Spaces:
Running
Running
Update app.py
Browse files
app.py
CHANGED
@@ -23,8 +23,8 @@ def detect_language(text):
|
|
23 |
openai.api_key = "YOUR_OPENAI_API_KEY"
|
24 |
|
25 |
def extract_files_from_folder(folder_path):
|
26 |
-
"""Scans a folder and its subfolders for PDF, TXT, and
|
27 |
-
extracted_files = {"pdf": [], "txt": [], "csv": []}
|
28 |
|
29 |
for root, _, files in os.walk(folder_path):
|
30 |
for file_name in files:
|
@@ -35,6 +35,8 @@ def extract_files_from_folder(folder_path):
|
|
35 |
extracted_files["txt"].append(file_path)
|
36 |
elif file_name.endswith(".csv"):
|
37 |
extracted_files["csv"].append(file_path)
|
|
|
|
|
38 |
return extracted_files
|
39 |
|
40 |
def read_text_from_files(file_paths):
|
@@ -99,15 +101,12 @@ def get_answer(question, vector_db, corrected_exercises):
|
|
99 |
|
100 |
def chatbot_interface(question):
|
101 |
folder_path = "/mnt/data/Data Analitics/"
|
102 |
-
if not folder_path:
|
103 |
-
return "Please provide a folder path before asking a question."
|
104 |
-
|
105 |
extracted_files = extract_files_from_folder(folder_path)
|
106 |
|
107 |
text = get_text_from_pdf(extracted_files["pdf"]) + read_text_from_files(extracted_files["txt"]) + get_text_from_csv(extracted_files["csv"])
|
108 |
|
109 |
if not text:
|
110 |
-
return "The folder does not contain valid PDF, TXT, or
|
111 |
|
112 |
corrected_exercises = correct_exercises(text)
|
113 |
vector_db = create_vector_database(text)
|
@@ -116,8 +115,7 @@ def chatbot_interface(question):
|
|
116 |
# Gradio interface
|
117 |
demo = gr.Interface(
|
118 |
fn=chatbot_interface,
|
119 |
-
inputs=
|
120 |
-
gr.Textbox(label="Ask a question", placeholder="Type your question here...")],
|
121 |
outputs=gr.Textbox(label="Answer")
|
122 |
)
|
123 |
|
|
|
23 |
openai.api_key = "YOUR_OPENAI_API_KEY"
|
24 |
|
25 |
def extract_files_from_folder(folder_path):
|
26 |
+
"""Scans a folder and its subfolders for PDF, TXT, CSV, and DOCX files."""
|
27 |
+
extracted_files = {"pdf": [], "txt": [], "csv": [], "docx": []}
|
28 |
|
29 |
for root, _, files in os.walk(folder_path):
|
30 |
for file_name in files:
|
|
|
35 |
extracted_files["txt"].append(file_path)
|
36 |
elif file_name.endswith(".csv"):
|
37 |
extracted_files["csv"].append(file_path)
|
38 |
+
elif file_name.endswith(".docx"):
|
39 |
+
extracted_files["docx"].append(file_path)
|
40 |
return extracted_files
|
41 |
|
42 |
def read_text_from_files(file_paths):
|
|
|
101 |
|
102 |
def chatbot_interface(question):
|
103 |
folder_path = "/mnt/data/Data Analitics/"
|
|
|
|
|
|
|
104 |
extracted_files = extract_files_from_folder(folder_path)
|
105 |
|
106 |
text = get_text_from_pdf(extracted_files["pdf"]) + read_text_from_files(extracted_files["txt"]) + get_text_from_csv(extracted_files["csv"])
|
107 |
|
108 |
if not text:
|
109 |
+
return "The folder does not contain valid PDF, TXT, CSV, or DOCX files. Please upload supported file types."
|
110 |
|
111 |
corrected_exercises = correct_exercises(text)
|
112 |
vector_db = create_vector_database(text)
|
|
|
115 |
# Gradio interface
|
116 |
demo = gr.Interface(
|
117 |
fn=chatbot_interface,
|
118 |
+
inputs=gr.Textbox(label="Ask a question", placeholder="Type your question here..."),
|
|
|
119 |
outputs=gr.Textbox(label="Answer")
|
120 |
)
|
121 |
|