klbr/khoj
1
0
Fork 0
mirror of https://github.com/khoaliber/khoj.git synced 2026-03-09 05:39:12 +00:00
Code Issues Packages Projects Releases Wiki Activity

Handle reporting chat estimated cost when some fields unavailable (#1026)

Browse Source 
Fix AttributeError: 'NoneType' object has no attribute 'model_extra'

* cost = chunk.usage.model_extra.get("estimated_cost", 0) if hasattr(chunk, "usage") and chunk.usage else 0  # Estimated costs returned by DeepInfra API
This commit is contained in:
thinker007
2025-01-07 01:03:49 +08:00
committed by GitHub
parent 4aed6f7e08
commit aa442c28eb
2 changed files with 3 additions and 3 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
src/khoj/database/admin.py
View File

@@ -136,7 +136,7 @@ class KhojUserAdmin(UserAdmin, unfold_admin.ModelAdmin):
fieldsets = ( fieldsets = (
( (
"Personal info", "Personal info",
{"fields": ("phone_number", "email_verification_code", "verified_phone_number", "verified_email")}, {"fields": ("phone_number", "email_verification_code", "verified_phone_number", "verified_email","email_verification_code_expiry")},
), ),
) + UserAdmin.fieldsets ) + UserAdmin.fieldsets

4
src/khoj/processor/conversation/openai/utils.py
View File

@@ -100,7 +100,7 @@ def completion_with_backoff(
# Calculate cost of chat # Calculate cost of chat
input_tokens = chunk.usage.prompt_tokens if hasattr(chunk, "usage") and chunk.usage else 0 input_tokens = chunk.usage.prompt_tokens if hasattr(chunk, "usage") and chunk.usage else 0
output_tokens = chunk.usage.completion_tokens if hasattr(chunk, "usage") and chunk.usage else 0 output_tokens = chunk.usage.completion_tokens if hasattr(chunk, "usage") and chunk.usage else 0
cost = chunk.usage.model_extra.get("estimated_cost") or 0 # Estimated costs returned by DeepInfra API cost = chunk.usage.model_extra.get("estimated_cost", 0) if hasattr(chunk, "usage") and chunk.usage else 0 # Estimated costs returned by DeepInfra API
tracer["usage"] = get_chat_usage_metrics(model_name, input_tokens, output_tokens, tracer.get("usage"), cost) tracer["usage"] = get_chat_usage_metrics(model_name, input_tokens, output_tokens, tracer.get("usage"), cost)
# Save conversation trace # Save conversation trace
@@ -215,7 +215,7 @@ def llm_thread(
# Calculate cost of chat # Calculate cost of chat
input_tokens = chunk.usage.prompt_tokens if hasattr(chunk, "usage") and chunk.usage else 0 input_tokens = chunk.usage.prompt_tokens if hasattr(chunk, "usage") and chunk.usage else 0
output_tokens = chunk.usage.completion_tokens if hasattr(chunk, "usage") and chunk.usage else 0 output_tokens = chunk.usage.completion_tokens if hasattr(chunk, "usage") and chunk.usage else 0
cost = chunk.usage.model_extra.get("estimated_cost") or 0 # Estimated costs returned by DeepInfra API cost = chunk.usage.model_extra.get("estimated_cost", 0) if hasattr(chunk, "usage") and chunk.usage else 0 # Estimated costs returned by DeepInfra API
tracer["usage"] = get_chat_usage_metrics(model_name, input_tokens, output_tokens, tracer.get("usage"), cost) tracer["usage"] = get_chat_usage_metrics(model_name, input_tokens, output_tokens, tracer.get("usage"), cost)
# Save conversation trace # Save conversation trace