Create app.py

app.py

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+from typing import List
+import typing
+from aiser import RestAiServer, KnowledgeBase, SemanticSearchResult, Agent
+from aiser.models import ChatMessage
+import asyncio
+import gradio as gr
+import requests
+import os
+
+# Define environment variables
+API_URL = os.getenv("API_URL", "YOUR_API_URL_PLACEHOLDER")
+API_TOKEN = os.getenv("API_TOKEN", "YOUR_API_TOKEN_PLACEHOLDER")
+
+class ChatBot:
+    def __init__(self):
+        self.history = []
+
+    def predict(self, input):
+        new_user_input = input  # User input should be converted into model input format
+
+        # Prepare payload for API call
+        payload = {"question": new_user_input}
+
+        # Make an external API call
+        headers = {"Authorization": API_TOKEN}
+        response = requests.post(API_URL, headers=headers, json=payload)
+        if response.status_code == 200:
+            chat_history_ids = response.json()
+        else:
+            chat_history_ids = {"response": "Error in API call"}
+
+        # Process the API response and update history
+        self.history.append(chat_history_ids['response'])
+        response_text = chat_history_ids['response']
+        return response_text
+
+bot = ChatBot()
+
+title = "👋🏻Welcome to Tonic's EZ Chat🚀"
+description = "You can use this Space to test out the current model (DialoGPT-medium) or duplicate this Space and use it for any other model on 🤗HuggingFace. Join me on [Discord](https://discord.gg/fpEPNZGsbt) to build together."
+examples = [["How are you?"]]
+
+iface = gr.Interface(
+    fn=bot.predict,
+    title=title,
+    description=description,
+    examples=examples,
+    inputs="text",
+    outputs="text",
+    theme="Tonic/indiansummer"
+)
+
+iface.launch()
+
+class KnowledgeBaseExample(KnowledgeBase):
+    def perform_semantic_search(self, query_text: str, desired_number_of_results: int) -> List[SemanticSearchResult]:
+        result_example = SemanticSearchResult(
+            content="This is an example of a semantic search result",
+            score=0.5,
+        )
+        return [result_example for _ in range(desired_number_of_results)]
+
+class AgentExample(Agent):
+    async def reply(self, messages: typing.List[ChatMessage]) -> typing.AsyncGenerator[ChatMessage, None]:
+        reply_message = "This is an example of a reply from an agent"
+        for character in reply_message:
+            yield ChatMessage(text_content=character)
+            await asyncio.sleep(0.1)
+
+if __name__ == '__main__':
+    server = RestAiServer(
+        agents=[
+            AgentExample(
+                agent_id='10209b93-2dd0-47a0-8eb2-33fb018a783b'  # replace with your agent id
+            ),
+        ],
+        knowledge_bases=[
+            KnowledgeBaseExample(
+                knowledge_base_id='85bc1c72-b8e0-4042-abcf-8eb2d478f207'  # replace with your knowledge base id
+            ),
+        ],
+        port=5000
+    )
+    server.run()