Delete FunctionTools.py

FunctionTools.py

@@ -1,249 +0,0 @@
-import json
-import chardet
-import streamlit as st
-import pandas as pd
-from llama_index.core.tools.tool_spec.base import BaseToolSpec
-
-class ScriptureDescriptionToolSpec(BaseToolSpec):
-    '''
-    Purpose: Obtains the description or summary about vedas, mandalas, kandas, shuktas, archakah, adhyaya, and other scriptural elements.
-    Returns: A dictionary containing the description or basic information about the specified scriptural element.
-    Sample query:
-    1. Describe the first kandah, second shukta from Atharvaveda?
-    2. Summarize ShuklaYajurVeda?
-    3. What is the difference between ShuklaYajurVeda and KrishnaYajurVeda?
-    '''
-    # Define the functions that we export to the LLM
-    spec_functions = ["get_description"]
-
-    with open("Data/scripture_descriptions.csv", 'rb') as f:
-        result = chardet.detect(f.read())
-
-    encoding = result['encoding']
-    df = pd.read_csv("Data/scripture_descriptions.csv", encoding=encoding)
-
-    @st.cache_data
-    def get_description(_self, level_0, level_1:int=None, level_2:int=None, level_3:int=None):
-        """
-        To get the description or basic information about vedas/mandalas/kandas/shukatas/archakah/adhyaya and others.
-        """
-        try:
-            if level_3 is not None:
-                # Case with Level-2 specified
-                result = _self.df[(_self.df['scripture_name'].str.lower() == level_0.lower())
-                                  & (_self.df['level_1'] == str(level_1))
-                                  & (_self.df['level_2'] == str(level_2)) & (_self.df['level_3'] == str(level_3))]
-            elif level_2 is not None:
-                # Case with Level-2 specified
-                result = _self.df[(_self.df['scripture_name'].str.lower() == level_0.lower())
-                                  & (_self.df['level_1'] == str(level_1)) & (_self.df['level_2'] == str(level_2))]
-            elif level_1 is not None:
-                # Case with Level-1 specified
-                result = _self.df[(_self.df['scripture_name'].str.lower() == level_0.lower())
-                                  & (_self.df['level_1'] == str(level_1))]
-            else:
-                # Case with only Level-0 specified
-                result = _self.df[_self.df['scripture_name'].str.lower() == level_0.lower()]
-
-            return result.iloc[0].to_dict()
-        except IndexError as e:
-            return json.dumps({"error": f"Failed to get scripture description. {e}"})
-
-class MantraToolSpec(BaseToolSpec):
-    '''
-    To obtain translations or meaning of vedamantras from RigVeda and AtharvaVeda using the function `get_translation`.
-    The mantra details such as vedamantra, padapatha, rishi, chandah, devata, and swarah from the vedas accessible through the function `get_vedamantra_details`.
-    The mantra summary like anvaya, adhibautic, ahyatmic, adhidaivic meaning of vedamantra accessible using the function 'get_vedamantra_summary'
-    Sample Query:
-    1. What is the vedamantra of the mantra from Rigveda, first mandala, first shukta, and first mantra?
-    2. What is the devata of the vedamantra from Rigveda, first mandala, first shukta, and first mantra?
-    3. What is the meaning of the vedamantra from Rigveda, first mandala, first shukta, and first mantra written by Tulsi Ram?
-    4. What is the (adhibautic) meaning of the vedamantra from RigVeda, first mandala, first shukta, and first mantra?
-    '''
-    spec_functions = ["get_translation", "get_vedamantra_details", "get_vedamantra_summary"]
-
-    TRANSLATION_CSV_PATH = 'Data/trans_Rig_Ath_index_v2.csv'
-    VEDAMANTRA_CSV_PATH = "Data/veda_content_modified_v3.csv"
-
-    def __init__(self):
-        super().__init__()
-        self.df_translation = pd.read_csv(self.TRANSLATION_CSV_PATH, encoding='utf-8')
-        self.df_vedamantra = pd.read_csv(self.VEDAMANTRA_CSV_PATH, encoding='utf-8')
-
-    @st.cache_data
-    def get_translation(_self, mantraid=None, scripture_name=None, MahatmaName=None, KandahNumber=None,
-                        MandalaNumber=None, ArchikahNumber=None, ShuktaNumber=None,
-                        AnvayaNumber=None, PrapatakNumber=None, MantraNumber=None,
-                        AnuvakNumber=None, AdhyayaNumber=None):
-        """
-        Get the translation of mantras from RigVeda and AtharvaVeda.
-        Sample Query:
-        1. What is the translation of Tulsi Ram of the vedamantra from Rigveda, first mandala, first shukta, and first mantra?
-        2. What is the translation or adhibautic meaning of the vedamantra from RigVeda, first mandala, first shukta, and first mantra?
-        3. What is the subject of the mantra 1.1.84.1?
-        """
-        try:
-            if mantraid is None:
-                scripture_name_lower = scripture_name.lower() if scripture_name is not None else False
-                if scripture_name_lower == 'rigveda':
-                    details = _self.df_translation[
-                        (_self.df_translation['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_translation['MandalaNumber'] == MandalaNumber)
-                        & (_self.df_translation['ShuktaNumber'] == int(ShuktaNumber))
-                        & (_self.df_translation['MantraNumber'] == int(MantraNumber))
-                    ].to_dict(orient='records')
-                elif scripture_name_lower == 'atharvaveda':
-                    details = _self.df_translation[
-                        (_self.df_translation['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_translation['KandahNumber'] == KandahNumber)
-                        & (_self.df_translation['ShuktaNumber'] == ShuktaNumber)
-                        & (_self.df_translation['MantraNumber'] == MantraNumber)].to_dict(orient='records')
-                elif scripture_name_lower == 'samaveda':
-                    details = _self.df_translation[
-                        (_self.df_translation['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_translation['ArchikahNumber'] == ArchikahNumber)
-                        & (_self.df_translation['ShuktaNumber'] == ShuktaNumber)
-                        & (_self.df_translation['MantraNumber'] == MantraNumber)].to_dict(orient='records')
-                elif scripture_name_lower == 'krishnayajurveda':
-                    details = _self.df_translation[
-                        (_self.df_translation['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_translation['PrapatakNumber'] == PrapatakNumber)
-                        & (_self.df_translation['AnuvakNumber'] == AnuvakNumber)
-                        & (_self.df_translation['MantraNumber'] == MantraNumber)].to_dict(orient='records')
-                else:
-                    details = _self.df_translation[
-                        (_self.df_translation['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_translation['AdhyayaNumber'] == AdhyayaNumber)
-                        & (_self.df_translation['MantraNumber'] == MantraNumber)
-                    ].to_dict(orient='records')
-            else:
-                details = _self.df_translation[_self.df_translation['mantra_id'] == mantraid].to_dict(orient='records')
-
-            if MahatmaName is not None:
-                for item in details:
-                    if item['MahatmaName'] == MahatmaName:
-                        return item
-            else:
-                return details
-        except Exception as e:
-            return json.dumps({"error": f"Failed to get translation. {e}"})
-
-    @st.cache_data
-    def get_vedamantra_details(_self, mantraid=None, scripture_name=None, KandahNumber=None,
-                               MandalaNumber=None, ArchikahNumber=None, ShuktaNumber=None,
-                               AnvayaNumber=None, PrapatakNumber=None, MantraNumber=None,
-                               AnuvakNumber=None, AdhyayaNumber=None):
-        """
-        To obtain the vedamantra details such as vedamantra, padapata, devata, rishi, swarah, and chandah.
-        1. What is the vedamantra of the mantra from Rigveda, first mandala, first shukta, and first mantra?
-        2. What is the devata of the vedamantra from Rigveda, first mandala, first shukta, and first mantra?
-        """
-        try:
-            if mantraid is None:
-                scripture_name_lower = scripture_name.lower() if scripture_name is not None else False
-
-                if scripture_name_lower == 'rigveda':
-                    conditions = (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower) & \
-                                  (_self.df_vedamantra['MandalaNumber'] == MandalaNumber) & \
-                                  (_self.df_vedamantra['ShuktaNumber'] == ShuktaNumber) & \
-                                  (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    details = _self.df_vedamantra[conditions]['mantra_json'].values
-                    vedamantra_details = json.loads(details[0])['mantraHeader']['language'][1]['mandala']['shukta']['mantra']
-
-                elif scripture_name_lower == 'atharvaveda':
-                    conditions = (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower) & \
-                                  (_self.df_vedamantra['KandahNumber'] == KandahNumber) & \
-                                  (_self.df_vedamantra['ShuktaNumber'] == ShuktaNumber) & \
-                                  (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    details = _self.df_vedamantra[conditions]['mantra_json'].values
-                    vedamantra_details = json.loads(details[0])['mantraHeader']['language'][1]['kandah']['shukta']['mantra']
-                elif scripture_name_lower == 'samaveda':
-                    conditions = (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower) & \
-                                  (_self.df_vedamantra['ArchikahNumber'] == ArchikahNumber) & \
-                                  (_self.df_vedamantra['ShuktaNumber'] == ShuktaNumber) & \
-                                  (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    details = _self.df_vedamantra[conditions]['mantra_json'].values
-                    vedamantra_details = json.loads(details[0])['mantraHeader']['language'][1]['archikah']
-                elif scripture_name_lower == 'krishnayajurveda':
-                    conditions = (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower) & \
-                                  (_self.df_vedamantra['PrapatakNumber'] == PrapatakNumber) & \
-                                  (_self.df_vedamantra['AnuvakNumber'] == AnuvakNumber) & \
-                                  (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    details = _self.df_vedamantra[conditions]['mantra_json'].values
-                    vedamantra_details = json.loads(details[0])['mantraHeader']['language'][1]['kandah']['prapatak']['anuvak']
-                else:
-                    conditions = (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower) & \
-                                  (_self.df_vedamantra['AdhyayaNumber'] == AdhyayaNumber) & \
-                                  (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    details = _self.df_vedamantra[conditions]['mantra_json'].values
-                    vedamantra_details = json.loads(details[0])['mantraHeader']['language'][1]['adhyaya']['mantra']
-
-            else:
-                # Handle case when mantraid is provided
-                details = _self.df_vedamantra[_self.df_vedamantra['mantra_number'] == mantraid]['mantra_json'].values
-                vedamantra_details = json.loads(details[0])['mantraHeader']['language'][1]
-
-            return vedamantra_details
-        except Exception as e:
-            return json.dumps({"error": f"Failed to get vedamantra details. {str(e)}"})
-
-    @st.cache_data
-    def get_vedamantra_summary(_self, mantraid=None, scripture_name=None, KandahNumber=None,
-                               MandalaNumber=None, ArchikahNumber=None, ShuktaNumber=None,
-                               AnvayaNumber=None, PrapatakNumber=None, MantraNumber=None,
-                               AnuvakNumber=None, AdhyayaNumber=None):
-        '''
-        To obtain the vedamantra summary like anvaya, translation, adhibautic, adhyatmic, adhidaivic meaning of the mantra.
-        1. What is the adhibautic meaning of the mantra from AtharvaVeda, first kandah, first shukta, and first mantra?
-        2. What is the anvaya of the vedamantra from Rigveda, first mandala, first shukta, and first mantra?
-        '''
-        try:
-            if mantraid is None:
-                scripture_name_lower = scripture_name.lower() if scripture_name is not None else False
-                if scripture_name_lower == 'rigveda':
-                    details = _self.df_vedamantra[
-                        (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_vedamantra['MandalaNumber'] == MandalaNumber)
-                        & (_self.df_vedamantra['ShuktaNumber'] == ShuktaNumber)
-                        & (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    ]['mantra_json'].values
-                elif scripture_name_lower == 'atharvaveda':
-                    details = _self.df_vedamantra[
-                        (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_vedamantra['KandahNumber'] == KandahNumber)
-                        & (_self.df_vedamantra['ShuktaNumber'] == ShuktaNumber)
-                        & (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    ]['mantra_json'].values
-                elif scripture_name_lower == 'samaveda':
-                    details = _self.df_vedamantra[
-                        (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_vedamantra['ArchikahNumber'] == ArchikahNumber)
-                        & (_self.df_vedamantra['ShuktaNumber'] == ShuktaNumber)
-                        & (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    ]['mantra_json'].values
-                elif scripture_name_lower == 'krishnayajurveda':
-                    details = _self.df_vedamantra[
-                        (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_vedamantra['PrapatakNumber'] == PrapatakNumber)
-                        & (_self.df_vedamantra['AnuvakNumber'] == AnuvakNumber)
-                        & (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    ]['mantra_json'].values
-                else:
-                    details = _self.df_vedamantra[
-                        (_self.df_vedamantra['scripture_name'].str.lower() == scripture_name_lower)
-                        & (_self.df_vedamantra['AdhyayaNumber'] == AdhyayaNumber)
-                        & (_self.df_vedamantra['MantraNumber'] == str(MantraNumber))
-                    ]['mantra_json'].values
-            else:
-                details = _self.df_vedamantra[_self.df_vedamantra['mantra_number'] == mantraid]['mantra_json'].values
-
-            jsonDict = json.loads(details[0])
-            mantraSummary = jsonDict['mantraSummary']['language']
-            mantraSummary_IAST = jsonDict['mantraSummary']['language'][1]
-            vedamantra_summary = {"Roman-IAST summary of vedamantra": mantraSummary_IAST}
-            for item in mantraSummary:
-                if item['languageName'] == 'English':
-                    vedamantra_summary.update({"English summary of vedamantra": item})
-            return vedamantra_summary
-        except Exception as e:
-            return json.dumps({"error": f"Failed to get vedamantra summary. {e}"})