feat: Improve Observability with Arize & Phoenix Integration (#19840)
Co-authored-by: crazywoola <427733928@qq.com> Co-authored-by: Gu <guchenhe@gmail.com>pull/21877/head
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31eb8548ef
commit
1af3d40c1a
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import hashlib
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import json
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import logging
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import os
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from datetime import datetime, timedelta
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from typing import Optional, Union, cast
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from openinference.semconv.trace import OpenInferenceSpanKindValues, SpanAttributes
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from opentelemetry import trace
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from opentelemetry.exporter.otlp.proto.grpc.trace_exporter import OTLPSpanExporter as GrpcOTLPSpanExporter
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from opentelemetry.exporter.otlp.proto.http.trace_exporter import OTLPSpanExporter as HttpOTLPSpanExporter
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from opentelemetry.sdk import trace as trace_sdk
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from opentelemetry.sdk.resources import Resource
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from opentelemetry.sdk.trace.export import SimpleSpanProcessor
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from opentelemetry.sdk.trace.id_generator import RandomIdGenerator
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from opentelemetry.trace import SpanContext, TraceFlags, TraceState
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from core.ops.base_trace_instance import BaseTraceInstance
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from core.ops.entities.config_entity import ArizeConfig, PhoenixConfig
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from core.ops.entities.trace_entity import (
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BaseTraceInfo,
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DatasetRetrievalTraceInfo,
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GenerateNameTraceInfo,
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MessageTraceInfo,
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ModerationTraceInfo,
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SuggestedQuestionTraceInfo,
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ToolTraceInfo,
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TraceTaskName,
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WorkflowTraceInfo,
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)
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from extensions.ext_database import db
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from models.model import EndUser, MessageFile
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from models.workflow import WorkflowNodeExecutionModel
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logger = logging.getLogger(__name__)
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def setup_tracer(arize_phoenix_config: ArizeConfig | PhoenixConfig) -> tuple[trace_sdk.Tracer, SimpleSpanProcessor]:
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"""Configure OpenTelemetry tracer with OTLP exporter for Arize/Phoenix."""
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try:
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# Choose the appropriate exporter based on config type
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exporter: Union[GrpcOTLPSpanExporter, HttpOTLPSpanExporter]
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if isinstance(arize_phoenix_config, ArizeConfig):
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arize_endpoint = f"{arize_phoenix_config.endpoint}/v1"
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arize_headers = {
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"api_key": arize_phoenix_config.api_key or "",
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"space_id": arize_phoenix_config.space_id or "",
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"authorization": f"Bearer {arize_phoenix_config.api_key or ''}",
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}
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exporter = GrpcOTLPSpanExporter(
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endpoint=arize_endpoint,
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headers=arize_headers,
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timeout=30,
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)
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else:
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phoenix_endpoint = f"{arize_phoenix_config.endpoint}/v1/traces"
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phoenix_headers = {
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"api_key": arize_phoenix_config.api_key or "",
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"authorization": f"Bearer {arize_phoenix_config.api_key or ''}",
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}
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exporter = HttpOTLPSpanExporter(
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endpoint=phoenix_endpoint,
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headers=phoenix_headers,
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timeout=30,
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)
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attributes = {
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"openinference.project.name": arize_phoenix_config.project or "",
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"model_id": arize_phoenix_config.project or "",
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}
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resource = Resource(attributes=attributes)
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provider = trace_sdk.TracerProvider(resource=resource)
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processor = SimpleSpanProcessor(
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exporter,
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)
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provider.add_span_processor(processor)
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# Create a named tracer instead of setting the global provider
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tracer_name = f"arize_phoenix_tracer_{arize_phoenix_config.project}"
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logger.info(f"[Arize/Phoenix] Created tracer with name: {tracer_name}")
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return cast(trace_sdk.Tracer, provider.get_tracer(tracer_name)), processor
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except Exception as e:
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logger.error(f"[Arize/Phoenix] Failed to setup the tracer: {str(e)}", exc_info=True)
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raise
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def datetime_to_nanos(dt: Optional[datetime]) -> int:
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"""Convert datetime to nanoseconds since epoch. If None, use current time."""
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if dt is None:
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dt = datetime.now()
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return int(dt.timestamp() * 1_000_000_000)
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def uuid_to_trace_id(string: Optional[str]) -> int:
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"""Convert UUID string to a valid trace ID (16-byte integer)."""
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if string is None:
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string = ""
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hash_object = hashlib.sha256(string.encode())
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# Take the first 16 bytes (128 bits) of the hash
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digest = hash_object.digest()[:16]
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# Convert to integer (128 bits)
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return int.from_bytes(digest, byteorder="big")
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class ArizePhoenixDataTrace(BaseTraceInstance):
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def __init__(
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self,
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arize_phoenix_config: ArizeConfig | PhoenixConfig,
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):
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super().__init__(arize_phoenix_config)
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import logging
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logging.basicConfig()
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logging.getLogger().setLevel(logging.DEBUG)
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self.arize_phoenix_config = arize_phoenix_config
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self.tracer, self.processor = setup_tracer(arize_phoenix_config)
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self.project = arize_phoenix_config.project
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self.file_base_url = os.getenv("FILES_URL", "http://127.0.0.1:5001")
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def trace(self, trace_info: BaseTraceInfo):
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logger.info(f"[Arize/Phoenix] Trace: {trace_info}")
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try:
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if isinstance(trace_info, WorkflowTraceInfo):
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self.workflow_trace(trace_info)
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if isinstance(trace_info, MessageTraceInfo):
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self.message_trace(trace_info)
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if isinstance(trace_info, ModerationTraceInfo):
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self.moderation_trace(trace_info)
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if isinstance(trace_info, SuggestedQuestionTraceInfo):
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self.suggested_question_trace(trace_info)
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if isinstance(trace_info, DatasetRetrievalTraceInfo):
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self.dataset_retrieval_trace(trace_info)
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if isinstance(trace_info, ToolTraceInfo):
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self.tool_trace(trace_info)
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if isinstance(trace_info, GenerateNameTraceInfo):
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self.generate_name_trace(trace_info)
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except Exception as e:
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logger.error(f"[Arize/Phoenix] Error in the trace: {str(e)}", exc_info=True)
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raise
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def workflow_trace(self, trace_info: WorkflowTraceInfo):
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if trace_info.message_data is None:
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return
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workflow_metadata = {
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"workflow_id": trace_info.workflow_run_id or "",
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"message_id": trace_info.message_id or "",
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"workflow_app_log_id": trace_info.workflow_app_log_id or "",
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"status": trace_info.workflow_run_status or "",
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"status_message": trace_info.error or "",
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"level": "ERROR" if trace_info.error else "DEFAULT",
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"total_tokens": trace_info.total_tokens or 0,
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}
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workflow_metadata.update(trace_info.metadata)
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trace_id = uuid_to_trace_id(trace_info.message_id)
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span_id = RandomIdGenerator().generate_span_id()
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context = SpanContext(
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trace_id=trace_id,
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span_id=span_id,
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is_remote=False,
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trace_flags=TraceFlags(TraceFlags.SAMPLED),
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trace_state=TraceState(),
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)
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workflow_span = self.tracer.start_span(
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name=TraceTaskName.WORKFLOW_TRACE.value,
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attributes={
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SpanAttributes.INPUT_VALUE: json.dumps(trace_info.workflow_run_inputs, ensure_ascii=False),
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SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.workflow_run_outputs, ensure_ascii=False),
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SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
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SpanAttributes.METADATA: json.dumps(workflow_metadata, ensure_ascii=False),
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SpanAttributes.SESSION_ID: trace_info.conversation_id or "",
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},
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start_time=datetime_to_nanos(trace_info.start_time),
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context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
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)
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try:
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# Process workflow nodes
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for node_execution in self._get_workflow_nodes(trace_info.workflow_run_id):
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created_at = node_execution.created_at or datetime.now()
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elapsed_time = node_execution.elapsed_time
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finished_at = created_at + timedelta(seconds=elapsed_time)
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process_data = json.loads(node_execution.process_data) if node_execution.process_data else {}
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node_metadata = {
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"node_id": node_execution.id,
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"node_type": node_execution.node_type,
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"node_status": node_execution.status,
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"tenant_id": node_execution.tenant_id,
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"app_id": node_execution.app_id,
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"app_name": node_execution.title,
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"status": node_execution.status,
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"level": "ERROR" if node_execution.status != "succeeded" else "DEFAULT",
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}
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if node_execution.execution_metadata:
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node_metadata.update(json.loads(node_execution.execution_metadata))
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# Determine the correct span kind based on node type
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span_kind = OpenInferenceSpanKindValues.CHAIN.value
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if node_execution.node_type == "llm":
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span_kind = OpenInferenceSpanKindValues.LLM.value
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provider = process_data.get("model_provider")
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model = process_data.get("model_name")
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if provider:
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node_metadata["ls_provider"] = provider
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if model:
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node_metadata["ls_model_name"] = model
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usage = json.loads(node_execution.outputs).get("usage", {}) if node_execution.outputs else {}
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if usage:
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node_metadata["total_tokens"] = usage.get("total_tokens", 0)
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node_metadata["prompt_tokens"] = usage.get("prompt_tokens", 0)
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node_metadata["completion_tokens"] = usage.get("completion_tokens", 0)
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elif node_execution.node_type == "dataset_retrieval":
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span_kind = OpenInferenceSpanKindValues.RETRIEVER.value
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elif node_execution.node_type == "tool":
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span_kind = OpenInferenceSpanKindValues.TOOL.value
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else:
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span_kind = OpenInferenceSpanKindValues.CHAIN.value
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node_span = self.tracer.start_span(
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name=node_execution.node_type,
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attributes={
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SpanAttributes.INPUT_VALUE: node_execution.inputs or "{}",
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SpanAttributes.OUTPUT_VALUE: node_execution.outputs or "{}",
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SpanAttributes.OPENINFERENCE_SPAN_KIND: span_kind,
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SpanAttributes.METADATA: json.dumps(node_metadata, ensure_ascii=False),
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SpanAttributes.SESSION_ID: trace_info.conversation_id or "",
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},
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start_time=datetime_to_nanos(created_at),
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)
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try:
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if node_execution.node_type == "llm":
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provider = process_data.get("model_provider")
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model = process_data.get("model_name")
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if provider:
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node_span.set_attribute(SpanAttributes.LLM_PROVIDER, provider)
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if model:
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node_span.set_attribute(SpanAttributes.LLM_MODEL_NAME, model)
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usage = json.loads(node_execution.outputs).get("usage", {}) if node_execution.outputs else {}
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if usage:
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node_span.set_attribute(SpanAttributes.LLM_TOKEN_COUNT_TOTAL, usage.get("total_tokens", 0))
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node_span.set_attribute(
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SpanAttributes.LLM_TOKEN_COUNT_PROMPT, usage.get("prompt_tokens", 0)
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)
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node_span.set_attribute(
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SpanAttributes.LLM_TOKEN_COUNT_COMPLETION, usage.get("completion_tokens", 0)
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)
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finally:
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node_span.end(end_time=datetime_to_nanos(finished_at))
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finally:
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workflow_span.end(end_time=datetime_to_nanos(trace_info.end_time))
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def message_trace(self, trace_info: MessageTraceInfo):
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if trace_info.message_data is None:
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return
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file_list = cast(list[str], trace_info.file_list) or []
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message_file_data: Optional[MessageFile] = trace_info.message_file_data
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if message_file_data is not None:
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file_url = f"{self.file_base_url}/{message_file_data.url}" if message_file_data else ""
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file_list.append(file_url)
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message_metadata = {
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"message_id": trace_info.message_id or "",
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"conversation_mode": str(trace_info.conversation_mode or ""),
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"user_id": trace_info.message_data.from_account_id or "",
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"file_list": json.dumps(file_list),
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"status": trace_info.message_data.status or "",
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"status_message": trace_info.error or "",
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"level": "ERROR" if trace_info.error else "DEFAULT",
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"total_tokens": trace_info.total_tokens or 0,
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"prompt_tokens": trace_info.message_tokens or 0,
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"completion_tokens": trace_info.answer_tokens or 0,
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"ls_provider": trace_info.message_data.model_provider or "",
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"ls_model_name": trace_info.message_data.model_id or "",
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}
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message_metadata.update(trace_info.metadata)
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# Add end user data if available
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if trace_info.message_data.from_end_user_id:
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end_user_data: Optional[EndUser] = (
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db.session.query(EndUser).filter(EndUser.id == trace_info.message_data.from_end_user_id).first()
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)
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if end_user_data is not None:
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message_metadata["end_user_id"] = end_user_data.session_id
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attributes = {
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SpanAttributes.INPUT_VALUE: trace_info.message_data.query,
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SpanAttributes.OUTPUT_VALUE: trace_info.message_data.answer,
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SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
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SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False),
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SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
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}
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trace_id = uuid_to_trace_id(trace_info.message_id)
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message_span_id = RandomIdGenerator().generate_span_id()
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span_context = SpanContext(
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trace_id=trace_id,
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span_id=message_span_id,
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is_remote=False,
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trace_flags=TraceFlags(TraceFlags.SAMPLED),
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trace_state=TraceState(),
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)
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message_span = self.tracer.start_span(
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name=TraceTaskName.MESSAGE_TRACE.value,
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attributes=attributes,
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start_time=datetime_to_nanos(trace_info.start_time),
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context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)),
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)
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try:
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if trace_info.error:
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message_span.add_event(
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"exception",
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attributes={
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"exception.message": trace_info.error,
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"exception.type": "Error",
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"exception.stacktrace": trace_info.error,
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},
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)
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# Convert outputs to string based on type
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if isinstance(trace_info.outputs, dict | list):
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outputs_str = json.dumps(trace_info.outputs, ensure_ascii=False)
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elif isinstance(trace_info.outputs, str):
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outputs_str = trace_info.outputs
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else:
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outputs_str = str(trace_info.outputs)
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llm_attributes = {
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SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.LLM.value,
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SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
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SpanAttributes.OUTPUT_VALUE: outputs_str,
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SpanAttributes.METADATA: json.dumps(message_metadata, ensure_ascii=False),
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SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
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}
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if isinstance(trace_info.inputs, list):
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for i, msg in enumerate(trace_info.inputs):
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if isinstance(msg, dict):
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llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.content"] = msg.get("text", "")
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llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.{i}.message.role"] = msg.get(
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"role", "user"
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)
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# todo: handle assistant and tool role messages, as they don't always
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# have a text field, but may have a tool_calls field instead
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# e.g. 'tool_calls': [{'id': '98af3a29-b066-45a5-b4b1-46c74ddafc58',
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# 'type': 'function', 'function': {'name': 'current_time', 'arguments': '{}'}}]}
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elif isinstance(trace_info.inputs, dict):
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llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = json.dumps(trace_info.inputs)
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llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user"
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elif isinstance(trace_info.inputs, str):
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llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.content"] = trace_info.inputs
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llm_attributes[f"{SpanAttributes.LLM_INPUT_MESSAGES}.0.message.role"] = "user"
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if trace_info.total_tokens is not None and trace_info.total_tokens > 0:
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llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_TOTAL] = trace_info.total_tokens
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if trace_info.message_tokens is not None and trace_info.message_tokens > 0:
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llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_PROMPT] = trace_info.message_tokens
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if trace_info.answer_tokens is not None and trace_info.answer_tokens > 0:
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llm_attributes[SpanAttributes.LLM_TOKEN_COUNT_COMPLETION] = trace_info.answer_tokens
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if trace_info.message_data.model_id is not None:
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llm_attributes[SpanAttributes.LLM_MODEL_NAME] = trace_info.message_data.model_id
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if trace_info.message_data.model_provider is not None:
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llm_attributes[SpanAttributes.LLM_PROVIDER] = trace_info.message_data.model_provider
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if trace_info.message_data and trace_info.message_data.message_metadata:
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metadata_dict = json.loads(trace_info.message_data.message_metadata)
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if model_params := metadata_dict.get("model_parameters"):
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llm_attributes[SpanAttributes.LLM_INVOCATION_PARAMETERS] = json.dumps(model_params)
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llm_span = self.tracer.start_span(
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name="llm",
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attributes=llm_attributes,
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start_time=datetime_to_nanos(trace_info.start_time),
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context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)),
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)
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try:
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if trace_info.error:
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llm_span.add_event(
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"exception",
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attributes={
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"exception.message": trace_info.error,
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"exception.type": "Error",
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"exception.stacktrace": trace_info.error,
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},
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)
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finally:
|
||||
llm_span.end(end_time=datetime_to_nanos(trace_info.end_time))
|
||||
finally:
|
||||
message_span.end(end_time=datetime_to_nanos(trace_info.end_time))
|
||||
|
||||
def moderation_trace(self, trace_info: ModerationTraceInfo):
|
||||
if trace_info.message_data is None:
|
||||
return
|
||||
|
||||
metadata = {
|
||||
"message_id": trace_info.message_id,
|
||||
"tool_name": "moderation",
|
||||
"status": trace_info.message_data.status,
|
||||
"status_message": trace_info.message_data.error or "",
|
||||
"level": "ERROR" if trace_info.message_data.error else "DEFAULT",
|
||||
}
|
||||
metadata.update(trace_info.metadata)
|
||||
|
||||
trace_id = uuid_to_trace_id(trace_info.message_id)
|
||||
span_id = RandomIdGenerator().generate_span_id()
|
||||
context = SpanContext(
|
||||
trace_id=trace_id,
|
||||
span_id=span_id,
|
||||
is_remote=False,
|
||||
trace_flags=TraceFlags(TraceFlags.SAMPLED),
|
||||
trace_state=TraceState(),
|
||||
)
|
||||
|
||||
span = self.tracer.start_span(
|
||||
name=TraceTaskName.MODERATION_TRACE.value,
|
||||
attributes={
|
||||
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
|
||||
SpanAttributes.OUTPUT_VALUE: json.dumps(
|
||||
{
|
||||
"action": trace_info.action,
|
||||
"flagged": trace_info.flagged,
|
||||
"preset_response": trace_info.preset_response,
|
||||
"inputs": trace_info.inputs,
|
||||
},
|
||||
ensure_ascii=False,
|
||||
),
|
||||
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
|
||||
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
|
||||
},
|
||||
start_time=datetime_to_nanos(trace_info.start_time),
|
||||
context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
|
||||
)
|
||||
|
||||
try:
|
||||
if trace_info.message_data.error:
|
||||
span.add_event(
|
||||
"exception",
|
||||
attributes={
|
||||
"exception.message": trace_info.message_data.error,
|
||||
"exception.type": "Error",
|
||||
"exception.stacktrace": trace_info.message_data.error,
|
||||
},
|
||||
)
|
||||
finally:
|
||||
span.end(end_time=datetime_to_nanos(trace_info.end_time))
|
||||
|
||||
def suggested_question_trace(self, trace_info: SuggestedQuestionTraceInfo):
|
||||
if trace_info.message_data is None:
|
||||
return
|
||||
|
||||
start_time = trace_info.start_time or trace_info.message_data.created_at
|
||||
end_time = trace_info.end_time or trace_info.message_data.updated_at
|
||||
|
||||
metadata = {
|
||||
"message_id": trace_info.message_id,
|
||||
"tool_name": "suggested_question",
|
||||
"status": trace_info.status,
|
||||
"status_message": trace_info.error or "",
|
||||
"level": "ERROR" if trace_info.error else "DEFAULT",
|
||||
"total_tokens": trace_info.total_tokens,
|
||||
"ls_provider": trace_info.model_provider or "",
|
||||
"ls_model_name": trace_info.model_id or "",
|
||||
}
|
||||
metadata.update(trace_info.metadata)
|
||||
|
||||
trace_id = uuid_to_trace_id(trace_info.message_id)
|
||||
span_id = RandomIdGenerator().generate_span_id()
|
||||
context = SpanContext(
|
||||
trace_id=trace_id,
|
||||
span_id=span_id,
|
||||
is_remote=False,
|
||||
trace_flags=TraceFlags(TraceFlags.SAMPLED),
|
||||
trace_state=TraceState(),
|
||||
)
|
||||
|
||||
span = self.tracer.start_span(
|
||||
name=TraceTaskName.SUGGESTED_QUESTION_TRACE.value,
|
||||
attributes={
|
||||
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
|
||||
SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.suggested_question, ensure_ascii=False),
|
||||
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
|
||||
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
|
||||
},
|
||||
start_time=datetime_to_nanos(start_time),
|
||||
context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
|
||||
)
|
||||
|
||||
try:
|
||||
if trace_info.error:
|
||||
span.add_event(
|
||||
"exception",
|
||||
attributes={
|
||||
"exception.message": trace_info.error,
|
||||
"exception.type": "Error",
|
||||
"exception.stacktrace": trace_info.error,
|
||||
},
|
||||
)
|
||||
finally:
|
||||
span.end(end_time=datetime_to_nanos(end_time))
|
||||
|
||||
def dataset_retrieval_trace(self, trace_info: DatasetRetrievalTraceInfo):
|
||||
if trace_info.message_data is None:
|
||||
return
|
||||
|
||||
start_time = trace_info.start_time or trace_info.message_data.created_at
|
||||
end_time = trace_info.end_time or trace_info.message_data.updated_at
|
||||
|
||||
metadata = {
|
||||
"message_id": trace_info.message_id,
|
||||
"tool_name": "dataset_retrieval",
|
||||
"status": trace_info.message_data.status,
|
||||
"status_message": trace_info.message_data.error or "",
|
||||
"level": "ERROR" if trace_info.message_data.error else "DEFAULT",
|
||||
"ls_provider": trace_info.message_data.model_provider or "",
|
||||
"ls_model_name": trace_info.message_data.model_id or "",
|
||||
}
|
||||
metadata.update(trace_info.metadata)
|
||||
|
||||
trace_id = uuid_to_trace_id(trace_info.message_id)
|
||||
span_id = RandomIdGenerator().generate_span_id()
|
||||
context = SpanContext(
|
||||
trace_id=trace_id,
|
||||
span_id=span_id,
|
||||
is_remote=False,
|
||||
trace_flags=TraceFlags(TraceFlags.SAMPLED),
|
||||
trace_state=TraceState(),
|
||||
)
|
||||
|
||||
span = self.tracer.start_span(
|
||||
name=TraceTaskName.DATASET_RETRIEVAL_TRACE.value,
|
||||
attributes={
|
||||
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
|
||||
SpanAttributes.OUTPUT_VALUE: json.dumps({"documents": trace_info.documents}, ensure_ascii=False),
|
||||
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.RETRIEVER.value,
|
||||
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
|
||||
"start_time": start_time.isoformat() if start_time else "",
|
||||
"end_time": end_time.isoformat() if end_time else "",
|
||||
},
|
||||
start_time=datetime_to_nanos(start_time),
|
||||
context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
|
||||
)
|
||||
|
||||
try:
|
||||
if trace_info.message_data.error:
|
||||
span.add_event(
|
||||
"exception",
|
||||
attributes={
|
||||
"exception.message": trace_info.message_data.error,
|
||||
"exception.type": "Error",
|
||||
"exception.stacktrace": trace_info.message_data.error,
|
||||
},
|
||||
)
|
||||
finally:
|
||||
span.end(end_time=datetime_to_nanos(end_time))
|
||||
|
||||
def tool_trace(self, trace_info: ToolTraceInfo):
|
||||
if trace_info.message_data is None:
|
||||
logger.warning("[Arize/Phoenix] Message data is None, skipping tool trace.")
|
||||
return
|
||||
|
||||
metadata = {
|
||||
"message_id": trace_info.message_id,
|
||||
"tool_config": json.dumps(trace_info.tool_config, ensure_ascii=False),
|
||||
}
|
||||
|
||||
trace_id = uuid_to_trace_id(trace_info.message_id)
|
||||
tool_span_id = RandomIdGenerator().generate_span_id()
|
||||
logger.info(f"[Arize/Phoenix] Creating tool trace with trace_id: {trace_id}, span_id: {tool_span_id}")
|
||||
|
||||
# Create span context with the same trace_id as the parent
|
||||
# todo: Create with the appropriate parent span context, so that the tool span is
|
||||
# a child of the appropriate span (e.g. message span)
|
||||
span_context = SpanContext(
|
||||
trace_id=trace_id,
|
||||
span_id=tool_span_id,
|
||||
is_remote=False,
|
||||
trace_flags=TraceFlags(TraceFlags.SAMPLED),
|
||||
trace_state=TraceState(),
|
||||
)
|
||||
|
||||
tool_params_str = (
|
||||
json.dumps(trace_info.tool_parameters, ensure_ascii=False)
|
||||
if isinstance(trace_info.tool_parameters, dict)
|
||||
else str(trace_info.tool_parameters)
|
||||
)
|
||||
|
||||
span = self.tracer.start_span(
|
||||
name=trace_info.tool_name,
|
||||
attributes={
|
||||
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.tool_inputs, ensure_ascii=False),
|
||||
SpanAttributes.OUTPUT_VALUE: trace_info.tool_outputs,
|
||||
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.TOOL.value,
|
||||
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
|
||||
SpanAttributes.TOOL_NAME: trace_info.tool_name,
|
||||
SpanAttributes.TOOL_PARAMETERS: tool_params_str,
|
||||
},
|
||||
start_time=datetime_to_nanos(trace_info.start_time),
|
||||
context=trace.set_span_in_context(trace.NonRecordingSpan(span_context)),
|
||||
)
|
||||
|
||||
try:
|
||||
if trace_info.error:
|
||||
span.add_event(
|
||||
"exception",
|
||||
attributes={
|
||||
"exception.message": trace_info.error,
|
||||
"exception.type": "Error",
|
||||
"exception.stacktrace": trace_info.error,
|
||||
},
|
||||
)
|
||||
finally:
|
||||
span.end(end_time=datetime_to_nanos(trace_info.end_time))
|
||||
|
||||
def generate_name_trace(self, trace_info: GenerateNameTraceInfo):
|
||||
if trace_info.message_data is None:
|
||||
return
|
||||
|
||||
metadata = {
|
||||
"project_name": self.project,
|
||||
"message_id": trace_info.message_id,
|
||||
"status": trace_info.message_data.status,
|
||||
"status_message": trace_info.message_data.error or "",
|
||||
"level": "ERROR" if trace_info.message_data.error else "DEFAULT",
|
||||
}
|
||||
metadata.update(trace_info.metadata)
|
||||
|
||||
trace_id = uuid_to_trace_id(trace_info.message_id)
|
||||
span_id = RandomIdGenerator().generate_span_id()
|
||||
context = SpanContext(
|
||||
trace_id=trace_id,
|
||||
span_id=span_id,
|
||||
is_remote=False,
|
||||
trace_flags=TraceFlags(TraceFlags.SAMPLED),
|
||||
trace_state=TraceState(),
|
||||
)
|
||||
|
||||
span = self.tracer.start_span(
|
||||
name=TraceTaskName.GENERATE_NAME_TRACE.value,
|
||||
attributes={
|
||||
SpanAttributes.INPUT_VALUE: json.dumps(trace_info.inputs, ensure_ascii=False),
|
||||
SpanAttributes.OUTPUT_VALUE: json.dumps(trace_info.outputs, ensure_ascii=False),
|
||||
SpanAttributes.OPENINFERENCE_SPAN_KIND: OpenInferenceSpanKindValues.CHAIN.value,
|
||||
SpanAttributes.METADATA: json.dumps(metadata, ensure_ascii=False),
|
||||
SpanAttributes.SESSION_ID: trace_info.message_data.conversation_id,
|
||||
"start_time": trace_info.start_time.isoformat() if trace_info.start_time else "",
|
||||
"end_time": trace_info.end_time.isoformat() if trace_info.end_time else "",
|
||||
},
|
||||
start_time=datetime_to_nanos(trace_info.start_time),
|
||||
context=trace.set_span_in_context(trace.NonRecordingSpan(context)),
|
||||
)
|
||||
|
||||
try:
|
||||
if trace_info.message_data.error:
|
||||
span.add_event(
|
||||
"exception",
|
||||
attributes={
|
||||
"exception.message": trace_info.message_data.error,
|
||||
"exception.type": "Error",
|
||||
"exception.stacktrace": trace_info.message_data.error,
|
||||
},
|
||||
)
|
||||
finally:
|
||||
span.end(end_time=datetime_to_nanos(trace_info.end_time))
|
||||
|
||||
def api_check(self):
|
||||
try:
|
||||
with self.tracer.start_span("api_check") as span:
|
||||
span.set_attribute("test", "true")
|
||||
return True
|
||||
except Exception as e:
|
||||
logger.info(f"[Arize/Phoenix] API check failed: {str(e)}", exc_info=True)
|
||||
raise ValueError(f"[Arize/Phoenix] API check failed: {str(e)}")
|
||||
|
||||
def get_project_url(self):
|
||||
try:
|
||||
if self.arize_phoenix_config.endpoint == "https://otlp.arize.com":
|
||||
return "https://app.arize.com/"
|
||||
else:
|
||||
return f"{self.arize_phoenix_config.endpoint}/projects/"
|
||||
except Exception as e:
|
||||
logger.info(f"[Arize/Phoenix] Get run url failed: {str(e)}", exc_info=True)
|
||||
raise ValueError(f"[Arize/Phoenix] Get run url failed: {str(e)}")
|
||||
|
||||
def _get_workflow_nodes(self, workflow_run_id: str):
|
||||
"""Helper method to get workflow nodes"""
|
||||
workflow_nodes = (
|
||||
db.session.query(
|
||||
WorkflowNodeExecutionModel.id,
|
||||
WorkflowNodeExecutionModel.tenant_id,
|
||||
WorkflowNodeExecutionModel.app_id,
|
||||
WorkflowNodeExecutionModel.title,
|
||||
WorkflowNodeExecutionModel.node_type,
|
||||
WorkflowNodeExecutionModel.status,
|
||||
WorkflowNodeExecutionModel.inputs,
|
||||
WorkflowNodeExecutionModel.outputs,
|
||||
WorkflowNodeExecutionModel.created_at,
|
||||
WorkflowNodeExecutionModel.elapsed_time,
|
||||
WorkflowNodeExecutionModel.process_data,
|
||||
WorkflowNodeExecutionModel.execution_metadata,
|
||||
)
|
||||
.filter(WorkflowNodeExecutionModel.workflow_run_id == workflow_run_id)
|
||||
.all()
|
||||
)
|
||||
return workflow_nodes
|
||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,17 @@
|
||||
<svg id="Layer_2" data-name="Layer 2" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 111 24" width="111" height="24">
|
||||
<g id="Layer_1-2" data-name="Layer 1">
|
||||
<rect style="fill: none;" y="0" width="111" height="24"/>
|
||||
<g id="Arize_-_standard" data-name="Arize - standard">
|
||||
<g>
|
||||
<path d="M100.94,14.55h-11.29c0,.13-.01.23.02.31.53,1.55,1.54,2.59,3.19,2.88,1.7.29,3.22,0,4.3-1.52.09-.13.28-.27.43-.28.99-.02,1.99-.01,2.99-.01-.16,2.69-3.89,4.98-7.6,4.7-3.99-.3-6.91-3.79-6.58-7.88.37-4.62,3.67-7.31,8.37-6.85,4.05.4,6.68,4.04,6.19,8.64ZM89.71,11.66h7.96c-.43-1.88-2.04-3.02-4.17-2.97-1.87.04-3.48,1.3-3.78,2.97Z"/>
|
||||
<path style="fill: #ff008c;" d="M20.81,2.53c.59-.03,1.11.26,1.49.8,3.05,4.38,6.09,8.77,9.13,13.16.63.91.43,1.99-.43,2.59-.84.59-1.97.35-2.62-.57-2.1-3.01-4.19-6.04-6.28-9.05-.04-.06-.08-.11-.12-.17-.83-1.17-1.65-1.18-2.47,0-2.11,3.05-4.23,6.09-6.34,9.14-.35.5-.77.88-1.4.95-.77.08-1.39-.19-1.79-.86-.41-.69-.38-1.38.07-2.03,1.01-1.47,2.04-2.93,3.06-4.4,2.01-2.89,4.03-5.77,6.03-8.67.39-.56.88-.9,1.67-.89Z"/>
|
||||
<path d="M52.84,20.43h-3.02v-1.16c-.1.02-.16.01-.19.03-2.46,1.73-5.09,1.88-7.68.51-2.61-1.38-3.71-3.77-3.68-6.67.03-3.26,1.82-5.96,4.64-6.86,2.35-.75,4.64-.67,6.69.93.04.03.09.03.2.07v-1.18h3.03v14.31ZM41.36,13.32c.01.17.02.46.05.75.22,2.09,1.76,3.58,3.91,3.76,2.1.18,3.8-.95,4.38-2.96.14-.47.2-.98.22-1.47.13-3.22-2.25-5.27-5.33-4.61-1.92.41-3.19,2.14-3.23,4.53Z"/>
|
||||
<path d="M80.41,8.9h-7.44v-2.77h11.64c0,.81.02,1.61-.01,2.41,0,.17-.19.35-.32.51-2.28,2.68-4.57,5.36-6.85,8.04-.11.13-.21.26-.38.47h7.53v2.86h-11.74c0-.82-.02-1.62.01-2.42,0-.16.17-.33.28-.47,2.32-2.74,4.64-5.47,6.96-8.21.09-.1.16-.21.32-.42Z"/>
|
||||
<path d="M59.39,20.54h-3.03V6.22h3.03v1.54c.8-.48,1.55-1.01,2.37-1.41.85-.41,1.79-.41,2.77-.35v2.94c-.16.01-.3.03-.45.03-2.37.03-4.01,1.36-4.51,3.69-.12.57-.16,1.16-.16,1.74-.02,1.85,0,3.71,0,5.56v.57Z"/>
|
||||
<path d="M67.1,6.09h2.99v14.33h-2.99V6.09Z"/>
|
||||
<path style="fill: #ff008c;" d="M20.73,19.53c1.25,0,2.24.96,2.25,2.19.01,1.24-1.02,2.29-2.24,2.28-1.23-.01-2.21-1.01-2.22-2.24,0-1.25.96-2.22,2.21-2.22Z"/>
|
||||
<path d="M70.7,2.11c0,1.19-.92,2.14-2.09,2.15-1.19.01-2.16-.95-2.16-2.14C66.46.95,67.4,0,68.58,0c1.18,0,2.12.93,2.12,2.11Z"/>
|
||||
</g>
|
||||
</g>
|
||||
</g>
|
||||
</svg>
|
||||
|
After Width: | Height: | Size: 2.2 KiB |
@ -0,0 +1,17 @@
|
||||
<svg id="Layer_2" data-name="Layer 2" xmlns="http://www.w3.org/2000/svg" viewBox="0 0 74 16" width="74" height="16">
|
||||
<g id="Layer_1-2" data-name="Layer 1">
|
||||
<rect style="fill: none;" y="0" width="74" height="16"/>
|
||||
<g id="Arize_-_standard" data-name="Arize - standard">
|
||||
<g>
|
||||
<path d="M67.29,9.7h-7.52c0,.08,0,.15.01.21.35,1.03,1.03,1.73,2.13,1.92,1.13.19,2.14,0,2.86-1.01.06-.09.19-.18.29-.19.66-.02,1.33,0,1.99,0-.1,1.79-2.59,3.32-5.07,3.14-2.66-.2-4.61-2.53-4.39-5.25.25-3.08,2.44-4.88,5.58-4.56,2.7.27,4.45,2.69,4.12,5.76ZM59.81,7.77h5.3c-.28-1.25-1.36-2.01-2.78-1.98-1.25.03-2.32.87-2.52,1.98Z"/>
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"name": "path",
|
||||
"attributes": {
|
||||
"d": "M47.13,1.41c0,.8-.61,1.43-1.39,1.43-.8,0-1.44-.63-1.44-1.43,0-.78.63-1.41,1.42-1.41.79,0,1.41.62,1.41,1.41Z"
|
||||
},
|
||||
"children": []
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
"name": "ArizeIcon"
|
||||
}
|
||||
@ -0,0 +1,20 @@
|
||||
// GENERATE BY script
|
||||
// DON NOT EDIT IT MANUALLY
|
||||
|
||||
import * as React from 'react'
|
||||
import data from './ArizeIcon.json'
|
||||
import IconBase from '@/app/components/base/icons/IconBase'
|
||||
import type { IconData } from '@/app/components/base/icons/IconBase'
|
||||
|
||||
const Icon = (
|
||||
{
|
||||
ref,
|
||||
...props
|
||||
}: React.SVGProps<SVGSVGElement> & {
|
||||
ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
|
||||
},
|
||||
) => <IconBase {...props} ref={ref} data={data as IconData} />
|
||||
|
||||
Icon.displayName = 'ArizeIcon'
|
||||
|
||||
export default Icon
|
||||
@ -0,0 +1,122 @@
|
||||
{
|
||||
"icon": {
|
||||
"type": "element",
|
||||
"isRootNode": true,
|
||||
"name": "svg",
|
||||
"attributes": {
|
||||
"id": "Layer_2",
|
||||
"data-name": "Layer 2",
|
||||
"xmlns": "http://www.w3.org/2000/svg",
|
||||
"viewBox": "0 0 111 24",
|
||||
"width": "111",
|
||||
"height": "24"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "g",
|
||||
"attributes": {
|
||||
"id": "Layer_1-2",
|
||||
"data-name": "Layer 1"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "rect",
|
||||
"attributes": {
|
||||
"style": "fill: none;",
|
||||
"y": "0",
|
||||
"width": "111",
|
||||
"height": "24"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "g",
|
||||
"attributes": {
|
||||
"id": "Arize_-_standard",
|
||||
"data-name": "Arize - standard"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "g",
|
||||
"attributes": {},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"d": "M100.94,14.55h-11.29c0,.13-.01.23.02.31.53,1.55,1.54,2.59,3.19,2.88,1.7.29,3.22,0,4.3-1.52.09-.13.28-.27.43-.28.99-.02,1.99-.01,2.99-.01-.16,2.69-3.89,4.98-7.6,4.7-3.99-.3-6.91-3.79-6.58-7.88.37-4.62,3.67-7.31,8.37-6.85,4.05.4,6.68,4.04,6.19,8.64ZM89.71,11.66h7.96c-.43-1.88-2.04-3.02-4.17-2.97-1.87.04-3.48,1.3-3.78,2.97Z"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"style": "fill: #ff008c;",
|
||||
"d": "M20.81,2.53c.59-.03,1.11.26,1.49.8,3.05,4.38,6.09,8.77,9.13,13.16.63.91.43,1.99-.43,2.59-.84.59-1.97.35-2.62-.57-2.1-3.01-4.19-6.04-6.28-9.05-.04-.06-.08-.11-.12-.17-.83-1.17-1.65-1.18-2.47,0-2.11,3.05-4.23,6.09-6.34,9.14-.35.5-.77.88-1.4.95-.77.08-1.39-.19-1.79-.86-.41-.69-.38-1.38.07-2.03,1.01-1.47,2.04-2.93,3.06-4.4,2.01-2.89,4.03-5.77,6.03-8.67.39-.56.88-.9,1.67-.89Z"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"d": "M52.84,20.43h-3.02v-1.16c-.1.02-.16.01-.19.03-2.46,1.73-5.09,1.88-7.68.51-2.61-1.38-3.71-3.77-3.68-6.67.03-3.26,1.82-5.96,4.64-6.86,2.35-.75,4.64-.67,6.69.93.04.03.09.03.2.07v-1.18h3.03v14.31ZM41.36,13.32c.01.17.02.46.05.75.22,2.09,1.76,3.58,3.91,3.76,2.1.18,3.8-.95,4.38-2.96.14-.47.2-.98.22-1.47.13-3.22-2.25-5.27-5.33-4.61-1.92.41-3.19,2.14-3.23,4.53Z"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"d": "M80.41,8.9h-7.44v-2.77h11.64c0,.81.02,1.61-.01,2.41,0,.17-.19.35-.32.51-2.28,2.68-4.57,5.36-6.85,8.04-.11.13-.21.26-.38.47h7.53v2.86h-11.74c0-.82-.02-1.62.01-2.42,0-.16.17-.33.28-.47,2.32-2.74,4.64-5.47,6.96-8.21.09-.1.16-.21.32-.42Z"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"d": "M59.39,20.54h-3.03V6.22h3.03v1.54c.8-.48,1.55-1.01,2.37-1.41.85-.41,1.79-.41,2.77-.35v2.94c-.16.01-.3.03-.45.03-2.37.03-4.01,1.36-4.51,3.69-.12.57-.16,1.16-.16,1.74-.02,1.85,0,3.71,0,5.56v.57Z"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"d": "M67.1,6.09h2.99v14.33h-2.99V6.09Z"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"style": "fill: #ff008c;",
|
||||
"d": "M20.73,19.53c1.25,0,2.24.96,2.25,2.19.01,1.24-1.02,2.29-2.24,2.28-1.23-.01-2.21-1.01-2.22-2.24,0-1.25.96-2.22,2.21-2.22Z"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"d": "M70.7,2.11c0,1.19-.92,2.14-2.09,2.15-1.19.01-2.16-.95-2.16-2.14C66.46.95,67.4,0,68.58,0c1.18,0,2.12.93,2.12,2.11Z"
|
||||
},
|
||||
"children": []
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
"name": "ArizeIconBig"
|
||||
}
|
||||
@ -0,0 +1,20 @@
|
||||
// GENERATE BY script
|
||||
// DON NOT EDIT IT MANUALLY
|
||||
|
||||
import * as React from 'react'
|
||||
import data from './ArizeIconBig.json'
|
||||
import IconBase from '@/app/components/base/icons/IconBase'
|
||||
import type { IconData } from '@/app/components/base/icons/IconBase'
|
||||
|
||||
const Icon = (
|
||||
{
|
||||
ref,
|
||||
...props
|
||||
}: React.SVGProps<SVGSVGElement> & {
|
||||
ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
|
||||
},
|
||||
) => <IconBase {...props} ref={ref} data={data as IconData} />
|
||||
|
||||
Icon.displayName = 'ArizeIconBig'
|
||||
|
||||
export default Icon
|
||||
@ -0,0 +1,853 @@
|
||||
{
|
||||
"icon": {
|
||||
"type": "element",
|
||||
"isRootNode": true,
|
||||
"name": "svg",
|
||||
"attributes": {
|
||||
"id": "Layer_2",
|
||||
"data-name": "Layer 2",
|
||||
"xmlns": "http://www.w3.org/2000/svg",
|
||||
"xmlns:xlink": "http://www.w3.org/1999/xlink",
|
||||
"viewBox": "0 0 74 16",
|
||||
"width": "74",
|
||||
"height": "16"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "defs",
|
||||
"attributes": {},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient",
|
||||
"x1": "6.05",
|
||||
"y1": ".98",
|
||||
"x2": "13.18",
|
||||
"y2": "13.34",
|
||||
"gradientUnits": "userSpaceOnUse"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "0",
|
||||
"stop-color": "#11bab5"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".5",
|
||||
"stop-color": "#00adee"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "1",
|
||||
"stop-color": "#0094c5"
|
||||
},
|
||||
"children": []
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient-2",
|
||||
"x1": "12.99",
|
||||
"y1": "10.87",
|
||||
"x2": "6.97",
|
||||
"y2": ".45",
|
||||
"gradientUnits": "userSpaceOnUse"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "0",
|
||||
"stop-color": "#fcfdff",
|
||||
"stop-opacity": "0"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".12",
|
||||
"stop-color": "#fcfdff",
|
||||
"stop-opacity": ".17"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".3",
|
||||
"stop-color": "#fcfdff",
|
||||
"stop-opacity": ".42"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".47",
|
||||
"stop-color": "#fcfdff",
|
||||
"stop-opacity": ".63"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".64",
|
||||
"stop-color": "#fcfdff",
|
||||
"stop-opacity": ".79"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".78",
|
||||
"stop-color": "#fcfdff",
|
||||
"stop-opacity": ".9"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".91",
|
||||
"stop-color": "#fcfdff",
|
||||
"stop-opacity": ".97"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "1",
|
||||
"stop-color": "#fcfdff"
|
||||
},
|
||||
"children": []
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient-3",
|
||||
"x1": "11.21",
|
||||
"y1": "10.8",
|
||||
"x2": "6.88",
|
||||
"y2": "3.29",
|
||||
"xlink:href": "#linear-gradient-2"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient-4",
|
||||
"x1": "10.62",
|
||||
"y1": "11.35",
|
||||
"x2": "8.2",
|
||||
"y2": "7.16",
|
||||
"xlink:href": "#linear-gradient-2"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient-5",
|
||||
"x1": "10.72",
|
||||
"y1": "12.2",
|
||||
"x2": "9.21",
|
||||
"y2": "9.59",
|
||||
"xlink:href": "#linear-gradient-2"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient-6",
|
||||
"x1": "8.17",
|
||||
"y1": "11.96",
|
||||
"x2": "8.17",
|
||||
"y2": "14.71",
|
||||
"gradientUnits": "userSpaceOnUse"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "0",
|
||||
"stop-color": "#231f20"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".03",
|
||||
"stop-color": "#231f20",
|
||||
"stop-opacity": ".9"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".22",
|
||||
"stop-color": "#231f20",
|
||||
"stop-opacity": ".4"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".42",
|
||||
"stop-color": "#231f20",
|
||||
"stop-opacity": ".1"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".65",
|
||||
"stop-color": "#231f20",
|
||||
"stop-opacity": "0"
|
||||
},
|
||||
"children": []
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "Fade_to_Black_2",
|
||||
"data-name": "Fade to Black 2",
|
||||
"x1": "11.26",
|
||||
"y1": "11.7",
|
||||
"x2": "11.26",
|
||||
"y2": "13.1",
|
||||
"gradientUnits": "userSpaceOnUse"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "0",
|
||||
"stop-color": "#231f20"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "1",
|
||||
"stop-color": "#231f20",
|
||||
"stop-opacity": "0"
|
||||
},
|
||||
"children": []
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient-7",
|
||||
"x1": "11.94",
|
||||
"y1": "8.07",
|
||||
"x2": "11.94",
|
||||
"y2": "6.92",
|
||||
"gradientUnits": "userSpaceOnUse"
|
||||
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"style": "fill: url(#linear-gradient-8); opacity: .4;",
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"children": []
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{
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: url(#Fade_to_Black_2-2); opacity: .5;",
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"d": "M16.19,9.7c-.14,0-.29.01-.43.04-.03,0-.05,0-.08,0-.04,0-.08,0-.11-.02,0,0,.01.01.02.02.06.09.1.18.11.28.02.02.03.04.04.07h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0t0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,.05,0,.07c0,.04,0,.07,0,.11,0,.05-.01.1-.02.14,0,0,0,.01,0,.02,0,.03.02.06.04.08h.02s.03.02.05.02c.03,0,.06-.01.08-.03.01-.01.02-.03.04-.04.15-.15.3-.26.45-.33.12-.05.23-.07.35-.07s.24.02.36.07c.12.05.23.11.34.19.05.03.1.07.14.12.03.03.06.05.08.08h0s.02.02.02.02h.01s.04.03.06.03c-.1-.21-.22-.41-.4-.56-.33-.29-.75-.41-1.18-.41"
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"style": "fill: url(#linear-gradient-10); opacity: .5;",
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"d": "M15,10.21l.18-.11.77-1.03s-.42-.08-.63-.17c0,0-.21.96-.99,1.77l.29-.21c.11-.08.22-.15.38-.25Z"
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{
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"type": "element",
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"name": "g",
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{
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"attributes": {
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"d": "M47.23,4.73h3.72v.74h-2.9v3.34h2.38v.74h-2.38v3.72h2.9v.76h-3.72V4.73Z"
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{
|
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: #404041;",
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"d": "M53.93,4.73h1.09l2.42,7.19v-7.19h.77v9.3h-.88l-2.64-7.93v7.93h-.76V4.73Z"
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"children": []
|
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},
|
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{
|
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"type": "element",
|
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"name": "path",
|
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"attributes": {
|
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"style": "fill: #404041;",
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"d": "M61.55,4.73h.82v9.3h-.82V4.73Z"
|
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},
|
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"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "path",
|
||||
"attributes": {
|
||||
"style": "fill: #404041;",
|
||||
"d": "M67.19,9.29l-1.82-4.56h.88l1.46,3.69,1.48-3.69h.8l-1.82,4.56,1.9,4.74h-.88l-1.54-3.91-1.55,3.91h-.8l1.9-4.74Z"
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},
|
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"children": []
|
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}
|
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]
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}
|
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]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
"name": "PhoenixIcon"
|
||||
}
|
||||
@ -0,0 +1,20 @@
|
||||
// GENERATE BY script
|
||||
// DON NOT EDIT IT MANUALLY
|
||||
|
||||
import * as React from 'react'
|
||||
import data from './PhoenixIcon.json'
|
||||
import IconBase from '@/app/components/base/icons/IconBase'
|
||||
import type { IconData } from '@/app/components/base/icons/IconBase'
|
||||
|
||||
const Icon = (
|
||||
{
|
||||
ref,
|
||||
...props
|
||||
}: React.SVGProps<SVGSVGElement> & {
|
||||
ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
|
||||
},
|
||||
) => <IconBase {...props} ref={ref} data={data as IconData} />
|
||||
|
||||
Icon.displayName = 'PhoenixIcon'
|
||||
|
||||
export default Icon
|
||||
@ -0,0 +1,853 @@
|
||||
{
|
||||
"icon": {
|
||||
"type": "element",
|
||||
"isRootNode": true,
|
||||
"name": "svg",
|
||||
"attributes": {
|
||||
"id": "Layer_2",
|
||||
"data-name": "Layer 2",
|
||||
"xmlns": "http://www.w3.org/2000/svg",
|
||||
"xmlns:xlink": "http://www.w3.org/1999/xlink",
|
||||
"viewBox": "0 0 111 24",
|
||||
"width": "111",
|
||||
"height": "24"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "defs",
|
||||
"attributes": {},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
"id": "linear-gradient",
|
||||
"x1": "9.07",
|
||||
"y1": "1.47",
|
||||
"x2": "19.77",
|
||||
"y2": "20",
|
||||
"gradientUnits": "userSpaceOnUse"
|
||||
},
|
||||
"children": [
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "0",
|
||||
"stop-color": "#11bab5"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": ".5",
|
||||
"stop-color": "#00adee"
|
||||
},
|
||||
"children": []
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "stop",
|
||||
"attributes": {
|
||||
"offset": "1",
|
||||
"stop-color": "#0094c5"
|
||||
},
|
||||
"children": []
|
||||
}
|
||||
]
|
||||
},
|
||||
{
|
||||
"type": "element",
|
||||
"name": "linearGradient",
|
||||
"attributes": {
|
||||
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"d": "M24.54,9.21c-.34.48-.77.9-1.26,1.24-.22.73-.57,1.42-1.12,2.04-.07.07-.14.14-.21.21-.07.07-.17.19-.25.19-.02,0-.03,0-.05-.02-.13-.09-.01-.27.03-.36.21-.48.37-.98.48-1.47-.35.13-.71.22-1.08.27-.05.15-.09.3-.15.44-.06.17-.14.34-.21.5-.07.14-.12.32-.3.32-.04,0-.08,0-.12-.02-.26-.09-.19-.29-.16-.47.05-.24.09-.49.12-.73-.33-.01-.65-.05-.96-.12-.03.19-.06.39-.1.58-.02.13-.08.35-.31.35-.03,0-.06,0-.09-.01,1.04.37,2.51.84,4.24,1.21h0s-.03-.01-.05-.02c-.28-.12.22-.61.45-.96.64-.98.95-2.06,1.1-3.18Z"
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},
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"children": []
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},
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{
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: url(#Fade_to_Black_2-2); opacity: .5;",
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"d": "M24.28,14.56c-.22,0-.43.02-.65.06-.04,0-.08.01-.12.01-.06,0-.12,0-.17-.03,0,.01.02.02.03.03.09.13.14.27.16.42.02.03.04.06.06.1h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0t0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0c0,0,0,0,0,0,0,0,0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,0,0,0h0s0,.07,0,.1c0,.05,0,.11,0,.17,0,.07-.02.15-.03.21,0,0,0,.02,0,.03,0,.05.02.09.06.12h.02s.05.03.07.03c.04,0,.08-.02.11-.05.02-.02.03-.04.05-.06.22-.23.44-.39.68-.49.17-.07.35-.11.53-.11s.36.04.55.11c.18.07.35.16.51.28.07.05.14.11.21.17.04.04.08.08.12.12h0s.03.04.03.04l.02.02s.06.03.09.03c-.15-.32-.33-.61-.6-.84-.5-.43-1.13-.62-1.77-.62"
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},
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"children": []
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},
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{
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: url(#linear-gradient-9); opacity: .4;",
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"d": "M24.22,12.45h-.03c-.07.01-.12.07-.13.14,0,.05,0,.11,0,.17,0,.02,0,.04-.01.05.27.4.84,1.1,1.72,1.36,0,0,1.36.71,1.01,1.74h0v-.03c.12-.31.14-.6.08-.89-.06-.28-.2-.53-.42-.76-.08-.09-.18-.17-.28-.25-.05-.04-.1-.07-.15-.1-.07-.04-.14-.08-.21-.12-.28-.14-.51-.29-.72-.44-.08-.06-.17-.13-.24-.19-.19-.16-.31-.3-.4-.45-.03-.05-.06-.1-.08-.15-.01-.02-.03-.04-.05-.05-.03-.02-.06-.03-.09-.03"
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},
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"children": []
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},
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{
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: url(#linear-gradient-10); opacity: .5;",
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"d": "M22.5,15.32l.28-.16,1.16-1.55s-.63-.12-.94-.26c0,0-.32,1.45-1.49,2.66l.43-.32c.17-.12.33-.23.56-.37Z"
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},
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"children": []
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},
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{
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"type": "element",
|
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"name": "g",
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"attributes": {},
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"children": [
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{
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: #404041;",
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"d": "M38,7.1h2.95c2.13,0,3.11,1.1,3.11,3.35v1.12c0,2.25-.98,3.35-3.11,3.35h-1.71v6.14h-1.24V7.1ZM40.95,13.78c1.3,0,1.87-.58,1.87-2.15v-1.26c0-1.55-.58-2.15-1.87-2.15h-1.71v5.56h1.71Z"
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"children": []
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: #404041;",
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"children": []
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"attributes": {
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"style": "fill: #404041;",
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"children": []
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"attributes": {
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"style": "fill: #404041;",
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"children": []
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{
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: #404041;",
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"d": "M80.9,7.1h1.63l3.63,10.78V7.1h1.16v13.95h-1.32l-3.97-11.9v11.9h-1.14V7.1Z"
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},
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"children": []
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},
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{
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"type": "element",
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"name": "path",
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"attributes": {
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"style": "fill: #404041;",
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"d": "M92.32,7.1h1.24v13.95h-1.24V7.1Z"
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},
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"children": []
|
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},
|
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{
|
||||
"type": "element",
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"name": "path",
|
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"attributes": {
|
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"style": "fill: #404041;",
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"d": "M100.79,13.94l-2.73-6.84h1.32l2.19,5.54,2.21-5.54h1.2l-2.73,6.84,2.85,7.12h-1.32l-2.31-5.86-2.33,5.86h-1.2l2.85-7.12Z"
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},
|
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"children": []
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}
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]
|
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}
|
||||
]
|
||||
}
|
||||
]
|
||||
}
|
||||
]
|
||||
},
|
||||
"name": "PhoenixIconBig"
|
||||
}
|
||||
@ -0,0 +1,20 @@
|
||||
// GENERATE BY script
|
||||
// DON NOT EDIT IT MANUALLY
|
||||
|
||||
import * as React from 'react'
|
||||
import data from './PhoenixIconBig.json'
|
||||
import IconBase from '@/app/components/base/icons/IconBase'
|
||||
import type { IconData } from '@/app/components/base/icons/IconBase'
|
||||
|
||||
const Icon = (
|
||||
{
|
||||
ref,
|
||||
...props
|
||||
}: React.SVGProps<SVGSVGElement> & {
|
||||
ref?: React.RefObject<React.MutableRefObject<HTMLOrSVGElement>>;
|
||||
},
|
||||
) => <IconBase {...props} ref={ref} data={data as IconData} />
|
||||
|
||||
Icon.displayName = 'PhoenixIconBig'
|
||||
|
||||
export default Icon
|
||||
@ -1,9 +1,13 @@
|
||||
export { default as ArizeIconBig } from './ArizeIconBig'
|
||||
export { default as ArizeIcon } from './ArizeIcon'
|
||||
export { default as LangfuseIconBig } from './LangfuseIconBig'
|
||||
export { default as LangfuseIcon } from './LangfuseIcon'
|
||||
export { default as LangsmithIconBig } from './LangsmithIconBig'
|
||||
export { default as LangsmithIcon } from './LangsmithIcon'
|
||||
export { default as OpikIconBig } from './OpikIconBig'
|
||||
export { default as OpikIcon } from './OpikIcon'
|
||||
export { default as PhoenixIconBig } from './PhoenixIconBig'
|
||||
export { default as PhoenixIcon } from './PhoenixIcon'
|
||||
export { default as TracingIcon } from './TracingIcon'
|
||||
export { default as WeaveIconBig } from './WeaveIconBig'
|
||||
export { default as WeaveIcon } from './WeaveIcon'
|
||||
|
||||
Loading…
Reference in New Issue