Spaces:
Running
on
Zero
Running
on
Zero
Commit
·
e65f100
1
Parent(s):
3fe9024
Refactor code for improved readability and consistency in function definitions and error handling
Browse files
app.py
CHANGED
@@ -68,15 +68,18 @@ if os.path.exists(cache_file):
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else:
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query_cache = {}
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def hash_query(query: str) -> str:
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"""Generate a unique hash for the query."""
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return hashlib.sha256(query.encode("utf-8")).hexdigest()
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def save_cache():
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"""Save the cache to a file."""
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with open(cache_file, "wb") as f:
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pickle.dump(query_cache, f)
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def init_embedding_model(
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model_name_or_path: str, model_revision: str = None, hf_token: str = None
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) -> SentenceTransformer:
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@@ -317,9 +320,7 @@ def format_search_results(abstract: str) -> tuple[pd.DataFrame, list[dict]]:
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papers = find_synergistic_papers(abstract)
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except ValueError as e:
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error_message = str(e)
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-
df = pd.DataFrame(
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[{"Error": error_message}]
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)
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return df, []
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# Convert to DataFrame for display
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@@ -475,7 +476,9 @@ def create_interface():
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key="paper_details",
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)
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analyze_btn = gr.Button("Analyze Connection", variant="primary", visible=False)
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-
with gr.Accordion(
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gr.Markdown(
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"""
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Please provide feedback on the relevance of this paper to your input.
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@@ -602,7 +605,10 @@ def create_interface():
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outputs=[paper_details_output, selected_paper_state],
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api_name=False,
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).then(
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-
lambda: (
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outputs=[analyze_btn, paper_feedback_accordion],
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api_name=False,
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)
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else:
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query_cache = {}
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+
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def hash_query(query: str) -> str:
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"""Generate a unique hash for the query."""
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return hashlib.sha256(query.encode("utf-8")).hexdigest()
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+
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def save_cache():
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"""Save the cache to a file."""
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with open(cache_file, "wb") as f:
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pickle.dump(query_cache, f)
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+
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def init_embedding_model(
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model_name_or_path: str, model_revision: str = None, hf_token: str = None
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) -> SentenceTransformer:
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papers = find_synergistic_papers(abstract)
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except ValueError as e:
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error_message = str(e)
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+
df = pd.DataFrame([{"Error": error_message}])
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return df, []
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# Convert to DataFrame for display
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key="paper_details",
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)
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analyze_btn = gr.Button("Analyze Connection", variant="primary", visible=False)
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with gr.Accordion(
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label="Feedback and Flagging", open=True, visible=False
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) as paper_feedback_accordion:
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gr.Markdown(
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"""
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Please provide feedback on the relevance of this paper to your input.
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outputs=[paper_details_output, selected_paper_state],
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api_name=False,
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).then(
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lambda: (
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gr.update(visible=True),
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gr.update(visible=True),
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), # Show analyze button and feedback accordion
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outputs=[analyze_btn, paper_feedback_accordion],
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api_name=False,
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)
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