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* feat(gateway): skill-aware slash commands, paginated /commands, Telegram 100-cap Map active skills to Telegram's slash command menu so users can discover and invoke skills directly. Three changes: 1. Telegram menu now includes active skill commands alongside built-in commands, capped at 100 entries (Telegram Bot API limit). Overflow commands remain callable but hidden from the picker. Logged at startup when cap is hit. 2. New /commands [page] gateway command for paginated browsing of all commands + skills. /help now shows first 10 skill commands and points to /commands for the full list. 3. When a user types a slash command that matches a disabled or uninstalled skill, they get actionable guidance: - Disabled: 'Enable it with: hermes skills config' - Optional (not installed): 'Install with: hermes skills install official/<path>' Built on ideas from PR #3921 by @kshitijk4poor. * chore: move 21 niche skills to optional-skills Move specialized/niche skills from built-in (skills/) to optional (optional-skills/) to reduce the default skill count. Users can install them with: hermes skills install official/<category>/<name> Moved skills (21): - mlops: accelerate, chroma, faiss, flash-attention, hermes-atropos-environments, huggingface-tokenizers, instructor, lambda-labs, llava, nemo-curator, pinecone, pytorch-lightning, qdrant, saelens, simpo, slime, tensorrt-llm, torchtitan - research: domain-intel, duckduckgo-search - devops: inference-sh cli Built-in skills: 96 → 75 Optional skills: 22 → 43 * fix: only include repo built-in skills in Telegram menu, not user-installed User-installed skills (from hub or manually added) stay accessible via /skills and by typing the command directly, but don't get registered in the Telegram slash command picker. Only skills whose SKILL.md is under the repo's skills/ directory are included in the menu. This keeps the Telegram menu focused on the curated built-in set while user-installed skills remain discoverable through /skills and /commands.
107 lines
2.3 KiB
Markdown
107 lines
2.3 KiB
Markdown
# Real-World Examples
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Practical examples of using Instructor for structured data extraction.
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## Data Extraction
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```python
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class CompanyInfo(BaseModel):
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name: str
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founded: int
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industry: str
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employees: int
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text = "Apple was founded in 1976 in the technology industry with 164,000 employees."
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company = client.messages.create(
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model="claude-sonnet-4-5-20250929",
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max_tokens=1024,
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messages=[{"role": "user", "content": f"Extract: {text}"}],
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response_model=CompanyInfo
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)
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```
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## Classification
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```python
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class Sentiment(str, Enum):
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POSITIVE = "positive"
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NEGATIVE = "negative"
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NEUTRAL = "neutral"
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class Review(BaseModel):
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sentiment: Sentiment
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confidence: float = Field(ge=0.0, le=1.0)
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review = client.messages.create(
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model="claude-sonnet-4-5-20250929",
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max_tokens=1024,
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messages=[{"role": "user", "content": "This product is amazing!"}],
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response_model=Review
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)
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```
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## Multi-Entity Extraction
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```python
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class Person(BaseModel):
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name: str
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role: str
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class Entities(BaseModel):
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people: list[Person]
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organizations: list[str]
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locations: list[str]
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entities = client.messages.create(
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model="claude-sonnet-4-5-20250929",
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max_tokens=1024,
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messages=[{"role": "user", "content": "Tim Cook, CEO of Apple, spoke in Cupertino..."}],
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response_model=Entities
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)
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```
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## Structured Analysis
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```python
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class Analysis(BaseModel):
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summary: str
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key_points: list[str]
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sentiment: Sentiment
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actionable_items: list[str]
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analysis = client.messages.create(
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model="claude-sonnet-4-5-20250929",
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max_tokens=1024,
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messages=[{"role": "user", "content": "Analyze: [long text]"}],
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response_model=Analysis
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)
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```
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## Batch Processing
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```python
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texts = ["text1", "text2", "text3"]
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results = [
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client.messages.create(
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model="claude-sonnet-4-5-20250929",
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max_tokens=1024,
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messages=[{"role": "user", "content": text}],
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response_model=YourModel
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)
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for text in texts
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]
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```
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## Streaming
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```python
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for partial in client.messages.create_partial(
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model="claude-sonnet-4-5-20250929",
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max_tokens=1024,
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messages=[{"role": "user", "content": "Generate report..."}],
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response_model=Report
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):
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print(f"Progress: {partial.title}")
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# Update UI in real-time
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```
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