Upload 3 files

PDFminer.py

@@ -0,0 +1,40 @@
+
+from gpt_index import SimpleDirectoryReader, GPTListIndex, GPTSimpleVectorIndex, LLMPredictor, PromptHelper
+from langchain.chat_models import ChatOpenAI
+import gradio as gr
+import sys
+import os
+
+os.environ["openai_api_key"] = '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'
+
+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=ChatOpenAI(temperature=0.7, model_name="gpt-3.5-turbo", max_tokens=num_outputs))
+
+    documents = SimpleDirectoryReader(directory_path).load_data()
+
+    index = GPTSimpleVectorIndex(documents, 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
+
+iface = gr.Interface(fn=chatbot,
+                     inputs=gr.components.Textbox(lines=7, label="Enter your text"),
+                     outputs="text",
+                     title="Custom-trained AI Chatbot")
+
+# Change the argument to point to "C:\temp" instead of "docs"
+index = construct_index(r"C:\Temp\AI Training")
+iface.launch(share=True)

app.py

@@ -0,0 +1,12 @@
+
+import gradio as gr
+
+def chatbot(input_text):
+    index = GPTSimpleVectorIndex.load_from_disk('index.json')
+    response = index.query(input_text, response_mode="compact")
+    return response.response
+
+iface = gr.Interface(fn=chatbot,
+                     inputs=gr.components.Textbox(lines=7, label="Enter your text"),
+                     outputs="text",
+                     title="Custom-trained AI Chatbot")

requirements.txt

@@ -0,0 +1,3 @@
+gpt_index
+langchain.chat_models
+gradio