Spaces:
Runtime error
Runtime error
Merge branch 'main' into feature/audio_output
Browse files- .gitignore +1 -3
- .streamlit/config.toml +1 -1
- app.py +1 -1
- core/pipelines.py +13 -4
- core/search_index.py +7 -1
- interface/components.py +21 -24
- interface/config.py +5 -1
- interface/pages.py +6 -3
- requirements.txt +1 -5
.gitignore
CHANGED
@@ -128,6 +128,4 @@ dmypy.json
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# Pyre type checker
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.pyre/
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-
.vscode/
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-
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-
data/audio/
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# Pyre type checker
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.pyre/
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+
.vscode/
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.streamlit/config.toml
CHANGED
@@ -1,5 +1,5 @@
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[theme]
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-
primaryColor="#
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backgroundColor="#0e1117"
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secondaryBackgroundColor="#282929"
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textColor = "#ffffff"
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[theme]
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+
primaryColor="#e5ab00"
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backgroundColor="#0e1117"
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secondaryBackgroundColor="#282929"
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textColor = "#ffffff"
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app.py
CHANGED
@@ -29,7 +29,7 @@ def run_demo():
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with navigation:
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selected_page = option_menu(
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-
menu_title=
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options=list(pages.keys()),
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icons=[f[1] for f in pages.values()],
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menu_icon="cast",
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with navigation:
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selected_page = option_menu(
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menu_title=None,
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options=list(pages.keys()),
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icons=[f[1] for f in pages.values()],
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menu_icon="cast",
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core/pipelines.py
CHANGED
@@ -25,6 +25,8 @@ def keyword_search(index="documents", split_word_length=100, audio_output=False)
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- Documents that have more lexical overlap with the query are more likely to be relevant
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- Words that occur in fewer documents are more significant than words that occur in many documents
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"""
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document_store = InMemoryDocumentStore(index=index)
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keyword_retriever = TfidfRetriever(document_store=(document_store))
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@@ -45,10 +47,7 @@ def keyword_search(index="documents", split_word_length=100, audio_output=False)
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index_pipeline = Pipeline()
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index_pipeline.add_node(processor, name="Preprocessor", inputs=["File"])
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index_pipeline.add_node(
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-
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)
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index_pipeline.add_node(
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document_store, name="DocumentStore", inputs=["TfidfRetriever"]
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)
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if audio_output:
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@@ -68,6 +67,7 @@ def dense_passage_retrieval(
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split_word_length=100,
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query_embedding_model="facebook/dpr-question_encoder-single-nq-base",
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passage_embedding_model="facebook/dpr-ctx_encoder-single-nq-base",
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):
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"""
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**Dense Passage Retrieval Pipeline**
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@@ -104,6 +104,15 @@ def dense_passage_retrieval(
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index_pipeline.add_node(
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document_store, name="DocumentStore", inputs=["DPRRetriever"]
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)
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return search_pipeline, index_pipeline
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- Documents that have more lexical overlap with the query are more likely to be relevant
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- Words that occur in fewer documents are more significant than words that occur in many documents
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+
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+
:warning: **(HAYSTACK BUG) Keyword Search doesn't work if you reindex:** Please refresh page in order to reindex
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"""
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document_store = InMemoryDocumentStore(index=index)
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keyword_retriever = TfidfRetriever(document_store=(document_store))
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index_pipeline = Pipeline()
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index_pipeline.add_node(processor, name="Preprocessor", inputs=["File"])
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index_pipeline.add_node(
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+
document_store, name="DocumentStore", inputs=["Preprocessor"]
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)
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if audio_output:
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split_word_length=100,
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query_embedding_model="facebook/dpr-question_encoder-single-nq-base",
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passage_embedding_model="facebook/dpr-ctx_encoder-single-nq-base",
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+
audio_output=False
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):
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"""
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**Dense Passage Retrieval Pipeline**
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index_pipeline.add_node(
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document_store, name="DocumentStore", inputs=["DPRRetriever"]
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)
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+
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if audio_output:
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doc2speech = DocumentToSpeech(
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model_name_or_path="espnet/kan-bayashi_ljspeech_vits",
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generated_audio_dir=Path(data_path + "audio"),
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)
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search_pipeline.add_node(
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doc2speech, name="DocumentToSpeech", inputs=["DPRRetriever"]
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)
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return search_pipeline, index_pipeline
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core/search_index.py
CHANGED
@@ -1,4 +1,5 @@
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from haystack.schema import Document
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import uuid
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@@ -17,8 +18,12 @@ def format_docs(documents):
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return db_docs, [doc.meta["id"] for doc in db_docs]
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-
def index(documents, pipeline):
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documents, doc_ids = format_docs(documents)
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pipeline.run(documents=documents)
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return doc_ids
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@@ -36,6 +41,7 @@ def search(queries, pipeline):
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"text": res.content,
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"id": res.meta["id"],
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"fragment_id": res.id,
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}
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if not score_is_empty:
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match.update({"score": res.score})
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from haystack.schema import Document
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+
from haystack.document_stores import BaseDocumentStore
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import uuid
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return db_docs, [doc.meta["id"] for doc in db_docs]
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+
def index(documents, pipeline, clear_index=True):
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documents, doc_ids = format_docs(documents)
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if clear_index:
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+
document_stores = pipeline.get_nodes_by_class(class_type=BaseDocumentStore)
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+
for docstore in document_stores:
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+
docstore.delete_index(docstore.index)
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pipeline.run(documents=documents)
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return doc_ids
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"text": res.content,
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"id": res.meta["id"],
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"fragment_id": res.id,
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+
"meta": res.meta,
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}
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if not score_is_empty:
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match.update({"score": res.score})
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interface/components.py
CHANGED
@@ -42,11 +42,15 @@ def component_select_pipeline(container):
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"index_pipeline": index_pipeline,
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"doc": pipeline_funcs[index_pipe].__doc__,
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}
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def component_show_pipeline(pipeline, pipeline_name):
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"""Draw the pipeline"""
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-
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if pipeline["doc"] is not None:
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st.markdown(pipeline["doc"])
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fig = get_pipeline_graph(pipeline[pipeline_name])
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@@ -59,6 +63,8 @@ def component_show_search_result(container, results):
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st.markdown(f"### Match {idx+1}")
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st.markdown(f"**Text**: {document['text']}")
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st.markdown(f"**Document**: {document['id']}")
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if "score" in document:
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st.markdown(f"**Score**: {document['score']:.3f}")
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if "content_audio" in document:
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@@ -66,36 +72,32 @@ def component_show_search_result(container, results):
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st.markdown("---")
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-
def component_text_input(container):
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"""Draw the Text Input widget"""
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with container:
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texts = []
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-
doc_id = 1
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with st.expander("Enter documents"):
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while True:
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text = st.text_input(f"Document {doc_id}", key=doc_id)
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if text != "":
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-
texts.append({"text": text})
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doc_id += 1
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st.markdown("---")
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else:
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break
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-
corpus = [
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-
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-
]
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-
return corpus
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-
def component_article_url(container):
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"""Draw the Article URL widget"""
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with container:
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urls = []
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-
doc_id = 1
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with st.expander("Enter URLs"):
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while True:
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url = st.text_input(f"URL {doc_id}", key=doc_id)
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if url != "":
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-
urls.append({"text": extract_text_from_url(url)})
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doc_id += 1
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st.markdown("---")
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else:
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@@ -103,19 +105,16 @@ def component_article_url(container):
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for idx, doc in enumerate(urls):
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with st.expander(f"Preview URL {idx}"):
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-
st.write(doc)
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-
corpus = [
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-
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-
]
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-
return corpus
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-
def component_file_input(container):
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"""Draw the extract text from file widget"""
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with container:
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files = []
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-
doc_id = 1
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with st.expander("Enter Files"):
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while True:
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file = st.file_uploader(
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@@ -124,7 +123,7 @@ def component_file_input(container):
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if file != None:
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extracted_text = extract_text_from_file(file)
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if extracted_text != None:
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-
files.append({"text": extracted_text})
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doc_id += 1
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st.markdown("---")
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else:
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@@ -134,9 +133,7 @@ def component_file_input(container):
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for idx, doc in enumerate(files):
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with st.expander(f"Preview File {idx}"):
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-
st.write(doc)
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-
corpus = [
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-
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-
]
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-
return corpus
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"index_pipeline": index_pipeline,
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"doc": pipeline_funcs[index_pipe].__doc__,
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}
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+
st.session_state["doc_id"] = 0
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def component_show_pipeline(pipeline, pipeline_name):
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"""Draw the pipeline"""
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+
expander_text = "Show pipeline"
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+
if pipeline["doc"] is not None and "BUG" in pipeline["doc"]:
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+
expander_text += " ⚠️"
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+
with st.expander(expander_text):
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if pipeline["doc"] is not None:
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st.markdown(pipeline["doc"])
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fig = get_pipeline_graph(pipeline[pipeline_name])
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st.markdown(f"### Match {idx+1}")
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st.markdown(f"**Text**: {document['text']}")
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st.markdown(f"**Document**: {document['id']}")
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+
if "_split_id" in document["meta"]:
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+
st.markdown(f"**Document Chunk**: {document['meta']['_split_id']}")
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if "score" in document:
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st.markdown(f"**Score**: {document['score']:.3f}")
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if "content_audio" in document:
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st.markdown("---")
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+
def component_text_input(container, doc_id):
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"""Draw the Text Input widget"""
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with container:
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texts = []
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with st.expander("Enter documents"):
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while True:
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text = st.text_input(f"Document {doc_id}", key=doc_id)
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if text != "":
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+
texts.append({"text": text, "doc_id": doc_id})
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doc_id += 1
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st.markdown("---")
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else:
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break
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+
corpus = [{"text": doc["text"], "id": doc["doc_id"]} for doc in texts]
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+
return corpus, doc_id
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+
def component_article_url(container, doc_id):
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"""Draw the Article URL widget"""
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with container:
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urls = []
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with st.expander("Enter URLs"):
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while True:
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url = st.text_input(f"URL {doc_id}", key=doc_id)
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if url != "":
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+
urls.append({"text": extract_text_from_url(url), "doc_id": doc_id})
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doc_id += 1
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st.markdown("---")
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else:
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for idx, doc in enumerate(urls):
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with st.expander(f"Preview URL {idx}"):
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+
st.write(doc["text"])
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+
corpus = [{"text": doc["text"], "id": doc["doc_id"]} for doc in urls]
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+
return corpus, doc_id
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+
def component_file_input(container, doc_id):
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"""Draw the extract text from file widget"""
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with container:
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files = []
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with st.expander("Enter Files"):
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119 |
while True:
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file = st.file_uploader(
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if file != None:
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extracted_text = extract_text_from_file(file)
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if extracted_text != None:
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+
files.append({"text": extracted_text, "doc_id": doc_id})
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doc_id += 1
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st.markdown("---")
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else:
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|
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for idx, doc in enumerate(files):
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135 |
with st.expander(f"Preview File {idx}"):
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+
st.write(doc["text"])
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+
corpus = [{"text": doc["text"], "id": doc["doc_id"]} for doc in files]
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return corpus, doc_id
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interface/config.py
CHANGED
@@ -1,7 +1,11 @@
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from interface.pages import page_landing_page, page_search, page_index
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3 |
# Define default Session Variables over the whole session.
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-
session_state_variables = {
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5 |
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# Define Pages for the demo
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7 |
pages = {
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1 |
from interface.pages import page_landing_page, page_search, page_index
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2 |
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3 |
# Define default Session Variables over the whole session.
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4 |
+
session_state_variables = {
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+
"pipeline": None,
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6 |
+
"pipeline_func_parameters": [],
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+
"doc_id": 0,
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+
}
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# Define Pages for the demo
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pages = {
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interface/pages.py
CHANGED
@@ -79,14 +79,17 @@ def page_index(container):
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orientation="horizontal",
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)
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82 |
-
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if len(corpus) > 0:
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index_results = None
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if st.button("Index"):
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87 |
index_results = index(
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-
corpus,
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-
st.session_state["pipeline"]["index_pipeline"],
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)
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if index_results:
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st.write(index_results)
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79 |
orientation="horizontal",
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)
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81 |
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82 |
+
clear_index = st.sidebar.checkbox("Clear Index", True)
|
83 |
+
|
84 |
+
doc_id = st.session_state["doc_id"]
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85 |
+
corpus, doc_id = input_funcs[selected_input][0](container, doc_id)
|
86 |
|
87 |
if len(corpus) > 0:
|
88 |
index_results = None
|
89 |
if st.button("Index"):
|
90 |
index_results = index(
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91 |
+
corpus, st.session_state["pipeline"]["index_pipeline"], clear_index
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|
92 |
)
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93 |
+
st.session_state["doc_id"] = doc_id
|
94 |
if index_results:
|
95 |
st.write(index_results)
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requirements.txt
CHANGED
@@ -5,8 +5,4 @@ black==22.8.0
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5 |
plotly==5.10.0
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6 |
newspaper3k==0.2.8
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7 |
PyPDF2==2.10.7
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8 |
-
pytesseract==0.3.10
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9 |
-
soundfile==0.10.3.post1
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10 |
-
espnet
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11 |
-
pydub==0.25.1
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12 |
-
espnet_model_zoo==0.1.7
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5 |
plotly==5.10.0
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6 |
newspaper3k==0.2.8
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7 |
PyPDF2==2.10.7
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8 |
+
pytesseract==0.3.10
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