add password for hf space
Browse files
config.py
CHANGED
@@ -15,6 +15,8 @@ class Config(BaseSettings):
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embedding_version: str
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embedding_dir: str
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model_name: str
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load_dotenv()
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@@ -26,4 +28,5 @@ config = Config(
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embedding_version=getenv("EMBEDDING_VERSION"),
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embedding_dir=getenv("EMBEDDING_DIR"),
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model_name=getenv("MODEL_NAME"),
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)
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embedding_version: str
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embedding_dir: str
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model_name: str
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# HF
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password: str
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load_dotenv()
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embedding_version=getenv("EMBEDDING_VERSION"),
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embedding_dir=getenv("EMBEDDING_DIR"),
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model_name=getenv("MODEL_NAME"),
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password=getenv("PASSWORD"),
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)
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main.py
CHANGED
@@ -44,21 +44,28 @@ def _get_embeddings(text: str):
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st.title("PubMed Embeddings")
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st.subheader("Search for a PubMed article and get its id.")
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with st.spinner("Loading Embedding Model..."):
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if st.button("Search"):
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st.title("PubMed Embeddings")
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st.subheader("Search for a PubMed article and get its id.")
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with st.text_input("Password", type="password") as password:
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if password == config.password:
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st.write("Password correct!")
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text = st.text_input("Search for a PubMed article", "Epidemiology of COVID-19")
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with st.spinner("Loading Embedding Model..."):
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pinecone.init(api_key=config.pinecone_api_key, env=config.pinecone_env)
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if "index" not in st.session_state:
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st.session_state.index = pinecone.Index(config.pinecone_index)
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if "tokenizer" not in st.session_state:
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st.session_state.tokenizer = AutoTokenizer.from_pretrained(config.model_name)
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if "model" not in st.session_state:
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st.session_state.model = AutoModel.from_pretrained(config.model_name)
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if st.button("Search"):
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with st.spinner("Searching..."):
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results = search(text)
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for res in results["matches"]:
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st.write(f"{res['id']} - confidence: {res['score']:.2f}")
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else:
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st.write("Password incorrect!")
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