# Conductor OSS — File Management Use Cases
Five real-world scenarios where Conductor orchestrates file creation, processing, and delivery across workflow stages.
---
## 1. Returns & Refund Document Processing
A customer initiates a product return. Conductor orchestrates the intake of return photos/documents, validates eligibility, generates an RMA (Return Merchandise Authorization) form, and produces the final refund receipt — all as a single traceable workflow.
### Workflow
```mermaid
flowchart TD
A["Customer Submits
Return Request"] --> B["HTTP Task:
Fetch Order Details"]
B --> C["INLINE Task:
Validate Return Window"]
C --> D{"SWITCH:
Eligible?"}
D -- No --> E["Generate Denial
Letter PDF"]
E --> E1["Email Denial
to Customer"]
D -- Yes --> F["HUMAN Task:
Agent Reviews Photos"]
F --> G{"SWITCH:
Condition Check"}
G -- Damaged --> H["Generate RMA Form
+ Prepaid Shipping Label"]
G -- Wrong Item --> H
G -- Other --> I["HUMAN Task:
Escalate to Supervisor"]
I --> H
H --> J["FORK"]
J --> K["Branch 1:
Process Refund via
Payment Gateway"]
J --> L["Branch 2:
Generate Refund
Receipt PDF"]
J --> M["Branch 3:
Update Inventory
System"]
K --> N["JOIN"]
L --> N
M --> N
N --> O["Email RMA + Receipt
+ Shipping Label
to Customer"]
O --> P["Archive All Docs
to S3"]
style A fill:#4CAF50,color:#fff
style D fill:#FF9800,color:#fff
style G fill:#FF9800,color:#fff
style J fill:#2196F3,color:#fff
style N fill:#2196F3,color:#fff
style P fill:#9C27B0,color:#fff
```
### Files Produced
| Stage | File | Format |
|-------|------|--------|
| RMA Generation | `rma_RET-9001.pdf` | PDF |
| Shipping Label | `label_RET-9001.png` | 4×6 ZPL/PNG |
| Refund Receipt | `receipt_RET-9001.pdf` | PDF |
| Denial Letter | `denial_RET-9001.pdf` | PDF (if ineligible) |
### Conductor Primitives
SWITCH, HUMAN, FORK/JOIN, HTTP, INLINE, SUB_WORKFLOW
---
## 2. AI-Powered Knowledge Base Builder (RAG Pipeline)
An organization ingests documents (PDFs, Word files, web pages) into an AI-ready knowledge base. Conductor orchestrates crawling, extraction, chunking, embedding generation, and vector store indexing — enabling retrieval-augmented generation (RAG) for chatbots and search.
### Workflow
```mermaid
flowchart TD
A["Trigger:
New Docs Uploaded
to S3 Bucket"] --> B["DO_WHILE:
Process Each Document"]
B --> C{"SWITCH:
File Type?"}
C -- PDF --> D["Extract Text
via Apache Tika"]
C -- DOCX --> E["Extract Text
via python-docx"]
C -- HTML --> F["Scrape & Clean
via BeautifulSoup"]
C -- Other --> G["OCR via
Tesseract"]
D --> H["INLINE Task:
Chunk Text
(512 tokens, 50 overlap)"]
E --> H
F --> H
G --> H
H --> I["DYNAMIC_FORK:
Generate Embeddings
(1 per chunk)"]
I --> J["LLM_TEXT_COMPLETE:
Create Embedding Vector"]
J --> K["JOIN:
Collect All Vectors"]
K --> L["HTTP Task:
Upsert to Vector DB
(Pinecone / Weaviate)"]
L --> M["Generate Metadata
Index JSON"]
M --> N{"More Docs?"}
N -- Yes --> B
N -- No --> O["Write Master
Index Manifest"]
O --> P["Upload Manifest
+ Logs to S3"]
style A fill:#4CAF50,color:#fff
style C fill:#FF9800,color:#fff
style I fill:#2196F3,color:#fff
style K fill:#2196F3,color:#fff
style N fill:#FF9800,color:#fff
style P fill:#9C27B0,color:#fff
```
### Files Produced
| Stage | File | Format |
|-------|------|--------|
| Extracted Text | `extracted_{doc_id}.txt` | Plain text |
| Chunk Manifest | `chunks_{doc_id}.jsonl` | JSONL |
| Embedding Vectors | `embeddings_{doc_id}.npy` | NumPy binary |
| Metadata Index | `index_{doc_id}.json` | JSON |
| Master Manifest | `kb_manifest_{run_id}.json` | JSON |
| Pipeline Log | `pipeline_log_{run_id}.txt` | Text |
### Conductor Primitives
DO_WHILE, SWITCH, DYNAMIC_FORK, LLM_TEXT_COMPLETE, HTTP, INLINE
---
## 3. Multi-Format Media Transcoding & Publishing
A media company uploads a master video file. Conductor fans out transcoding jobs to produce multiple resolutions and formats, generates thumbnails, extracts subtitles via speech-to-text, and publishes everything to a CDN — all in parallel where possible.
### Workflow
```mermaid
flowchart TD
A["Master Video
Uploaded (4K ProRes)"] --> B["INLINE Task:
Validate & Extract
Media Metadata"]
B --> C["FORK (3 Branches)"]
C --> D["Branch 1:
DYNAMIC_FORK
Transcode Variants"]
D --> D1["1080p H.264 MP4"]
D --> D2["720p H.264 MP4"]
D --> D3["480p H.264 MP4"]
D --> D4["1080p WebM VP9"]
D --> D5["HLS Adaptive
Playlist (.m3u8)"]
C --> E["Branch 2:
Thumbnail Generation"]
E --> E1["Extract Keyframes
(every 30s)"]
E1 --> E2["Resize to
320×180 JPG"]
E2 --> E3["Generate Poster
Image 1920×1080"]
C --> F["Branch 3:
Speech-to-Text"]
F --> F1["LLM_TEXT_COMPLETE:
Transcribe Audio"]
F1 --> F2["Generate SRT
Subtitle File"]
F2 --> F3["Generate VTT
Subtitle File"]
D1 --> G["JOIN"]
D2 --> G
D3 --> G
D4 --> G
D5 --> G
E3 --> G
F3 --> G
G --> H["Generate
Manifest JSON"]
H --> I["HTTP Task:
Upload All Assets
to CDN"]
I --> J["HTTP Task:
Update CMS
with URLs"]
J --> K["Notify Editorial
Team via Slack"]
style A fill:#4CAF50,color:#fff
style C fill:#2196F3,color:#fff
style D fill:#FF5722,color:#fff
style G fill:#2196F3,color:#fff
style K fill:#9C27B0,color:#fff
```
### Files Produced
| Stage | File | Format |
|-------|------|--------|
| Transcoded Videos | `video_{res}.mp4`, `video_1080p.webm` | MP4, WebM |
| HLS Playlist | `stream.m3u8` + segment `.ts` files | HLS |
| Thumbnails | `thumb_{timestamp}.jpg` | JPEG |
| Poster Image | `poster.jpg` | JPEG 1920×1080 |
| Subtitles | `subs_en.srt`, `subs_en.vtt` | SRT, VTT |
| Manifest | `publish_manifest.json` | JSON |
### Conductor Primitives
FORK/JOIN, DYNAMIC_FORK, LLM_TEXT_COMPLETE, HTTP, INLINE
---
## 4. Order Invoice, Packing Slip & Shipping Label Generation
An e-commerce order triggers Conductor to fetch order data, then fan out in parallel to generate three documents — a customer-facing invoice, a warehouse packing slip (no pricing), and a carrier shipping label — before bundling and distributing them.
### Workflow
```mermaid
flowchart TD
A["Order Placed
(Webhook)"] --> B["HTTP Task:
Fetch Order +
Customer Profile"]
B --> C["INLINE Task:
Calculate Totals
(tax, discounts, shipping)"]
C --> D["FORK (3 Branches)"]
D --> E["Branch 1:
Generate Invoice PDF"]
E --> E1["Apply Branding
(logo, colors, footer)"]
E1 --> E2["Format Line Items
+ Tax Breakdown"]
E2 --> E3["Render PDF
invoice_ORD-12345.pdf"]
D --> F["Branch 2:
Generate Packing Slip"]
F --> F1["Strip Pricing Info"]
F1 --> F2["Add Pick Locations
+ Bin Numbers"]
F2 --> F3["Add Warehouse
Barcode"]
F3 --> F4["Render PDF
packslip_ORD-12345.pdf"]
D --> G["Branch 3:
Generate Shipping Label"]
G --> G1{"SWITCH:
Carrier?"}
G1 -- FedEx --> G2["Call FedEx API"]
G1 -- UPS --> G3["Call UPS API"]
G1 -- USPS --> G4["Call USPS API"]
G2 --> G5["Receive Tracking #
+ Label Image"]
G3 --> G5
G4 --> G5
G5 --> G6["Render Label
label_ORD-12345.png"]
E3 --> H["JOIN"]
F4 --> H
G6 --> H
H --> I["Bundle 3 Files
into Order Package"]
I --> J["Upload to S3
orders/ORD-12345/"]
J --> K["FORK (2 Branches)"]
K --> L["Email Invoice
to Customer"]
K --> M["Send Slip + Label
to Warehouse Printer"]
L --> N["JOIN"]
M --> N
N --> O["Update Order Status:
Ready to Ship"]
style A fill:#4CAF50,color:#fff
style D fill:#2196F3,color:#fff
style G1 fill:#FF9800,color:#fff
style H fill:#2196F3,color:#fff
style K fill:#2196F3,color:#fff
style N fill:#2196F3,color:#fff
style O fill:#9C27B0,color:#fff
```
### Files Produced
| Stage | File | Format |
|-------|------|--------|
| Invoice | `invoice_ORD-12345.pdf` | PDF |
| Packing Slip | `packslip_ORD-12345.pdf` | PDF |
| Shipping Label | `label_ORD-12345.png` | 4×6 ZPL/PNG |
### Conductor Primitives
FORK/JOIN, SWITCH, HTTP, INLINE, SUB_WORKFLOW
---
## 5. Enterprise Video Surveillance Archival & Alert Pipeline
A network of security cameras streams footage to edge servers. Conductor orchestrates the pipeline: ingest video segments, run AI-based anomaly detection, generate alert clips with annotations, archive raw footage with retention policies, and produce daily summary reports.
### Workflow
```mermaid
flowchart TD
A["Camera Feed:
60s Segment Arrives
on Edge Server"] --> B["INLINE Task:
Extract Metadata
(camera ID, timestamp,
resolution)"]
B --> C["Upload Raw Segment
to Cold Storage
(S3 Glacier)"]
C --> D["HTTP Task:
AI Anomaly Detection
Model Inference"]
D --> E{"SWITCH:
Anomaly Detected?"}
E -- No --> F["Log: Normal
Update Daily Counter"]
E -- Yes --> G["FORK (3 Branches)"]
G --> H["Branch 1:
Clip 30s Around
Anomaly Timestamp"]
H --> H1["Overlay Bounding
Boxes + Labels"]
H1 --> H2["Render Alert Clip
alert_CAM04_1712345678.mp4"]
G --> I["Branch 2:
Generate Alert
Snapshot"]
I --> I1["Extract Best Frame"]
I1 --> I2["Annotate with
Detection Metadata"]
I2 --> I3["Save Snapshot
alert_CAM04_1712345678.jpg"]
G --> J["Branch 3:
Create Incident
Report"]
J --> J1["LLM_TEXT_COMPLETE:
Summarize Event"]
J1 --> J2["Generate PDF
incident_1712345678.pdf"]
H2 --> K["JOIN"]
I3 --> K
J2 --> K
K --> L["Upload Alert Bundle
to Hot Storage (S3)"]
L --> M["HTTP Task:
Push Notification
to Security Team"]
M --> N["Log Incident
to SIEM"]
F --> O["TIMER:
End of Day?"]
N --> O
O --> P["DO_WHILE:
Aggregate All
Camera Logs"]
P --> Q["Generate Daily
Summary Report PDF"]
Q --> R["Apply Retention
Policy (90-day
hot → cold → delete)"]
R --> S["Email Daily Report
to Facility Manager"]
style A fill:#4CAF50,color:#fff
style E fill:#FF9800,color:#fff
style G fill:#2196F3,color:#fff
style K fill:#2196F3,color:#fff
style O fill:#FF5722,color:#fff
style S fill:#9C27B0,color:#fff
```
### Files Produced
| Stage | File | Format |
|-------|------|--------|
| Raw Segment | `raw_CAM04_1712345678.mp4` | MP4 (60s) |
| Alert Clip | `alert_CAM04_1712345678.mp4` | MP4 (30s, annotated) |
| Alert Snapshot | `alert_CAM04_1712345678.jpg` | JPEG (annotated) |
| Incident Report | `incident_1712345678.pdf` | PDF |
| Daily Summary | `daily_report_2026-04-08.pdf` | PDF |
### Conductor Primitives
FORK/JOIN, SWITCH, DO_WHILE, TIMER, LLM_TEXT_COMPLETE, HTTP, INLINE
---
*Generated for Conductor OSS file management use case exploration.*