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

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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
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2
src/khoj/database/admin.py
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@@ -136,7 +136,7 @@ class KhojUserAdmin(UserAdmin, unfold_admin.ModelAdmin):
fieldsets = (
(
"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

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

@@ -100,7 +100,7 @@ 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") 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)
# Save conversation trace
@@ -215,7 +215,7 @@ 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") 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)
# Save conversation trace