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fix: fix OPENAI_API_KEY bug in retrieval

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This commit is contained in:
Abhishek Kumar 2026-01-17 18:12:56 +05:30
parent 692ef27751
commit d35eeb1b7b
11 changed files with 508 additions and 115 deletions
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43
api/services/pipecat/run_pipeline.py
View file

@ -29,7 +29,6 @@ from api.services.pipecat.service_factory import (
create_llm_service,
create_stt_service,
create_tts_service,
create_voicemail_classification_llm,
)
from api.services.pipecat.tracing_config import setup_pipeline_tracing
from api.services.pipecat.transport_setup import (
@ -501,12 +500,21 @@ async def _run_pipeline(
node_transition_callback = send_node_transition
# Extract embeddings configuration from user config
embeddings_api_key = None
embeddings_model = None
if user_config and user_config.embeddings:
embeddings_api_key = user_config.embeddings.api_key
embeddings_model = user_config.embeddings.model
engine = PipecatEngine(
llm=llm,
workflow=workflow_graph,
call_context_vars=merged_call_context_vars,
workflow_run_id=workflow_run_id,
node_transition_callback=node_transition_callback,
embeddings_api_key=embeddings_api_key,
embeddings_model=embeddings_model,
)
# Create pipeline components with audio configuration and engine
@ -562,24 +570,23 @@ async def _run_pipeline(
voicemail_detector = None
start_node = workflow_graph.nodes.get(workflow_graph.start_node_id)
if start_node and start_node.detect_voicemail:
classification_llm = create_voicemail_classification_llm()
if classification_llm:
logger.info(
f"Voicemail detection enabled for workflow run {workflow_run_id}"
)
voicemail_detector = VoicemailDetector(
llm=classification_llm,
voicemail_response_delay=2.0,
)
logger.info(f"Voicemail detection enabled for workflow run {workflow_run_id}")
# Create a separate LLM instance for the voicemail sub-pipeline
# (can't share with main pipeline as it would mess up frame linking)
voicemail_llm = create_llm_service(user_config)
voicemail_detector = VoicemailDetector(
llm=voicemail_llm,
voicemail_response_delay=2.0,
)
# Register event handler to end task when voicemail is detected
@voicemail_detector.event_handler("on_voicemail_detected")
async def _on_voicemail_detected(_processor):
logger.info(f"Voicemail detected for workflow run {workflow_run_id}")
await engine.send_end_task_frame(
reason=EndTaskReason.VOICEMAIL_DETECTED.value,
abort_immediately=True,
)
# Register event handler to end task when voicemail is detected
@voicemail_detector.event_handler("on_voicemail_detected")
async def _on_voicemail_detected(_processor):
logger.info(f"Voicemail detected for workflow run {workflow_run_id}")
await engine.send_end_task_frame(
reason=EndTaskReason.VOICEMAIL_DETECTED.value,
abort_immediately=True,
)
# Build the pipeline with the STT mute filter and context controller
pipeline = build_pipeline(

22
api/services/pipecat/service_factory.py
View file

@ -1,4 +1,3 @@
import os
from typing import TYPE_CHECKING
from fastapi import HTTPException
@ -242,24 +241,3 @@ def create_llm_service(user_config):
)
else:
raise HTTPException(status_code=400, detail="Invalid LLM provider")
def create_voicemail_classification_llm():
"""Create a fast, lightweight LLM service for voicemail classification.
Uses gpt-4o-mini which is fast and cost-effective for simple classification tasks.
The model only needs to output "CONVERSATION" or "VOICEMAIL" based on transcriptions.
Returns:
OpenAILLMService instance, or None if OPENAI_API_KEY is not set.
"""
api_key = os.environ.get("OPENAI_API_KEY")
if not api_key:
logger.warning("OPENAI_API_KEY not set - voicemail detection will be disabled")
return None
return OpenAILLMService(
api_key=api_key,
model="gpt-4o",
params=OpenAILLMService.InputParams(temperature=0.0),
)