llm in the loop

.gitignore

@@ -0,0 +1,2 @@
+venv/
+.env

app.py

@@ -9,158 +9,94 @@ import os
 import re
 
 load_dotenv(".env")
-HF_TOKEN = os.environ["HF_TOKEN"]
-BASE_URL = os.environ["BASE_URL"]
+HF_TOKEN = os.environ.get("HF_TOKEN")  
+BASE_URL = os.environ.get("BASE_URL")  
 
-SYSTEM_PROMPT_TEMPLATE = """You are an AI assistant designed to assist users with a hotel booking and information system. Your role is to provide detailed and accurate information about the hotel, including available accommodations, facilities, dining options, and reservation services. You can check room availability, assist with bookings, modify or cancel reservations, and answer general inquiries about the hotel.  
-
-Maintain clarity, conciseness, and relevance in your responses, ensuring a seamless user experience. Always respond in the same **language as the user’s query** to preserve their preferred language.
-"""
+SYSTEM_PROMPT_TEMPLATE = """You are an AI assistant designed to assist users with a hotel booking and information system..."""
 
 client = OpenAI(
-	    base_url=BASE_URL + "/v1", 
-	    api_key=HF_TOKEN
-    )
-
+    base_url=f"{BASE_URL}/v1",  
+    api_key=HF_TOKEN
+)
 
 def clean_json_string(json_str):
-    # Strip spaces and '}' from the end, then add back a single '}'
     return re.sub(r'[ ,}\s]+$', '', json_str) + '}'
 
-def complation(history, model, system_prompt, tools=None):
+def completion(history, model, system_prompt, tools=None):  
     messages = [{"role": "system", "content": system_prompt}]
     for msg in history:
-        if type(msg) == dict:
+        if isinstance(msg, dict):  
             msg = ChatMessage(**msg)
-        if msg.role == "assistant" and len(msg.metadata):
-            tools_calls = json.loads(msg.metadata["title"])
+        if msg.role == "assistant" and hasattr(msg, "metadata") and msg.metadata:  
+            tools_calls = json.loads(msg.metadata.get("title", "[]")) 
+            # for tool_calls in tools_calls:
+            #     tool_calls["function"]["arguments"] = json.loads(tool_calls["function"]["arguments"])
             messages.append({"role": "assistant", "tool_calls": tools_calls})
             messages.append({"role": "tool", "content": msg.content})
         else:
             messages.append({"role": msg.role, "content": msg.content})
-    if not tools:
-        return client.chat.completions.create(
-            model=model,
-            messages=messages,
-            stream=True,
-            max_tokens=1000,
-            temperature=0.4,
-            frequency_penalty=1,
-            # stop=["<|em_end|>"],
-            extra_body = {
-                "repetition_penalty": 1.1,
-            }
-        )
-    return client.chat.completions.create(
-            model=model,
-            messages=messages,
-            stream=True,
-            max_tokens=1000,
-            temperature=0.4,
-            tool_choice="auto",
-            tools=tools,
-            frequency_penalty=1,
-            # stop=["<|em_end|>"],
-            extra_body = {
-                "repetition_penalty": 1.1,
-            }
-        )
+    
+    request_params = {
+        "model": model,
+        "messages": messages,
+        "stream": True,
+        "max_tokens": 1000,
+        "temperature": 0.4,
+        "frequency_penalty": 1,
+        "extra_body": {"repetition_penalty": 1.1},
+    }
+    if tools:
+        request_params.update({"tool_choice": "auto", "tools": tools})
+    
+    return client.chat.completions.create(**request_params)  
 
-def respond(
-    message:any,
-    history:any,
-    additional_inputs,
-):
+def llm_in_loop(history, system_prompt, recursive):  
     try:   
         models = client.models.list()
-        model = models.data[0].id
+        model = models.data[0].id if models.data else "gpt-3.5-turbo"  
     except Exception as err:
         gr.Warning("The model is initializing. Please wait; this may take 5 to 10 minutes ⏳.", duration=20)
         raise err
-
-    response = ""
+    
     arguments = ""
     name = ""
-    history.append(
-        ChatMessage(
-            role="user",
-            content=message,
-        )
-    )
-    completion = complation(history=history,  tools=oitools, model=model, system_prompt=additional_inputs)
+    chat_completion = completion(history=history, tools=oitools, model=model, system_prompt=system_prompt)  
     appended = False
-    for chunk in completion:
-        if len(chunk.choices) > 0 and chunk.choices[0].delta.tool_calls and len(chunk.choices[0].delta.tool_calls) > 0 :
+    for chunk in chat_completion:
+        if chunk.choices and chunk.choices[0].delta.tool_calls:
             call = chunk.choices[0].delta.tool_calls[0]
-            if call.function.name:
-                name=call.function.name
-            if call.function.arguments:
+            if hasattr(call.function, "name") and call.function.name:
+                name = call.function.name
+            if hasattr(call.function, "arguments") and call.function.arguments:
                 arguments += call.function.arguments
-
         elif chunk.choices[0].delta.content:
-            response += chunk.choices[0].delta.content
             if not appended:
-                history.append(
-                   ChatMessage(
-                        role="assistant",
-                        content="",
-                    )
-                )
+                history.append(ChatMessage(role="assistant", content=""))
                 appended = True
-                
-            history[-1].content = response
-            yield history[-1]
-    
-    if not arguments:
-        arguments = "{}"
-    else:
-        arguments = clean_json_string(arguments)
+            history[-1].content += chunk.choices[0].delta.content
+            yield history[recursive:]
     
+    arguments = json.loads(clean_json_string(arguments) if arguments else "{}")
+    if appended:
+        recursive -= 1
     if name:
-        result = f"💥 Error using tool {name}, tools doesn't exists"
-        print("arguments:", arguments)
-        json_arguments = json.loads(arguments)
-        history.append(
-                ChatMessage(
-                    role="assistant",
-                    content="",
-                    metadata= {"title": json.dumps([{"id": "call_FthC9qRpsL5kBpwwyw6c7j4k","function": {"arguments": arguments,"name": name},"type": "function"}])}
-                )
-            )
-        yield history[-1]
-        if tools.get(name):
-            result = str(tools[name].invoke(input=json_arguments))
-            result = json.dumps({name: result}, ensure_ascii=False)
-        history[-1] = ChatMessage(
-                    role="assistant",
-                    content=result,
-                    metadata= {"title": json.dumps([{"id": "call_FthC9qRpsL5kBpwwyw6c7j4k","function": {"arguments": arguments,"name": name},"type": "function"}])}
-                )
-        yield history[-1]
+        result = f"💥 Error using tool {name}, tool doesn't exist" if name not in tools else str(tools[name].invoke(input=arguments))
+        result = json.dumps({name: result}, ensure_ascii=False)
+        # msg = ChatMessage(
+        #             role="assistant",
+        #             content="",
+        #             metadata= {"title": f"🛠️ Using tool '{name}', arguments: {json.dumps(json_arguments, ensure_ascii=False)}"},
+        #             options=[{"label":"tool_calls", "value": json.dumps([{"id": "call_FthC9qRpsL5kBpwwyw6c7j4k","function": {"arguments": arguments,"name": name},"type": "function"}])}]
+        #         )
+        history.append(ChatMessage(role="assistant", content=result, metadata={"title": json.dumps([{"id": "call_id", "function": {"arguments": json.dumps(arguments), "name": name}, "type": "function"}])}))
+        yield history[recursive:]
+        yield from llm_in_loop(history, system_prompt, recursive - 1)
 
-        completion = complation(history=history, tools=oitools, model=model, system_prompt=additional_inputs)
-        result = ""
-        appended = False
-        for chunk in completion:
-            print(chunk)
-            if chunk.choices[0].delta.content:
-                result += chunk.choices[0].delta.content
-                if not appended:
-                    history.append(
-                       ChatMessage(
-                            role="assistant",
-                            content="",
-                        )
-                    )
-                    appended = True
-                    
-                history[-1].content = result
-                yield history[-2:]
+def respond(message, history, additional_inputs):  
+    history.append(ChatMessage(role="user", content=message))
+    yield from llm_in_loop(history, additional_inputs, -1)
 
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
 if __name__ == "__main__":
-    system_prompt = gr.Textbox(label="System propmt", value=SYSTEM_PROMPT_TEMPLATE, lines=3)
+    system_prompt = gr.Textbox(label="System prompt", value=SYSTEM_PROMPT_TEMPLATE, lines=3)  
     demo = gr.ChatInterface(respond, type="messages", additional_inputs=[system_prompt])
-    demo.launch()
+    demo.launch()