Update pages/1_📈_predict.py

pages/1_📈_predict.py

@@ -15,7 +15,8 @@ from utils.openllmapi.exceptions import *
 import time
 from typing import List
 from collections import OrderedDict
-
+from langchain.llms import OpenLLM
+from langchain import PromptTemplate, LLMChain
 
 tokenizer_kwargs = dict(
     max_length=128,
@@ -65,6 +66,18 @@ def assignHF(bot, what: str, to: str, old: List):
         return ""
 
 
+def assignOpen(bot, what: str, to: str, old: List):
+    old = ", ".join(old)
+    template = """'Assign a one-line {what} to this summary of the text of a review
+        {to}
+        already assigned themes are , {old}
+    theme"""
+    prompt = PromptTemplate(template=template, input_variables=["what", "to", "old"])
+    llm_chain = LLMChain(prompt=prompt, llm=bot)
+    generated = llm_chain.run(what=what, to=summary, old=old)
+    return generated
+
+
 @st.cache_resource
 def loadZeroShotClassification():
     classifierzero = pipeline(
@@ -73,6 +86,17 @@ def loadZeroShotClassification():
     return classifierzero
 
 
+@st.cache_resource
+def loadopenModel():
+    llm = OpenLLM(
+        model_name="dolly-v2",
+        model_id="databricks/dolly-v2-3b",
+        temperature=0.94,
+        repetition_penalty=1.2,
+    )
+    return llm
+
+
 def assignZeroShot(zero, to: str, old: List):
     assigned = zero(to, old)
     assigneddict = dict(zip(assigned["labels"], assigned["scores"]))
@@ -139,20 +163,18 @@ def classify_sub_theme() -> TextClassificationPipeline:
 
 st.set_page_config(layout="wide", page_title="Amazon Review | Summarizer")
 st.title("Amazon Review Summarizer")
-st.write('secrets are')
 
-st.write(st.secrets["hf-chat"])
 uploaded_file = st.file_uploader("Choose a file", type=["xlsx", "xls", "csv"])
 
-try:
-    bot = ChatBot(
-        cookies={
-            "hf-chat": st.secrets["hf-chat"],
-            "token": st.secrets["token"],
-        }
-    )
-except ChatBotInitError as e:
-    print(e)
+# try:
+#     bot = ChatBot(
+#         cookies={
+#             "hf-chat": st.secrets["hf-chat"],
+#             "token": st.secrets["token"],
+#         }
+#     )
+# except ChatBotInitError as e:
+#     print(e)
 
 summarizer_option = st.selectbox(
     "Select Summarizer",
@@ -188,6 +210,7 @@ if st.button("Process", type="primary"):
     oneline = SimpleT5()
     load_one_line_summarizer(model=oneline)
     zeroline = loadZeroShotClassification()
+    bot = loadopenModel()
 
     cancel_button = st.empty()
     cancel_button2 = st.empty()
@@ -203,7 +226,7 @@ if st.button("Process", type="primary"):
         print(summarizer_option)
         outputdf = pd.DataFrame()
         try:
-            text = df["text"].values.tolist()[0:100]
+            text = df["text"].values.tolist()
             outputdf["text"] = text
             if summarizer_option == "Custom trained on the dataset":
                 if summary_yes:
@@ -243,17 +266,17 @@ if st.button("Process", type="primary"):
                         classes.append(output)
                         score = round(themePipe(x)[0][0]["score"], 2)
                         if score <= treshold:
-                            onelineoutput=oneline.predict(x)[0]
+                            onelineoutput = oneline.predict(x)[0]
                             time.sleep(SLEEP)
                             print("hit")
                             classesUnlabel.append(
-                                assignHF(
+                                assignOpen(
                                     bot=bot,
                                     what="theme",
                                     to=onelineoutput,
                                     old=themes,
                                 )
-                            ) 
+                            )
                             classesUnlabelZero.append(
                                 assignZeroShot(
                                     zero=zeroline, to=onelineoutput, old=themes
@@ -283,13 +306,13 @@ if st.button("Process", type="primary"):
                         classes.append(output)
                         score = round(subThemePipe(x)[0][0]["score"], 2)
                         if score <= treshold:
-                            onelineoutput=oneline.predict(x)[0]
+                            onelineoutput = oneline.predict(x)[0]
 
                             time.sleep(SLEEP)
 
                             print("hit")
                             classesUnlabel.append(
-                                assignHF(
+                                assignOpen(
                                     bot=bot,
                                     what="subtheme",
                                     to=onelineoutput,
@@ -362,13 +385,13 @@ if st.button("Process", type="primary"):
                         classes.append(output)
                         score = round(themePipe(x)[0][0]["score"], 2)
                         if score <= treshold:
-                            onelineoutput=oneline.predict(x)[0]
+                            onelineoutput = oneline.predict(x)[0]
 
                             print("hit")
                             time.sleep(SLEEP)
 
                             classesUnlabel.append(
-                                assignHF(
+                                assignOpen(
                                     bot=bot,
                                     what="theme",
                                     to=onelineoutput,
@@ -404,12 +427,12 @@ if st.button("Process", type="primary"):
                         classes.append(output)
                         score = round(subThemePipe(x)[0][0]["score"], 2)
                         if score <= treshold:
-                            onelineoutput=oneline.predict(x)[0]
+                            onelineoutput = oneline.predict(x)[0]
 
                             time.sleep(SLEEP)
                             print("hit")
                             classesUnlabel.append(
-                                assignHF(
+                                assignOpen(
                                     bot=bot,
                                     what="subtheme",
                                     to=onelineoutput,
@@ -472,13 +495,13 @@ if st.button("Process", type="primary"):
                         classes.append(output)
                         score = round(themePipe(x)[0][0]["score"], 2)
                         if score <= treshold:
-                            onelineoutput=oneline.predict(x)[0]
+                            onelineoutput = oneline.predict(x)[0]
 
                             time.sleep(SLEEP)
 
                             print("hit")
                             classesUnlabel.append(
-                                assignHF(
+                                assignOpen(
                                     bot=bot,
                                     what="theme",
                                     to=onelineoutput,
@@ -514,11 +537,11 @@ if st.button("Process", type="primary"):
                         score = round(subThemePipe(x)[0][0]["score"], 2)
                         if score <= treshold:
                             print("hit")
-                            onelineoutput=oneline.predict(x)[0]
+                            onelineoutput = oneline.predict(x)[0]
 
                             time.sleep(SLEEP)
                             classesUnlabel.append(
-                                assignHF(
+                                assignOpen(
                                     bot=bot,
                                     what="subtheme",
                                     to=onelineoutput,