update

app.py

@@ -1,4 +1,72 @@
+import json
+import http.client
 import streamlit as st
+from openai import AzureOpenAI
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)
+class ContentFormatter:
+    @staticmethod
+    def chat_completions(text, settings_params):
+        message = [
+            {"role": "system", "content": "You are a helpful assistant."},
+            {"role": "user", "content": text}
+        ]
+        data = {"messages": message, **settings_params}
+        return json.dumps(data)
+
+class AzureAgent:
+    def __init__(self, api_key, azure_uri):
+        self.azure_uri = azure_uri
+        self.headers = {
+            'Authorization': f"Bearer {api_key}",
+            'Content-Type': 'application/json'
+        }
+        self.chat_formatter = ContentFormatter
+
+    def invoke(self, text, **kwargs):
+        body = self.chat_formatter.chat_completions(text, {**kwargs})
+        conn = http.client.HTTPSConnection(self.azure_uri)
+        conn.request("POST", '/v1/chat/completions', body=body, headers=self.headers)
+        response = conn.getresponse()
+        data = response.read()
+        conn.close()
+        decoded_data = data.decode("utf-8")
+        parsed_data = json.loads(decoded_data)
+        content = parsed_data["choices"][0]["message"]["content"]
+        return content
+
+class GPTAgent:
+    def __init__(self, api_key, azure_endpoint):
+        self.client = AzureOpenAI(
+            api_key=api_key,
+            api_version='2022-11-01',  # Defaulting to a specific API version
+            azure_endpoint=azure_endpoint
+        )
+        self.deployment_name = 'your-model-deployment-name'  # Update this based on actual deployment name
+
+    def invoke(self, text, **kwargs):
+        response = self.client.chat.completions.create(
+            model=self.deployment_name,
+            messages=[
+                {"role": "system", "content": "You are a helpful assistant."},
+                {"role": "user", "content": text}
+            ],
+            **kwargs
+        )
+        return response.choices[0].message.content
+
+# Streamlit app interface
+st.title('Model Invocation with User Credentials')
+
+model_type = st.radio("Select the type of agent", ('AzureAgent', 'GPTAgent'))
+api_key = st.text_input("API Key", type="password")
+endpoint_url = st.text_input("Endpoint URL")
+
+input_text = st.text_area('Enter your text')
+if st.button('Invoke Model'):
+    if model_type == 'AzureAgent':
+        agent = AzureAgent(api_key, endpoint_url)
+    else:
+        agent = GPTAgent(api_key, endpoint_url)
+
+    output = agent.invoke(input_text, temperature=0, max_tokens=5)
+    st.write('Response:', output)