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feat: refactor node spec and add mcp tools (#244)
* refactor: carve out extraction panel * refactor: create spec versions for node types * refactor: create a GenericNode and remove custom nodes * feat: add python and typescript sdk * add dograh sdk * fix: fetch draft workflow definition over published one * fix: fix routes of SDKs to use code gen * chore: remove doclink dependency to reduce image size * chore: format files * chore: bump pipecat * feat: let mcp fetch archived workflows on demand * chore: fix tests * feat: add sdk documentation * chore: change banner and add badge
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Abhishek
GitHub
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0a61ef295f
commit
00a1a22b74
162 changed files with 14355 additions and 3554 deletions
248
api/services/workflow/node_specs/start_call.py
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248
api/services/workflow/node_specs/start_call.py
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"""Spec for the Start Call node — the single entry point of every workflow.
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Carries greeting, pre-call data fetch, and the same prompt/extraction/tools
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fields as agent nodes."""
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from api.services.workflow.node_specs._base import (
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DisplayOptions,
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GraphConstraints,
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NodeCategory,
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NodeExample,
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NodeSpec,
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PropertyOption,
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PropertySpec,
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PropertyType,
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)
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SPEC = NodeSpec(
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name="startCall",
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display_name="Start Call",
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description="Entry point of the workflow — plays a greeting and opens the conversation.",
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llm_hint=(
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"The entry point of every workflow (exactly one required). Plays an "
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"optional greeting, can fetch context from an external API before "
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"the call begins, and executes the first conversational turn."
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),
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category=NodeCategory.call_node,
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icon="Play",
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properties=[
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PropertySpec(
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name="name",
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type=PropertyType.string,
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display_name="Name",
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description="Short identifier shown in the canvas and call logs.",
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required=True,
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min_length=1,
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default="Start Call",
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),
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# ---- Greeting (variant via greeting_type) ----
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PropertySpec(
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name="greeting_type",
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type=PropertyType.options,
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display_name="Greeting Type",
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description=(
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"Whether the optional greeting is spoken via TTS from text "
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"or played from a pre-recorded audio file."
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),
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default="text",
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options=[
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PropertyOption(value="text", label="Text (TTS)"),
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PropertyOption(value="audio", label="Pre-recorded Audio"),
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],
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),
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PropertySpec(
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name="greeting",
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type=PropertyType.string,
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display_name="Greeting Text",
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description=(
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"Text spoken via TTS at the start of the call. Supports "
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"{{template_variables}}. Leave empty to skip the greeting."
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),
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display_options=DisplayOptions(show={"greeting_type": ["text"]}),
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editor="textarea",
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placeholder="Hi {{first_name}}, this is Sarah from Acme.",
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),
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PropertySpec(
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name="greeting_recording_id",
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type=PropertyType.recording_ref,
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display_name="Greeting Recording",
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description="Pre-recorded audio file played at the start of the call.",
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llm_hint=(
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"Value is the `recording_id` string. Use the `list_recordings` "
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"MCP tool to discover available recordings."
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),
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display_options=DisplayOptions(show={"greeting_type": ["audio"]}),
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),
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PropertySpec(
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name="prompt",
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type=PropertyType.mention_textarea,
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display_name="Prompt",
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description=(
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"Agent system prompt for the opening turn. Supports "
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"{{template_variables}} from pre-call fetch and the initial context."
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),
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required=True,
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min_length=1,
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placeholder="Greet the caller warmly and ask how you can help today.",
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),
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# ---- Behavior toggles ----
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PropertySpec(
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name="allow_interrupt",
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type=PropertyType.boolean,
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display_name="Allow Interruption",
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description=("When true, the user can interrupt the agent mid-utterance."),
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default=False,
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),
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PropertySpec(
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name="add_global_prompt",
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type=PropertyType.boolean,
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display_name="Add Global Prompt",
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description=(
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"When true and a Global node exists, prepends the global "
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"prompt to this node's prompt at runtime."
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),
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default=True,
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),
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PropertySpec(
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name="delayed_start",
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type=PropertyType.boolean,
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display_name="Delayed Start",
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description=(
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"When true, the agent waits before speaking after pickup. "
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"Useful for outbound calls where the called party needs a "
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"moment to settle."
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),
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default=False,
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),
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PropertySpec(
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name="delayed_start_duration",
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type=PropertyType.number,
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display_name="Delay Duration (seconds)",
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description="Seconds to wait before the agent speaks. 0.1–10.",
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default=2.0,
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min_value=0.1,
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max_value=10.0,
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display_options=DisplayOptions(show={"delayed_start": [True]}),
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),
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# ---- Variable extraction ----
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PropertySpec(
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name="extraction_enabled",
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type=PropertyType.boolean,
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display_name="Enable Variable Extraction",
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description=(
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"When true, runs an LLM extraction pass on transition out of "
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"this node to capture variables from the opening turn."
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),
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default=False,
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),
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PropertySpec(
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name="extraction_prompt",
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type=PropertyType.string,
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display_name="Extraction Prompt",
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description="Overall instructions guiding variable extraction.",
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display_options=DisplayOptions(show={"extraction_enabled": [True]}),
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editor="textarea",
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),
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PropertySpec(
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name="extraction_variables",
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type=PropertyType.fixed_collection,
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display_name="Variables to Extract",
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description=(
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"Each entry declares one variable to capture, with its name, "
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"data type, and per-variable extraction hint."
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),
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display_options=DisplayOptions(show={"extraction_enabled": [True]}),
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properties=[
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PropertySpec(
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name="name",
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type=PropertyType.string,
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display_name="Variable Name",
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description="snake_case identifier used downstream.",
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required=True,
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),
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PropertySpec(
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name="type",
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type=PropertyType.options,
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display_name="Type",
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description="Data type of the extracted value.",
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required=True,
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default="string",
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options=[
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PropertyOption(value="string", label="String"),
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PropertyOption(value="number", label="Number"),
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PropertyOption(value="boolean", label="Boolean"),
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],
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),
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PropertySpec(
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name="prompt",
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type=PropertyType.string,
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display_name="Extraction Hint",
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description="Per-variable hint describing what to look for.",
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editor="textarea",
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),
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],
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),
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# ---- Tools / documents ----
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PropertySpec(
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name="tool_uuids",
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type=PropertyType.tool_refs,
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display_name="Tools",
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description="Tools the agent can invoke during the opening turn.",
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llm_hint="List of tool UUIDs from `list_tools`.",
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),
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PropertySpec(
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name="document_uuids",
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type=PropertyType.document_refs,
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display_name="Knowledge Base Documents",
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description="Documents the agent can reference.",
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llm_hint="List of document UUIDs from `list_documents`.",
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),
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# ---- Pre-call data fetch (advanced) ----
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PropertySpec(
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name="pre_call_fetch_enabled",
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type=PropertyType.boolean,
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display_name="Pre-Call Data Fetch",
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description=(
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"When true, makes a POST request to an external API before "
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"the call starts and merges the JSON response into the call "
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"context as template variables."
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),
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default=False,
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),
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PropertySpec(
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name="pre_call_fetch_url",
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type=PropertyType.url,
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display_name="Endpoint URL",
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description=(
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"URL the pre-call POST request is sent to. The request body "
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"includes caller and called numbers."
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),
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display_options=DisplayOptions(show={"pre_call_fetch_enabled": [True]}),
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placeholder="https://api.example.com/customer-lookup",
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),
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PropertySpec(
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name="pre_call_fetch_credential_uuid",
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type=PropertyType.credential_ref,
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display_name="Authentication",
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description="Optional credential attached to the pre-call request.",
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llm_hint="Credential UUID from `list_credentials`.",
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display_options=DisplayOptions(show={"pre_call_fetch_enabled": [True]}),
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),
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],
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examples=[
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NodeExample(
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name="warm_greeting",
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data={
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"name": "Greeting",
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"prompt": "Greet warmly and ask the caller's reason for calling.",
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"greeting_type": "text",
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"greeting": "Hi {{first_name}}, this is Sarah from Acme.",
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"allow_interrupt": True,
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},
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),
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],
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graph_constraints=GraphConstraints(
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min_incoming=0,
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max_incoming=0,
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min_outgoing=1,
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),
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)
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