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+## use the official Python 3.9 image
+FROM python:3.9
+
+## set the working directory to /code
+
+WORKDIR /code
+
+## copy the current directory contents in the container at /code
+
+COPY ./requirements.txt /code/requirements.txt
+
+# install the requirements.txt
+RUN pip install --no-cache-dir --upgrade -r /code/requirements.txt
+
+# set up a new user named user
+RUN useradd user
+
+# switch to the "user" user 
+USER user
+
+# set home to the user's home directory
+
+ENV HOME=/home/user \
+    PATH=/home/user/.local/bin:$PATH
+
+
+# set the working directory to the user's home directory
+
+WORKDIR $HOME/app
+
+# copy the current directory contents into the container at $HOME/app setting the owner to user
+
+COPY --chown=user . $HOME/app
+
+# start the FastApi app on port 7860
+
+CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]
+

app.py

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+# text generation
+
+from fastapi import FastAPI
+from transformers import pipeline
+
+# create a fastapi instances
+
+app = FastAPI()
+
+# initialize the text generation pipeline
+pipe = pipeline("text2text-generation", model="google/flan-t5-small")
+
+@app.get("/")
+def home():
+    return {"message":"Hello World!"}
+
+
+# get request '/generate'
+
+@app.get("/generate")
+def generate(text:str):
+    # use the pipeline to generate text from given input text
+
+    output = pipe(text)
+
+    # return the generate text in json response
+
+    return {"output":output[0]['generated_text']}
+
+

requirements.txt

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+python-dotenv
+langchain-groq
+langchain
+langchain_core
+langchain_community
+crewai
+crewai_tools
+groq
+langchainhub
+langchain_google_genai
+requests
+langchain-astradb
+SpeechRecognition
+pyaudio
+soundfile
+opencv-python
+# pyttsx3
+numpy
+sounddevice
+cartesia
+openai
+faiss-cpu
+streamlit
+pypdf
+langchain_nvidia_ai_endpoints
+langchain-huggingface
+huggingface_hub
+assemblyai
+yt-dlp
+mesop
+google-generativeai
+fastapi
+uvicorn[standard]
+sentencepiece
+torch
+transformers