flemming-it
4a04abf4f0
Port the multi-API client from llm.chat (llm.rs kept in lockstep): the optional api input selects the dialect, default stays the unchanged v0.1.x Ollama behavior. openai covers vLLM, LM Studio, LiteLLM and cloud OpenAI; api-specific error hints; api_key sent as Bearer (ollama/openai) or x-api-key (anthropic). model_digest stays an Ollama-only best-effort probe and is documented as such. Proven end-to-end against a hermetic OpenAI-wire fake (request shape validated, response parsed) via a hub flow run. Signed-off-by: flemming-it <sf@flemming.it>
95 lines
3.5 KiB
Markdown
95 lines
3.5 KiB
Markdown
# text.summarize
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LLM-backed faithful summarisation. Sends source text to a
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configured LLM endpoint with a fidelity-over-creativity system
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prompt and emits the summary plus audit-grade
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model-provenance fields.
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## Capability
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- `text.summarize@0.1.0`
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## Inputs
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| Name | Type | Description |
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| ----------- | ---- | ---------------------------------------------------------------------------- |
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| `text` | text | Source text to summarise. |
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| `style` | text | Optional style hint (e.g. `one paragraph`, `three bullet points`, `a tweet`). Default: `one paragraph`. |
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| `language` | text | Optional output-language hint (e.g. `German`, `ja-JP`). Empty = same as source. |
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| `endpoint` | text | Chat endpoint URL matching the selected `api` (Ollama `/api/chat`, OpenAI-compatible `/v1/chat/completions` — vLLM etc., Anthropic `/v1/messages`). |
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| `api` | text | Optional wire format: `ollama` (default), `openai`, `anthropic`. |
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| `model` | text | Model identifier the endpoint serves. |
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| `api_key` | text | Optional bearer token for cloud-hosted endpoints. |
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## Outputs
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| Name | Type | Description |
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| ---------------- | ---- | ------------------------------------------------------------ |
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| `summary` | text | The summary. |
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| `style` | text | Echo of the input style. |
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| `language` | text | Echo of the input language. |
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| `model_endpoint` | text | URL the summary was generated against. |
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| `model_name` | text | Model identifier as supplied to the LLM API. |
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| `model_digest` | text | SHA-256 digest of the served model — Ollama only, empty elsewhere. |
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## Fidelity over creativity
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The system prompt is tuned so the summary is derivable from
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the source — no speculation, no implied context, no
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"creative" rephrasing that drifts. Suitable for compliance
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flows where a hallucinated summary is worse than a verbose
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one. The model still has the freedom the operator's chosen
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LLM gives it; this module is the prompt + audit harness, not
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a fine-tuned model.
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## Permissions
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```yaml
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permissions:
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- "net: localhost"
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- "net: 127.0.0.1"
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- "net: api.openai.com"
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- "net: api.anthropic.com"
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```
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Same shape as `text.translate` — local Ollama by default,
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opt-in cloud via operator policy.
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## Limits in v0.1.0
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- Single-shot. Very long source texts (>32k tokens depending
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on the model) need an upstream chunker; v0.1.0 does not yet
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do automatic chunked-summarise + reduce.
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- No structured output. `summary` is free-form text. JSON-
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formatted summaries (e.g. `{ key_points: [], conclusions:
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[] }`) are a v0.2.0 candidate.
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## Example flow
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```yaml
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name: extract-summarise
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inputs:
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document: bytes
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steps:
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- id: extract
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use: text.extract@^0
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with:
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document: $inputs.document
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- id: summarise
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use: text.summarize@^0
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with:
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text: $extract.extracted.pages[*].text
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style: "three bullet points"
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endpoint: "http://localhost:11434/api/chat"
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model: "qwen2.5:14b"
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outputs:
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summary: $summarise.summary
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audit_model: $summarise.model_digest
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```
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## Build
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```bash
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cargo build --release --target wasm32-wasip2
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# Output: target/wasm32-wasip2/release/text_summarize.wasm
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```
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