diff --git a/.gitignore b/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..bf45f91845113f9e432d623feedf792c80ff67c6
--- /dev/null
+++ b/.gitignore
@@ -0,0 +1,28 @@
+__pycache__/
+*.py[cod]
+.venv/
+venv/
+.env
+.env.*
+*.env
+kaggle.json
+~/.kaggle/
+.ipynb_checkpoints/
+.pytest_cache/
+node_modules/
+frontend/dist/
+data/raw/*
+!data/raw/.gitkeep
+data/raw/gcc/*.csv
+!data/raw/gcc/source_manifest.csv
+data/interim/*
+!data/interim/.gitkeep
+data/processed/*
+!data/processed/.gitkeep
+# Large model weights
+*.h5
+*.bin
+*.pt
+*.ckpt
+*.gguf
+*.safetensors
diff --git a/Dockerfile.backend b/Dockerfile.backend
new file mode 100644
index 0000000000000000000000000000000000000000..fc0dd1201c6fd573d92b5e144e4478156a567500
--- /dev/null
+++ b/Dockerfile.backend
@@ -0,0 +1,6 @@
+FROM python:3.11-slim
+WORKDIR /app
+COPY requirements.txt .
+RUN pip install --no-cache-dir -r requirements.txt
+COPY . .
+EXPOSE 8000
diff --git a/Dockerfile.frontend b/Dockerfile.frontend
new file mode 100644
index 0000000000000000000000000000000000000000..f0fad2147b8f4c656f09755ebcdb237041ddc7df
--- /dev/null
+++ b/Dockerfile.frontend
@@ -0,0 +1,6 @@
+FROM node:20-alpine
+WORKDIR /app
+COPY frontend/package*.json ./
+RUN npm install
+COPY frontend/ .
+EXPOSE 5173
diff --git a/Makefile b/Makefile
new file mode 100644
index 0000000000000000000000000000000000000000..cd88fcb1c07df2bba72756d4f77079b445147460
--- /dev/null
+++ b/Makefile
@@ -0,0 +1,19 @@
+PYTHON=python
+
+prepare:
+ $(PYTHON) -m src.cli.run_prepare --input data/raw/US_Accidents_March23.csv
+
+sample-eval:
+ $(PYTHON) -m src.data.sample_eval_set --input data/interim/eval_candidates.csv --output data/processed/eval_set_with_refs.csv --n 150
+
+infer:
+ $(PYTHON) -m src.cli.run_inference --input data/processed/eval_set_with_refs.csv --output data/processed/model_outputs.csv --models lead1 textrank flan_t5_small bart_large_cnn
+
+eval:
+ $(PYTHON) -m src.cli.run_evaluation --input data/processed/model_outputs.csv --output data/processed/aggregate_metrics.csv
+
+backend:
+ uvicorn backend.main:app --reload --port 8000
+
+frontend:
+ cd frontend && npm install && npm run dev
diff --git a/README.md b/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..2952119f2a15fe5bd71fc8efff9aa7a749ca3031
--- /dev/null
+++ b/README.md
@@ -0,0 +1,72 @@
+# CUD - AAI - Midterm Project - Traffic Incident Summarization
+
+This repo compares extractive and abstractive summarization methods for traffic incident reports and ships with a polished React + FastAPI demo.
+
+## What is included
+
+- U.S. Accidents ingestion with automatic Kaggle download support
+- GCC regional track with bundled Dubai, Abu Dhabi, and UAE federal sample datasets
+- Rule-based GCC narrative generation so structured GCC records become natural-language incident reports
+- Baselines: Lead-1 and TextRank
+- Abstractive models: BART, Flan-T5, optional PEGASUS
+- Evaluation pipeline, notebooks, LaTeX paper draft, poster content, and a demo UI
+
+## GCC data note
+
+The repo now includes **official source references** for Dubai Pulse, Abu Dhabi Open Data, and UAE federal traffic statistics, along with **normalized bundled sample files** so the project runs immediately offline. This is the practical compromise because public GCC portals often expose structured records, JavaScript-only dashboards, or gated exports rather than ready-to-bundle narrative text.
+
+In the paper, describe the GCC track like this:
+
+> Structured GCC traffic records were normalized into a common schema and converted into operator-style narrative incident descriptions using a rule-based text generator. Official source references were retained for provenance, while bundled sample extracts were used to make the demo reproducible offline.
+
+## Quick start
+
+### 1. Python environment
+
+```bash
+python -m venv .venv
+source .venv/bin/activate
+pip install -r requirements.txt
+```
+
+### 2. Prepare data
+
+```bash
+python -m src.cli.run_prepare --source both
+```
+
+Behavior:
+
+- If `data/raw/US_Accidents_March23.csv` is missing, the script attempts Kaggle download.
+- GCC sample sources are already bundled.
+- A combined corpus is written to `data/interim/combined_incident_corpus.csv`.
+
+### 3. Start backend
+
+```bash
+uvicorn backend.main:app --reload --port 8000
+```
+
+### 4. Start frontend
+
+```bash
+cd frontend
+npm install
+npm run dev
+```
+
+## Demo features
+
+- Beautiful hero dashboard for screenshots
+- Dataset track toggle: US or GCC
+- Sample incident picker
+- Summarize and compare endpoints
+- Copy and download summary cards
+- Batch CSV upload preview
+
+## Important paths
+
+- `data/raw/gcc/source_manifest.csv`
+- `data/interim/gcc_narratives.csv`
+- `docs/paper/main.tex`
+- `docs/poster/poster_content.md`
diff --git a/backend/dependencies.py b/backend/dependencies.py
new file mode 100644
index 0000000000000000000000000000000000000000..13099f97fc307d2781e5b2875e3d68e13a6446f4
--- /dev/null
+++ b/backend/dependencies.py
@@ -0,0 +1,4 @@
+from functools import lru_cache
+@lru_cache(maxsize=1)
+def app_metadata():
+ return {"name": "Traffic Incident Summarization API", "version": "0.1.0"}
diff --git a/backend/main.py b/backend/main.py
new file mode 100644
index 0000000000000000000000000000000000000000..c82610dbdedd746a6eccccd2f49cf5165cc29a74
--- /dev/null
+++ b/backend/main.py
@@ -0,0 +1,132 @@
+from __future__ import annotations
+
+from pathlib import Path
+
+import pandas as pd
+from fastapi import FastAPI, HTTPException
+from fastapi.middleware.cors import CORSMiddleware
+
+from src.app.schemas import (
+ CompareRequest,
+ CompareResponse,
+ CompareResponseItem,
+ SampleItem,
+ SamplesResponse,
+ SummarizeRequest,
+ SummarizeResponse,
+)
+from src.app.services import summarize_with_model
+from src.data.prepare import prepare_dataset
+from src.data.utils import load_config
+
+app = FastAPI(title="Traffic Incident Summarization API", version="0.4.0")
+app.add_middleware(
+ CORSMiddleware,
+ allow_origins=["http://localhost:5173", "http://127.0.0.1:5173"],
+ allow_credentials=True,
+ allow_methods=["*"],
+ allow_headers=["*"],
+)
+
+
+@app.on_event("startup")
+def startup_prepare() -> None:
+ cfg = load_config()
+ combined = Path(cfg["paths"]["combined_corpus_csv"])
+ if not combined.exists():
+ try:
+ prepare_dataset(source="gcc", config_path="config.yaml")
+ except Exception:
+ # keep startup resilient, especially when Kaggle credentials are absent
+ pass
+
+
+@app.get("/health")
+def health():
+ return {"status": "ok", "service": "traffic-incident-summarization", "version": "0.4.0"}
+
+
+@app.get("/samples", response_model=SamplesResponse)
+def get_samples(track: str = "gcc"):
+ cfg = load_config()
+ combined_path = Path(cfg["paths"]["combined_corpus_csv"])
+ if not combined_path.exists():
+ prepare_dataset(source="gcc", config_path="config.yaml")
+ df = pd.read_csv(combined_path)
+ if "dataset_track" in df.columns:
+ df = df[df["dataset_track"].fillna("us") == track]
+ if df.empty:
+ raise HTTPException(status_code=404, detail=f"No samples found for dataset track: {track}")
+
+ if "Start_Time" in df.columns:
+ df["Start_Time"] = pd.to_datetime(df["Start_Time"], errors="coerce")
+ df = df.sort_values(by="Start_Time", ascending=False)
+
+ sample_df = df.head(10).copy()
+ items = []
+ for idx, row in sample_df.iterrows():
+ def clean(val):
+ s = str(val).strip() if pd.notna(val) else ""
+ return "" if s.lower() in ("nan", "none", "") else s
+
+ loc_cols = ["road_name", "Street", "district", "City", "State", "emirate"]
+ location_parts = [clean(row.get(col)) for col in loc_cols]
+ title = " · ".join([p for p in location_parts if p][:3]) or f"Sample incident {idx + 1}"
+
+ desc = clean(row.get("Description", "")) or "No description available."
+
+ sev = row.get("Severity", "")
+ if clean(str(sev)):
+ if "severity" not in desc.lower():
+ try:
+ sev_int = int(float(sev))
+ sev_map = {1: "Low", 2: "Medium", 3: "High", 4: "Critical"}
+ sev_str = sev_map.get(sev_int, "Medium")
+ desc = f"{desc} Classified as {sev_str} severity."
+ except Exception:
+ pass
+
+ src_lbl = clean(row.get("source_label", ""))
+ if not src_lbl:
+ src_lbl = "US Accidents" if track == "us" else "GCC sample"
+
+ items.append(
+ SampleItem(
+ id=str(idx + 1),
+ dataset_track=track,
+ title=title,
+ text=desc,
+ source_label=src_lbl,
+ )
+ )
+ return SamplesResponse(items=items)
+
+
+@app.post("/summarize", response_model=SummarizeResponse)
+def summarize(request: SummarizeRequest):
+ try:
+ summary = summarize_with_model(request.text, request.model_choice, request.max_length)
+ return SummarizeResponse(
+ model_name=request.model_choice,
+ summary=summary,
+ dataset_track=request.dataset_track,
+ word_count=len(summary.split()),
+ )
+ except Exception as exc:
+ raise HTTPException(status_code=500, detail=str(exc)) from exc
+
+
+@app.post("/compare", response_model=CompareResponse)
+def compare(request: CompareRequest):
+ try:
+ items = [
+ CompareResponseItem(
+ model_name=m,
+ summary=summarize_with_model(request.text, m, request.max_length),
+ word_count=len(summarize_with_model(request.text, m, request.max_length).split()),
+ )
+ for m in request.model_choices
+ ]
+ return CompareResponse(dataset_track=request.dataset_track, items=items)
+ except Exception as exc:
+ raise HTTPException(status_code=500, detail=str(exc)) from exc
diff --git a/backend/model_cache.py b/backend/model_cache.py
new file mode 100644
index 0000000000000000000000000000000000000000..d5419070106244eb5c85798fbd32c7173239e3e7
--- /dev/null
+++ b/backend/model_cache.py
@@ -0,0 +1,9 @@
+from src.models.abstractive import available_abstractive_models, build_generation_config, load_tokenizer_and_model
+from functools import lru_cache
+@lru_cache(maxsize=8)
+def warm_model(model_name: str):
+ if model_name in available_abstractive_models() or model_name == "pegasus_cnn":
+ hf_name, _ = build_generation_config(model_name)
+ load_tokenizer_and_model(hf_name)
+ return hf_name
+ return model_name
diff --git a/backend/routers/compare.py b/backend/routers/compare.py
new file mode 100644
index 0000000000000000000000000000000000000000..c46b6069de932a48b872ded940bc3e4bc346a554
--- /dev/null
+++ b/backend/routers/compare.py
@@ -0,0 +1,2 @@
+from fastapi import APIRouter
+router=APIRouter()
diff --git a/backend/routers/health.py b/backend/routers/health.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbe9fb82fd762cca2af05f989ce1152eeec06c17
--- /dev/null
+++ b/backend/routers/health.py
@@ -0,0 +1,4 @@
+from fastapi import APIRouter
+router=APIRouter()
+@router.get("/health")
+def health(): return {"status":"ok"}
diff --git a/backend/routers/summarize.py b/backend/routers/summarize.py
new file mode 100644
index 0000000000000000000000000000000000000000..c46b6069de932a48b872ded940bc3e4bc346a554
--- /dev/null
+++ b/backend/routers/summarize.py
@@ -0,0 +1,2 @@
+from fastapi import APIRouter
+router=APIRouter()
diff --git a/config.yaml b/config.yaml
new file mode 100644
index 0000000000000000000000000000000000000000..ad1cad61772e8070514a1a3409949304cbe16374
--- /dev/null
+++ b/config.yaml
@@ -0,0 +1,91 @@
+project:
+ name: "traffic-incident-summarization"
+ random_seed: 42
+
+paths:
+ raw_csv: "data/raw/US_Accidents_March23.csv"
+ cleaned_csv: "data/interim/cleaned_incidents.csv"
+ experiment_sample_csv: "data/interim/experiment_sample.csv"
+ eval_candidates_csv: "data/interim/eval_candidates.csv"
+ eval_set_csv: "data/processed/eval_set_with_refs.csv"
+ model_outputs_csv: "data/processed/model_outputs.csv"
+ aggregate_metrics_csv: "data/processed/aggregate_metrics.csv"
+ gcc_dir: "data/raw/gcc"
+ gcc_manifest_csv: "data/raw/gcc/source_manifest.csv"
+ gcc_combined_structured_csv: "data/interim/gcc_structured_combined.csv"
+ gcc_narratives_csv: "data/interim/gcc_narratives.csv"
+ combined_corpus_csv: "data/interim/combined_incident_corpus.csv"
+
+dataset:
+ kaggle_handle: "sobhanmoosavi/us-accidents"
+ expected_filename: "US_Accidents_March23.csv"
+ auto_download: true
+
+gcc:
+ enabled: true
+ include_in_combined_corpus: true
+ narrative_rows_per_source: 250
+ default_country: "United Arab Emirates"
+ source_priority:
+ - "dubai_pulse_incidents"
+ - "uae_federal_traffic_stats"
+ - "abu_dhabi_open_data"
+ sources:
+ dubai_pulse_incidents:
+ label: "Dubai Pulse Traffic Incidents"
+ official_url: "https://www.dubaipulse.gov.ae/data/dp-traffic/dp_traffic_incidents-open"
+ access_type: "open-data-portal"
+ local_sample_csv: "data/raw/gcc/dubai_pulse_incidents_sample.csv"
+ status: "bundled_sample"
+ notes: "Real-time Dubai Police incident feed surfaced through Dubai Pulse. The bundled CSV is a normalized local sample schema for immediate demo use."
+ uae_federal_traffic_stats:
+ label: "UAE Federal Traffic Statistics"
+ official_url: "https://uaestat.fcsc.gov.ae/vis?df%5Bag%5D=FCSA&df%5Bds%5D=FCSC-RDS&df%5Bid%5D=DF_TRA_TYPE&df%5Bvs%5D=3.0.0"
+ access_type: "web-statistics-portal"
+ local_sample_csv: "data/raw/gcc/uae_federal_traffic_stats_sample.csv"
+ status: "bundled_sample"
+ notes: "Federal accident indicators by emirate and accident type. The bundled CSV is a narrative-ready extracted sample schema."
+ abu_dhabi_open_data:
+ label: "Abu Dhabi Open Data"
+ official_url: "https://data.abudhabi/opendata/dataset"
+ access_type: "open-data-catalog"
+ local_sample_csv: "data/raw/gcc/abu_dhabi_incidents_sample.csv"
+ status: "bundled_sample"
+ notes: "Abu Dhabi open data catalog entry point. The bundled CSV is a normalized road incident sample for regional coverage."
+
+data:
+ text_column: "Description"
+ min_chars: 50
+ max_chars: 1500
+ experiment_sample_size: 3000
+ eval_candidate_size: 300
+ gcc_eval_candidate_size: 120
+ deduplicate: true
+ stratify_by:
+ - "Severity"
+
+generation:
+ default_max_input_tokens: 512
+ default_max_new_tokens: 96
+ default_min_new_tokens: 20
+ num_beams: 4
+ length_penalty: 1.0
+ no_repeat_ngram_size: 3
+ early_stopping: true
+
+models:
+ bart_large_cnn:
+ hf_name: "facebook/bart-large-cnn"
+ enabled: true
+ prompt_prefix: ""
+ max_input_tokens: 512
+ flan_t5_small:
+ hf_name: "google/flan-t5-small"
+ enabled: true
+ prompt_prefix: "summarize: "
+ max_input_tokens: 512
+ pegasus_cnn:
+ hf_name: "google/pegasus-cnn_dailymail"
+ enabled: false
+ prompt_prefix: ""
+ max_input_tokens: 512
diff --git a/data/interim/.gitkeep b/data/interim/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/data/processed/.gitkeep b/data/processed/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/data/raw/.gitkeep b/data/raw/.gitkeep
new file mode 100644
index 0000000000000000000000000000000000000000..e69de29bb2d1d6434b8b29ae775ad8c2e48c5391
diff --git a/docker-compose.yml b/docker-compose.yml
new file mode 100644
index 0000000000000000000000000000000000000000..241a80a8596e51d36d13fc35c5c438414b6f7699
--- /dev/null
+++ b/docker-compose.yml
@@ -0,0 +1,19 @@
+version: "3.9"
+services:
+ backend:
+ build:
+ context: .
+ dockerfile: Dockerfile.backend
+ command: uvicorn backend.main:app --host 0.0.0.0 --port 8000
+ ports: ["8000:8000"]
+ volumes: ["./:/app"]
+ working_dir: /app
+ frontend:
+ build:
+ context: .
+ dockerfile: Dockerfile.frontend
+ command: npm run dev -- --host 0.0.0.0
+ ports: ["5173:5173"]
+ volumes: ["./frontend:/app"]
+ working_dir: /app
+ depends_on: [backend]
diff --git a/docs/architecture.md b/docs/architecture.md
new file mode 100644
index 0000000000000000000000000000000000000000..354d6c37cb1f060df2cf26045bd2141a6ccb1fe2
--- /dev/null
+++ b/docs/architecture.md
@@ -0,0 +1,6 @@
+# GCC V4 architecture update
+
+- US track uses Kaggle U.S. Accidents data.
+- GCC track uses official source references plus bundled normalized sample extracts.
+- A rule-based generator transforms structured GCC records into narrative incident descriptions.
+- The same summarization layer powers notebooks, CLI runs, FastAPI endpoints, and the React demo.
diff --git a/docs/paper/main.tex b/docs/paper/main.tex
new file mode 100644
index 0000000000000000000000000000000000000000..a306a4af263b6789d23a6966e686a7959cc3531e
--- /dev/null
+++ b/docs/paper/main.tex
@@ -0,0 +1,17 @@
+\documentclass[conference]{IEEEtran}
+\usepackage{graphicx}
+\usepackage{booktabs}
+\usepackage{url}
+\begin{document}
+\title{Transformer-Based Abstractive Summarization for Traffic Incident Reports: Comparative Evaluation of BART, Flan-T5, PEGASUS, and Extractive Baselines}
+\author{Rajeev Ranjan Pandey}
+\maketitle
+\begin{abstract}
+This project evaluates extractive and abstractive summarization methods for traffic incident reports using a large U.S. narrative corpus and a GCC regional track derived from structured traffic records tied to Dubai Pulse, Abu Dhabi open data, and UAE federal road-safety statistics. The GCC records are normalized into a common schema and transformed into operator-style narrative descriptions to enable summarization experiments in a regional smart-mobility context.\end{abstract}
+\section{Dataset Note}
+The U.S. Accidents dataset provides large-scale narrative descriptions. GCC public sources more often provide structured records, portal-based feeds, or JavaScript dashboards rather than directly downloadable narrative incident text. To preserve reproducibility, this project bundles normalized sample extracts aligned to official source references and converts those records into narrative incident descriptions through a rule-based generator.
+\section{Demo Note}
+The React frontend includes a GCC-aware dataset toggle and polished output cards for poster-quality screenshots.
+\bibliographystyle{IEEEtran}
+\bibliography{references}
+\end{document}
diff --git a/docs/paper/references.bib b/docs/paper/references.bib
new file mode 100644
index 0000000000000000000000000000000000000000..7c566623cab4bb482195cc90ecf92cd66ba1422d
--- /dev/null
+++ b/docs/paper/references.bib
@@ -0,0 +1,27 @@
+@article{moosavi2019usaccidents,
+ title={A Countrywide Traffic Accident Dataset},
+ author={Moosavi, Sobhan and others},
+ journal={arXiv preprint arXiv:1906.05409},
+ year={2019}
+}
+
+@article{lewis2020bart,
+ title={BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension},
+ author={Lewis, Mike and others},
+ journal={ACL},
+ year={2020}
+}
+
+@article{raffel2020t5,
+ title={Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer},
+ author={Raffel, Colin and others},
+ journal={JMLR},
+ year={2020}
+}
+
+@article{zhang2020pegasus,
+ title={PEGASUS: Pre-training with Extracted Gap-sentences for Abstractive Summarization},
+ author={Zhang, Jingqing and others},
+ journal={ICML},
+ year={2020}
+}
diff --git a/docs/poster/poster_content.md b/docs/poster/poster_content.md
new file mode 100644
index 0000000000000000000000000000000000000000..7fb376e9976aace9846f3ab40973498a6c3db897
--- /dev/null
+++ b/docs/poster/poster_content.md
@@ -0,0 +1,16 @@
+# Poster content, GCC V4
+
+## Title
+Transformer-Based Abstractive Summarization for Traffic Incident Reports
+
+## Regional angle
+- Includes a GCC track centered on Dubai, Abu Dhabi, and UAE federal sources
+- Structured regional traffic records converted into operator-style incident descriptions
+- Demo supports direct US vs GCC comparison
+
+## Visuals
+1. Model comparison bar chart
+2. GCC source manifest table
+3. Example GCC structured record to narrative conversion
+4. Side-by-side summaries in the React UI
+5. Demo QR linking to the local or hosted app screenshot
diff --git a/docs/presentation/outline.md b/docs/presentation/outline.md
new file mode 100644
index 0000000000000000000000000000000000000000..0b153ddd77201b118d35af8524f1cfa7e4924491
--- /dev/null
+++ b/docs/presentation/outline.md
@@ -0,0 +1,7 @@
+1. Problem
+2. Dataset
+3. Models
+4. Evaluation
+5. Results
+6. Demo
+7. Future work
diff --git a/frontend/index.html b/frontend/index.html
new file mode 100644
index 0000000000000000000000000000000000000000..9687b85573dc08d7b73744ea61709e35c4943573
--- /dev/null
+++ b/frontend/index.html
@@ -0,0 +1 @@
+Traffic Incident Summarizer
\ No newline at end of file
diff --git a/frontend/package-lock.json b/frontend/package-lock.json
new file mode 100644
index 0000000000000000000000000000000000000000..5de97d7a38687003975df1542b711111974537a6
--- /dev/null
+++ b/frontend/package-lock.json
@@ -0,0 +1,2881 @@
+{
+ "name": "traffic-incident-summarization-frontend",
+ "version": "0.1.0",
+ "lockfileVersion": 3,
+ "requires": true,
+ "packages": {
+ "": {
+ "name": "traffic-incident-summarization-frontend",
+ "version": "0.1.0",
+ "dependencies": {
+ "axios": "^1.7.2",
+ "lucide-react": "^0.395.0",
+ "react": "^18.3.1",
+ "react-dom": "^18.3.1"
+ },
+ "devDependencies": {
+ "@vitejs/plugin-react": "^4.3.1",
+ "autoprefixer": "^10.4.19",
+ "postcss": "^8.4.38",
+ "tailwindcss": "^3.4.4",
+ "vite": "^5.2.12"
+ }
+ },
+ "node_modules/@alloc/quick-lru": {
+ "version": "5.2.0",
+ "resolved": "https://registry.npmjs.org/@alloc/quick-lru/-/quick-lru-5.2.0.tgz",
+ "integrity": "sha512-UrcABB+4bUrFABwbluTIBErXwvbsU/V7TZWfmbgJfbkwiBuziS9gxdODUyuiecfdGQ85jglMW6juS3+z5TsKLw==",
+ "dev": true,
+ "license": "MIT",
+ "engines": {
+ "node": ">=10"
+ },
+ "funding": {
+ "url": "https://github.com/sponsors/sindresorhus"
+ }
+ },
+ "node_modules/@babel/code-frame": {
+ "version": "7.29.0",
+ "resolved": "https://registry.npmjs.org/@babel/code-frame/-/code-frame-7.29.0.tgz",
+ "integrity": "sha512-9NhCeYjq9+3uxgdtp20LSiJXJvN0FeCtNGpJxuMFZ1Kv3cWUNb6DOhJwUvcVCzKGR66cw4njwM6hrJLqgOwbcw==",
+ "dev": true,
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diff --git a/frontend/package.json b/frontend/package.json
new file mode 100644
index 0000000000000000000000000000000000000000..49f3f8f46e0002606f6b8a0b27a2abc25ad07822
--- /dev/null
+++ b/frontend/package.json
@@ -0,0 +1,24 @@
+{
+ "name": "traffic-incident-summarization-frontend",
+ "private": true,
+ "version": "0.1.0",
+ "type": "module",
+ "scripts": {
+ "dev": "vite",
+ "build": "vite build",
+ "preview": "vite preview"
+ },
+ "dependencies": {
+ "axios": "^1.7.2",
+ "lucide-react": "^0.395.0",
+ "react": "^18.3.1",
+ "react-dom": "^18.3.1"
+ },
+ "devDependencies": {
+ "@vitejs/plugin-react": "^4.3.1",
+ "autoprefixer": "^10.4.19",
+ "postcss": "^8.4.38",
+ "tailwindcss": "^3.4.4",
+ "vite": "^5.2.12"
+ }
+}
diff --git a/frontend/postcss.config.js b/frontend/postcss.config.js
new file mode 100644
index 0000000000000000000000000000000000000000..99417eb5a5d1ed54b838b9a5260bf0e9d6c6e07a
--- /dev/null
+++ b/frontend/postcss.config.js
@@ -0,0 +1 @@
+export default { plugins: { tailwindcss: {}, autoprefixer: {} } };
diff --git a/frontend/src/App.jsx b/frontend/src/App.jsx
new file mode 100644
index 0000000000000000000000000000000000000000..2ef5f6bf3224724de260303b7bc745f6e055f9e8
--- /dev/null
+++ b/frontend/src/App.jsx
@@ -0,0 +1,2 @@
+import Home from "./pages/Home";
+export default function App() { return ; }
diff --git a/frontend/src/api/client.js b/frontend/src/api/client.js
new file mode 100644
index 0000000000000000000000000000000000000000..cc8b686a3fc8f394f4765bb1f950b5032b0c675f
--- /dev/null
+++ b/frontend/src/api/client.js
@@ -0,0 +1,20 @@
+import axios from "axios";
+
+const api = axios.create({
+ baseURL: "http://127.0.0.1:8000"
+});
+
+export async function summarizeText(payload) {
+ const { data } = await api.post("/summarize", payload);
+ return data;
+}
+
+export async function compareModels(payload) {
+ const { data } = await api.post("/compare", payload);
+ return data;
+}
+
+export async function fetchSamples(track) {
+ const { data } = await api.get(`/samples?track=${track}`);
+ return data.items || [];
+}
diff --git a/frontend/src/components/BatchUpload.jsx b/frontend/src/components/BatchUpload.jsx
new file mode 100644
index 0000000000000000000000000000000000000000..715e430e1b834ee4e47c46a95e257ffe22624dfb
--- /dev/null
+++ b/frontend/src/components/BatchUpload.jsx
@@ -0,0 +1,21 @@
+import { UploadCloud } from "lucide-react";
+
+export default function BatchUpload() {
+ return (
+
+
Batch Processing
+
Bulk Generation
+
+ Load custom evaluation datasets by uploading a CSV. The system expects a Description column to generate summaries in bulk for evaluation.
+
+
+
+
+
+
+
Upload CSV or JSON Dataset
+
Supports .csv up to 50MB
+
+
+ Compare all models to render side-by-side summaries for qualitative analysis.
+
+ );
+ }
+
+ return (
+
+ {items.map((item) => (
+
+
+
{item.model_name}
+
+ {item.word_count || item.summary?.split(/\s+/).filter(Boolean).length || 0} words
+
+
+
{item.summary}
+
+ ))}
+
+
+ Analysis Dataset Track
+
+
+ {options.map((option) => {
+ const isSelected = value === option.value;
+ return (
+
+ );
+ })}
+
+
+
+
+
+ {value} tokens
+
+
+
onChange(Number(e.target.value))}
+ className="h-2 w-full appearance-none rounded-lg bg-slate-200 accent-indigo-500 hover:accent-indigo-600 focus:outline-none focus:ring-2 focus:ring-indigo-500/50"
+ />
+
+ Short base
+ Detailed report
+
+
+
+
+ {selected && (
+
{selected.note}
+ )}
+
Critical Severity
;
+ case 'HIGH': return High Severity
;
+ case 'MEDIUM': return Medium Severity
;
+ case 'LOW': return Low Severity
;
+ default: return null;
+ }
+}
+
+export default function SampleGallery({ items, onPick }) {
+ if (!items?.length) {
+ return (
+
+ No sample incidents available for this dataset track yet.
+
+ );
+ }
+
+ return (
+
+ {items.map((item) => (
+
+ ))}
+
+
+
+ AI-powered traffic intelligence
+
+
+ Turn Traffic Chaos
into Clarity
+
+
+ Paste raw incident reports and instantly get AI-distilled summaries from state-of-the-art models. Check the split-view output above.
+
+
+
+
+
+ {/* Input and Output Split Area */}
+
+ {/* LEFT PANE: INPUT */}
+
+
+
Original Incident
+
+ {wordCount} words
+
+
+