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feat: add Tuner Integration to Dograh (#311)
* Add tuner integration * bump pipecat version * chore: update pipecat submodule to match upstream and use tuner-pipecat-sdk 0.2.0 Update pipecat submodule from 0.0.109.dev23 to 13e98d0d9 (the exact commit upstream dograh-hq/dograh uses after v1.30.1). This installs pipecat-ai as 1.1.0.post277 via setuptools_scm, satisfying tuner-pipecat-sdk 0.2.0's pipecat-ai>=1.0.0 requirement. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> * wire tuner * feat: refactor integrations into self contained packages * chore: simplify ensure_public_access_token * fix: remove NodeSpec and make DTOs the source of truth * feat: send relevant signal to mcp using to_mcp_dict * fix: fix tests * cleanup: remove nango integrations * feat: add agents.md for integrations --------- Co-authored-by: Claude Sonnet 4.6 <noreply@anthropic.com> Co-authored-by: Abhishek Kumar <abhishek@a6k.me>
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93 changed files with 3388 additions and 3414 deletions
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@ -1,10 +1,11 @@
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import re
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from collections import Counter
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from typing import Dict, List, Set
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from typing import Any, Dict, List, Set
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from api.services.workflow.dto import EdgeDataDTO, NodeType, ReactFlowDTO
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from api.services.workflow.errors import ItemKind, WorkflowError
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from api.services.workflow.node_specs import REGISTRY
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from api.services.workflow.node_data import BaseNodeData
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from api.services.workflow.node_specs import get_spec
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# Regex for matching {{ variable }} template placeholders.
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# Captures: group(1) = variable path, group(2) = filter name, group(3) = filter value.
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@ -62,7 +63,7 @@ class Edge:
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class Node:
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def __init__(self, id: str, node_type: NodeType, data):
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def __init__(self, id: str, node_type: str, data: BaseNodeData):
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self.id, self.node_type, self.data = id, node_type, data
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self.out: Dict[str, "Node"] = {} # forward nodes
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self.out_edges: List[Edge] = [] # forward edges with properties
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@ -75,7 +76,6 @@ class Node:
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# Type-specific fields — read with getattr so this works for every
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# node variant in the discriminated union.
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self.prompt = getattr(data, "prompt", None)
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self.is_static = getattr(data, "is_static", False)
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self.allow_interrupt = getattr(data, "allow_interrupt", False)
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self.extraction_enabled = getattr(data, "extraction_enabled", False)
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self.extraction_prompt = getattr(data, "extraction_prompt", None)
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@ -84,7 +84,6 @@ class Node:
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self.greeting = getattr(data, "greeting", None)
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self.greeting_type = getattr(data, "greeting_type", None)
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self.greeting_recording_id = getattr(data, "greeting_recording_id", None)
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self.detect_voicemail = getattr(data, "detect_voicemail", False)
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self.delayed_start = getattr(data, "delayed_start", False)
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self.delayed_start_duration = getattr(data, "delayed_start_duration", None)
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self.tool_uuids = getattr(data, "tool_uuids", None)
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@ -106,11 +105,11 @@ class WorkflowGraph:
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"""
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def __init__(self, dto: ReactFlowDTO):
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# build adjacency list. n.type comes off the discriminated-union
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# variant as a literal string; coerce to NodeType for downstream
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# comparisons.
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# Build adjacency list from validated DTO nodes. Core node comparisons
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# still use NodeType string enums; integration nodes remain plain
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# strings and resolve constraints through node specs.
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self.nodes: Dict[str, Node] = {
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n.id: Node(n.id, NodeType(n.type), n.data) for n in dto.nodes
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n.id: Node(n.id, n.type, n.data) for n in dto.nodes
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}
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# Store all edges
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@ -140,7 +139,7 @@ class WorkflowGraph:
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# Get a reference to the global node
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try:
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self.global_node_id = [
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n.id for n in dto.nodes if n.type == NodeType.globalNode
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n.id for n in dto.nodes if n.type == NodeType.globalNode.value
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][0]
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except IndexError:
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self.global_node_id = None
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@ -250,7 +249,7 @@ class WorkflowGraph:
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def _assert_global_node(self):
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errors: list[WorkflowError] = []
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global_node = [
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n for n in self.nodes.values() if n.node_type == NodeType.globalNode
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n for n in self.nodes.values() if n.node_type == NodeType.globalNode.value
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]
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if not len(global_node) <= 1:
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errors.append(
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@ -282,7 +281,7 @@ class WorkflowGraph:
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in_deg[m.id] += 1
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for n in self.nodes.values():
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spec = REGISTRY.get(n.node_type.value)
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spec = get_spec(n.node_type)
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if spec is None or spec.graph_constraints is None:
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continue
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gc = spec.graph_constraints
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