Bumps version from 0.28.0 to 0.29.0

burr/tracking/server/backend.py

@@ -244,7 +244,7 @@ async def list_apps(
     ) -> Tuple[Sequence[ApplicationSummary], int]:
         project_filepath = os.path.join(self.path, project_id)
         if not os.path.exists(project_filepath):
-            return []
+            return [], 0
             # raise fastapi.HTTPException(status_code=404, detail=f"Project: {project_id} not found")
         out = []
         for entry in await aiofilesos.listdir(project_filepath):

burr/tracking/server/demo_data/demo_chatbot/chat-1-giraffe/graph.json

@@ -0,0 +1 @@
+{"type": "application", "entrypoint": "prompt", "actions": [{"type": "action", "name": "prompt", "reads": [], "writes": ["chat_history", "prompt"], "code": "@action(reads=[], writes=[\"chat_history\", \"prompt\"])\ndef process_prompt(state: State, prompt: str) -> State:\n    result = {\"chat_item\": {\"role\": \"user\", \"content\": prompt, \"type\": \"text\"}}\n    return (\n        state.wipe(keep=[\"prompt\", \"chat_history\"])\n        .append(chat_history=result[\"chat_item\"])\n        .update(prompt=prompt)\n    )\n", "inputs": [], "optional_inputs": ["prompt"]}, {"type": "action", "name": "check_openai_key", "reads": [], "writes": ["has_openai_key"], "code": "@action(reads=[], writes=[\"has_openai_key\"])\ndef check_openai_key(state: State) -> State:\n    result = {\"has_openai_key\": \"OPENAI_API_KEY\" in os.environ}\n    return state.update(**result)\n", "inputs": [], "optional_inputs": []}, {"type": "action", "name": "check_safety", "reads": ["prompt"], "writes": ["safe"], "code": "@action(reads=[\"prompt\"], writes=[\"safe\"])\ndef check_safety(state: State) -> State:\n    result = {\"safe\": \"unsafe\" not in state[\"prompt\"]}  # quick hack to demonstrate\n    return state.update(safe=result[\"safe\"])\n", "inputs": [], "optional_inputs": []}, {"type": "action", "name": "decide_mode", "reads": ["prompt"], "writes": ["mode"], "code": "@action(reads=[\"prompt\"], writes=[\"mode\"])\ndef choose_mode(state: State) -> State:\n    prompt = (\n        f\"You are a chatbot. You've been prompted this: {state['prompt']}. \"\n        f\"You have the capability of responding in the following modes: {', '.join(MODES)}. \"\n        \"Please respond with *only* a single word representing the mode that most accurately \"\n        \"corresponds to the prompt. Fr instance, if the prompt is 'draw a picture of a cat', \"\n        \"the mode would be 'generate_image'. If the prompt is 'what is the capital of France', the mode would be 'answer_question'.\"\n        \"If none of these modes apply, please respond with 'unknown'.\"\n    )\n\n    result = _get_openai_client().chat.completions.create(\n        model=\"gpt-4\",\n        messages=[\n            {\"role\": \"system\", \"content\": \"You are a helpful assistant\"},\n            {\"role\": \"user\", \"content\": prompt},\n        ],\n    )\n    content = result.choices[0].message.content\n    mode = content.lower()\n    if mode not in MODES:\n        mode = \"unknown\"\n    result = {\"mode\": mode}\n    return state.update(**result)\n", "inputs": [], "optional_inputs": []}, {"type": "action", "name": "generate_image", "reads": ["prompt", "chat_history", "mode"], "writes": ["response"], "code": "@action(reads=[\"prompt\", \"chat_history\", \"mode\"], writes=[\"response\"])\ndef image_response(state: State, model: str = \"dall-e-2\") -> State:\n    \"\"\"Generates an image response to the prompt. Optional save function to save the image to a URL.\"\"\"\n    client = _get_openai_client()\n    result = client.images.generate(\n        model=model, prompt=state[\"prompt\"], size=\"1024x1024\", quality=\"standard\", n=1\n    )\n    response = result.data[0].url\n    result = {\"response\": {\"content\": response, \"type\": MODES[state[\"mode\"]], \"role\": \"assistant\"}}\n    return state.update(**result)\n", "inputs": ["model"], "optional_inputs": []}, {"type": "action", "name": "generate_code", "reads": ["prompt", "chat_history", "mode"], "writes": ["response"], "code": "@action(reads=[\"prompt\", \"chat_history\", \"mode\"], writes=[\"response\"])\ndef chat_response(\n    state: State, prepend_prompt: str, display_type: str = \"text\", model: str = \"gpt-3.5-turbo\"\n) -> State:\n    chat_history = copy.deepcopy(state[\"chat_history\"])\n    chat_history[-1][\"content\"] = f\"{prepend_prompt}: {chat_history[-1]['content']}\"\n    chat_history_api_format = [\n        {\n            \"role\": chat[\"role\"],\n            \"content\": chat[\"content\"],\n        }\n        for chat in chat_history\n    ]\n    client = _get_openai_client()\n    result = client.chat.completions.create(\n        model=model,\n        messages=chat_history_api_format,\n    )\n    response = result.choices[0].message.content\n    result = {\"response\": {\"content\": response, \"type\": MODES[state[\"mode\"]], \"role\": \"assistant\"}}\n    return state.update(**result)\n", "inputs": ["display_type", "model"], "optional_inputs": []}, {"type": "action", "name": "answer_question", "reads": ["prompt", "chat_history", "mode"], "writes": ["response"], "code": "@action(reads=[\"prompt\", \"chat_history\", \"mode\"], writes=[\"response\"])\ndef chat_response(\n    state: State, prepend_prompt: str, display_type: str = \"text\", model: str = \"gpt-3.5-turbo\"\n) -> State:\n    chat_history = copy.deepcopy(state[\"chat_history\"])\n    chat_history[-1][\"content\"] = f\"{prepend_prompt}: {chat_history[-1]['content']}\"\n    chat_history_api_format = [\n        {\n            \"role\": chat[\"role\"],\n            \"content\": chat[\"content\"],\n        }\n        for chat in chat_history\n    ]\n    client = _get_openai_client()\n    result = client.chat.completions.create(\n        model=model,\n        messages=chat_history_api_format,\n    )\n    response = result.choices[0].message.content\n    result = {\"response\": {\"content\": response, \"type\": MODES[state[\"mode\"]], \"role\": \"assistant\"}}\n    return state.update(**result)\n", "inputs": ["display_type", "model"], "optional_inputs": []}, {"type": "action", "name": "prompt_for_more", "reads": ["prompt", "chat_history"], "writes": ["response"], "code": "@action(reads=[\"prompt\", \"chat_history\"], writes=[\"response\"])\ndef prompt_for_more(state: State) -> State:\n    result = {\n        \"response\": {\n            \"content\": \"None of the response modes I support apply to your question. Please clarify?\",\n            \"type\": \"text\",\n            \"role\": \"assistant\",\n        }\n    }\n    return state.update(**result)\n", "inputs": [], "optional_inputs": []}, {"type": "action", "name": "response", "reads": ["response", "mode", "safe", "has_openai_key"], "writes": ["chat_history"], "code": "@action(reads=[\"response\", \"mode\", \"safe\", \"has_openai_key\"], writes=[\"chat_history\"])\ndef response(state: State) -> State:\n    if not state[\"has_openai_key\"]:\n        result = {\n            \"chat_item\": {\n                \"role\": \"assistant\",\n                \"content\": \"You have not set an API key for [OpenAI](https://www.openai.com). Do this \"\n                \"by setting the environment variable `OPENAI_API_KEY` to your key. \"\n                \"You can get a key at [OpenAI](https://platform.openai.com). \"\n                \"You can still look at chat history/examples.\",\n                \"type\": \"error\",\n            }\n        }\n    elif not state[\"safe\"]:\n        result = {\n            \"chat_item\": {\n                \"role\": \"assistant\",\n                \"content\": \"I'm sorry, I can't respond to that.\",\n                \"type\": \"error\",\n            }\n        }\n    else:\n        result = {\"chat_item\": state[\"response\"]}\n    return state.append(chat_history=result[\"chat_item\"])\n", "inputs": [], "optional_inputs": []}], "transitions": [{"type": "transition", "from_": "prompt", "to": "check_openai_key", "condition": "default"}, {"type": "transition", "from_": "check_openai_key", "to": "check_safety", "condition": "has_openai_key=True"}, {"type": "transition", "from_": "check_openai_key", "to": "response", "condition": "default"}, {"type": "transition", "from_": "check_safety", "to": "decide_mode", "condition": "safe=True"}, {"type": "transition", "from_": "check_safety", "to": "response", "condition": "default"}, {"type": "transition", "from_": "decide_mode", "to": "generate_image", "condition": "mode=generate_image"}, {"type": "transition", "from_": "decide_mode", "to": "generate_code", "condition": "mode=generate_code"}, {"type": "transition", "from_": "decide_mode", "to": "answer_question", "condition": "mode=answer_question"}, {"type": "transition", "from_": "decide_mode", "to": "prompt_for_more", "condition": "default"}, {"type": "transition", "from_": "generate_image", "to": "response", "condition": "default"}, {"type": "transition", "from_": "answer_question", "to": "response", "condition": "default"}, {"type": "transition", "from_": "generate_code", "to": "response", "condition": "default"}, {"type": "transition", "from_": "prompt_for_more", "to": "response", "condition": "default"}, {"type": "transition", "from_": "response", "to": "prompt", "condition": "default"}]}