openrag/src/api/settings.py
2025-09-10 12:03:11 -04:00

102 lines
4.3 KiB
Python

from starlette.responses import JSONResponse
from config.settings import (
LANGFLOW_URL,
LANGFLOW_CHAT_FLOW_ID,
LANGFLOW_INGEST_FLOW_ID,
LANGFLOW_PUBLIC_URL,
clients,
)
async def get_settings(request, session_manager):
"""Get application settings"""
try:
# Return public settings that are safe to expose to frontend
settings = {
"langflow_url": LANGFLOW_URL,
"flow_id": LANGFLOW_CHAT_FLOW_ID,
"ingest_flow_id": LANGFLOW_INGEST_FLOW_ID,
"langflow_public_url": LANGFLOW_PUBLIC_URL,
}
# Only expose edit URLs when a public URL is configured
if LANGFLOW_PUBLIC_URL and LANGFLOW_CHAT_FLOW_ID:
settings["langflow_edit_url"] = (
f"{LANGFLOW_PUBLIC_URL.rstrip('/')}/flow/{LANGFLOW_CHAT_FLOW_ID}"
)
if LANGFLOW_PUBLIC_URL and LANGFLOW_INGEST_FLOW_ID:
settings["langflow_ingest_edit_url"] = (
f"{LANGFLOW_PUBLIC_URL.rstrip('/')}/flow/{LANGFLOW_INGEST_FLOW_ID}"
)
# Fetch ingestion flow configuration to get actual component defaults
if LANGFLOW_INGEST_FLOW_ID:
try:
response = await clients.langflow_request(
"GET",
f"/api/v1/flows/{LANGFLOW_INGEST_FLOW_ID}"
)
if response.status_code == 200:
flow_data = response.json()
# Extract component defaults (ingestion-specific settings only)
ingestion_defaults = {
"chunkSize": 1000,
"chunkOverlap": 200,
"separator": "\\n",
"embeddingModel": "text-embedding-3-small",
}
if flow_data.get("data", {}).get("nodes"):
for node in flow_data["data"]["nodes"]:
node_template = (
node.get("data", {})
.get("node", {})
.get("template", {})
)
# Split Text component (SplitText-QIKhg)
if node.get("id") == "SplitText-QIKhg":
if node_template.get("chunk_size", {}).get(
"value"
):
ingestion_defaults["chunkSize"] = (
node_template["chunk_size"]["value"]
)
if node_template.get("chunk_overlap", {}).get(
"value"
):
ingestion_defaults["chunkOverlap"] = (
node_template["chunk_overlap"]["value"]
)
if node_template.get("separator", {}).get(
"value"
):
ingestion_defaults["separator"] = (
node_template["separator"]["value"]
)
# OpenAI Embeddings component (OpenAIEmbeddings-joRJ6)
elif node.get("id") == "OpenAIEmbeddings-joRJ6":
if node_template.get("model", {}).get("value"):
ingestion_defaults["embeddingModel"] = (
node_template["model"]["value"]
)
# Note: OpenSearch component settings are not exposed for ingestion
# (search-related parameters like number_of_results, score_threshold
# are for retrieval, not ingestion)
settings["ingestion_defaults"] = ingestion_defaults
except Exception as e:
print(f"[WARNING] Failed to fetch ingestion flow defaults: {e}")
# Continue without ingestion defaults
return JSONResponse(settings)
except Exception as e:
return JSONResponse(
{"error": f"Failed to retrieve settings: {str(e)}"}, status_code=500
)