diff --git a/src/khoj/database/admin.py b/src/khoj/database/admin.py index 160c1544..a90a339e 100644 --- a/src/khoj/database/admin.py +++ b/src/khoj/database/admin.py @@ -136,7 +136,15 @@ class KhojUserAdmin(UserAdmin, unfold_admin.ModelAdmin): fieldsets = ( ( "Personal info", - {"fields": ("phone_number", "email_verification_code", "verified_phone_number", "verified_email","email_verification_code_expiry")}, + { + "fields": ( + "phone_number", + "email_verification_code", + "verified_phone_number", + "verified_email", + "email_verification_code_expiry", + ) + }, ), ) + UserAdmin.fieldsets diff --git a/src/khoj/processor/conversation/openai/utils.py b/src/khoj/processor/conversation/openai/utils.py index e952b767..132c5230 100644 --- a/src/khoj/processor/conversation/openai/utils.py +++ b/src/khoj/processor/conversation/openai/utils.py @@ -100,7 +100,10 @@ def completion_with_backoff( # Calculate cost of chat 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 - cost = chunk.usage.model_extra.get("estimated_cost", 0) if hasattr(chunk, "usage") and chunk.usage else 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) # Save conversation trace @@ -215,7 +218,9 @@ def llm_thread( # Calculate cost of chat 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 - cost = chunk.usage.model_extra.get("estimated_cost", 0) if hasattr(chunk, "usage") and chunk.usage else 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) # Save conversation trace