Create app.py

app.py

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+from llama_index import SimpleDirectoryReader, LLMPredictor, PromptHelper, StorageContext, ServiceContext, GPTVectorStoreIndex, load_index_from_storage
+from langchain.chat_models import ChatOpenAI
+import gradio as gr
+import sys
+import os
+
+#from langchain.chat_models import ChatOpenAI
+
+os.environ["OPENAI_API_KEY"] = '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'
+
+def construct_index(directory_path):
+    max_input_size = 4096
+    num_outputs = 512
+    max_chunk_overlap = 0.2
+    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=ChatOpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
+
+    documents = SimpleDirectoryReader(directory_path).load_data()
+
+    index = GPTVectorStoreIndex(documents, llm_predictor=llm_predictor, prompt_helper=prompt_helper)
+
+    #index.save_to_disk('index.json')
+    index.storage_context.persist(persist_dir="index.json")
+
+    return index
+
+index = construct_index("docs")
+
+def chatbot(input_text):
+    query_engine = index.as_query_engine()
+    response = query_engine.query(input_text)
+    return response.response
+
+iface = gr.Interface(fn=chatbot,
+                     inputs=gr.components.Textbox(lines=7, label="Enter your question"),
+                     outputs="text",
+                     title="Starkbot")
+
+
+iface.launch(share=True, debug=True)