feat: ollama support

lua/codecompanion/adapter.lua

@@ -0,0 +1,33 @@
+---@class CodeCompanion.Adapter
+---@field name string
+---@field url string
+---@field header table
+---@field parameters table
+---@field schema table
+local Adapter = {}
+
+---@class CodeCompanion.AdapterArgs
+---@field name string
+---@field url string
+---@field header table
+---@field parameters table
+---@field schema table
+
+---@param args table
+---@return CodeCompanion.Adapter
+function Adapter.new(args)
+  return setmetatable(args, { __index = Adapter })
+end
+
+---@param settings table
+---@return CodeCompanion.Adapter
+function Adapter:set_params(settings)
+  -- TODO: Need to take into account the schema's "mapping" field
+  for k, v in pairs(settings) do
+    self.parameters[k] = v
+  end
+
+  return self
+end
+
+return Adapter

lua/codecompanion/adapters/openai.lua

@@ -0,0 +1,134 @@
+local Adapter = require("codecompanion.adapter")
+
+---@class CodeCompanion.Adapter
+---@field name string
+---@field url string
+---@field headers table
+---@field parameters table
+---@field schema table
+
+local adapter = {
+  name = "OpenAI",
+  url = "https://api.openai.com/v1/chat/completions",
+  headers = {
+    content_type = "application/json",
+    Authorization = "Bearer ", -- ignore the API key for now
+  },
+  parameters = {
+    stream = true,
+  },
+  schema = {
+    model = {
+      order = 1,
+      mapping = "parameters",
+      type = "enum",
+      desc = "ID of the model to use. See the model endpoint compatibility table for details on which models work with the Chat API.",
+      default = "gpt-4-0125-preview",
+      choices = {
+        "gpt-4-1106-preview",
+        "gpt-4",
+        "gpt-3.5-turbo-1106",
+        "gpt-3.5-turbo",
+      },
+    },
+    temperature = {
+      order = 2,
+      mapping = "parameters",
+      type = "number",
+      optional = true,
+      default = 1,
+      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.",
+      validate = function(n)
+        return n >= 0 and n <= 2, "Must be between 0 and 2"
+      end,
+    },
+    top_p = {
+      order = 3,
+      mapping = "parameters",
+      type = "number",
+      optional = true,
+      default = 1,
+      desc = "An alternative to sampling with temperature, called nucleus sampling, where the model considers the results of the tokens with top_p probability mass. So 0.1 means only the tokens comprising the top 10% probability mass are considered. We generally recommend altering this or temperature but not both.",
+      validate = function(n)
+        return n >= 0 and n <= 1, "Must be between 0 and 1"
+      end,
+    },
+    stop = {
+      order = 4,
+      mapping = "parameters",
+      type = "list",
+      optional = true,
+      default = nil,
+      subtype = {
+        type = "string",
+      },
+      desc = "Up to 4 sequences where the API will stop generating further tokens.",
+      validate = function(l)
+        return #l >= 1 and #l <= 4, "Must have between 1 and 4 elements"
+      end,
+    },
+    max_tokens = {
+      order = 5,
+      mapping = "parameters",
+      type = "integer",
+      optional = true,
+      default = nil,
+      desc = "The maximum number of tokens to generate in the chat completion. The total length of input tokens and generated tokens is limited by the model's context length.",
+      validate = function(n)
+        return n > 0, "Must be greater than 0"
+      end,
+    },
+    presence_penalty = {
+      order = 6,
+      mapping = "parameters",
+      type = "number",
+      optional = true,
+      default = 0,
+      desc = "Number between -2.0 and 2.0. Positive values penalize new tokens based on whether they appear in the text so far, increasing the model's likelihood to talk about new topics.",
+      validate = function(n)
+        return n >= -2 and n <= 2, "Must be between -2 and 2"
+      end,
+    },
+    frequency_penalty = {
+      order = 7,
+      mapping = "parameters",
+      type = "number",
+      optional = true,
+      default = 0,
+      desc = "Number between -2.0 and 2.0. Positive values penalize new tokens based on their existing frequency in the text so far, decreasing the model's likelihood to repeat the same line verbatim.",
+      validate = function(n)
+        return n >= -2 and n <= 2, "Must be between -2 and 2"
+      end,
+    },
+    logit_bias = {
+      order = 8,
+      mapping = "parameters",
+      type = "map",
+      optional = true,
+      default = nil,
+      desc = "Modify the likelihood of specified tokens appearing in the completion. Maps tokens (specified by their token ID) to an associated bias value from -100 to 100. Use https://platform.openai.com/tokenizer to find token IDs.",
+      subtype_key = {
+        type = "integer",
+      },
+      subtype = {
+        type = "integer",
+        validate = function(n)
+          return n >= -100 and n <= 100, "Must be between -100 and 100"
+        end,
+      },
+    },
+    user = {
+      order = 9,
+      mapping = "parameters",
+      type = "string",
+      optional = true,
+      default = nil,
+      desc = "A unique identifier representing your end-user, which can help OpenAI to monitor and detect abuse. Learn more.",
+      validate = function(u)
+        return u:len() < 100, "Cannot be longer than 100 characters"
+      end,
+    },
+  },
+}
+
+return Adapter.new(adapter)

lua/spec/codecompanion/adapter_spec.lua

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+local assert = require("luassert")
+
+local chat_buffer_settings = {
+  frequency_penalty = 0,
+  model = "gpt-4-0125-preview",
+  presence_penalty = 0,
+  temperature = 1,
+  top_p = 1,
+  stop = nil,
+  max_tokens = nil,
+  logit_bias = nil,
+  user = nil,
+}
+
+describe("Adapter", function()
+  it("can form parameters from a chat buffer's settings", function()
+    local adapter = require("codecompanion.adapters.openai")
+    local result = adapter:set_params(chat_buffer_settings)
+
+    -- Ignore this for now
+    result.parameters.stream = nil
+
+    assert.are.same(chat_buffer_settings, result.parameters)
+  end)
+end)