🚀 The Problem / Use Case
We want to run a private, cost-effective deployment of DeepSeek-R1 (Distilled 8B/32B) using RunPod Serverless instead of paying for the official DeepSeek API or a flat-rate dedicated cloud GPU.While the deepseek-v4-for-copilot extension supports custom baseUrl settings, connecting it to a scale-to-zero serverless endpoint (like RunPod) introduces a cold start latency (20–40 seconds) on the very first API request. This causes the initial connection to occasionally hang or fail if standard HTTP timeouts are strictly enforced.
💡 Proposed Solution
Formally document and optimize the configuration pipeline to support RunPod Serverless as a backend provider via standard OpenAI-compatible endpoints.Base URL Mapping: Override "deepseek-copilot.baseUrl" to route directly to https://runpod.ai{endpoint_id}/vllm/v1.Model Identifiers: Map "deepseek-copilot.modelIdOverrides" to the exact Hugging Face identifiers deployed on the RunPod worker (e.g., deepseek-ai/DeepSeek-R1-Distill-Llama-8B).
Timeout Resilience (Optional Feature Request)
If applicable, expose an internal request timeout configuration setting (e.g., deepseek-copilot.requestTimeout) or increase the default network timeout to 60 seconds to prevent cold-start failures.
Proposed Configuration Changes:
(settings.json)json{
"deepseek-copilot.baseUrl": "https://runpod.ai",
"deepseek-copilot.modelIdOverrides": {
"deepseek-v4-flash": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"deepseek-v4-pro": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
}
}
Use code with caution.
Alternatives :
ConsideredDedicated RunPod Instances: Fast execution and no cold starts, but costs run 24/7 ($150+ / month) even when idle.Ollama (Local Deployment): Free, but restricted by local hardware (VRAM limits) and slows down local IDE compilation performance.
BenefitsCost Efficiency:
Zero cost when the developer is not writing code or using Copilot Chat.Privacy: Model weights and execution run completely inside an isolated, private RunPod container.Native Integration: Retains all of Copilot's superior UI features, agent tools, and file workspace searching.
🚀 The Problem / Use Case
We want to run a private, cost-effective deployment of DeepSeek-R1 (Distilled 8B/32B) using RunPod Serverless instead of paying for the official DeepSeek API or a flat-rate dedicated cloud GPU.While the deepseek-v4-for-copilot extension supports custom baseUrl settings, connecting it to a scale-to-zero serverless endpoint (like RunPod) introduces a cold start latency (20–40 seconds) on the very first API request. This causes the initial connection to occasionally hang or fail if standard HTTP timeouts are strictly enforced.
💡 Proposed Solution
Formally document and optimize the configuration pipeline to support RunPod Serverless as a backend provider via standard OpenAI-compatible endpoints.Base URL Mapping: Override "deepseek-copilot.baseUrl" to route directly to https://runpod.ai{endpoint_id}/vllm/v1.Model Identifiers: Map "deepseek-copilot.modelIdOverrides" to the exact Hugging Face identifiers deployed on the RunPod worker (e.g., deepseek-ai/DeepSeek-R1-Distill-Llama-8B).
Timeout Resilience (Optional Feature Request)
If applicable, expose an internal request timeout configuration setting (e.g., deepseek-copilot.requestTimeout) or increase the default network timeout to 60 seconds to prevent cold-start failures.
Proposed Configuration Changes:
(settings.json)json{
"deepseek-copilot.baseUrl": "https://runpod.ai",
"deepseek-copilot.modelIdOverrides": {
"deepseek-v4-flash": "deepseek-ai/DeepSeek-R1-Distill-Llama-8B",
"deepseek-v4-pro": "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
}
}
Use code with caution.
Alternatives :
ConsideredDedicated RunPod Instances: Fast execution and no cold starts, but costs run 24/7 ($150+ / month) even when idle.Ollama (Local Deployment): Free, but restricted by local hardware (VRAM limits) and slows down local IDE compilation performance.
BenefitsCost Efficiency:
Zero cost when the developer is not writing code or using Copilot Chat.Privacy: Model weights and execution run completely inside an isolated, private RunPod container.Native Integration: Retains all of Copilot's superior UI features, agent tools, and file workspace searching.