Spaces:
Runtime error
Runtime error
Upload 2 files
Browse files
app.py
ADDED
|
@@ -0,0 +1,65 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import gradio as gr
|
| 2 |
+
from haystack.nodes import FARMReader, PreProcessor, PDFToTextConverter, TfidfRetriever
|
| 3 |
+
from haystack.document_stores import InMemoryDocumentStore
|
| 4 |
+
from haystack.pipelines import ExtractiveQAPipeline
|
| 5 |
+
|
| 6 |
+
document_store = InMemoryDocumentStore()
|
| 7 |
+
model = "./artifacts/model-afwukuq2:v0/"
|
| 8 |
+
reader = FARMReader(model_name_or_path=model)
|
| 9 |
+
preprocessor = PreProcessor(
|
| 10 |
+
clean_empty_lines=True,
|
| 11 |
+
clean_whitespace=True,
|
| 12 |
+
clean_header_footer=True,
|
| 13 |
+
split_by="word",
|
| 14 |
+
split_length=100,
|
| 15 |
+
split_respect_sentence_boundary=True,
|
| 16 |
+
split_overlap=3
|
| 17 |
+
)
|
| 18 |
+
|
| 19 |
+
|
| 20 |
+
def print_answers(results):
|
| 21 |
+
fields = ["answer", "score"] # "context",
|
| 22 |
+
answers = results["answers"]
|
| 23 |
+
filtered_answers = []
|
| 24 |
+
|
| 25 |
+
for ans in answers:
|
| 26 |
+
filtered_ans = {
|
| 27 |
+
field: getattr(ans, field)
|
| 28 |
+
for field in fields
|
| 29 |
+
if getattr(ans, field) is not None
|
| 30 |
+
}
|
| 31 |
+
filtered_answers.append(filtered_ans)
|
| 32 |
+
|
| 33 |
+
return filtered_answers
|
| 34 |
+
|
| 35 |
+
|
| 36 |
+
def pdf_to_document_store(pdf_file):
|
| 37 |
+
document_store.delete_documents()
|
| 38 |
+
converter = PDFToTextConverter(
|
| 39 |
+
remove_numeric_tables=True, valid_languages=["es"])
|
| 40 |
+
documents = [converter.convert(file_path=pdf_file, meta=None)[0]]
|
| 41 |
+
preprocessed_docs = preprocessor.process(documents)
|
| 42 |
+
document_store.write_documents(preprocessed_docs)
|
| 43 |
+
return None
|
| 44 |
+
|
| 45 |
+
|
| 46 |
+
def predict(question):
|
| 47 |
+
pdf_to_document_store("data.pdf")
|
| 48 |
+
retriever = TfidfRetriever(document_store=document_store)
|
| 49 |
+
pipe = ExtractiveQAPipeline(reader, retriever)
|
| 50 |
+
result = pipe.run(query=question, params={"Retriever": {
|
| 51 |
+
"top_k": 5}, "Reader": {"top_k": 3}})
|
| 52 |
+
answers = print_answers(result)
|
| 53 |
+
return answers
|
| 54 |
+
|
| 55 |
+
|
| 56 |
+
title = "Chatbot Refugiados"
|
| 57 |
+
|
| 58 |
+
iface = gr.Interface(fn=predict,
|
| 59 |
+
inputs=[gr.inputs.Textbox(lines=3, label='Haz una pregunta')],
|
| 60 |
+
outputs="text",
|
| 61 |
+
title=title,
|
| 62 |
+
theme="huggingface",
|
| 63 |
+
examples=['Dónde pedir ayuda?', 'qué hacer al llegar a España?']
|
| 64 |
+
)
|
| 65 |
+
iface.launch()
|
data.pdf
ADDED
|
Binary file (54.2 kB). View file
|
|
|