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# Supabase Tutorial
[Supabase](https://supabase.com/) is an open source Firebase alternative.
Start your project with a Postgres database, Authentication, instant APIs, Edge Functions, Realtime subscriptions, Storage, and Vector embeddings.
## Use Supabase to log requests and see total spend across all LLM Providers (OpenAI, Azure, Anthropic, Cohere, Replicate, PaLM)
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.
In this case, we want to log requests to Supabase in both scenarios - when it succeeds and fails.
### Create a supabase table
Go to your Supabase project > go to the [Supabase SQL Editor](https://supabase.com/dashboard/projects) and create a new table with this configuration.
Note: You can change the table name. Just don't change the column names.
```sql
create table
public.request_logs (
id bigint generated by default as identity,
created_at timestamp with time zone null default now(),
model text null default ''::text,
messages json null default '{}'::json,
response json null default '{}'::json,
end_user text null default ''::text,
error json null default '{}'::json,
response_time real null default '0'::real,
total_cost real null,
additional_details json null default '{}'::json,
constraint request_logs_pkey primary key (id)
) tablespace pg_default;
```
### Use Callbacks
Use just 2 lines of code, to instantly see costs and log your responses **across all providers** with Supabase:
```
litellm.success_callback=["supabase"]
litellm.failure_callback=["supabase"]
```
Complete code
```python
from litellm import completion
## set env variables
### SUPABASE
os.environ["SUPABASE_URL"] = "your-supabase-url"
os.environ["SUPABASE_KEY"] = "your-supabase-key"
## LLM API KEY
os.environ["OPENAI_API_KEY"] = ""
# set callbacks
litellm.success_callback=["supabase"]
litellm.failure_callback=["supabase"]
#openai call
response = completion(model="gpt-3.5-turbo", messages=[{"role": "user", "content": "Hi 👋 - i'm openai"}])
#bad call
response = completion(model="chatgpt-test", messages=[{"role": "user", "content": "Hi 👋 - i'm a bad call to test error logging"}])
```
### Additional Controls
**Different Table name**
If you modified your table name, here's how to pass the new name.
```python
litellm.modify_integration("supabase",{"table_name": "litellm_logs"})
```
**Identify end-user**
Here's how to map your llm call to an end-user
```python
litellm.identify({"end_user": "[email protected]"})
``` |