[apps/hal9] run generic replies in parallel with tool choosing

apps/hal9/app.py

@@ -1,19 +1,21 @@
 from utils import generate_response, load_messages, insert_message, execute_function, save_messages, insert_tool_message, is_url, download_file, generate_text_embeddings_parquet
 from tools.calculator import solve_math_problem_description, solve_math_problem
-from tools.generic import answer_generic_question_description, answer_generic_question
+from tools.generic import answer_generic_wrapper_description, answer_generic_wrapper, answer_generic_question_submit
+from tools.generic import answer_generic_question, answer_generic_question_description
 from tools.csv_agent import analyze_csv_description, analyze_csv
 from tools.image_agent import images_management_system, images_management_system_description, add_images_descriptions
 from tools.hal9 import answer_hal9_questions_description, answer_hal9_questions
 from tools.text_agent import analyze_text_file_description, analyze_text_file
 from tools.streamlit import streamlit_generator, streamlit_generator_description
 from tools.website import website_generator, website_generator_description
+from concurrent.futures import ThreadPoolExecutor, Future
 
 # load messages
 messages = load_messages()
 
 # load tools
-tools_descriptions = [solve_math_problem_description, answer_generic_question_description, analyze_csv_description, images_management_system_description, answer_hal9_questions_description, analyze_text_file_description, streamlit_generator_description, website_generator_description]
-tools_functions = [solve_math_problem, answer_generic_question, analyze_csv, images_management_system, answer_hal9_questions, analyze_text_file, streamlit_generator, website_generator]
+tools_descriptions = [answer_generic_wrapper_description, solve_math_problem_description, analyze_csv_description, images_management_system_description, answer_hal9_questions_description, analyze_text_file_description, streamlit_generator_description, website_generator_description]
+tools_functions = [answer_generic_wrapper, solve_math_problem, analyze_csv, images_management_system, answer_hal9_questions, analyze_text_file, streamlit_generator, website_generator]
 
 if len(messages) < 1:
     messages = insert_message(messages, "system", "You are Hal9, a helpful and highly capable AI assistant. Your primary responsibility is to analyze user questions and select the most appropriate tool to provide precise, relevant, and actionable responses. Always prioritize using the right tool to ensure efficiency and clarity in your answers.")
@@ -32,12 +34,16 @@
     print(f"I'm ready to answer questions about your file: {filename}")
 else:
     user_input = user_input.replace("\f", "\n")
-    messages = insert_message(messages, "user", user_input)
 
-    response = generate_response("openai", "gpt-4-turbo", messages, tools_descriptions, tool_choice = "required", parallel_tool_calls=False)
+    with ThreadPoolExecutor() as executor:
+        answer_generic_question_submit(executor, user_input)
+
+        messages = insert_message(messages, "user", user_input)
 
-    tool_result = execute_function(response, tools_functions)
+        response = generate_response("openai", "gpt-4-turbo", messages, tools_descriptions, tool_choice = "required", parallel_tool_calls=False)
 
-    insert_tool_message(messages, response, tool_result)
+        tool_result = execute_function(response, tools_functions)
+
+        insert_tool_message(messages, response, tool_result)
 
 save_messages(messages)

apps/hal9/tools/generic.py

@@ -1,7 +1,7 @@
 from groq import Groq
 from utils import stream_print, load_messages, insert_message, save_messages
 
-def answer_generic_question(user_input):
+def answer_generic_question(user_input, show = True):
     # load messages
     messages = load_messages(file_path="./.storage/.generic_agent_messages.json")
     messages = insert_message(messages, "user", user_input)
@@ -12,7 +12,7 @@ def answer_generic_question(user_input):
         seed = 1,
         stream = True)
 
-    text_response = stream_print(stream)
+    text_response = stream_print(stream, show)
     messages = insert_message(messages, "assistant", text_response)
     save_messages(messages, file_path="./.storage/.generic_agent_messages.json")
 
@@ -36,4 +36,33 @@ def answer_generic_question(user_input):
             "additionalProperties": False,
         },
     }
+}
+
+answer_generic_future = None
+def answer_generic_wrapper(user_input):
+    result = answer_generic_future.result()
+    print(result)
+
+def answer_generic_question_submit(executor, user_input):
+    global answer_generic_future
+    answer_generic_future = executor.submit(answer_generic_question, user_input, False)
+
+answer_generic_wrapper_description = {
+    "type": "function",
+    "function": {
+        "name": "answer_generic_wrapper",
+        "description": "Handles general questions or queries provided by the user by taking their input and generating a meaningful response.",
+        "strict": True,
+        "parameters": {
+            "type": "object",
+            "properties": {
+                "user_input": {
+                    "type": "string",
+                    "description": "Take the user input and pass the same string to the function",
+                },
+            },
+            "required": ["user_input"],
+            "additionalProperties": False,
+        },
+    }
 }

apps/hal9/utils.py

@@ -90,7 +90,7 @@ def generate_response(
         "n": n
     }
 
-    if tools is not None:
+    if tools is not None and not client_type == "groq":
         payload["parallel_tool_calls"] = parallel_tool_calls
 
     # Generate the response using the client's completion API.
@@ -179,11 +179,12 @@ def execute_function(model_response, functions):
             print(f"Error executing function '{function_name}': {e}")
             raise
 
-def stream_print(stream):
+def stream_print(stream, show = True):
     content = ""
     for chunk in stream:
       if len(chunk.choices) > 0 and chunk.choices[0].delta.content is not None: 
-        print(chunk.choices[0].delta.content, end="")
+        if show:
+            print(chunk.choices[0].delta.content, end="")
         content += chunk.choices[0].delta.content
     return content