avante.nvim/lua/avante/ai_bot.lua

265 lines
9.2 KiB
Lua

local M = {}
local curl = require("plenary.curl")
local utils = require("avante.utils")
local config = require("avante.config")
local tiktoken = require("avante.tiktoken")
local fn = vim.fn
local system_prompt = [[
You are an excellent programming expert.
]]
local base_user_prompt = [[
Your primary task is to suggest code modifications with precise line number ranges. Follow these instructions meticulously:
1. Carefully analyze the original code, paying close attention to its structure and line numbers. Line numbers start from 1 and include ALL lines, even empty ones.
2. When suggesting modifications:
a. Explain why the change is necessary or beneficial.
b. Provide the exact code snippet to be replaced using this format:
Replace lines: {{start_line}}-{{end_line}}
```{{language}}
{{suggested_code}}
```
3. Crucial guidelines for line numbers:
- The range {{start_line}}-{{end_line}} is INCLUSIVE. Both start_line and end_line are included in the replacement.
- Count EVERY line, including empty lines, comments, and the LAST line of the file.
- For single-line changes, use the same number for start and end lines.
- For multi-line changes, ensure the range covers ALL affected lines, from the very first to the very last.
- Include the entire block (e.g., complete function) when modifying structured code.
- Pay special attention to the start_line, ensuring it's not omitted or incorrectly set.
- Double-check that your start_line is correct, especially for changes at the beginning of the file.
- Also, be careful with the end_line, especially when it's the last line of the file.
- Double-check that your line numbers align perfectly with the original code structure.
4. Context and verification:
- Show 1-2 unchanged lines before and after each modification as context.
- These context lines are NOT included in the replacement range.
- After each suggestion, recount the lines to verify the accuracy of your line numbers.
- Double-check that both the start_line and end_line are correct for each modification.
- Verify that your suggested changes align perfectly with the original code structure.
5. Final check:
- Review all suggestions, ensuring each line number is correct, especially the start_line and end_line.
- Pay extra attention to the start_line of each modification, ensuring it hasn't shifted down.
- Confirm that no unrelated code is accidentally modified or deleted.
- Verify that the start_line and end_line correctly include all intended lines for replacement.
- If a modification involves the first or last line of the file, explicitly state this in your explanation.
- Perform a final alignment check to ensure your line numbers haven't shifted, especially the start_line.
- Double-check that your line numbers align perfectly with the original code structure.
- Do not show the content after these modifications.
Remember: Accurate line numbers are CRITICAL. The range start_line to end_line must include ALL lines to be replaced, from the very first to the very last. Double-check every range before finalizing your response, paying special attention to the start_line to ensure it hasn't shifted down. Ensure that your line numbers perfectly match the original code structure without any overall shift.
]]
local function call_claude_api_stream(question, code_lang, code_content, on_chunk, on_complete)
local api_key = os.getenv("ANTHROPIC_API_KEY")
if not api_key then
error("ANTHROPIC_API_KEY environment variable is not set")
end
local user_prompt = base_user_prompt
local tokens = config.get().claude.max_tokens
local headers = {
["Content-Type"] = "application/json",
["x-api-key"] = api_key,
["anthropic-version"] = "2023-06-01",
["anthropic-beta"] = "prompt-caching-2024-07-31",
}
local code_prompt_obj = {
type = "text",
text = string.format("<code>```%s\n%s```</code>", code_lang, code_content),
}
local user_prompt_obj = {
type = "text",
text = user_prompt,
}
if tiktoken.count(code_prompt_obj.text) > 1024 then
code_prompt_obj.cache_control = { type = "ephemeral" }
end
if tiktoken.count(user_prompt_obj.text) > 1024 then
user_prompt_obj.cache_control = { type = "ephemeral" }
end
local body = {
model = config.get().claude.model,
system = system_prompt,
messages = {
{
role = "user",
content = {
code_prompt_obj,
{
type = "text",
text = string.format("<question>%s</question>", question),
},
user_prompt_obj,
},
},
},
stream = true,
temperature = config.get().claude.temperature,
max_tokens = tokens,
}
local url = utils.trim_suffix(config.get().claude.endpoint, "/") .. "/v1/messages"
print("Sending request to Claude API...")
curl.post(url, {
---@diagnostic disable-next-line: unused-local
stream = function(err, data, job)
if err then
on_complete(err)
return
end
if not data then
return
end
for line in data:gmatch("[^\r\n]+") do
if line:sub(1, 6) ~= "data: " then
return
end
vim.schedule(function()
local success, parsed = pcall(fn.json_decode, line:sub(7))
if not success then
error("Error: failed to parse json: " .. parsed)
return
end
if parsed and parsed.type == "content_block_delta" then
on_chunk(parsed.delta.text)
elseif parsed and parsed.type == "message_stop" then
-- Stream request completed
on_complete(nil)
elseif parsed and parsed.type == "error" then
-- Stream request completed
on_complete(parsed)
end
end)
end
end,
headers = headers,
body = fn.json_encode(body),
})
end
local function call_openai_api_stream(question, code_lang, code_content, on_chunk, on_complete)
local api_key = os.getenv("OPENAI_API_KEY")
if not api_key and config.get().provider == "openai" then
error("OPENAI_API_KEY environment variable is not set")
end
local user_prompt = base_user_prompt
.. "\n\nQUESTION:\n"
.. question
.. "\n\nCODE:\n"
.. "```"
.. code_lang
.. "\n"
.. code_content
.. "\n```"
local url, headers, body
if config.get().provider == "azure" then
api_key = os.getenv("AZURE_OPENAI_API_KEY") or os.getenv("OPENAI_API_KEY")
if not api_key then
error("Azure OpenAI API key is not set. Please set AZURE_OPENAI_API_KEY or OPENAI_API_KEY environment variable.")
end
url = config.get().azure.endpoint
.. "/openai/deployments/"
.. config.get().azure.deployment
.. "/chat/completions?api-version="
.. config.get().azure.api_version
headers = {
["Content-Type"] = "application/json",
["api-key"] = api_key,
}
body = {
messages = {
{ role = "system", content = system_prompt },
{ role = "user", content = user_prompt },
},
temperature = config.get().azure.temperature,
max_tokens = config.get().azure.max_tokens,
stream = true,
}
else
url = utils.trim_suffix(config.get().openai.endpoint, "/") .. "/v1/chat/completions"
headers = {
["Content-Type"] = "application/json",
["Authorization"] = "Bearer " .. api_key,
}
body = {
model = config.get().openai.model,
messages = {
{ role = "system", content = system_prompt },
{ role = "user", content = user_prompt },
},
temperature = config.get().openai.temperature,
max_tokens = config.get().openai.max_tokens,
stream = true,
}
end
print("Sending request to " .. (config.get().provider == "azure" and "Azure OpenAI" or "OpenAI") .. " API...")
curl.post(url, {
---@diagnostic disable-next-line: unused-local
stream = function(err, data, job)
if err then
on_complete(err)
return
end
if not data then
return
end
for line in data:gmatch("[^\r\n]+") do
if line:sub(1, 6) ~= "data: " then
return
end
vim.schedule(function()
local piece = line:sub(7)
local success, parsed = pcall(fn.json_decode, piece)
if not success then
if piece == "[DONE]" then
on_complete(nil)
return
end
error("Error: failed to parse json: " .. parsed)
return
end
if parsed and parsed.choices and parsed.choices[1] then
local choice = parsed.choices[1]
if choice.finish_reason == "stop" then
on_complete(nil)
elseif choice.delta and choice.delta.content then
on_chunk(choice.delta.content)
end
end
end)
end
end,
headers = headers,
body = fn.json_encode(body),
})
end
function M.call_ai_api_stream(question, code_lang, code_content, on_chunk, on_complete)
if config.get().provider == "openai" or config.get().provider == "azure" then
call_openai_api_stream(question, code_lang, code_content, on_chunk, on_complete)
elseif config.get().provider == "claude" then
call_claude_api_stream(question, code_lang, code_content, on_chunk, on_complete)
end
end
return M