Update app.py

app.py

@@ -1,91 +1,37 @@
 import openai
 import gradio as gr
 import os
+import pandas as pd
 
-# Google docs access
-import googleapiclient.discovery as discovery
-from httplib2 import Http
-from oauth2client import client
-from oauth2client import file
-from oauth2client import tools
-
-SCOPES = 'https://www.googleapis.com/auth/documents.readonly'
-DISCOVERY_DOC = 'https://docs.googleapis.com/$discovery/rest?version=v1'
-DOCUMENT_ID = '16hjgy8pqI_2KI1vZfHdPk_VVuQUHLnZu-fdSQAVi45Q'
 
 # env
 openai.api_key = os.environ.get('openai-api')
+SHEET_ID = '119qz8UpCdwCu_gyPtayi7JmhSM0nUddolOyJcqsMnmA'
+SHEET_NAME = 'MIW_Sources'
 
 # Blocks
 with gr.Blocks(theme=gr.themes.Glass()) as demo:
 
-    def get_credentials():
-        """Gets valid user credentials from storage.
-    
-        If nothing has been stored, or if the stored credentials are invalid,
-        the OAuth 2.0 flow is completed to obtain the new credentials.
-    
-        Returns:
-            Credentials, the obtained credential.
-        """
-        store = file.Storage('token.json')
-        credentials = store.get()
-    
-        if not credentials or credentials.invalid:
-            flow = client.flow_from_clientsecrets('credentials.json', SCOPES)
-            credentials = tools.run_flow(flow, store)
-        return credentials
-    
-    def main():
-        credentials = get_credentials()
-        http = credentials.authorize(Http())
-        docs_service = discovery.build(
-            'docs', 'v1', http=http, discoveryServiceUrl=DISCOVERY_DOC)
-        doc = docs_service.documents().get(documentId=DOCUMENT_ID).execute()
-        doc_content = doc.get('body').get('content')
-        docsread = read_structural_elements(doc_content)
-    
-    if __name__ == '__main__':
-        main()
-   
-    def read_paragraph_element(element):
-        """Returns the text in the given ParagraphElement.
-    
-            Args:
-                element: a ParagraphElement from a Google Doc.
-        """
-        text_run = element.get('textRun')
-        if not text_run:
-            return ''
-        return text_run.get('content')
-    
+    #Initiatlize data
+    url = f'https://docs.google.com/spreadsheets/d/{SHEET_ID}/gviz/tq?tqx=out:csv&sheet={SHEET_NAME}'
+    df = pd.read_csv(url)
+
+    def filter_and_concatenate(df, input_string):
+        # If input string is empty, return concatenation of all values
+        if input_string == "":
+            concatenated_string = ""
+            for _, row in df.iterrows():
+                concatenated_string += '|'.join(str(value) for value in row.values) + '\n'
+            return concatenated_string
     
-    def read_structural_elements(elements):
-        """Recurses through a list of Structural Elements to read a document's text where text may be
-            in nested elements.
+        # Filter the dataframe based on the input string
+        filtered_df = df[df['category'] == input_string]
     
-            Args:
-                elements: a list of Structural Elements.
-        """
-        text = ''
-        for value in elements:
-            if 'paragraph' in value:
-                elements = value.get('paragraph').get('elements')
-                for elem in elements:
-                    text += read_paragraph_element(elem)
-            elif 'table' in value:
-                # The text in table cells are in nested Structural Elements and tables may be
-                # nested.
-                table = value.get('table')
-                for row in table.get('tableRows'):
-                    cells = row.get('tableCells')
-                    for cell in cells:
-                        text += read_structural_elements(cell.get('content'))
-            elif 'tableOfContents' in value:
-                # The text in the TOC is also in a Structural Element.
-                toc = value.get('tableOfContents')
-                text += read_structural_elements(toc.get('content'))
-        return text
+        # Concatenate the values from other columns
+        concatenated_string = ''
+        for _, row in filtered_df.iterrows():
+            concatenated_string += '|'.join(str(value) for value in row.values[1:]) + '\n'
+        return concatenated_string
     
     def showall(code:str):
         visibility = gr.update(visible = True)
@@ -134,7 +80,16 @@ with gr.Blocks(theme=gr.themes.Glass()) as demo:
         messages_history3 += {"role": "system", "content": themehelp}
         messages_history3 += {"role": "assistant", "content": languagedict[language]['helpfirst']}
         return messages_history1, messages_history2, messages_history3
-
+    
+    def getlist(df):
+        # Extract distinct values from the first column
+        distinct_values = df.iloc[:, 0].unique()
+    
+        # Join the distinct values into a string separated by ", "
+        distinct_values_string = ",".join(str(value) for value in distinct_values)
+    
+        return distinct_values_string
+    
     def user(msg, chatbot, state, language: str, mode: str):
         #Bot context
         if mode == "mode1":
@@ -149,7 +104,15 @@ with gr.Blocks(theme=gr.themes.Glass()) as demo:
         elif len(state) > 10:
             state.append({'role':'system','content':f"Remember your mission as briefed earlier:\n\n{context}"})
         chatbot.append([msg, None])
-        msg = msg + f"\n\nAnswer in {language}"
+
+        if mode == 'mode3'
+            #Append instructions to msg
+            listvalues = getlist(df)
+            queryforcategory = [{'role':'user','content':f"Out of this list of words/expressions separated by a comma:\n{listvalues}\n, which one corresponds the best to the theme in this message:\n{msg}\n\nThe result should be one of the elements from the list only."}]
+            matchcat = answer(queryforcategory)
+            instructions = filter_and_concatenate(df, matchcat)
+            msg = msg +f"\n\nUse the following elements to document your answer:\n{instructions}"
+        msg = msg + f"\n\nAnswer in {language}, keep it casual but respectful"
         state.append({'role':'user','content':msg})
         print(f'state is\n{state}')
         print(f'chatbot is\n{chatbot}')
@@ -171,8 +134,7 @@ with gr.Blocks(theme=gr.themes.Glass()) as demo:
         chatbot2up = [[None,languagedict[language]['interviewquestionsfirst']]]
         state2up = [{"role": "system", "content": themeinterviewquestions},{"role": "assistant", "content": languagedict[language]['interviewquestionsfirst']}]
         chatbot3up = [[None,languagedict[language]['whatcanidofirst']]]
-        complement = f"To answer, use primarily the information indicated here:\n{instructions}"
-        state3up = [{"role": "system", "content": themehelp + f"\n{complement}"},{"role": "assistant", "content": languagedict[language]['helpfirst']}]
+        state3up = [{"role": "system", "content": themehelp},{"role": "assistant", "content": languagedict[language]['helpfirst']}]
         return titleup, input1up, input2up, input3up, chatbot1up, chatbot2up, chatbot3up, state1up, state2up, state3up
 
     languageoptions = ["English", "廣東話"]
@@ -237,7 +199,7 @@ with gr.Blocks(theme=gr.themes.Glass()) as demo:
         - Breakdown the potential challenges for them to anticipate
         - Provide advice on how to overcome these challenges
         
-        IMPORTANT: write in {language}, in the style of a native inhabitant from Kowloon
+        IMPORTANT: write in {language}, in the style of a native. Keep it casual but respectful.
         """
             
             themeinterviewquestions = f"""
@@ -248,7 +210,7 @@ with gr.Blocks(theme=gr.themes.Glass()) as demo:
         
         Then ask another question.
         
-        IMPORTANT: write in {language}, in the style of a native inhabitant from Kowloon
+        IMPORTANT: write in {language}, in the style of a native. Keep it casual but respectful.
         """
         
             themehelp = f"""
@@ -261,7 +223,7 @@ with gr.Blocks(theme=gr.themes.Glass()) as demo:
         - leisure
         If the question is not related to any of these topics, answer 'This is beyond my domain of competence, please ask a social worker.'
         
-        IMPORTANT: write in {language}, in the style of a native inhabitant from Kowloon
+        IMPORTANT: write in {language}, in the style of a native. Keep it casual but respectful.
         """
         
             #INTERFACE
@@ -276,9 +238,7 @@ with gr.Blocks(theme=gr.themes.Glass()) as demo:
             with gr.Tab(f"{languagedict['English']['help']} / {languagedict['廣東話']['help']}"):
                 chatbot3 = gr.Chatbot([[None,languagedict['English']['helpfirst']]])
                 input3 = gr.Textbox(label = languagedict['English']['helplabel'], placeholder = languagedict['English']['helpph'], visible = False)
-                instructions = gr.Textbox(value = docsread, label = 'Instructions', lines=10, max_lines= 100, visible = False)
-                complement = f"To answer, use primarily the information indicated here:\n{instructions}"
-                state3 = gr.State([{"role": "system", "content": themehelp + f"\n{complement}"},{"role": "assistant", "content": languagedict['English']['helpfirst']}])
+                state3 = gr.State([{"role": "system", "content": themehelp},{"role": "assistant", "content": languagedict['English']['helpfirst']}])
             clear = gr.Button('Clear')
     
     # Launcher