forked from phoenix/litellm-mirror
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2.5 KiB
Markdown
77 lines
No EOL
2.5 KiB
Markdown
# Supabase Tutorial
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[Supabase](https://supabase.com/) is an open source Firebase alternative.
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Start your project with a Postgres database, Authentication, instant APIs, Edge Functions, Realtime subscriptions, Storage, and Vector embeddings.
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## Use Supabase to see total spend across all LLM Providers (OpenAI, Azure, Anthropic, Cohere, Replicate, PaLM)
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liteLLM provides `success_callbacks` and `failure_callbacks`, making it easy for you to send data to a particular provider depending on the status of your responses.
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In this case, we want to log requests to Supabase in both scenarios - when it succeeds and fails.
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### Create a supabase table
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Go to your Supabase project > go to the [Supabase SQL Editor](https://supabase.com/dashboard/projects) and create a new table with this configuration.
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Note: You can change the table name. Just don't change the column names.
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```sql
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create table
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public.request_logs (
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id bigint generated by default as identity,
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created_at timestamp with time zone null default now(),
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model text null default ''::text,
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messages json null default '{}'::json,
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response json null default '{}'::json,
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end_user text null default ''::text,
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error json null default '{}'::json,
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response_time real null default '0'::real,
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total_cost real null,
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additional_details json null default '{}'::json,
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constraint request_logs_pkey primary key (id)
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) tablespace pg_default;
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```
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### Use Callbacks
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Use just 2 lines of code, to instantly see costs and log your responses **across all providers** with Supabase:
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```
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litellm.success_callback=["supabase"]
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litellm.failure_callback=["supabase"]
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```
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Complete code
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```python
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from litellm import completion
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## set env variables
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os.environ["SUPABASE_URL"] = "your-supabase-url"
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os.environ["SUPABASE_key"] = "your-supabase-key"
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os.environ["OPENAI_API_KEY"] = ""
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# set callbacks
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litellm.success_callback=["supabase"]
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litellm.failure_callback=["supabase"]
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#openai call
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response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
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#bad call
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response = completion(model="chatgpt-test", messages=[{"role": "user", "content": "Hi 👋 - i'm a bad call to test error logging"}])
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```
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### Additional Controls
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**Different Table name**
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If you modified your table name, here's how to pass the new name.
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```python
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litellm.modify_integration("supabase",{"table_name": "litellm_logs"})
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```
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**Identify end-user**
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Here's how to map your llm call to an end-user
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```python
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litellm.identify({"end_user": "krrish@berri.ai"})
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``` |