feat: custom telemetry configuration

api/services/workflow/pipecat_engine.py

@@ -25,6 +25,7 @@ if TYPE_CHECKING:
     from pipecat.services.anthropic.llm import AnthropicLLMService
     from pipecat.services.google.llm import GoogleLLMService
     from pipecat.services.openai.llm import OpenAILLMService
+    from pipecat.utils.tracing.tracing_context import TracingContext
 
     LLMService = Union[OpenAILLMService, AnthropicLLMService, GoogleLLMService]
 
@@ -135,7 +136,9 @@ class PipecatEngine:
         Returns the turn-level context if available, otherwise the
         conversation-level context, or None.
         """
-        tracing_ctx = getattr(self.task, "_tracing_context", None)
+        tracing_ctx: TracingContext | None = getattr(
+            self.task, "_tracing_context", None
+        )
         if not tracing_ctx:
             return None
         return tracing_ctx.get_turn_context() or tracing_ctx.get_conversation_context()
@@ -439,6 +442,10 @@ class PipecatEngine:
                     )
                 )
                 self._gathered_context.update(extracted_data)
+                extracted_variables = self._gathered_context.setdefault(
+                    "extracted_variables", {}
+                )
+                extracted_variables.update(extracted_data)
                 logger.debug(
                     f"Variable extraction completed. Extracted: {extracted_data}"
                 )

api/services/workflow/pipecat_engine_variable_extractor.py

@@ -7,7 +7,7 @@ from loguru import logger
 from opentelemetry import trace
 
 from api.services.gen_ai.json_parser import parse_llm_json
-from api.services.pipecat.tracing_config import is_tracing_enabled
+from api.services.pipecat.tracing_config import ensure_tracing
 from api.services.workflow.dto import ExtractionVariableDTO
 from pipecat.processors.aggregators.llm_context import LLMContext
 from pipecat.utils.tracing.service_attributes import add_llm_span_attributes
@@ -206,7 +206,7 @@ class VariableExtractionManager:
         # Get model name for tracing
         model_name = getattr(self._engine.llm, "model_name", "unknown")
 
-        if is_tracing_enabled():
+        if ensure_tracing():
             tracer = trace.get_tracer("pipecat")
             with tracer.start_as_current_span(
                 "llm-variable-extraction", context=parent_ctx

api/services/workflow/qa/tracing.py

@@ -5,18 +5,21 @@ import re
 from loguru import logger
 
 from api.db.models import WorkflowRunModel
+from api.services.pipecat.tracing_config import get_trace_url
 
 
 def extract_trace_id(gathered_context: dict) -> str | None:
     """Extract Langfuse trace_id from gathered_context trace_url.
 
-    URL format: https://langfuse.dograh.com/project/<project_id>/traces/<trace_id>
+    Supports both URL formats:
+    - New: https://langfuse.dograh.com/trace/<trace_id>
+    - Legacy: https://langfuse.dograh.com/project/<project_id>/traces/<trace_id>
     """
     trace_url = gathered_context.get("trace_url")
     if not trace_url:
         return None
     try:
-        match = re.search(r"/traces/([a-fA-F0-9]+)$", trace_url)
+        match = re.search(r"/traces?/([a-fA-F0-9]+)$", trace_url)
         if match:
             return match.group(1)
     except Exception:
@@ -37,16 +40,11 @@ def setup_langfuse_parent_context(workflow_run: WorkflowRunModel):
             set_span_in_context,
         )
 
-        from api.services.pipecat.tracing_config import (
-            is_tracing_enabled,
-            setup_tracing_exporter,
-        )
+        from api.services.pipecat.tracing_config import ensure_tracing
 
-        if not is_tracing_enabled():
+        if not ensure_tracing():
             return None
 
-        setup_tracing_exporter()
-
         gathered_context = workflow_run.gathered_context or {}
         trace_id = extract_trace_id(gathered_context)
         if not trace_id:
@@ -114,17 +112,12 @@ def create_node_summary_trace(
         from opentelemetry import trace as otel_trace
         from opentelemetry.context import Context
 
-        from api.services.pipecat.tracing_config import (
-            is_tracing_enabled,
-            setup_tracing_exporter,
-        )
+        from api.services.pipecat.tracing_config import ensure_tracing
         from pipecat.utils.tracing.service_attributes import add_llm_span_attributes
 
-        if not is_tracing_enabled():
+        if not ensure_tracing():
             return None
 
-        setup_tracing_exporter()
-
         tracer = otel_trace.get_tracer("pipecat")
 
         # Create a root span (new trace) for this node summary generation
@@ -144,10 +137,7 @@ def create_node_summary_trace(
             )
             trace_id = format(span.get_span_context().trace_id, "032x")
 
-        from langfuse import get_client
-
-        langfuse = get_client()
-        return langfuse.get_trace_url(trace_id=trace_id)
+        return get_trace_url(trace_id)
 
     except Exception as e:
         logger.warning(f"Failed to create node summary trace for '{node_name}': {e}")

api/services/workflow/tools/knowledge_base.py

@@ -14,7 +14,7 @@ from opentelemetry import trace
 
 from api.db import db_client
 from api.services.gen_ai import OpenAIEmbeddingService
-from api.services.pipecat.tracing_config import is_tracing_enabled
+from api.services.pipecat.tracing_config import ensure_tracing
 
 
 async def retrieve_from_knowledge_base(
@@ -51,7 +51,7 @@ async def retrieve_from_knowledge_base(
         - total_results: Number of results returned
     """
     # Create span for retrieval operation if tracing is enabled
-    if is_tracing_enabled():
+    if ensure_tracing():
         try:
             parent_context = tracing_context