Update app.py

app.py

@@ -1,70 +1,65 @@
 import gradio as gr
 import json
-import os
 from huggingface_hub import InferenceClient
-from groq import Groq
-from groq.types.chat.chat_completion_tool_param import ChatCompletionToolParam
 
-# Use the fine-tuned maritime legal model
-MODEL = "nomiChroma3.1"
-##client = Groq(api_key=os.environ["GROQ_API_KEY"])
+# Hugging Face model for maritime legal advice
+MODEL = "HuggingFaceH4/zephyr-7b-beta"
 
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
+# Initialize the client
+client = InferenceClient(MODEL)
 
-
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
+def respond(message, history: list[tuple[str, str]], system_message, max_tokens, temperature, top_p):
+    # Build the messages list for the model
     messages = [{"role": "system", "content": system_message}]
+    
+    # Add conversation history
+    for user_input, assistant_response in history:
+        if user_input:
+            messages.append({"role": "user", "content": user_input})
+        if assistant_response:
+            messages.append({"role": "assistant", "content": assistant_response})
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
-
+    # Add the latest user input
     messages.append({"role": "user", "content": message})
 
     response = ""
+    
+    try:
+        # Streaming the chat completion response
+        for message in client.chat_completion(
+            messages,
+            max_tokens=max_tokens,
+            stream=True,
+            temperature=temperature,
+            top_p=top_p,
+        ):
+            try:
+                # Safely parse each streamed message item
+                payload = message.choices[0].delta.content
+                response += payload
+                yield response
+            except json.JSONDecodeError as e:
+                # Handle JSON parsing error
+                yield f"Error decoding JSON: {str(e)}"
 
-    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
+    except Exception as e:
+        yield f"Error: {str(e)}"
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
+# Gradio interface
 demo = gr.ChatInterface(
     respond,
     additional_inputs=[
-        gr.Textbox(value="You are a maritime legal assistant with expertise strictly in indian maritime law. Provide detailed legal advice and information based on indian maritime legal principles and regulations.", 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)",
+        gr.Textbox(
+            value="You are a maritime legal assistant with expertise strictly in Indian maritime law. Provide detailed legal advice and information based on Indian maritime legal principles and regulations.",
+            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)"),
     ],
     title="Maritime Legal Compliance",
-    description="This chatbot uses the fine tune Llama 3.1 which has the capabilities of responding and helping in legal advices regarding maritime",
+    description="This chatbot uses a fine-tuned model for providing legal advice on Indian maritime law.",
 )
 
-
 if __name__ == "__main__":
-    demo.launch()
+    demo.launch()