feat: extract AI providers into dedicated providers module

src/providers.ts

@@ -0,0 +1,234 @@
+import * as vscode from "vscode"
+
+const SYSTEM_PROMPT =
+  "You are a helpful assistant that generates informative git commit messages based on git diffs output. Skip preamble and remove all backticks surrounding the commit message."
+
+const CONVENTIONAL_INSTRUCTION = `Based on the provided git diff, generate a concise and descriptive commit message.
+
+The commit message should:
+1. Have a short title (50-72 characters)
+2. Follow the Conventional Commits format (feat:, fix:, chore:, docs:, refactor:, test:, style:, etc.)
+3. Describe what was changed and why
+4. Be clear and informative`
+
+const SIMPLE_INSTRUCTION = `Based on the provided git diff, generate a short and clear one-line commit message (50-72 characters).`
+
+export interface AIProvider {
+  generateCommitMessage(diff: string, style: string, signal: AbortSignal): AsyncIterable<string>
+}
+
+// ─── OpenAI / Ollama ────────────────────────────────────────────────────────
+
+class OpenAICompatibleProvider implements AIProvider {
+  constructor(
+    private readonly apiKey: string,
+    private readonly model: string,
+    private readonly baseUrl: string,
+  ) {}
+
+  async *generateCommitMessage(diff: string, style: string, signal: AbortSignal): AsyncIterable<string> {
+    const instruction = style === "conventional" ? CONVENTIONAL_INSTRUCTION : SIMPLE_INSTRUCTION
+    const url = `${this.baseUrl}/chat/completions`
+
+    const response = await fetch(url, {
+      method: "POST",
+      signal,
+      headers: {
+        "Content-Type": "application/json",
+        Authorization: `Bearer ${this.apiKey}`,
+      },
+      body: JSON.stringify({
+        model: this.model,
+        stream: true,
+        messages: [
+          { role: "system", content: SYSTEM_PROMPT },
+          { role: "user", content: `${instruction}\n\n${diff}` },
+        ],
+      }),
+    })
+
+    if (!response.ok) {
+      const error = await response.text()
+      throw new Error(`OpenAI API error ${response.status}: ${error}`)
+    }
+
+    if (!response.body) {
+      throw new Error("No response body received")
+    }
+
+    yield* parseSSEStream(response.body, extractOpenAIDelta)
+  }
+}
+
+// ─── Anthropic ───────────────────────────────────────────────────────────────
+
+class AnthropicProvider implements AIProvider {
+  constructor(
+    private readonly apiKey: string,
+    private readonly model: string,
+    private readonly baseUrl: string,
+  ) {}
+
+  async *generateCommitMessage(diff: string, style: string, signal: AbortSignal): AsyncIterable<string> {
+    const instruction = style === "conventional" ? CONVENTIONAL_INSTRUCTION : SIMPLE_INSTRUCTION
+    const url = `${this.baseUrl}/messages`
+
+    const response = await fetch(url, {
+      method: "POST",
+      signal,
+      headers: {
+        "Content-Type": "application/json",
+        "x-api-key": this.apiKey,
+        "anthropic-version": "2023-06-01",
+      },
+      body: JSON.stringify({
+        model: this.model,
+        max_tokens: 512,
+        stream: true,
+        system: SYSTEM_PROMPT,
+        messages: [{ role: "user", content: `${instruction}\n\n${diff}` }],
+      }),
+    })
+
+    if (!response.ok) {
+      const error = await response.text()
+      throw new Error(`Anthropic API error ${response.status}: ${error}`)
+    }
+
+    if (!response.body) {
+      throw new Error("No response body received")
+    }
+
+    yield* parseSSEStream(response.body, extractAnthropicDelta)
+  }
+}
+
+// ─── SSE parsing helpers ─────────────────────────────────────────────────────
+
+async function* parseSSEStream(
+  body: ReadableStream<Uint8Array>,
+  extractDelta: (data: string) => string | null,
+): AsyncIterable<string> {
+  const reader = body.getReader()
+  const decoder = new TextDecoder()
+  let buffer = ""
+
+  try {
+    while (true) {
+      const { done, value } = await reader.read()
+      if (done) break
+
+      buffer += decoder.decode(value, { stream: true })
+      const lines = buffer.split("\n")
+      buffer = lines.pop() ?? ""
+
+      for (const line of lines) {
+        const trimmed = line.trim()
+        if (!trimmed.startsWith("data:")) continue
+
+        const data = trimmed.slice(5).trim()
+        if (data === "[DONE]") return
+
+        const text = extractDelta(data)
+        if (text) yield text
+      }
+    }
+  } finally {
+    reader.releaseLock()
+  }
+}
+
+function extractOpenAIDelta(data: string): string | null {
+  try {
+    const parsed = JSON.parse(data)
+    return parsed?.choices?.[0]?.delta?.content ?? null
+  } catch {
+    return null
+  }
+}
+
+function extractAnthropicDelta(data: string): string | null {
+  try {
+    const parsed = JSON.parse(data)
+    if (parsed?.type === "content_block_delta" && parsed?.delta?.type === "text_delta") {
+      return parsed.delta.text ?? null
+    }
+    return null
+  } catch {
+    return null
+  }
+}
+
+// ─── Factory ─────────────────────────────────────────────────────────────────
+
+export function createProvider(config: vscode.WorkspaceConfiguration): AIProvider {
+  const provider = config.get<string>("provider", "anthropic")
+  const apiKey = config.get<string>("apiKey", "")
+  const model = config.get<string>("model", "claude-haiku-4-5-20251001")
+  const customBaseUrl = config.get<string>("baseUrl", "")
+
+  switch (provider) {
+    case "anthropic": {
+      const baseUrl = customBaseUrl || "https://api.anthropic.com/v1"
+      if (!apiKey) throw new Error("Anthropic API key is required. Set it in Settings → Zemit AI Commit.")
+      return new AnthropicProvider(apiKey, model, baseUrl)
+    }
+    case "ollama": {
+      const baseUrl = customBaseUrl || "http://localhost:11434/v1"
+      return new OpenAICompatibleProvider("ollama", model, baseUrl)
+    }
+    default: {
+      const baseUrl = customBaseUrl || "https://api.openai.com/v1"
+      if (!apiKey) throw new Error("OpenAI API key is required. Set it in Settings → Zemit AI Commit.")
+      return new OpenAICompatibleProvider(apiKey, model, baseUrl)
+    }
+  }
+}
+
+// ─── Model discovery ──────────────────────────────────────────────────────────
+
+export async function fetchAvailableModels(config: vscode.WorkspaceConfiguration): Promise<string[]> {
+  const provider = config.get<string>("provider", "anthropic")
+  const apiKey = config.get<string>("apiKey", "")
+  const customBaseUrl = config.get<string>("baseUrl", "")
+
+  switch (provider) {
+    case "anthropic": {
+      const baseUrl = customBaseUrl || "https://api.anthropic.com/v1"
+      if (!apiKey) throw new Error("Anthropic API key is required. Set it in Settings → Zemit AI Commit.")
+      const response = await fetch(`${baseUrl}/models`, {
+        headers: {
+          "x-api-key": apiKey,
+          "anthropic-version": "2023-06-01",
+        },
+      })
+      if (!response.ok) throw new Error(`Anthropic API error ${response.status}: ${await response.text()}`)
+      const data = (await response.json()) as { data: { id: string }[] }
+      return data.data.map((m) => m.id).sort()
+    }
+    case "openai": {
+      const baseUrl = customBaseUrl || "https://api.openai.com/v1"
+      if (!apiKey) throw new Error("OpenAI API key is required. Set it in Settings → Zemit AI Commit.")
+      const response = await fetch(`${baseUrl}/models`, {
+        headers: { Authorization: `Bearer ${apiKey}` },
+      })
+      if (!response.ok) throw new Error(`OpenAI API error ${response.status}: ${await response.text()}`)
+      const data = (await response.json()) as { data: { id: string }[] }
+      return data.data
+        .map((m) => m.id)
+        .filter((id) => /^(gpt-|o1|o3|chatgpt-)/.test(id))
+        .sort()
+    }
+    case "ollama": {
+      const baseUrl = customBaseUrl || "http://localhost:11434/v1"
+      const response = await fetch(`${baseUrl}/models`)
+      if (!response.ok) throw new Error(`Ollama API error ${response.status}: ${await response.text()}`)
+      const data = (await response.json()) as { data?: { id: string }[]; models?: { name: string }[] }
+      if (data.data) return data.data.map((m) => m.id).sort()
+      if (data.models) return data.models.map((m) => m.name).sort()
+      return []
+    }
+    default:
+      return []
+  }
+}