.env.example

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

.gitignore

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

aitist/app.py

@@ -1,46 +0,0 @@
-#!/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

@@ -0,0 +1,34 @@
+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

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+# 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

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+# This is a simple Python script that prints 'Hey there!'
+print("Hey there!")

pyproject.toml

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

tasks.py

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+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