Initial files

app.py

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+import gradio as gr
+import os
+import openai
+import chromadb
+from chromadb.config import Settings
+from langchain.embeddings import OpenAIEmbeddings
+
+
+css="""
+#col-container {max-width: 700px; margin-left: auto; margin-right: auto;}
+"""
+
+title = """
+<div style="text-align: center;max-width: 700px;">
+    <h1>Ask P360 Help • OpenAI</h1>
+    <p style="text-align: center;">Ask questions about the P360 documentation.
+</div>
+"""
+
+def init():
+    '''
+    Setup.
+    '''
+    chroma_client = chromadb.Client(
+        Settings(
+            chroma_db_impl='duckdb+parquet',
+            persist_directory='./vectorstore/',
+        )
+    )
+
+    global db
+    db = chroma_client.get_collection(
+        name='help-360',
+    )
+
+    global embeddings_generator
+    embeddings_generator = OpenAIEmbeddings(
+        openai_api_key=os.getenv('AZURE_OPENAI_KEY'),
+        openai_api_base=os.getenv('AZURE_OPENAI_ENDPOINT'),
+        openai_api_type='azure',
+        openai_api_version='2023-05-15',
+        deployment='embedding-test'
+    )
+
+
+def respond(query):
+    '''
+    OpenAI GPT response.
+    '''
+    query_embedding = embeddings_generator.embed_query(query)
+    results = db.query(
+        query_embeddings=query_embedding,
+        n_results=1,
+    )
+    relevant_help = results['documents'][0][0]
+
+    openai.api_type = 'azure'
+    openai.api_base = os.getenv('AZURE_OPENAI_ENDPOINT')
+    openai.api_key = os.getenv('AZURE_OPENAI_KEY')
+    openai.api_version = '2023-05-15'
+
+    response = openai.ChatCompletion.create(
+        engine='entest-gpt-35-turbo',
+        messages=[
+            {"role": "system", "content": "You are a helpful assistant in the P360 document archiving system."},
+            {"role": "user", "content": "What do you know about P360?"},
+            {"role": "assistant", "content": relevant_help},
+            {"role": "user", "content": query},
+        ]
+    )
+    return response['choices'][0]['message']['content']
+
+
+with gr.Blocks(css=css) as demo:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML(title)        
+        question = gr.Textbox(label='Question', placeholder='Type your question and hit Enter ')
+        answer = gr.Textbox(label='Answer').style(height=350)
+        question.submit(respond, [question], [answer])
+
+
+demo.launch()

requirements.txt

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+openai
+tiktoken
+chromadb
+langchain

vectorstore/chroma-collections.parquet

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+size 552

vectorstore/chroma-embeddings.parquet

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+size 7056150

vectorstore/index/id_to_uuid_621498b8-3f11-4417-a09e-a7c5d047d1f8.pkl

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vectorstore/index/index_621498b8-3f11-4417-a09e-a7c5d047d1f8.bin

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