Upload huggingface_app.py

huggingface_app.py

@@ -0,0 +1,66 @@
+import streamlit as st
+
+from run_eval import run_generate
+
+st.write("# GupShup")
+st.write("## Summarizing Open-Domain Code-Switched Conversations")
+task_type = st.sidebar.selectbox(
+    "Task type", ["Hinglish to English", "English to English"]
+)
+model_name = st.sidebar.selectbox(
+    "Model", ["Pegasus", "mBart", "Bart", "GPT", "T5", "T5_MTL"]
+)
+
+
+default_value = "summarize: Debanjan: Hi! kya tum EMNLP attend kar rahein ho? Anish: nehi I will skip this year. what about you? Debanjan: mein virtually attend kar raha hu  Debanjan: hopefully can attend the conference in person from next year... Anish: haan dekhtey hain, in person attend karney mein alaag hi maaza hain Debanjan: but I also like this hybrid mode allows to attend the sessions in case you do not make it Anish: right Anish: if you are attending to mujhe interesting papers kuch bhej dena Debanjan: sure"
+
+conv_form = st.sidebar.form(key="conv_form")
+conv_ip = conv_form.text_input(label="Please enter the conversastion", value=default_value)
+conv_submit_button = conv_form.form_submit_button(label="Submit")
+
+# sent = st.text_area("Text", default_value, height=275)
+
+st.write("### Task Type:", task_type)
+st.write("### Model:", model_name)
+x = "fg"
+
+src_file = None
+tar_file = None
+gen_file = "generated_summary.txt"
+score_file = None
+
+if conv_submit_button:
+    if conv_ip == "":
+        st.write("Pls enter non empty conversastion")
+    else:
+        st.write("### Summarizing below Conversastion")
+        st.write(conv_ip)
+        src_file = "conversastion.txt"
+        src_fp = open(src_file, "w")
+        src_fp.write(conv_ip)
+        src_fp.close()
+
+tt = "h2e"
+if task_type == "English to English":
+    tt = "e2e"
+elif task_type == "Hinglish to English":
+    tt = "h2e"
+model_name_path = "midas/gupshup_" + str(tt) + "_" + str(model_name).lower()
+
+
+result = run_generate(
+    verbose=True,
+    model_name_path=model_name_path,
+    src_txt=src_file,
+    tar_txt=tar_file,
+    gen_path=gen_file,
+    scor_path=score_file,
+    batch_size=8,
+)
+
+if conv_submit_button:
+    st.write("summary:")
+    fp = open(gen_file, "r")
+    summary = fp.readlines()
+    fp.close()
+    st.write(summary)