update files

Dockerfile

@@ -1,21 +1,21 @@
-# 使用官方 Python 镜像
 FROM python:3.9-slim
 
-# 设置工作目录
 WORKDIR /app
 
-# 拷贝依赖和代码
-COPY requirements.txt .
-RUN pip install --no-cache-dir -r requirements.txt
+RUN apt-get update && apt-get install -y \
+    build-essential \
+    curl \
+    software-properties-common \
+    git \
+    && rm -rf /var/lib/apt/lists/*
 
-COPY . .
+COPY requirements.txt ./
+COPY src/ ./src/
 
-RUN pwd
-RUN ls -a
-RUN chmod +x start.sh
+RUN pip3 install -r requirements.txt
 
-# 设置默认端口
-ENV PORT=7860
+EXPOSE 8501
 
-# 启动 FastAPI 服务
-CMD ["./start.sh"]
+HEALTHCHECK CMD curl --fail http://localhost:8501/_stcore/health
+
+ENTRYPOINT ["streamlit", "run", "src/streamlit_app.py", "--server.port=8501", "--server.address=0.0.0.0"]

app.py

@@ -1,47 +0,0 @@
-import os
-from transformers import AutoTokenizer, AutoModelForCausalLM, T5Tokenizer, T5ForConditionalGeneration
-from peft import PeftModel
-from fastapi import FastAPI
-from pydantic import BaseModel
-from huggingface_hub import login
-
-login(token=os.getenv("HF_TOKEN"))
-print("Hugging Face Successfully Login!")
-
-app = FastAPI()
-
-# Load fine-tuned model and tokenizer
-# tokenizer = AutoTokenizer.from_pretrained("./llama2-7b", local_files_only=True)
-# base_model = AutoModelForCausalLM.from_pretrained("./llama2-7b", local_files_only=True)
-# model = PeftModel.from_pretrained(base_model, "./checkpoint-5400", local_files_only=True)
-
-
-tokenizer = T5Tokenizer.from_pretrained("google/flan-t5-small")
-model = T5ForConditionalGeneration.from_pretrained("google/flan-t5-small")
-
-# Define data structure of parameters
-class PromptInput(BaseModel):
-    prompt: str
-
-# define API interface
-# @app.post("/generate")
-# def generate_script(input: PromptInput):
-#     print("Starts Generating!")
-#     inputs = tokenizer(input.prompt, return_tensors="pt")
-#     print("Inputs Tokenized! Generating Begins~")
-#     outputs = model.generate(**inputs, max_new_tokens=200)
-#     print("Generating Succeed!")
-#     result = tokenizer.decode(outputs[0], skip_special_tokens=True)
-#     print("Results formed!")
-#     return {"generated_script": result}
-
-@app.post("/generate")
-def generate_script(input: PromptInput):
-    print("Starts Generating!")
-    inputs = tokenizer(input.prompt, return_tensors="pt").input_ids
-    print("Inputs Tokenized! Generating Begins~")
-    outputs = model.generate(inputs)
-    print("Generating Succeed!")
-    result = tokenizer.decode(outputs[0])
-    print("Results formed!")
-    return {"generated_script": result}

requirements.txt

@@ -1,45 +1,3 @@
-accelerate==1.6.0
-annotated-types==0.7.0
-anyio==4.9.0
-certifi==2025.4.26
-charset-normalizer==3.4.2
-click==8.1.8
-exceptiongroup==1.2.2
-fastapi==0.115.12
-filelock==3.18.0
-fsspec==2025.3.2
-h11==0.16.0
-httptools==0.6.4
-huggingface-hub==0.30.2
-idna==3.10
-Jinja2==3.1.6
-MarkupSafe==3.0.2
-mpmath==1.3.0
-networkx==3.2.1
-numpy==2.0.2
-packaging==25.0
-peft==0.15.2
-psutil==7.0.0
-pydantic==2.11.4
-pydantic_core==2.33.2
-python-dotenv==1.1.0
-PyYAML==6.0.2
-regex==2024.11.6
-requests==2.32.3
-safetensors==0.5.3
-sniffio==1.3.1
-starlette==0.46.2
-sympy==1.14.0
-tokenizers==0.21.1
-torch==2.7.0
-tqdm==4.67.1
-transformers==4.51.3
-typing-inspection==0.4.0
-typing_extensions==4.13.2
-urllib3==2.4.0
-uvicorn==0.34.2
-uvloop==0.21.0
-watchfiles==1.0.5
-websockets==15.0.1
-sentencepiece
+altair
+pandas
 streamlit

start.sh

@@ -1,6 +0,0 @@
-#!/bin/bash
-
-echo "✅ start.sh is running!"
-uvicorn app:app --host 0.0.0.0 --port 8000 &
-
-streamlit run ./streamlit_app.py --server.port 7860 --server.enableCORS false

streamlit_app.py

@@ -1,18 +0,0 @@
-import streamlit as st
-import requests
-
-st.title("LLaMA2 TV Script Generator")
-prompt = st.text_area("Enter your prompt:")
-
-if st.button("Generate"):
-    with st.spinner("Generating..."):
-        response = requests.post(
-            "http://localhost:8000/generate",
-            json={"prompt": prompt}
-        )
-
-        if response.ok:
-            st.markdown("### Output")
-            st.write(response.json()["generated_script"])
-        else:
-            st.error("Something went wrong.")