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Overview

The Supabase provider stores chat history, metrics, and feedback in your Supabase database.

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Features

  • ✅ Chat History - Automatic conversation storage
  • ✅ Metrics Tracking - Request performance data
  • ✅ Feedback Collection - User feedback storage
  • ✅ Auto Setup - Tables created automatically

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Basic Usage

from langchat.database import Supabase

db = Supabase(
    url="https://xxxxx.supabase.co",
    key="eyJhbGc..."
)

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Configuration

db = Supabase(
    url="https://xxxxx.supabase.co",  # Required
    key="eyJhbGc..."  # Required (anon or service role key)
)
LangChat automatically creates database tables on first run if they don’t exist.

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Using with LangChat

from langchat import LangChat
from langchat.llm import OpenAI
from langchat.vector_db import Pinecone
from langchat.database import Supabase

llm = OpenAI(api_key="sk-...", model="gpt-4o-mini")
vector_db = Pinecone(api_key="...", index_name="...")
db = Supabase(url="https://...", key="...")

ai = LangChat(llm=llm, vector_db=vector_db, db=db)

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Database Tables

LangChat uses these tables:
  • chat_history - User conversation history
  • request_metrics - Request performance metrics
  • feedback - User feedback on responses

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Table Setup

Tables are created automatically. You can also get the SQL: 
db = Supabase(url="...", key="...")
sql = db.get_create_tables_sql()
print(sql)  # SQL to create tables manually

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Best Practices

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1. Use Service Role Key for Setup

For initial setup, use service role key: 
# Setup (service role key)
db = Supabase(url="...", key="service_role_key")
db.create_tables_if_not_exist()

# Runtime (anon key)
db = Supabase(url="...", key="anon_key")

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2. Monitor Database

Check table status: 
# Tables are checked automatically
# You can verify in Supabase dashboard

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Troubleshooting

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Tables Not Created

Solution: Run create_tables_if_not_exist() or use the SQL from get_create_tables_sql().

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Permission Errors

Solution: Ensure your key has proper permissions. Use service role key for setup.

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Next Steps

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