Spaces:
Sleeping
Sleeping
File size: 1,681 Bytes
0c591a7 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 |
"""
Workflow execution wrapper with LangSmith tracing.
"""
from langsmith import traceable
from src.workflow.graph import app
@traceable(
name="Run - Self-Correcting SWOT Analysis",
tags=["cyclic", "quality-control", "demo"],
metadata={"purpose": "iterative_improvement"}
)
def run_self_correcting_workflow(
company_name: str = "Tesla",
ticker: str = "",
strategy_focus: str = "Cost Leadership",
workflow_id: str = None,
progress_store: dict = None
):
"""
Execute the complete self-correcting SWOT analysis workflow.
Args:
company_name: Name of the company to analyze
ticker: Stock ticker symbol
strategy_focus: Strategic focus for analysis
workflow_id: Optional workflow ID for progress tracking
progress_store: Optional dict for storing progress updates
Returns:
Final workflow state with analysis results
"""
# Initialize state with default values
initial_state = {
"company_name": company_name,
"ticker": ticker or company_name,
"strategy_focus": strategy_focus,
"raw_data": None,
"draft_report": None,
"critique": None,
"revision_count": 0,
"messages": [],
"score": 0,
"data_source": "live",
"provider_used": None,
"sources_failed": [],
"workflow_id": workflow_id,
"progress_store": progress_store,
"error": None
}
# Execute the workflow
output = app.invoke(initial_state, config={
"configurable": {
"workflow_id": workflow_id,
"progress_store": progress_store
}
})
return output
|