Upload 3 files

app.py

@@ -1,22 +1,5 @@
-import os
-import streamlit as st
-import tempfile
-import pandas as pd
-from JSONPath_Generator import JSONPath_Generator
-from dotenv import load_dotenv
-load_dotenv()
+from frontend import JSONQuery_Frontend
 
-#Initialize Streamlit app
-st.set_page_config(page_title="👨‍💻 JSON Path Generator")
-st.header("JSON Path Generator")
-
-#Input Text Area
-json_value = st.text_area(label="JSON Body Input: ")
-target_input = st.text_input(label="Target JSON Key: ")
-json_condition = st.text_input(label="JSON Conditions (If any): ")
-
-if st.button("Submit"):
-    json_path_gen = JSONPath_Generator(json_input=json_value, target_value=target_input,
-                                       json_condition=json_condition)
-    res = json_path_gen.create_llm_chain()
-    st.write(res)
+if __name__ == "__main__":
+    app_frntend = JSONQuery_Frontend()
+    app_frntend.run()

backend.py

@@ -0,0 +1,47 @@
+from langchain.prompts import PromptTemplate, SystemMessagePromptTemplate, ChatPromptTemplate, \
+    HumanMessagePromptTemplate
+from langchain.llms import OpenAI
+from langchain.chat_models import ChatOpenAI, AzureChatOpenAI
+from langchain.cache import InMemoryCache
+import langchain
+langchain.llm_cache = InMemoryCache()
+import  pandas as pd
+import os
+from langchain.chains import LLMChain
+from langchain.output_parsers import PydanticOutputParser
+from pydantic import BaseModel, Field
+
+
+class JSONPath_Generator:
+    def __init__(self, json_input, target_value, json_condition, openai_key):
+        self.json_input = json_input
+        self.target_value = target_value
+        self.json_condition = json_condition
+        self.openai_api_key = openai_key
+        self.model = OpenAI(
+            temperature=0,
+            openai_api_key=self.openai_api_key,
+            model_name="gpt-3.5-turbo-instruct"
+        )
+
+    def create_chat_prompt(self):
+        # System Template
+        with open("system_template.txt", "r") as sys_temp:
+            system_template = sys_temp.read().strip()
+        system_prompt = SystemMessagePromptTemplate.from_template(system_template)
+        # Humman Template
+        with open("human_template.txt", "r") as hum_temp:
+            human_template = hum_temp.read().strip()
+        if self.json_condition != '':
+            human_template += " provided the {json_condition}"
+        human_prompt = HumanMessagePromptTemplate.from_template(human_template)
+        # Chat Prompt
+        self.chat_prompt = ChatPromptTemplate.from_messages([system_prompt, human_prompt])
+
+    def create_llm_chain(self):
+        # self.read_extract_api_details()
+        self.create_chat_prompt()
+        chain = LLMChain(llm=self.model, prompt=self.chat_prompt)
+        self.response = chain.run(Target_value=self.target_value,json_condition = self.json_condition,
+                                  JSON_Input=self.json_input)
+        return self.response

frontend.py

@@ -0,0 +1,40 @@
+import streamlit as st
+from backend import JSONPath_Generator
+
+
+class JSONQuery_Frontend:
+    def __init__(self):
+        pass
+
+    def run(self):
+        self.titleheader()
+        self.input_text()
+        self.submit_btn()
+
+    def titleheader(self):
+        # Initialize Streamlit app
+        st.set_page_config(page_title="👨‍💻 JSON Path Generator")
+        st.header("JSON Path Generator")
+
+
+    def input_text(self):
+        # Input Text Area
+        self.open_ai_key = st.text_input(label="Enter the OpenAI Key: ")
+        self.json_value = st.text_area(label="JSON Body Input: ")
+        self.target_input = st.text_input(label="Target JSON Key: ")
+        self.json_condition = st.text_input(label="JSON Conditions (If any): ")
+
+    def submit_btn(self):
+        if st.button("Submit"):
+            self.json_path_gen = JSONPath_Generator(json_input=self.json_value, target_value=self.target_input,
+                                               json_condition=self.json_condition,
+                                               openai_key=self.open_ai_key)
+            res = self.json_path_gen.create_llm_chain()
+            st.write(res)
+
+
+
+
+
+
+