Spaces:
Running
Running
Attempting sessions states and annotations
Browse files- app.py +66 -5
- requirements.txt +2 -1
app.py
CHANGED
@@ -4,6 +4,9 @@ from haystack.schema import Answer
|
|
4 |
from haystack.document_stores import InMemoryDocumentStore
|
5 |
from haystack.pipelines import ExtractiveQAPipeline
|
6 |
from haystack.nodes import FARMReader, TfidfRetriever
|
|
|
|
|
|
|
7 |
import validators
|
8 |
import json
|
9 |
|
@@ -13,24 +16,82 @@ retriever = TfidfRetriever(document_store=document_store)
|
|
13 |
reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2", use_gpu=True)
|
14 |
pipeline = ExtractiveQAPipeline(reader, retriever)
|
15 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
16 |
def load_and_write_data():
|
17 |
doc_dir = './article_txt_got'
|
18 |
docs = convert_files_to_docs(dir_path=doc_dir, clean_func=clean_wiki_text, split_paragraphs=True)
|
19 |
|
20 |
document_store.write_documents(docs)
|
21 |
|
|
|
22 |
#Streamlit App
|
23 |
|
24 |
st.title('Game of Thrones QA with Haystack')
|
25 |
-
question = st.text_input(
|
26 |
|
27 |
load_and_write_data()
|
28 |
|
29 |
def ask_question(question):
|
30 |
prediction = pipeline.run(query=question, params={"Retriever": {"top_k": 10}, "Reader": {"top_k": 5}})
|
31 |
-
|
32 |
-
|
33 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
34 |
|
35 |
if question:
|
36 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
4 |
from haystack.document_stores import InMemoryDocumentStore
|
5 |
from haystack.pipelines import ExtractiveQAPipeline
|
6 |
from haystack.nodes import FARMReader, TfidfRetriever
|
7 |
+
import logging
|
8 |
+
from markdown import markdown
|
9 |
+
from annotated_text import annotation
|
10 |
import validators
|
11 |
import json
|
12 |
|
|
|
16 |
reader = FARMReader(model_name_or_path="deepset/tinyroberta-squad2", use_gpu=True)
|
17 |
pipeline = ExtractiveQAPipeline(reader, retriever)
|
18 |
|
19 |
+
def set_state_if_absent(key, value):
|
20 |
+
if key not in st.session_state:
|
21 |
+
st.session_state[key] = value
|
22 |
+
|
23 |
+
|
24 |
+
st.set_page_config(page_title="Game of Thrones QA with Haystack", page_icon="https://haystack.deepset.ai/img/HaystackIcon.png")
|
25 |
+
|
26 |
+
set_state_if_absent("question", "Who is Arya's father")
|
27 |
+
set_state_if_absent("results", None)
|
28 |
+
|
29 |
+
|
30 |
+
def reset_results(*args):
|
31 |
+
st.session_state.results = None
|
32 |
+
|
33 |
def load_and_write_data():
|
34 |
doc_dir = './article_txt_got'
|
35 |
docs = convert_files_to_docs(dir_path=doc_dir, clean_func=clean_wiki_text, split_paragraphs=True)
|
36 |
|
37 |
document_store.write_documents(docs)
|
38 |
|
39 |
+
|
40 |
#Streamlit App
|
41 |
|
42 |
st.title('Game of Thrones QA with Haystack')
|
43 |
+
question = st.text_input("", value=st.session_state.question, max_chars=100, on_change=reset_results)
|
44 |
|
45 |
load_and_write_data()
|
46 |
|
47 |
def ask_question(question):
|
48 |
prediction = pipeline.run(query=question, params={"Retriever": {"top_k": 10}, "Reader": {"top_k": 5}})
|
49 |
+
results = []
|
50 |
+
for answer in prediction["answers"]:
|
51 |
+
if answer.get("answer", None):
|
52 |
+
results.append(
|
53 |
+
{
|
54 |
+
"context": "..." + answer["context"] + "...",
|
55 |
+
"answer": answer.get("answer", None),
|
56 |
+
"relevance": round(answer["score"] * 100, 2),
|
57 |
+
"offset_start_in_doc": answer["offsets_in_document"][0]["start"],
|
58 |
+
}
|
59 |
+
)
|
60 |
+
else:
|
61 |
+
results.append(
|
62 |
+
{
|
63 |
+
"context": None,
|
64 |
+
"answer": None,
|
65 |
+
"relevance": round(answer["score"] * 100, 2),
|
66 |
+
}
|
67 |
+
)
|
68 |
+
return results
|
69 |
+
# st.write(prediction['answers'][0].to_dict())
|
70 |
+
# st.write(prediction['answers'][1].to_dict())
|
71 |
+
# st.write(prediction['answers'][2].to_dict())
|
72 |
+
|
73 |
|
74 |
if question:
|
75 |
+
try:
|
76 |
+
st.session_state.results = ask_question(question)
|
77 |
+
except Exception as e:
|
78 |
+
logging.exception(e)
|
79 |
+
|
80 |
+
|
81 |
+
|
82 |
+
if st.session_state.results:
|
83 |
+
st.write('## Top Results')
|
84 |
+
for count, result in enumerate(st.session_state.results):
|
85 |
+
if result["answer"]:
|
86 |
+
answer, context = result["answer"], result["context"]
|
87 |
+
start_idx = context.find(answer)
|
88 |
+
end_idx = start_idx + len(answer)
|
89 |
+
st.write(
|
90 |
+
markdown(context[:start_idx] + str(annotation(answer, "ANSWER", "#8ef")) + context[end_idx:]),
|
91 |
+
unsafe_allow_html=True,
|
92 |
+
)
|
93 |
+
st.markdown(f"**Relevance:** {result['relevance']}")
|
94 |
+
else:
|
95 |
+
st.info(
|
96 |
+
"🤔 Haystack is unsure whether any of the documents contain an answer to your question. Try to reformulate it!"
|
97 |
+
)
|
requirements.txt
CHANGED
@@ -1,2 +1,3 @@
|
|
1 |
farm-haystack==1.4.0
|
2 |
-
validators==0.18.2
|
|
|
|
1 |
farm-haystack==1.4.0
|
2 |
+
validators==0.18.2
|
3 |
+
markdown
|