| # from fastapi import FastAPI | |
| # from fastapi.staticfiles import StaticFiles | |
| # from fastapi.responses import FileResponse | |
| # from transformers import pipeline | |
| # app = FastAPI() | |
| # pipe_flan = pipeline("text2text-generation", model="FreedomIntelligence/Apollo-2B",trust_remote_code=True) | |
| # @app.get("/infer_t5") | |
| # def t5(input): | |
| # output = pipe_flan(input) | |
| # return {"output": output[0]["generated_text"]} | |
| # app.mount("/", StaticFiles(directory="static", html=True), name="static") | |
| # @app.get("/") | |
| # def index() -> FileResponse: | |
| # return FileResponse(path="/app/static/index.html", media_type="text/html") | |
| from fastapi import FastAPI | |
| from fastapi.staticfiles import StaticFiles | |
| from fastapi.responses import FileResponse | |
| from transformers import pipeline | |
| app = FastAPI() | |
| # 更改pipeline类型到text-generation，并使用一个示例模型（如GPT-2） | |
| pipe_gpt = pipeline("text-generation", model="FreedomIntelligence/Apollo-0.5B",trust_remote_code=True) | |
| def infer_gpt(input: str): | |
| output = pipe_gpt(input, max_length=500) # 你可以调整max_length来控制生成文本的长度 | |
| return {"output": output[0]["generated_text"]} | |
| app.mount("/", StaticFiles(directory="static", html=True), name="static") | |
| def index() -> FileResponse: | |
| return FileResponse(path="static/index.html", media_type="text/html") |