Update app.py

app.py

@@ -87,37 +87,100 @@
 # if __name__ == "__main__":
 #     demo.launch()
 
-import os  # Import the os module
-import time
-import gradio as gr
-from langchain_community.chat_models import ChatOpenAI  # Updated import based on deprecation warning
-from langchain.schema import AIMessage, HumanMessage
-import openai
-
-# Set your OpenAI API key
-os.environ["OPENAI_API_KEY"] = "sk-3_mJiR5z9Q3XN-D33cgrAIYGffmMvHfu5Je1U0CW1ZT3BlbkFJA2vfSvDqZAVUyHo2JIcU91XPiAq424OSS8ci29tWMA"  # Replace with your OpenAI key
-
-# Initialize ChatOpenAI
-llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')
-
-def predict(message, history):
-    # Reformat history for LangChain
-    history_langchain_format = []
-    for human, ai in history:
-        history_langchain_format.append(HumanMessage(content=human))
-        history_langchain_format.append(AIMessage(content=ai))
+# import os  # Import the os module
+# import time
+# import gradio as gr
+# from langchain_community.chat_models import ChatOpenAI  # Updated import based on deprecation warning
+# from langchain.schema import AIMessage, HumanMessage
+# import openai
+
+# # Set your OpenAI API key
+# os.environ["OPENAI_API_KEY"] = "sk-3_mJiR5z9Q3XN-D33cgrAIYGffmMvHfu5Je1U0CW1ZT3BlbkFJA2vfSvDqZAVUyHo2JIcU91XPiAq424OSS8ci29tWMA"  # Replace with your OpenAI key
+
+# # Initialize ChatOpenAI
+# llm = ChatOpenAI(temperature=1.0, model='gpt-3.5-turbo-0613')
+
+# def predict(message, history):
+#     # Reformat history for LangChain
+#     history_langchain_format = []
+#     for human, ai in history:
+#         history_langchain_format.append(HumanMessage(content=human))
+#         history_langchain_format.append(AIMessage(content=ai))
     
-    # Add latest human message
-    history_langchain_format.append(HumanMessage(content=message))
+#     # Add latest human message
+#     history_langchain_format.append(HumanMessage(content=message))
     
-    # Get response from the model
-    gpt_response = llm(history_langchain_format)
+#     # Get response from the model
+#     gpt_response = llm(history_langchain_format)
     
-    # Return response
-    return gpt_response.content
+#     # Return response
+#     return gpt_response.content
+
+# # Using ChatInterface to create a chat-style UI
+# demo = gr.ChatInterface(fn=predict, type="messages")
+# if __name__ == "__main__":
+#     demo.launch()
+import gradio as gr
+from huggingface_hub import InferenceClient
+
+"""
+For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
+"""
+client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+
+
+def respond(
+    message,
+    history: list[tuple[str, str]],
+    system_message,
+    max_tokens,
+    temperature,
+    top_p,
+):
+    messages = [{"role": "system", "content": system_message}]
+
+    for val in history:
+        if val[0]:
+            messages.append({"role": "user", "content": val[0]})
+        if val[1]:
+            messages.append({"role": "assistant", "content": val[1]})
+
+    messages.append({"role": "user", "content": message})
+
+    response = ""
+
+    for message in client.chat_completion(
+        messages,
+        max_tokens=max_tokens,
+        stream=True,
+        temperature=temperature,
+        top_p=top_p,
+    ):
+        token = message.choices[0].delta.content
+
+        response += token
+        yield response
+
+
+"""
+For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
+"""
+demo = gr.ChatInterface(
+    respond,
+    additional_inputs=[
+        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
+        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
+        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
+        gr.Slider(
+            minimum=0.1,
+            maximum=1.0,
+            value=0.95,
+            step=0.05,
+            label="Top-p (nucleus sampling)",
+        ),
+    ],
+)
 
-# Using ChatInterface to create a chat-style UI
-demo = gr.Interface(fn=predict, type="messages")
 
 if __name__ == "__main__":
     demo.launch()
@@ -134,3 +197,4 @@ if __name__ == "__main__":
 
 
 
+