# Flow SDK Quickstart Review Report

## Executive Summary

This report reviews the proposed quickstart design in `tmp/quickstart-design.md` against the existing Flow SDK documentation, examples, and llms.txt specification. The review identifies key findings and recommendations for alignment.

## Key Findings

### 1. vLLM Inference Examples

**Finding**: The proposed vLLM inference examples are well-structured but need alignment with Flow SDK patterns.

**Issues Identified**:
- The vLLM example uses `flow.run(config)` returning a server object with `.endpoint` property, but the actual SDK returns a Task object
- The proposed syntax `server.endpoint` doesn't exist in the current API
- Port forwarding and endpoint access patterns need clarification

**Recommendations**:
```python
# Align with actual Flow SDK patterns
task = flow.run(config)
task.wait_for_ready()  # Wait for server to start
endpoint = task.get_port_forward_url(8000)  # Or similar method
```

### 2. Instance Type Syntax

**Finding**: The quickstart uses correct instance type syntax that aligns with llms.txt.

**Validated Patterns**:
- ✅ `"l40s"` - Simple name format (correct)
- ✅ `"a100_40gb"` - With memory specification (correct)
- ✅ `"4xa100_40gb"` - Count prefix format (correct)
- ✅ `"8xa100"` - Multiple GPU format (correct)

**Note**: The llms.txt explicitly states that formats like `"a100x8"` or `"A100"` (uppercase) are NOT supported.

### 3. API Consistency

**Finding**: Several API inconsistencies between quickstart examples and actual SDK.

**Issues**:
1. **Cost Tracking**: 
   - Quickstart: `result.estimated_cost`
   - Actual SDK: Cost tracking not directly exposed on Task object

2. **Output Access**:
   - Quickstart: `result.output`
   - Actual SDK: `task.logs()` or streaming logs

3. **Artifact Handling**:
   - Quickstart: `task.download_artifact()` 
   - Actual SDK: Need to verify artifact download API

### 4. Configuration Patterns

**Finding**: The TaskConfig usage is mostly correct but some parameters need verification.

**Aligned**:
- ✅ `command` parameter
- ✅ `instance_type` parameter
- ✅ `max_run_time_hours` and `max_run_time_seconds`
- ✅ `max_price_per_hour`
- ✅ `ports` parameter
- ✅ `environment` parameter

**Need Verification**:
- ❓ `output_artifacts` parameter format
- ❓ `spot_instance` parameter (vs `spot` or provider-specific)

### 5. CLI Command Mapping

**Finding**: The SLURM → Flow migration commands need validation.

**Proposed Mappings**:
```bash
sbatch job.sh              →  flow run job.sh
squeue                     →  flow list --status running
scancel <id>               →  flow cancel <id>
sinfo                      →  flow instances --available
```

**Note**: Need to verify these CLI commands exist in the actual implementation.

### 6. Code Upload Mechanism

**Finding**: The quickstart examples don't clearly explain the code upload behavior.

**From llms.txt**:
- FCP provider has a 10KB script limit
- Code is packaged and uploaded via `_FLOW_CODE_ARCHIVE` environment variable
- Working directory set to `/workspace` when `upload_code=True`

**Recommendation**: Add explicit documentation about when code upload happens automatically vs when users need to handle it manually.

### 7. Error Handling

**Finding**: The quickstart examples lack error handling patterns.

**Missing**:
- How to handle `ResourceUnavailableError`
- How to handle authentication failures
- How to handle spot instance preemption
- How to handle quota limits

### 8. Production Patterns

**Strengths**:
- ✅ Explicit cost controls in every example
- ✅ Real workloads (not toy examples)
- ✅ Time estimates for operations
- ✅ GPU validation before main workload

**Gaps**:
- Missing checkpoint/resume patterns
- Missing distributed training setup
- Missing logging/monitoring integration
- Missing retry configuration

## Recommendations

### 1. API Alignment

Update all quickstart examples to use actual Flow SDK API:

```python
# Instead of
server = flow.run(config)
print(server.endpoint)

# Use
task = flow.run(config)
task.wait()  # or task.wait_for_ready()
# Document port forwarding approach
```

### 2. Add Error Handling

Include error handling in every example:

```python
try:
    task = flow.run(config)
except flow.ResourceUnavailableError:
    print("No instances available. Try different type or increase price limit")
except flow.AuthenticationError:
    print("Run 'flow init' to configure API key")
```

### 3. Document Code Upload

Add explicit section on code upload behavior:

```python
# When code is uploaded automatically
config = TaskConfig(
    command="python train.py",  # Local file triggers upload
    upload_code=True  # Explicit control
)

# When using remote scripts only
config = TaskConfig(
    shell="curl -s https://example.com/script.sh | bash"
)
```

### 4. Clarify Streaming Patterns

Show actual log streaming API:

```python
task = flow.run(config)
for line in task.logs(follow=True):
    print(line, end='')
```

### 5. Add Monitoring Examples

Include OpenTelemetry integration examples as mentioned in llms.txt.

### 6. Instance Resolution Documentation

Add clear documentation about instance type formats:

```markdown
## Instance Type Formats

Supported:
- Simple: "a100", "h100", "l40s"
- Count prefix: "2xa100", "4xa100", "8xa100"
- FCP format: "a100-80gb.sxm.1x"

NOT supported:
- "a100x8" or "a100*8" syntax
- Uppercase: "A100", "H100"
- Vendor prefix: "nvidia-a100"
```

## Conclusion

The quickstart design is well-structured and follows good principles (explicit configuration, cost transparency, production patterns). However, it needs alignment with the actual Flow SDK API and should include more error handling and edge case documentation. The vLLM examples are particularly valuable but need the most work to align with actual SDK capabilities.

## Action Items

1. Verify and update all API calls to match actual SDK
2. Add comprehensive error handling examples
3. Document code upload behavior explicitly
4. Clarify port forwarding and endpoint access patterns
5. Add instance type format documentation
6. Include checkpoint/resume examples
7. Verify CLI command mappings
8. Add OpenTelemetry monitoring examples