Update app.py

Duplicate and change AI Engine

app.py

@@ -15,8 +15,32 @@ dir_path = "./docs"
 # Create the directory using the os module
 os.makedirs(dir_path, exist_ok=True)
 
-# Print a confirmation message
-print(f"New directory created at {dir_path}")
+def construct_index(directory_path):
+    max_input_size = 4096
+    num_outputs = 512
+    max_chunk_overlap = 20
+    chunk_size_limit = 600
+
+    prompt_helper = PromptHelper(max_input_size, num_outputs, max_chunk_overlap, chunk_size_limit=chunk_size_limit)
+
+    #llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.4, model_name="text-davinci-003", max_tokens=num_outputs))
+    llm_predictor = LLMPredictor(llm=OpenAI(temperature=0.2, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
+
+
+    service_context = ServiceContext.from_defaults(llm_predictor=llm_predictor,  prompt_helper=prompt_helper)
+
+    documents = SimpleDirectoryReader(directory_path).load_data()
+
+    index = GPTSimpleVectorIndex.from_documents(documents, service_context=service_context) #, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+
+    index.save_to_disk('index.json')
+
+    return index
+
+def chatbot(input_text):
+    index = GPTSimpleVectorIndex.load_from_disk('index.json')
+    response = index.query(input_text, response_mode="compact")
+    return response.response
 
 def qa_system(pdf_file, openai_key, prompt, chain_type, k):
     os.environ["OPENAI_API_KEY"] = openai_key
@@ -47,8 +71,18 @@ def qa_system(pdf_file, openai_key, prompt, chain_type, k):
     result = qa({"query": prompt})
     return result['result'], [doc.page_content for doc in result["source_documents"]]
 
+# New interface 
+iface = gr.Interface(fn=chatbot,
+                     inputs=gr.inputs.Textbox(lines=7, label="Enter your text"),
+                     outputs="text",
+                     title="Tikehau-trained AI Chatbot")
+
+#index = construct_index("docs")
+index = construct_index(dir_path)
+
+
 # define the Gradio interface
-input_file = gr.inputs.File(label="PDF File")
+# input_file = gr.inputs.File(label="PDF File")
 openai_key = gr.inputs.Textbox(label="OpenAI API Key", type="password")
 prompt = gr.inputs.Textbox(label="Question Prompt")
 chain_type = gr.inputs.Radio(['stuff', 'map_reduce', "refine", "map_rerank"], label="Chain Type")
@@ -57,7 +91,9 @@ k = gr.inputs.Slider(minimum=1, maximum=5, default=1, label="Number of Relevant
 output_text = gr.outputs.Textbox(label="Answer")
 output_docs = gr.outputs.Textbox(label="Relevant Source Text")
 
-gr.Interface(qa_system, inputs=[input_file, openai_key, prompt, chain_type, k], outputs=[output_text, output_docs], 
+gr.Interface(fn=chatbot, 
+             inputs=[openai_key, prompt, chain_type, k], outputs=[output_text, output_docs], 
              title="Question Answering with PDF File and OpenAI", 
-             description="Upload a PDF file, enter your OpenAI API key, type a question prompt, select a chain type, and choose the number of relevant chunks to use for the answer.").launch(debug = True)
+             description="Tikehau URDs.").launch(debug = True)
+