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Add custom headers to Langflow ingestion requests

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Introduces custom headers containing JWT and owner information to the Langflow ingestion API requests for improved authentication and traceability. Also refactors debug logging and formatting for better readability and error handling in the combined upload, ingest, and delete operation.
This commit is contained in:
Edwin Jose 2025-09-25 15:45:32 -04:00
parent 44a51514a3
commit fff4a63995
1 changed files with 44 additions and 25 deletions
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69
src/services/langflow_file_service.py
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@ -130,9 +130,16 @@ class LangflowFileService:
)
# Avoid logging full payload to prevent leaking sensitive data (e.g., JWT)
headers = {
"X-Langflow-Global-Var-JWT": jwt_token,
"X-Langflow-Global-Var-Owner": owner,
"X-Langflow-Global-Var-Owner-Name": owner_name,
"X-Langflow-Global-Var-Owner-Email": owner_email,
"X-Langflow-Global-Var-Connector-Type": connector_type,
}
resp = await clients.langflow_request(
"POST", f"/api/v1/run/{self.flow_id_ingest}", json=payload
"POST", f"/api/v1/run/{self.flow_id_ingest}", json=payload, headers=headers
)
logger.debug(
"[LF] Run response", status_code=resp.status_code, reason=resp.reason_phrase
@ -168,7 +175,7 @@ class LangflowFileService:
"""
Combined upload, ingest, and delete operation.
First uploads the file, then runs ingestion on it, then optionally deletes the file.
Args:
file_tuple: File tuple (filename, content, content_type)
session_id: Optional session ID for the ingestion flow
@ -176,12 +183,12 @@ class LangflowFileService:
settings: Optional UI settings to convert to component tweaks
jwt_token: Optional JWT token for authentication
delete_after_ingest: Whether to delete the file from Langflow after ingestion (default: True)
Returns:
Combined result with upload info, ingestion result, and deletion status
"""
logger.debug("[LF] Starting combined upload and ingest operation")
# Step 1: Upload the file
try:
upload_result = await self.upload_user_file(file_tuple, jwt_token=jwt_token)
@ -190,10 +197,12 @@ class LangflowFileService:
extra={
"file_id": upload_result.get("id"),
"file_path": upload_result.get("path"),
}
},
)
except Exception as e:
logger.error("[LF] Upload failed during combined operation", extra={"error": str(e)})
logger.error(
"[LF] Upload failed during combined operation", extra={"error": str(e)}
)
raise Exception(f"Upload failed: {str(e)}")
# Step 2: Prepare for ingestion
@ -203,9 +212,11 @@ class LangflowFileService:
# Convert UI settings to component tweaks if provided
final_tweaks = tweaks.copy() if tweaks else {}
if settings:
logger.debug("[LF] Applying ingestion settings", extra={"settings": settings})
logger.debug(
"[LF] Applying ingestion settings", extra={"settings": settings}
)
# Split Text component tweaks (SplitText-QIKhg)
if (
@ -216,7 +227,9 @@ class LangflowFileService:
if "SplitText-QIKhg" not in final_tweaks:
final_tweaks["SplitText-QIKhg"] = {}
if settings.get("chunkSize"):
final_tweaks["SplitText-QIKhg"]["chunk_size"] = settings["chunkSize"]
final_tweaks["SplitText-QIKhg"]["chunk_size"] = settings[
"chunkSize"
]
if settings.get("chunkOverlap"):
final_tweaks["SplitText-QIKhg"]["chunk_overlap"] = settings[
"chunkOverlap"
@ -228,9 +241,14 @@ class LangflowFileService:
if settings.get("embeddingModel"):
if "OpenAIEmbeddings-joRJ6" not in final_tweaks:
final_tweaks["OpenAIEmbeddings-joRJ6"] = {}
final_tweaks["OpenAIEmbeddings-joRJ6"]["model"] = settings["embeddingModel"]
final_tweaks["OpenAIEmbeddings-joRJ6"]["model"] = settings[
"embeddingModel"
]
logger.debug("[LF] Final tweaks with settings applied", extra={"tweaks": final_tweaks})
logger.debug(
"[LF] Final tweaks with settings applied",
extra={"tweaks": final_tweaks},
)
# Step 3: Run ingestion
try:
@ -244,10 +262,7 @@ class LangflowFileService:
except Exception as e:
logger.error(
"[LF] Ingestion failed during combined operation",
extra={
"error": str(e),
"file_path": file_path
}
extra={"error": str(e), "file_path": file_path},
)
# Note: We could optionally delete the uploaded file here if ingestion fails
raise Exception(f"Ingestion failed: {str(e)}")
@ -256,10 +271,13 @@ class LangflowFileService:
file_id = upload_result.get("id")
delete_result = None
delete_error = None
if delete_after_ingest and file_id:
try:
logger.debug("[LF] Deleting file after successful ingestion", extra={"file_id": file_id})
logger.debug(
"[LF] Deleting file after successful ingestion",
extra={"file_id": file_id},
)
await self.delete_user_file(file_id)
delete_result = {"status": "deleted", "file_id": file_id}
logger.debug("[LF] File deleted successfully")
@ -267,26 +285,27 @@ class LangflowFileService:
delete_error = str(e)
logger.warning(
"[LF] Failed to delete file after ingestion",
extra={
"error": delete_error,
"file_id": file_id
}
extra={"error": delete_error, "file_id": file_id},
)
delete_result = {"status": "delete_failed", "file_id": file_id, "error": delete_error}
delete_result = {
"status": "delete_failed",
"file_id": file_id,
"error": delete_error,
}
# Return combined result
result = {
"status": "success",
"upload": upload_result,
"ingestion": ingest_result,
"message": f"File '{upload_result.get('name')}' uploaded and ingested successfully"
"message": f"File '{upload_result.get('name')}' uploaded and ingested successfully",
}
if delete_after_ingest:
result["deletion"] = delete_result
if delete_result and delete_result.get("status") == "deleted":
result["message"] += " and cleaned up"
elif delete_error:
result["message"] += f" (cleanup warning: {delete_error})"
return result