68 lines
2.9 KiB
Markdown
68 lines
2.9 KiB
Markdown
# Analysis Skill
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The analysis skill provides computational analysis via code execution. It writes and runs Python code in a sandboxed interpreter to answer questions that require computation, aggregation, or data traversal.
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## `create_skill(db_path?, config?)`
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```python
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from haiku.rag.skills.analysis import create_skill
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skill = create_skill(db_path=db_path, config=config)
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```
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| Parameter | Default | Description |
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|-----------|---------|-------------|
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| `db_path` | `None` | Path to LanceDB database. Falls back to `HAIKU_RAG_DB` env var, then config default. |
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| `config` | `None` | `AppConfig` instance. If None, uses `get_config()`. |
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## Tools
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| Tool | Purpose |
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|------|---------|
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| `search(query, limit?)` | Hybrid search (vector + full-text) with context expansion |
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| `list_documents()` | List all documents in the knowledge base |
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| `execute_code(code)` | Execute Python code in a sandboxed interpreter with VFS access |
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| `cite(chunk_ids)` | Register chunk IDs as citations for the current answer |
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## State
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The skill manages an `AnalysisState` under the `"analysis"` namespace:
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```python
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class AnalysisState(BaseModel):
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document_filter: str | None = None
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executions: list[CodeExecutionEntry] = []
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citation_index: dict[str, Citation] = {}
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citations: list[str] = []
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searches: dict[str, list[SearchResult]] = {}
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```
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- **document_filter** — SQL WHERE clause applied to `search` and `list_documents` calls. Persists across invocations as session-level configuration.
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- **executions** — Each `execute_code` call appends a `CodeExecutionEntry` with code, stdout, stderr, and success status. Cleared at the start of each invocation; mirrors the sandbox lifecycle (variables persist across calls within one invocation, a fresh sandbox is built per invocation).
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- **citation_index** — Citations indexed by chunk ID. Accumulates across invocations (same semantics as the RAG skill).
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- **citations** — Chunk IDs cited during the current invocation. Deduplicated; cleared at the start of each invocation.
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- **searches** — Search results from both the `search` tool and sandbox-internal searches. Cleared at the start of each invocation.
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## Usage with RAG Skill
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Combine both skills to give the agent full RAG + analysis capabilities:
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```python
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from haiku.rag.skills.rag import create_skill as create_rag_skill
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from haiku.rag.skills.analysis import create_skill as create_analysis_skill
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from haiku.skills.agent import SkillToolset
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from haiku.skills.prompts import build_system_prompt
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from pydantic_ai import Agent
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rag = create_rag_skill(db_path=db_path)
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analysis = create_analysis_skill(db_path=db_path)
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toolset = SkillToolset(skills=[rag, analysis])
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agent = Agent(
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"openai-chat:gpt-4o",
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instructions=build_system_prompt(toolset.skill_catalog),
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toolsets=[toolset],
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)
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```
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See the [Analysis Agent](../agents/analysis.md) documentation for details on how the underlying sandbox works.
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