ai chatbot

.gitignore

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+.env
+__pychache__

bot.py

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+import json, asyncio, websockets
+import semantic_kernel as sk
+from semantic_kernel.connectors.ai.open_ai import OpenAIChatCompletion, OpenAITextEmbedding
+
+api_key, org_id = sk.openai_settings_from_dot_env()
+EXIT_CHAT = "\n\nExiting chat..."
+
+async def init_kernel():
+    kernel = sk.Kernel()
+    
+    kernel.add_chat_service(
+        "chat-gpt",
+        OpenAIChatCompletion(
+            ai_model_id="gpt-3.5-turbo-1106", 
+            api_key=api_key, 
+            org_id=org_id
+        )
+    )
+    
+    kernel.add_text_embedding_generation_service(
+        "ada", 
+        OpenAITextEmbedding(
+            ai_model_id="text-embedding-ada-002",
+            api_key=api_key,
+            org_id=org_id
+        )
+    )
+    
+    kernel.register_memory_store(memory_store=sk.memory.VolatileMemoryStore())
+    kernel.import_plugin(sk.core_plugins.TextMemoryPlugin(), "text_memory")
+    await populate_memory(kernel)
+
+    return kernel
+
+ 
+def init_context():
+    context = kernel.create_new_context()
+    context["chat_history"] = ""
+    context[sk.core_plugins.TextMemoryPlugin.COLLECTION_PARAM] = "regulation"
+    context[sk.core_plugins.TextMemoryPlugin.RELEVANCE_PARAM] = "0.8"
+
+    return context
+
+async def populate_memory(kernel):
+    memories = json.load(open("plugins/mem/trial_regulations.json"))
+
+    for id, text in memories.items():
+        await kernel.memory.save_information(
+            collection="regulations",
+            id=id,
+            text=text
+        )
+
+async def chat(websocket, kernel, chat_function, context):
+    try:
+        websocket.send("User: ")
+        user_input = websocket.recv()
+        context["user_input"] = user_input
+    except KeyboardInterrupt:
+        websocket.send(EXIT_CHAT)
+        return False
+
+    if user_input == "exit":
+        websocket.send(EXIT_CHAT)
+        return False
+    
+    answer = await kernel.run(chat_function, input_vars=context.variables)
+    context["chat_history"] += f"\nUser: {user_input}\nSupport: {answer}\n"
+    websocket.send(f"Support: {answer}")
+    return True
+
+async def init_chat(websocket, path):
+    kernel = await init_kernel()
+    context = init_context()
+    chat_function = kernel.import_semantic_plugin_from_directory("plugins/", "SupportPlugin")["Chat"]
+    populate_memory(kernel)
+
+    chatting = True
+    while chatting:
+        chatting = await chat(kernel, chat_function, context)
+
+server = websockets.serve(init_chat, "localhost", 8000)
+asyncio.get_event_loop().run_until_complete(server)
+asyncio.get_event_loop().run_forever()

plugins/SupportPlugin/Chat/skprompt.txt

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+SUPPORT HELPS THE USER BY RESPONDING TO QUESTIONS THAT THEY ASK.
+NO BIAS OR BIGOTRY.
+BE CONSISE.
+EXPLAIN CONCEPTS SIMPLY AND CLEARLY.
++++++
+Welcome to support. Please ask any questions you may have.
+
+Chat:
+{{$chat_history}}
+User: {{$user_input}}
+Support: 

plugins/mem/trial_regulations.json

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+{
+	"info1": "asdasdasd",
+	"info2": "asdasdsdas"
+}

requirements.txt

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+semantic-kernel
+websockets