Writing Better Code with Ollama
TLDRThe video discusses the release of an official Node.js library for Ollama and its integration with Python. The creator shares their experience with using Ollama's chat endpoint, highlighting the benefits of streaming responses via an async generator for a faster feel. They also introduce Llama Coder and Continue.dev, two VS Code extensions that offer local coding assistance without internet, perfect for those in areas with limited connectivity. The video provides a setup guide for these tools, encouraging viewers to explore and customize their coding experience with different models and settings.
Takeaways
- 🚀 The Ollama team has released an official Node.js library for Ollama, which can be found on GitHub.
- 📝 The speaker plans to start building with the Node.js library and its Python equivalent soon.
- 🔌 Initially, the chat endpoint is used with a system prompt, and the response is in JSON format, including performance metrics.
- ⏱️ Streaming is introduced as a way to get faster feedback, though it results in an error when set to true due to the return type changing to an async generator.
- 🧠 Llama Coder is a tool that autocompletes code based on user input, including comments, and is an alternative to GitHub Copilot.
- 🛠️ The speaker seeks help from Continue.dev to find an alternative to console.log that doesn't add a newline, leading to the use of process.stdout.write.
- 🔧 Both Llama Coder and Continue.dev are free VS Code extensions that work offline, which is useful for those without constant internet access.
- 🏞️ The speaker, living on an island, values being able to work on code during their ferry rides without internet.
- 🛠️ The setup for using Ollama involves installing Ollama, the Llama Coder extension, and Continue, with specific model configurations detailed.
- 📚 The speaker suggests reviewing Continue's documentation for further capabilities and disabling telemetry for offline use.
- 🤖 Other VS Code extensions like Code GPT and Ollama Autocoder are mentioned, but the speaker finds Llama Coder and Continue to be the best fit.
Q & A
What is the recent development from the Ollama team?
-The Ollama team has recently released an official Node.js library for Ollama, which can be found on GitHub.
How does the chat endpoint of the Ollama library work?
-The chat endpoint of the Ollama library works by taking a system prompt and an initial question as input and returns a JSON blob containing the output and performance metrics.
What is the default behavior of the chat endpoint in terms of response delivery?
-By default, the chat endpoint does not stream responses. It waits for the full response to be completed before delivering it as a JSON blob.
What happens when you set the stream to true in the Ollama library?
-Setting the stream to true changes the function to return an async generator instead of a JSON blob, which requires a different handling approach.
What is Llama Coder and how does it assist in coding?
-Llama Coder is a VS Code extension that assists in coding by automatically typing out code suggestions based on the user's needs. It can complete code snippets when the user presses tab.
How can you avoid newlines when printing tokens in the Ollama library?
-To avoid newlines when printing tokens, you can use 'process.stdout.write' instead of 'console.log' to output the tokens without breaking the lines.
What are the benefits of using Continue.dev in conjunction with Llama Coder?
-Continue.dev is beneficial as it provides an alternative to console.log that doesn't add a newline, and it allows users to ask questions and receive code suggestions without an internet connection, making it ideal for offline coding scenarios.
How does the setting of the Llama Coder extension affect its performance?
-The setting of the Llama Coder extension, specifically the model used, affects its performance in terms of speed and accuracy. Users can choose the model that best suits their needs based on response time and accuracy.
What is the role of the JSON config file in Continue?
-The JSON config file in Continue allows users to add any model available with Ollama, providing flexibility in selecting the desired model for code suggestions.
What are some other VS Code extensions similar to Llama Coder and Continue?
-Other VS Code extensions similar to Llama Coder and Continue include Code GPT and Ollama Autocoder. These extensions offer different features and capabilities to assist in coding.
What is the significance of offline capabilities for a coder living on an island near Seattle?
-Offline capabilities are significant for a coder living on an island near Seattle because the journey to the mainland involves a ferry ride where there is no cell service. Being able to code effectively without an internet connection ensures productive use of time during such travel.
Outlines
🚀 Introduction to Ollama Node.js Library and Llama Coder
The speaker introduces the Ollama Node.js library and shares their intention to start building with it and its Python equivalent. They demonstrate the use of the library by importing it and calling the chat endpoint with a system prompt and initial question. The output is initially a JSON blob, which is received after the full response. The speaker then discusses the benefits of streaming responses and the error encountered when trying to use an async generator. They mention the use of Llama Coder, an alternative to Copilot, and its ability to autocomplete code based on typed comments. The speaker also talks about the process of refining the output to display tokens without newlines and the role of Continue.dev in assisting with coding questions.
Mindmap
Keywords
💡Ollama
💡GitHub
💡Python
💡Chat Endpoint
💡JSON
💡Streaming
💡Async Generator
💡Llama Coder
💡Continue.dev
💡process.stdout.write
💡VS Code Extensions
Highlights
The Ollama team has released an official Node.js library for Ollama, which is available on GitHub.
The user plans to start building with the Node.js library and its Python equivalent soon.
The chat endpoint of Ollama can be called with a system prompt and an initial question.
By default, the chat endpoint does not stream, resulting in a JSON blob with output and performance metrics.
Setting the stream to true changes the function to return an async generator instead of a JSON blob, requiring a different handling method.
The user utilizes Llama Coder, an alternative to Copilot, which auto-completions code snippets based on typed prompts.
Llama Coder is not perfect but provides a good starting point for coding.
Continue.dev is a platform that allows users to ask coding-related questions and receive answers.
process.stdout.write is an alternative to console.log that doesn't add a newline, which can be useful for certain coding scenarios.
The user mentions living on an island near Seattle and coding on a ferry without internet, highlighting the offline utility of these tools.
Ollama needs to be installed and running to use the Node.js library and Llama Coder extension.
The Llama Coder extension offers different models to choose from, with Deepseek Coder 1.3b q4 being a fast and efficient option.
Continue.dev has no upfront settings but allows users to select the model to use and disable telemetry for offline use.
Other VS Code extensions like Code GPT and Ollama Autocoder are available, but Llama Coder and Continue seem to be the most suitable for the user's needs.
The user expresses interest in trying out Cody from Sourcegraph and is open to suggestions for other configurations.
The user invites viewers to share their setups and experiences with local alternatives to Copilot.
The video aims to provide insights into the use of local coding tools as an alternative to cloud-based services like Copilot.