0265de5816
- Formatted 103 files to comply with ruff format requirements - No code logic changes, only formatting/whitespace - Fixes CI formatting check failures
252 lines
7.6 KiB
Python
Executable File
252 lines
7.6 KiB
Python
Executable File
#!/usr/bin/env python3
|
|
"""
|
|
Automatic Skill Uploader
|
|
Uploads a skill package to LLM platforms (Claude, Gemini, OpenAI, etc.)
|
|
|
|
Usage:
|
|
# Claude (default)
|
|
export ANTHROPIC_API_KEY=sk-ant-...
|
|
skill-seekers upload output/react.zip
|
|
|
|
# Gemini
|
|
export GOOGLE_API_KEY=AIzaSy...
|
|
skill-seekers upload output/react-gemini.tar.gz --target gemini
|
|
|
|
# OpenAI
|
|
export OPENAI_API_KEY=sk-proj-...
|
|
skill-seekers upload output/react-openai.zip --target openai
|
|
"""
|
|
|
|
import argparse
|
|
import os
|
|
import sys
|
|
from pathlib import Path
|
|
|
|
# Import utilities
|
|
try:
|
|
from utils import print_upload_instructions
|
|
except ImportError:
|
|
sys.path.insert(0, str(Path(__file__).parent))
|
|
from utils import print_upload_instructions
|
|
|
|
|
|
def upload_skill_api(package_path, target="claude", api_key=None, **kwargs):
|
|
"""
|
|
Upload skill package to LLM platform
|
|
|
|
Args:
|
|
package_path: Path to skill package file
|
|
target: Target platform ('claude', 'gemini', 'openai', 'chroma', 'weaviate')
|
|
api_key: Optional API key (otherwise read from environment)
|
|
**kwargs: Platform-specific upload options
|
|
|
|
Returns:
|
|
tuple: (success, message)
|
|
"""
|
|
try:
|
|
from skill_seekers.cli.adaptors import get_adaptor
|
|
except ImportError:
|
|
return False, "Adaptor system not available. Reinstall skill-seekers."
|
|
|
|
# Get platform-specific adaptor
|
|
try:
|
|
adaptor = get_adaptor(target)
|
|
except ValueError as e:
|
|
return False, str(e)
|
|
|
|
# Get API key
|
|
if not api_key:
|
|
api_key = os.environ.get(adaptor.get_env_var_name(), "").strip()
|
|
|
|
# API key validation only for platforms that require it
|
|
if target in ["claude", "gemini", "openai"]:
|
|
if not api_key:
|
|
return False, f"{adaptor.get_env_var_name()} not set. Export your API key first."
|
|
|
|
# Validate API key format
|
|
if not adaptor.validate_api_key(api_key):
|
|
return False, f"Invalid API key format for {adaptor.PLATFORM_NAME}"
|
|
|
|
package_path = Path(package_path)
|
|
|
|
# Basic file validation
|
|
if not package_path.exists():
|
|
return False, f"File not found: {package_path}"
|
|
|
|
skill_name = package_path.stem
|
|
|
|
print(f"📤 Uploading skill: {skill_name}")
|
|
print(f" Target: {adaptor.PLATFORM_NAME}")
|
|
print(f" Source: {package_path}")
|
|
print(f" Size: {package_path.stat().st_size:,} bytes")
|
|
print()
|
|
|
|
# Upload using adaptor
|
|
print(f"⏳ Uploading to {adaptor.PLATFORM_NAME}...")
|
|
|
|
try:
|
|
result = adaptor.upload(package_path, api_key, **kwargs)
|
|
|
|
if result["success"]:
|
|
print()
|
|
print(f"✅ {result['message']}")
|
|
print()
|
|
if result.get("url"):
|
|
print("Your skill is now available at:")
|
|
print(f" {result['url']}")
|
|
if result.get("skill_id"):
|
|
print(f" Skill ID: {result['skill_id']}")
|
|
if result.get("collection"):
|
|
print(f" Collection: {result['collection']}")
|
|
if result.get("class_name"):
|
|
print(f" Class: {result['class_name']}")
|
|
if result.get("count"):
|
|
print(f" Documents uploaded: {result['count']}")
|
|
print()
|
|
return True, "Upload successful"
|
|
else:
|
|
return False, result["message"]
|
|
|
|
except Exception as e:
|
|
return False, f"Unexpected error: {str(e)}"
|
|
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(
|
|
description="Upload a skill package to LLM platforms and vector databases",
|
|
formatter_class=argparse.RawDescriptionHelpFormatter,
|
|
epilog="""
|
|
Setup:
|
|
Claude:
|
|
export ANTHROPIC_API_KEY=sk-ant-...
|
|
|
|
Gemini:
|
|
export GOOGLE_API_KEY=AIzaSy...
|
|
|
|
OpenAI:
|
|
export OPENAI_API_KEY=sk-proj-...
|
|
|
|
ChromaDB (local):
|
|
# No API key needed for local instance
|
|
chroma run # Start server
|
|
|
|
Weaviate (local):
|
|
# No API key needed for local instance
|
|
docker run -p 8080:8080 semitechnologies/weaviate:latest
|
|
|
|
Examples:
|
|
# Upload to Claude (default)
|
|
skill-seekers upload output/react.zip
|
|
|
|
# Upload to Gemini
|
|
skill-seekers upload output/react-gemini.tar.gz --target gemini
|
|
|
|
# Upload to OpenAI
|
|
skill-seekers upload output/react-openai.zip --target openai
|
|
|
|
# Upload to ChromaDB (local)
|
|
skill-seekers upload output/react-chroma.json --target chroma
|
|
|
|
# Upload to ChromaDB with OpenAI embeddings
|
|
skill-seekers upload output/react-chroma.json --target chroma --embedding-function openai
|
|
|
|
# Upload to Weaviate (local)
|
|
skill-seekers upload output/react-weaviate.json --target weaviate
|
|
|
|
# Upload to Weaviate Cloud
|
|
skill-seekers upload output/react-weaviate.json --target weaviate --use-cloud --cluster-url https://xxx.weaviate.network --api-key YOUR_KEY
|
|
""",
|
|
)
|
|
|
|
parser.add_argument("package_file", help="Path to skill package file (e.g., output/react.zip)")
|
|
|
|
parser.add_argument(
|
|
"--target",
|
|
choices=["claude", "gemini", "openai", "chroma", "weaviate"],
|
|
default="claude",
|
|
help="Target platform (default: claude)",
|
|
)
|
|
|
|
parser.add_argument("--api-key", help="Platform API key (or set environment variable)")
|
|
|
|
# ChromaDB upload options
|
|
parser.add_argument(
|
|
"--chroma-url",
|
|
help="ChromaDB URL (default: http://localhost:8000 for HTTP, or use --persist-directory for local)",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--persist-directory",
|
|
help="Local directory for persistent ChromaDB storage (default: ./chroma_db)",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--embedding-function",
|
|
choices=["openai", "sentence-transformers", "none"],
|
|
help="Embedding function for ChromaDB/Weaviate (default: platform default)",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--openai-api-key", help="OpenAI API key for embeddings (or set OPENAI_API_KEY env var)"
|
|
)
|
|
|
|
# Weaviate upload options
|
|
parser.add_argument(
|
|
"--weaviate-url",
|
|
default="http://localhost:8080",
|
|
help="Weaviate URL (default: http://localhost:8080)",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--use-cloud",
|
|
action="store_true",
|
|
help="Use Weaviate Cloud (requires --api-key and --cluster-url)",
|
|
)
|
|
|
|
parser.add_argument(
|
|
"--cluster-url", help="Weaviate Cloud cluster URL (e.g., https://xxx.weaviate.network)"
|
|
)
|
|
|
|
args = parser.parse_args()
|
|
|
|
# Build kwargs for vector DB upload
|
|
upload_kwargs = {}
|
|
|
|
if args.target == "chroma":
|
|
if args.chroma_url:
|
|
upload_kwargs["chroma_url"] = args.chroma_url
|
|
if args.persist_directory:
|
|
upload_kwargs["persist_directory"] = args.persist_directory
|
|
if args.embedding_function:
|
|
upload_kwargs["embedding_function"] = args.embedding_function
|
|
if args.openai_api_key:
|
|
upload_kwargs["openai_api_key"] = args.openai_api_key
|
|
|
|
elif args.target == "weaviate":
|
|
upload_kwargs["weaviate_url"] = args.weaviate_url
|
|
upload_kwargs["use_cloud"] = args.use_cloud
|
|
if args.cluster_url:
|
|
upload_kwargs["cluster_url"] = args.cluster_url
|
|
if args.embedding_function:
|
|
upload_kwargs["embedding_function"] = args.embedding_function
|
|
if args.openai_api_key:
|
|
upload_kwargs["openai_api_key"] = args.openai_api_key
|
|
|
|
# Upload skill
|
|
success, message = upload_skill_api(
|
|
args.package_file, args.target, args.api_key, **upload_kwargs
|
|
)
|
|
|
|
if success:
|
|
sys.exit(0)
|
|
else:
|
|
print(f"\n❌ Upload failed: {message}")
|
|
print()
|
|
print("📝 Manual upload instructions:")
|
|
print_upload_instructions(args.package_file)
|
|
sys.exit(1)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
main()
|