.env.example

@@ -0,0 +1,2 @@
+OPENAI_API_KEY = ''
+OAI_CONFIG_LIST = '[]'

.gitignore

@@ -1,2 +1,5 @@
-.aider*
+.cache
-.idea
+.coding
+.env
+__pycache__
+

aitist/app.py

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+#!/usr/bin/env python
+"""Sample code slightly modified from https://github.com/microsoft/autogen/blob/main/notebook/agentchat_auto_feedback_from_code_execution.ipynb """
+
+from os import getenv
+
+import autogen
+from dotenv import load_dotenv
+
+# Load local configuration from .env
+load_dotenv()
+
+config_list = autogen.config_list_from_json(
+    "OAI_CONFIG_LIST",
+    filter_dict={
+        "model": ["gpt-3.5-turbo"]
+    },
+)
+
+# create an AssistantAgent named "assistant"
+assistant = autogen.AssistantAgent(
+    name="assistant",
+    llm_config={
+        "cache_seed": 42,  # seed for caching and reproducibility
+        "config_list": config_list,  # a list of OpenAI API configurations
+        "temperature": 0,  # temperature for sampling
+    },  # configuration for autogen's enhanced inference API which is compatible with OpenAI API
+)
+
+# create a UserProxyAgent instance named "user_proxy"
+user_proxy = autogen.UserProxyAgent(
+    name="user_proxy",
+    human_input_mode="NEVER",
+    max_consecutive_auto_reply=10,
+    is_termination_msg=lambda x: x.get("content", "").rstrip().endswith("TERMINATE"),
+    code_execution_config={
+        "work_dir": ".coding",
+        "use_docker": False,  # set to True or image name like "python:3" to use docker
+    },
+)
+
+if __name__ == "__main__":
+    # the assistant receives a message from the user_proxy, which contains the task description
+    user_proxy.initiate_chat(
+        assistant,
+        message="""What date is today? Compare the year-to-date gain for META and TESLA.""",
+    )

app.py

@@ -1,34 +0,0 @@
-from fastapi import FastAPI, File, UploadFile
-import tempfile
-import os
-from fastapi import FastAPI
-from fastapi.openapi.docs import get_swagger_ui_html
-
-# Assuming Celery is already set up and imported correctly in the project.
-from tasks import delete_temp_file  # Import your Celery task here.
-
-app = FastAPI(
-    title="AITist API",
-    description="This is a simple API for AI Tist.",
-    version="1.0.0",
-    docs_url="/docs",  # Enable Swagger UI
-)
-
-@app.get("/docs")
-async def custom_swagger_ui_html():
-    return get_swagger_ui_html(openapi_url=app.openapi_url, title=app.title + " - Swagger UI")
-
-@app.post("/uploadfile/")
-async def upload_file(file: UploadFile = File(...)):
-    contents = await file.read()
-    
-    # Save the file to a temporary directory
-    temp_dir = tempfile.gettempdir()
-    temp_file_path = os.path.join(temp_dir, file.filename)
-    with open(temp_file_path, 'wb') as f:
-        f.write(contents)
-
-    # Call the Celery task that deletes the file after processing.
-    delete_temp_file.delay(temp_file_path)  # Assuming this is your Celery task name.
-
-    return {"filename": file.filename}

flow.md

@@ -1,27 +0,0 @@
-# The AItist Listening Flow
-
-(implementation outline: https://github.com/lablab-ai/Whisper-transcription_and_diarization-speaker-identification-/blob/main/transcribtion_diarization.ipynb
-
-```mermaid
-flowchart TD
-    subgraph "Context Input"
-    record[\VAD/] --> transcribe
-    record --> diarize
-    diarize --> identify_speakers
-    identify_speakers --> regard{{Do speakers matter}}
-    transcribe --> regard
-    regard --yes--> parse_context
-    regard --"no"--> stop[/Stop\]
-    regard --some--> log_speakers
-    log_speakers --> parse_context
-    parse_context --> known{{Context known}}
-    known --"no"--> log_context[Log for async analysis]
-    end
-
-    subgraph Process
-        known --yes--> apply_context_prompt
-        apply_context_prompt --> llm_find_action["Find action from text"]
-    end
-
-    
-```

main.py

@@ -1,2 +0,0 @@
-# This is a simple Python script that prints 'Hey there!'
-print("Hey there!")

pyproject.toml

@@ -1,18 +1,16 @@
 [tool.poetry]
 name = "aitist"
 version = "0.1.0"
-description = "A new Python project managed by Poetry."
+description = ""
-authors = ["Timothy Farrell <tim@thecookiejar.me>"]
+authors = ["Your Name <you@example.com>"]
-package-mode = false
+readme = "README.md"
 
 [tool.poetry.dependencies]
-python = "^3.11"
+python = ">=3.9,<3.12"
-fastapi = "^0.111.1"
+pyautogen = "^0.2.2"
-uvicorn = {extras = ["standard"], version = "^0.17.6"}
+python-dotenv = "^1.0.0"
-celery = "^5.4.0"
+
-pydantic = "^2.8.2"
-pyannote-audio = "^3.3.1"
 
 [build-system]
-requires = ["poetry-core>=1.0.0"]
+requires = ["poetry-core"]
 build-backend = "poetry.core.masonry.api"

tasks.py

@@ -1,31 +0,0 @@
-from celery import shared_task
-
-@shared_task
-def delete_temp_file(file_path):
-    """Celery task to delete a temporary file."""
-    # Implementation goes here.
-    pass
-
-@shared_task
-def diarize(audio_path):
-    """
-    Celery task that performs diarization on an audio file.
-    Placeholder for actual implementation.
-    """
-    pass
-
-@shared_task
-def transcribe(audio_path):
-    """
-    Celery task that transcribes speech from an audio file to text.
-    Placeholder for actual implementation.
-    """
-    pass
-
-@shared_task
-def identify(image_path):
-    """
-    Celery task that identifies objects or features in an image.
-    Placeholder for actual implementation.
-    """
-    pass