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78 lines
2.1 KiB
Markdown
78 lines
2.1 KiB
Markdown
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# dograh-sdk
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Typed builder for Dograh voice-AI workflows. Fetches the node-spec catalog from
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the Dograh backend at session start, validates every call against it at the
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call site, and produces `ReactFlowDTO`-compatible JSON.
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## Install
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```bash
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pip install dograh-sdk
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```
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For local development against a checked-out monorepo:
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```bash
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pip install -e sdk/python/
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```
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## Usage
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```python
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from dograh_sdk import DograhClient, Workflow
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with DograhClient(base_url="http://localhost:8000", api_key="...") as client:
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wf = Workflow(client=client, name="loan_qualification")
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start = wf.add(
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type="startCall",
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name="greeting",
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prompt="You are Sarah from Acme Loans. Greet the caller warmly.",
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greeting_type="text",
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greeting="Hi {{first_name}}, this is Sarah.",
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)
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qualify = wf.add(
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type="agentNode",
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name="qualify",
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prompt="Ask about loan amount and timeline.",
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)
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done = wf.add(type="endCall", name="done", prompt="Thank the caller.")
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wf.edge(start, qualify, label="interested", condition="Caller expressed interest.")
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wf.edge(qualify, done, label="done", condition="Qualification complete.")
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client.save_workflow(workflow_id=123, workflow=wf)
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```
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## What gets validated at the call site
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The SDK fetches the spec for each node type via `get_node_type` and raises
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`ValidationError` immediately when:
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- an unknown field is passed (catches typos)
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- a required field is missing or empty
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- a scalar type is wrong (e.g., string for a boolean)
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- an `options` value isn't in the allowed list
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When a spec carries an `llm_hint`, the hint is appended to the error message so
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an LLM agent can self-correct on retry:
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```
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tool_uuids: expected tool_refs, got str
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Hint: List of tool UUIDs from `list_tools`.
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```
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Server-side Pydantic validators run on save and surface anything the SDK lets
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through (compound invariants, cross-field rules).
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## Environment
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```bash
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DOGRAH_API_URL=http://localhost:8000 # default
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DOGRAH_API_KEY=sk-... # sent as X-API-Key
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```
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## License
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BSD 2-Clause — see `LICENSE`.
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