Update app.py

app.py

@@ -1,30 +1,48 @@
-import openai
+from gpt_index import SimpleDirectoryReader, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
+from langchain.chat_models import ChatOpenAI
 import gradio as gr
-import sys
 import os
 
-os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
+# Set your OpenAI API key here
+os.environ["OPENAI_API_KEY"] = 'Your Secret API Key'
 
 def construct_index(directory_path):
-    # Your existing code for index construction remains unchanged
-        def construct_index(directory_path):
-            max_input_size = 4096
-            num_outputs = 512
-            max_chunk_overlap = 20
-            chunk_size_limit = 600
+    max_input_size = 4096
+    num_outputs = 512
+    max_chunk_overlap = 20
+    chunk_size_limit = 600
+
+    # Initialize the prompt helper
+    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
+    
+    # Initialize the LLM predictor with an updated model name if available
+    llm_predictor = LLMPredictor(llm=ChatOpenAI(temperature=0.7, model_name="gpt-4", max_tokens=num_outputs))  # Updated to GPT-4 or latest available model
+    
+    # Load documents from the directory
+    documents = SimpleDirectoryReader(directory_path).load_data()
+    
+    # Create and populate the index
+    index = GPTSimpleVectorIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+    index.save_to_disk('index.json')
     
+    return index
+
 def chatbot(input_text):
-    response = openai.Completion.create(
-        model="text-davinci-003",  # Specify the GPT-3 model you want to use
-        prompt=input_text,
-        max_tokens=150  # Adjust the max tokens based on your requirements
-    )
-    return response.choices[0].text.strip()
+    # Load the index from disk
+    index = GPTSimpleVectorIndex.load_from_disk('index.json')
+    
+    # Query the index and return the response
+    response = index.query(input_text, response_mode="compact")
+    return response.response
 
+# Set up the Gradio interface
 iface = gr.Interface(fn=chatbot,
-                     inputs=gr.inputs.Textbox(lines=7, label="Enter your text"),
+                     inputs=gr.components.Textbox(lines=7, label="Enter your text"),
                      outputs="text",
                      title="Custom-trained AI Chatbot")
 
-# index = construct_index("docs")  # You may not need this line anymore
-iface.launch(share=True)
+# Construct the index with your documents directory
+index = construct_index("docs")
+
+# Launch the Gradio interface
+iface.launch(share=True)