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from transformers import pipeline
from fastapi import FastAPI, Request, HTTPException
from payload import SomeText
from api_contract import components_dict as api_components
from error_handling import ErrorCodes
app = FastAPI()
app=FastAPI(title="Huggingface Gen LLM gest",
version="1.0",
debug=True,
components=api_components,
swagger_ui_bundle_js= "//unpkg.com/swagger-ui-dist@3/swagger-ui-bundle.js",
swagger_ui_standalone_preset_js= "//unpkg.com/swagger-ui-dist@3/swagger-ui-standalone-preset.js",
summary="API to perform generative prompt completion using small LLM (without GPU).",
)
pipe_flan = pipeline("text2text-generation", model="google/flan-t5-small")
@app.get("/")
def read_root():
return {'detail': 'API running. Try out the endpoints in swagger'}
@app.get("/api/check-heartbeat")
def get_heartbeat():
return {"detail": "seems to be working"}
@app.post("/api/generatel-language", summary="Generate text from prompt", tags=["Generate"])
def inference(request: Request, input_prompt: SomeText):
if len(input_prompt.text) >0:
output = pipe_flan(input_prompt.text)
return {"output": output[0]["generated_text"]}
else:
raise HTTPException(status_code=400, detail = ErrorCodes.REQUEST_VALIDATION_ERROR.value[1])
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