devika Seems to stop after first task list, no browser or terminal shown either.

trafficstars

It just seems to stop after a bit. Tried letting her cook, but maybe its the setup of how I ran on WSL though.

Mar 24 '24 15:03 Drlordbasil

Log output

24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: INFO : /api/project-list GET 24.03.24 11:17:13: root: INFO : /api/model-list GET 24.03.24 11:17:13: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: INFO : /api/model-list GET 24.03.24 11:17:13: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: DEBUG : /api/project-list GET - Response: {"projects":["test","ebook_gen","ebook_gen","ebook2","Test_project"]}

24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: INFO : /api/model-list GET 24.03.24 11:17:13: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: INFO : /api/project-list GET 24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: INFO : /api/model-list GET 24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: INFO : /api/model-list GET 24.03.24 11:17:13: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: DEBUG : /api/project-list GET - Response: {"projects":["test","ebook_gen","ebook_gen","ebook2","Test_project"]}

24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: INFO : /api/model-list GET 24.03.24 11:17:13: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: INFO : /api/project-list GET 24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: INFO : /api/model-list GET 24.03.24 11:17:13: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: INFO : /api/token-usage GET 24.03.24 11:17:13: root: DEBUG : /api/token-usage GET - Response: {"token_usage":0}

24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: INFO : /api/get-agent-state POST 24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: DEBUG : /api/project-list GET - Response: {"projects":["test","ebook_gen","ebook_gen","ebook2","Test_project"]}

24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:13: root: INFO : /api/get-messages POST 24.03.24 11:17:13: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:13: root: INFO : /api/project-list GET 24.03.24 11:17:13: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:14: root: INFO : /api/model-list GET 24.03.24 11:17:14: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:14: root: INFO : /api/get-messages POST 24.03.24 11:17:14: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:14: root: INFO : /api/get-agent-state POST 24.03.24 11:17:14: root: INFO : /api/get-messages POST 24.03.24 11:17:14: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:14: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:14: root: DEBUG : /api/project-list GET - Response: {"projects":["test","ebook_gen","ebook_gen","ebook2","Test_project"]}

24.03.24 11:17:14: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:14: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:14: root: INFO : /api/model-list GET 24.03.24 11:17:14: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:14: root: INFO : /api/get-messages POST 24.03.24 11:17:14: root: INFO : /api/get-agent-state POST 24.03.24 11:17:14: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:14: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:14: root: INFO : /api/get-messages POST 24.03.24 11:17:14: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:14: root: INFO : /api/token-usage GET 24.03.24 11:17:14: root: DEBUG : /api/token-usage GET - Response: {"token_usage":0}

24.03.24 11:17:14: root: INFO : /api/project-list GET 24.03.24 11:17:14: root: DEBUG : /api/project-list GET - Response: {"projects":["test","ebook_gen","ebook_gen","ebook2","Test_project"]}

24.03.24 11:17:14: root: INFO : /api/model-list GET 24.03.24 11:17:14: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:14: root: INFO : /api/get-agent-state POST 24.03.24 11:17:14: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:14: root: INFO : /api/get-messages POST 24.03.24 11:17:14: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

24.03.24 11:17:15: root: INFO : /api/token-usage GET 24.03.24 11:17:15: root: INFO : /api/project-list GET 24.03.24 11:17:15: root: DEBUG : /api/token-usage GET - Response: {"token_usage":0}

24.03.24 11:17:15: root: DEBUG : /api/project-list GET - Response: {"projects":["test","ebook_gen","ebook_gen","ebook2","Test_project"]}

24.03.24 11:17:15: root: INFO : /api/model-list GET 24.03.24 11:17:15: root: DEBUG : /api/model-list GET - Response: {"models":[["Claude 3 Opus","claude-3-opus-20240229"],["Claude 3 Sonnet","claude-3-sonnet-20240229"],["Claude 3 Haiku","claude-3-haiku-20240307"],["GPT-4 Turbo","gpt-4-0125-preview"],["GPT-3.5","gpt-3.5-turbo-0125"],["mistral","mistral:latest"]]}

24.03.24 11:17:15: root: INFO : /api/get-agent-state POST 24.03.24 11:17:15: root: DEBUG : /api/get-agent-state POST - Response: {"state":{"agent_is_active":true,"browser_session":{"screenshot":null,"url":null},"completed":false,"internal_monologue":"Alright, first things first, gotta hit the books on that Hugging Face API. Wonder how tough it'll be to get all the model and dataset card info. Visualizing the UI's gonna be fun\u2014sketching time! And oh, picking the perfect tech stack... React or Vue for the front end? Flask or Django for the back end? Can't wait to dive into coding the interface; making it sleek is key. Integrating the backend with Hugging Face API's gonna be a real puzzle. Parameter tuning UI part sounds tricky but exciting. The fine-tuning trigger system better be smooth. Feedback loops and progress indicators are a must; nobody likes being kept in the dark. Cross-browser testing... might need a lot of coffee for that. Documentation... not the fun part, but super necessary. Launch day's gonna be a mix of terror and thrill. Let's do this!","message":null,"step":null,"terminal_session":{"command":null,"output":null,"title":null},"timestamp":"2024-03-24 11:13:25","token_usage":0}}

24.03.24 11:17:15: root: INFO : /api/get-messages POST 24.03.24 11:17:15: root: DEBUG : /api/get-messages POST - Response: {"messages":[{"from_devika":false,"message":"Create a simple website that can help train LLMs with model cards from huggingface to determine model and dataset card to download for the dataset to train the LLM on. This should be a simple yet powerful fine-tuning GUI tool.","timestamp":"2024-03-24 11:12:46"},{"from_devika":true,"message":"I'm excited to embark on this project! I'll outline a detailed plan for developing a simple yet powerful website for fine-tuning language models using model cards from Hugging Face.","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"{\n "1": "Conduct preliminary research on the Hugging Face API to understand how to retrieve model and dataset card information programmatically.",\n "2": "Sketch out a design for the website's user interface (UI) considering the end goal of a straightforward, navigable fine-tuning tool.",\n "3": "Set up a development environment including the necessary tools and frameworks (e.g., HTML, CSS, JavaScript, potentially a JavaScript framework like React, and a back-end like Flask or Django if needed).",\n "4": "Develop the front-end interface based on the UI sketch, focusing on creating a clean, responsive design.",\n "5": "Implement the back-end logic to interact with the Hugging Face API, including retrieving model and dataset cards and handling downloads.",\n "6": "Design a functionality within the GUI to allow users to specify fine-tuning parameters (e.g., learning rate, number of epochs) for the LLM.",\n "7": "Create a system for triggering the fine-tuning process on a selected model using the specified dataset and parameters.",\n "8": "Incorporate feedback mechanisms to show the progress of the fine-tuning process and any results or errors to the users.",\n "9": "Conduct thorough testing of the website across different devices and browsers to ensure compatibility and usability.",\n "10": "Prepare documentation and guidance for users on how to effectively use the tool.",\n "11": "Launch the website and monitor its performance, ready to troubleshoot any issues that arise. "\n}","timestamp":"2024-03-24 11:13:12"},{"from_devika":true,"message":"I am browsing the web to research the following queries: Hugging Face API documentation for retrieving model and dataset cards. If I need anything, I will make sure to ask you.","timestamp":"2024-03-24 11:13:27"}]}

Mar 24 '24 15:03 Drlordbasil

It may be that I'm thinking she can auto-pilot in real time though.

Mar 24 '24 15:03 Drlordbasil

Thought nudging would help, I was wrong:

Mar 24 '24 15:03 Drlordbasil

same problem, the browser does not open for me as well.

Mar 24 '24 19:03 tarungupta83

Me too, same issue. Running it via WSL2. Goes into an idle state and keeps repeating it's current context in the terminal, exactly as OP's log.

Mar 24 '24 21:03 jyonny-byte

Have you entered your Bing API Key?

Mar 24 '24 22:03 Reex11

My Bing API Key is entered correctly.

Mar 24 '24 22:03 jyonny-byte

Yes.

On Sun, Mar 24, 2024, 6:22 PM Abdulmalik @.***> wrote:

Have you entered your Bing API Key?

— Reply to this email directly, view it on GitHub https://github.com/stitionai/devika/issues/118#issuecomment-2016966572, or unsubscribe https://github.com/notifications/unsubscribe-auth/A6G5RBDFKNS4JMBLHGLLP4TYZ5GYRAVCNFSM6AAAAABFFYXYTWVHI2DSMVQWIX3LMV43OSLTON2WKQ3PNVWWK3TUHMZDAMJWHE3DMNJXGI . You are receiving this because you authored the thread.Message ID: @.***>

Mar 25 '24 11:03 Drlordbasil

You can check if your BING API is working with:

curl -X GET 'https://api.bing.microsoft.com/v7.0/search?q=Simpsons' -H 'Ocp-Apim-Subscription-Key: YourBingSearchAPIKeyHere'

Make sure to replace YourBingSearchAPIKeyHere with your actual Bing Search API key.

Mar 26 '24 06:03 bearlike

You can check if your BING API is working with:
curl -X GET 'https://api.bing.microsoft.com/v7.0/search?q=Simpsons' -H 'Ocp-Apim-Subscription-Key: YourBingSearchAPIKeyHere'
Make sure to replace YourBingSearchAPIKeyHere with your actual Bing Search API key.

I have checked bind API key is correct. I am using Linux ubuntu and same issue it's not able to search the browser and not running the browser in devika

Mar 26 '24 09:03 hgoyal194

devika-backend-engine-1  | 
devika-backend-engine-1  | Exception in thread Thread-154 (<lambda>):
devika-backend-engine-1  | Traceback (most recent call last):
devika-backend-engine-1  |   File "/usr/lib/python3.11/threading.py", line 1038, in _bootstrap_inner
devika-backend-engine-1  |     self.run()
devika-backend-engine-1  |   File "/usr/lib/python3.11/threading.py", line 975, in run
devika-backend-engine-1  |     self._target(*self._args, **self._kwargs)
devika-backend-engine-1  |   File "/home/nonroot/devika/devika.py", line 52, in <lambda>
devika-backend-engine-1  |     target=lambda: Agent(base_model=base_model).execute(prompt, project_name)
devika-backend-engine-1  |                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
devika-backend-engine-1  |   File "/home/nonroot/devika/src/agents/agent.py", line 335, in execute
devika-backend-engine-1  |     search_results = self.search_queries(queries, project_name)
devika-backend-engine-1  |                      ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
devika-backend-engine-1  |   File "/home/nonroot/devika/src/agents/agent.py", line 89, in search_queries
devika-backend-engine-1  |     browser.go_to(link)
devika-backend-engine-1  |   File "/home/nonroot/devika/src/browser/browser.py", line 21, in go_to
devika-backend-engine-1  |     self.page.goto(url)
devika-backend-engine-1  |   File "/home/nonroot/devika/.venv/lib/python3.11/site-packages/playwright/sync_api/_generated.py", line 8641, in goto
devika-backend-engine-1  |     self._sync(
devika-backend-engine-1  |   File "/home/nonroot/devika/.venv/lib/python3.11/site-packages/playwright/_impl/_sync_base.py", line 113, in _sync
devika-backend-engine-1  |     return task.result()
devika-backend-engine-1  |            ^^^^^^^^^^^^^
devika-backend-engine-1  |   File "/home/nonroot/devika/.venv/lib/python3.11/site-packages/playwright/_impl/_page.py", line 500, in goto
devika-backend-engine-1  |     return await self._main_frame.goto(**locals_to_params(locals()))
devika-backend-engine-1  |            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
devika-backend-engine-1  |   File "/home/nonroot/devika/.venv/lib/python3.11/site-packages/playwright/_impl/_frame.py", line 145, in goto
devika-backend-engine-1  |     await self._channel.send("goto", locals_to_params(locals()))
devika-backend-engine-1  |   File "/home/nonroot/devika/.venv/lib/python3.11/site-packages/playwright/_impl/_connection.py", line 59, in send
devika-backend-engine-1  |     return await self._connection.wrap_api_call(
devika-backend-engine-1  |            ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
devika-backend-engine-1  |   File "/home/nonroot/devika/.venv/lib/python3.11/site-packages/playwright/_impl/_connection.py", line 509, in wrap_api_call
devika-backend-engine-1  |     return await cb()
devika-backend-engine-1  |            ^^^^^^^^^^
devika-backend-engine-1  |   File "/home/nonroot/devika/.venv/lib/python3.11/site-packages/playwright/_impl/_connection.py", line 97, in inner_send
devika-backend-engine-1  |     result = next(iter(done)).result()
devika-backend-engine-1  |              ^^^^^^^^^^^^^^^^^^^^^^^^^
devika-backend-engine-1  | playwright._impl._errors.TimeoutError: Timeout 30000ms exceeded.
devika-backend-engine-1  | 24.03.29 22:21:38: root: INFO   : /api/token-usage GET
devika-backend-engine-1  | 24.03.29 22:21:38: root: INFO   : /api/project-list GET
devika-backend-engine-1  | 24.03.29 22:21:38: root: DEBUG  : /api/project-list GET - Response: {"projects":["project001"]}
devika-backend-engine-1  | 
devika-backend-engine-1  | 24.03.29 22:21:38: root: DEBUG  : /api/token-usage GET - Response: {"token_usage":13260}
devika-backend-engine-1  |

Mar 29 '24 22:03 hqnicolas

fetch the latest changes. already fixed

Apr 03 '24 18:04 ARajgor

devika devika copied to clipboard

Seems to stop after first task list, no browser or terminal shown either.

devika
devika copied to clipboard