add local llama.cpp
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@@ -31,13 +31,23 @@ return {
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end,
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llama_cpp = function()
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return require("codecompanion.adapters").extend("openai_compatible", {
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name = "llama-cpp",
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name = "llama.cpp",
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formatted_name = "llama.cpp",
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opts = {
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stream = true,
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stream = false,
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},
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schema = {
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model = {
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default = "qwen2.5-coder-14b-instruct",
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choices = {
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["qwen2.5-coder-14b-instruct"] = { opts = { can_reason = true } },
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["/models/lmstudio-community/DeepSeek-R1-Distill-Qwen-7B-GGUF/DeepSeek-R1-Distill-Qwen-7B-Q4_K_M.gguf"] = {
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opts = { can_reason = true },
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},
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["/models/lmstudio-community/Qwen2.5-7B-Instruct-1M-GGUF/Qwen2.5-7B-Instruct-1M-Q4_K_M.gguf"] = {
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opts = { can_reason = true },
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},
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},
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},
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temperature = {
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order = 2,
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@@ -45,7 +55,6 @@ return {
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type = "number",
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optional = true,
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default = 0.2,
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desc = "What sampling temperature to use, between 0 and 2. Higher values like 0.8 will make the output more random, while lower values like 0.2 will make it more focused and deterministic. We generally recommend altering this or top_p but not both.",
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validate = function(n)
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return n >= 0 and n <= 2, "Must be between 0 and 2"
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end,
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@@ -60,11 +69,11 @@ return {
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},
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strategies = {
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chat = {
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adapter = "llama_cpp",
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adapter = "copilot",
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roles = {
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-- llm = " Assistant",
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llm = function(adapter)
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return "CodeCompanion (" .. adapter.formatted_name .. ")"
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print(vim.inspect(adapter))
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return " Assistant (" .. adapter.formatted_name .. " - " .. adapter.parameters.model .. ")"
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end,
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user = " User",
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},
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