor.py
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- env:
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- DATABASE_URL: ${{secrets.PROD_DATABASE_URL}}
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- MLFLOW_TRACKING_URI: ${{secrets.MLFLOW_TRACKING_URI}}
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- - uses: actions/upload-artifact@v4
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- with:
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- name: drift-report
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- path: monitoring/reports/
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
README.md CHANGED
@@ -33,7 +33,6 @@ This repository is designed following a **Python-first paradigm**:
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  ```text
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  Multilingual-Absa/
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- β”œβ”€β”€ .github/workflows/ # CI/CD pipelines
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  β”œβ”€β”€ api/ # FastAPI backend and inference services
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  β”œβ”€β”€ config/ # DVC and Docker configuration files
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  β”œβ”€β”€ dashboard/ # React frontend for inference & monitoring
 
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  ```text
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  Multilingual-Absa/
 
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  β”œβ”€β”€ api/ # FastAPI backend and inference services
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  β”œβ”€β”€ config/ # DVC and Docker configuration files
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  β”œβ”€β”€ dashboard/ # React frontend for inference & monitoring
docs/architecture.md CHANGED
@@ -28,15 +28,3 @@ graph LR
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  F --> G[Stage 2: Sentiment Classifier]
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  G --> H[aspect, sentiment, confidence]
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  ```
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-
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- ## 3. CI/CD Pipeline
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- ```mermaid
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- graph LR
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- A[git push] --> B[GitHub Actions]
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- B --> C[pytest + ruff]
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- C --> D[Docker build]
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- D --> E[Push to GHCR]
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- E --> F[Deploy to Railway]
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- B --> G[npm build]
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- G --> H[Deploy to Vercel]
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- ```
 
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  F --> G[Stage 2: Sentiment Classifier]
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  G --> H[aspect, sentiment, confidence]
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  ```
 
 
 
 
 
 
 
 
 
 
 
 
docs/demo_script.md CHANGED
@@ -23,10 +23,7 @@
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  *Action*: Switch tabs to the Grafana dashboard (`localhost:3001` or deployed URL).
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  *Narration*: "Production reliability is crucial. Here we see our Prometheus metrics scraped from FastAPI: request rates, P95 latency consistently under 200ms, and Celery worker health."
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- **02:45 β€” Show GitHub Actions CI/CD green checks**
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- *Action*: Switch tabs to the GitHub Actions page.
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- *Narration*: "Every push goes through a rigorous CI/CD pipelineβ€”testing, linting, Docker builds, and automated deployments to Railway and Vercel."
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-
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- **03:00 β€” Show HuggingFace Hub model page**
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  *Action*: Switch to the HuggingFace Hub repository.
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  *Narration*: "Finally, our optimized INT8 ONNX models are hosted publicly on HuggingFace Hub. Thank you for watching!"
 
 
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  *Action*: Switch tabs to the Grafana dashboard (`localhost:3001` or deployed URL).
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  *Narration*: "Production reliability is crucial. Here we see our Prometheus metrics scraped from FastAPI: request rates, P95 latency consistently under 200ms, and Celery worker health."
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+ **02:45 β€” Show HuggingFace Hub model page**
 
 
 
 
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  *Action*: Switch to the HuggingFace Hub repository.
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  *Narration*: "Finally, our optimized INT8 ONNX models are hosted publicly on HuggingFace Hub. Thank you for watching!"
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+
docs/resume_bullets.md CHANGED
@@ -4,11 +4,11 @@
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  > Multilingual ABSA system: XLM-RoBERTa fine-tuned for aspect-level sentiment in English/Hindi, deployed with <300ms latency.
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  **Project bullet (for projects section):**
7
- > Built end-to-end Multilingual ABSA platform supporting English and Hindi: fine-tuned XLM-RoBERTa achieving 78.1% EN / 67.8% HI macro-F1; exported to ONNX INT8 for <300ms CPU inference; deployed FastAPI backend on Railway + React dashboard on Vercel with CI/CD, Prometheus monitoring, and weekly drift detection.
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  **Skills demonstrated (for recruiter talking points):**
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  - NLP: ABSA, BIO tagging, multilingual transfer learning
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  - MLOps: MLflow, DVC, Evidently AI, drift monitoring
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  - Engineering: FastAPI, Celery, Docker, PostgreSQL, Redis
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- - Deployment: Railway, Vercel, HuggingFace Hub, GitHub Actions
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- - Monitoring: Prometheus, Grafana, CI/CD pipelines
 
4
  > Multilingual ABSA system: XLM-RoBERTa fine-tuned for aspect-level sentiment in English/Hindi, deployed with <300ms latency.
5
 
6
  **Project bullet (for projects section):**
7
+ > Built end-to-end Multilingual ABSA platform supporting English and Hindi: fine-tuned XLM-RoBERTa achieving 78.1% EN / 67.8% HI macro-F1; exported to ONNX INT8 for <300ms CPU inference; deployed FastAPI backend on Railway + React dashboard on Vercel with Prometheus monitoring, and weekly drift detection.
8
 
9
  **Skills demonstrated (for recruiter talking points):**
10
  - NLP: ABSA, BIO tagging, multilingual transfer learning
11
  - MLOps: MLflow, DVC, Evidently AI, drift monitoring
12
  - Engineering: FastAPI, Celery, Docker, PostgreSQL, Redis
13
+ - Deployment: Railway, Vercel, HuggingFace Hub
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+ - Monitoring: Prometheus, Grafana