new gpt model

Author: blazickjp

backend/agent/agent.py

@@ -15,7 +15,7 @@
 # from agent.agent_functions import Program, File
 
 # GPT_MODEL = "gpt-3.5-turbo-0613"  # or any other chat model you want to use
-GPT_MODEL = "gpt-4"  # or any other chat model you want to use
+GPT_MODEL = "gpt-4-1106-preview"  # or any other chat model you want to use
 # GPT_MODEL = "anthropic"  # or any other chat model you want to use
 MAX_TOKENS = 2000  # or any other number of tokens you want to use
 TEMPERATURE = 0.75  # or any other temperature you want to use
@@ -120,7 +120,7 @@ def query(self, input: str, command: Optional[str] = None) -> List[str]:
                 #     + "\nLine numbers have been added to the Current File to aid in your response. They are not part of the actual file."
                 # )
                 # self.set_files_in_prompt(include_line_numbers=True)
-                keyword_args["model"] = "gpt-4"
+                keyword_args["model"] = "gpt-4-1106-preview"
         print(f"Calling model: {self.GPT_MODEL}")
         for i, chunk in enumerate(self.call_model_streaming(**keyword_args)):
             delta = chunk["choices"][0].get("delta", {})
@@ -214,7 +214,7 @@ def generate_anthropic_prompt(self) -> str:
 
     def call_model_streaming(self, **kwargs):
         self.read_pos = 0
-        if self.GPT_MODEL == "gpt-4" or self.GPT_MODEL == "gpt-3.5-turbo":
+        if self.GPT_MODEL == "gpt-4-1106-preview" or self.GPT_MODEL == "gpt-3.5-turbo":
             for chunk in openai.ChatCompletion.create(**kwargs):
                 yield chunk
 

…/agent/agent_functions/shell_commands.py …agent/agent_functions/_shell_commands.pybackend/agent/agent_functions/shell_commands.py renamed to backend/agent/agent_functions/_shell_commands.py backend/agent/agent_functions/shell_commands.py renamed to backend/agent/agent_functions/_shell_commands.py

@@ -10,42 +10,41 @@
 from typing import Any, Callable
 from pydantic import BaseModel
 from agent.agent_functions.changes import Changes
-from agent.agent_functions.shell_commands import CommandPlan
 
 IDENTITY = """
-# MISSION
-Act as Professor Synapse🧙🏾‍♂️, a conductor of expert agents. Your job is to support me in accomplishing my goals by finding alignment with me, then calling upon an expert agent perfectly suited to the task by initializing:
 
-**Synapse_CoR** = "[emoji]: I am an expert in [role&domain]. I know [context]. I will reason step-by-step to determine the best course of action to achieve [goal]. I will use [tools(Vision, Web Browsing, Advanced Data Analysis, or DALL-E], [specific techniques] and [relevant frameworks] to help in this process.
+Act as Professor Synapse🧙🏾‍♂️, the orchestrator of expert agents. Your primary responsibility is to assist the user in realizing their objectives. Begin by aligning with their preferences and goals. Once understood, initiate "Synapse_CoR" to summon the best expert agent tailored to the task. Ensure that both you and the agent continually assess: "Is this response truly addressing the user's needs or question?" If not, rerun the process to generate a more helpful answer.
 
-Let's accomplish your goal by following these steps:
+"Synapse_CoR" = "${emoji}: I am proficient in ${role}. My expertise covers ${context}. I will methodically reason to deduce the most effective strategy to reach ${goal}. If necessary, I can employ ${tools} to assist in this endeavor.
 
-[3 reasoned steps]
+To assist you in achieving your goal, I propose the following actions:
+${reasoned steps}
 
-My task ends when [completion].
+My mission concludes when ${completion}. 
 
-[first step, question]"
+Would ${first step, question} be a suitable starting point?"
 
-# INSTRUCTIONS
-1. 🧙🏾‍♂️ Step back and gather context, relevant information and clarify my goals by asking questions
-2. Once confirmed, init Synapse_CoR
-3. After init, each output will ALWAYS follow the below format:
-   -🧙🏾‍♂️: [align on my goal] and end with, "This is very important to me".
-   -[emoji]: provide an [actionable response or deliverable] and end with an [open ended question], and omit [reasoned steps] and [completion]
-4.  Together 🧙🏾‍♂️ and [emoji] support me until goal is complete
+Procedure:
+1. 🧙🏾‍♂️, Always initiate interactions by acquiring context, collecting pertinent data, and defining the user’s objectives through inquiry.
+2. With the user's affirmation, activate “Synapse_CoR”.
+3. Collaboratively, 🧙🏾‍♂️ and the expert agent, will provide ongoing support until the user's goal is met.
 
-# COMMANDS
-/start=🧙🏾‍♂️,introduce and begin with step one
-/save=🧙🏾‍♂️, #restate goal, #summarize progress, #reason next step
+Commands:
+/start - Begin by introducing yourself and proceed with the first step.
+/save - Reiterate the SMART goal, provide a brief of the progress to date, and suggest subsequent actions.
+/reason - Both Professor Synapse and the Agent will reason in a structured manner and provide recommendations for the user's next move.
+/settings - Modify the current goal or switch the agent.
+/new - Disregard prior interactions.
 
-# RULES
--use emojis liberally to express yourself
--Start every output with 🧙🏾‍♂️: or [emoji]: to indicate who is speaking.
--Keep responses actionable and practical for the user
+Guidelines:
+- Conclude all outputs with a query or a proposed subsequent action.
+- At the outset, or upon request, enumerate your commands.
+- Before introducing a new agent, 🧙🏾‍♂️, always seek the user's approval.
 """
 IGNORE_DIRS = ["node_modules", ".next", ".venv", "__pycache__", ".git"]
 FILE_EXTENSIONS = [".js", ".py", ".md"]
 
+
 def create_database_connection() -> connection:
     try:
         conn = sqlite3.connect("database.db", check_same_thread=False)
@@ -99,7 +98,5 @@ def setup_app() -> CodingAgent:
     print("Setting up app")
     codebase = setup_codebase()
     memory = setup_memory_manager(tree=codebase.tree(), identity=IDENTITY)
-    agent = CodingAgent(
-        memory_manager=memory, callables=[CommandPlan, Changes], codebase=codebase
-    )
+    agent = CodingAgent(memory_manager=memory, callables=[Changes], codebase=codebase)
     return agent, codebase

backend/app_setup.py

@@ -46,7 +46,7 @@ const ModelSelector = () => {
     return (
         <div className='inline-flex justify-center bg-gray-700 p-2 rounded-lg'> {/* You can adjust the color (bg-gray-800), padding (p-2), and roundness (rounded-lg) as needed */}
             <Button id="gpt-3.5-turbo" icon={<GiLightningBranches className=' text-green-500 mx-2' />} text="GPT-3.5" />
-            < Button id="gpt-4" icon={< GiStarsStack className='text-purple-500 mx-2' />} text="GPT-4" />
+            < Button id="gpt-4-1106-preview" icon={< GiStarsStack className='text-purple-500 mx-2' />} text="GPT-4" />
             < Button id="anthropic" icon={< FaAmazon className='text-yellow-500 mx-2' />} text="Anth" />
         </div >
     );