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from ctransformers import AutoModelForCausalLM
from fastapi import FastAPI
from pydantic import BaseModel
# Model loading with the new model name
llm = AutoModelForCausalLM.from_pretrained("sqlcoder-7b.Q4_K_S.gguf")
class Validation(BaseModel):
prompt: str # Assuming this includes both user_question and table_metadata_string
app = FastAPI()
@app.post("/generate_sql")
async def generate_sql(item: Validation):
# Updated system prompt
system_prompt = """### Task
Generate a SQL query to answer the following question:
`{question}`
### Database Schema
The query will run on a database with the following schema:
{schema}
### Answer
Given the database schema, here is the SQL query that answers `{question}`:
```sql
"""
# Format the actual prompt using item.prompt
prompt = system_prompt.format(user_question="Your question here", table_metadata_string="Your schema here")
completion = llm(prompt)
return completion
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