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@ -75,15 +75,15 @@ To install Devika, follow these steps:
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1. Clone the Devika repository:
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```bash
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git clone https://github.com/stitionai/devika.git
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git clone https://git.telavivmakers.space/ro/prompt2code.git
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```
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2. Navigate to the project directory:
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```bash
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cd devika
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cd prompt2code
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```
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3. Create a virtual environment and install the required dependencies (you can use any virtual environment manager):
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```bash
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uv venv
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python -m venv venv
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# On macOS and Linux.
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source .venv/bin/activate
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22
challange.md
Normal file
22
challange.md
Normal file
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@ -0,0 +1,22 @@
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# Challenge: Generate img2vid using GenAI only!
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To generate a video from images using GenAI, we must first set up and Devika IDE for the TAMI server and then fix it to generate the code for the img2vid task.
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Tech specs:
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Find the Tesla-P40 spec on the TAMI server using the following command:
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```bash
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nvidia-smi
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```
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Steps:
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1. Install and set up Devika on TAMI computer with llama
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2. How does Devika work under the hood?
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- Is it using the same LLM thread or is it different for each iteration?
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- How does it generate the plan?
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- Fix : the bug that saves the file names wraped with `` !!!
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- Add logs to all files
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@ -1,27 +1,29 @@
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version: "3.9"
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services:
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ollama-service:
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image: ollama/ollama:latest
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expose:
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- 11434
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ports:
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- 11434:11434
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healthcheck:
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test: ["CMD-SHELL", "curl -f http://localhost:11434/ || exit 1"]
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interval: 5s
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timeout: 30s
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retries: 5
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start_period: 30s
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networks:
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- devika-subnetwork
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# ollama is running locally
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# ollama-service:
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# image: ollama/ollama:latest
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# expose:
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# - 11434
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# ports:
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# - 11434:11434
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# healthcheck:
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# test: ["CMD-SHELL", "curl -f http://localhost:11434/ || exit 1"]
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# interval: 5s
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# timeout: 30s
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# retries: 5
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# start_period: 30s
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# networks:
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# - devika-subnetwork
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devika-backend-engine:
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build:
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context: .
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dockerfile: devika.dockerfile
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depends_on:
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- ollama-service
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# ollama is running locally
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# depends_on:
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# - ollama-service
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expose:
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- 1337
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ports:
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