Create app.py

app.py

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+'''
+ Fintelligence (C) 2024
+ Intelligent Finance
+ Released in Apache 2.0 license
+
+'''
+import streamlit as st
+import os
+from openai import OpenAI
+import json
+
+# Initialize the client
+client = OpenAI(
+    base_url="https://api-inference.huggingface.co/v1",
+    api_key=os.environ.get('API_KEY')
+)
+
+# Model configuration
+MODEL = "HuggingFaceH4/zephyr-7b-beta"
+
+# Define a custom function
+def get_current_weather(location, unit="celsius"):
+    """Get the current weather in a given location"""
+    weather_info = {
+        "location": location,
+        "temperature": "22",
+        "unit": unit,
+        "forecast": ["sunny", "windy"],
+    }
+    return weather_info
+
+# Set up the Streamlit app
+st.title("Chatbot with Hugging Face and Zephyr-7B-Beta")
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# Accept user input
+if prompt := st.chat_input("What is up?"):
+    # Add user message to chat history
+    st.session_state.messages.append({"role": "user", "content": prompt})
+    # Display user message in chat message container
+    with st.chat_message("user"):
+        st.markdown(prompt)
+
+    # Prepare the messages for the API call
+    messages = [
+        {"role": msg["role"], "content": msg["content"]}
+        for msg in st.session_state.messages
+    ]
+
+    # Call the Hugging Face API
+    try:
+        response = client.chat.completions.create(
+            model=MODEL,
+            messages=messages,
+            functions=[
+                {
+                    "name": "get_current_weather",
+                    "description": "Get the current weather in a given location",
+                    "parameters": {
+                        "type": "object",
+                        "properties": {
+                            "location": {"type": "string"},
+                            "unit": {"type": "string", "enum": ["celsius", "fahrenheit"]},
+                        },
+                        "required": ["location"],
+                    },
+                }
+            ],
+            function_call="auto",
+        )
+
+        # Process the response
+        assistant_response = response.choices[0].message.content
+        function_call = response.choices[0].message.function_call
+
+        if function_call:
+            function_name = function_call.name
+            function_args = json.loads(function_call.arguments)
+            
+            if function_name == "get_current_weather":
+                function_response = get_current_weather(**function_args)
+                
+                # Call the API again with the function response
+                messages.append({"role": "function", "name": function_name, "content": json.dumps(function_response)})
+                final_response = client.chat.completions.create(
+                    model=MODEL,
+                    messages=messages
+                )
+                assistant_response = final_response.choices[0].message.content
+
+        # Display assistant response in chat message container
+        with st.chat_message("assistant"):
+            st.markdown(assistant_response)
+        
+        # Add assistant response to chat history
+        st.session_state.messages.append({"role": "assistant", "content": assistant_response})
+
+    except Exception as e:
+        st.error(f"An error occurred: {str(e)}")
+
+    # Note: Token usage information is not available with the Hugging Face API
+    st.sidebar.write("Note: Token usage information is not available with the Hugging Face API.")