feat: add Docker entrypoints, LLM providers, pipeline hardening, workbench pages

Phase 9 — four parallel workstreams:

- Stream A: 14 Docker entrypoints for containerized deployment
- Stream B: Pipeline hardening — robust JSON parsing, LLM retry logic,
  consumer negative-ack, FalkorDB test import fix
- Stream C: Azure OpenAI, OpenAI-compatible, and Mistral LLM providers
- Stream D: Workbench Prompts, Token Cost, Knowledge Cores pages +
  Settings feature switches

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

ts/packages/flow/src/model/text-completion/mistral.ts

@@ -0,0 +1,144 @@
+/**
+ * Mistral text completion service.
+ *
+ * Env:
+ *   MISTRAL_TOKEN (required – Mistral API key)
+ *   MISTRAL_MODEL (default: ministral-8b-latest)
+ */
+
+import { Mistral } from "@mistralai/mistralai";
+import {
+  LlmService,
+  type ProcessorConfig,
+  type LlmResult,
+  type LlmChunk,
+  TooManyRequestsError,
+} from "@trustgraph/base";
+
+export class MistralProcessor extends LlmService {
+  private client: Mistral;
+  private readonly defaultModel: string;
+  private readonly defaultTemperature: number;
+  private readonly maxOutput: number;
+
+  constructor(
+    config: ProcessorConfig & {
+      model?: string;
+      apiKey?: string;
+      temperature?: number;
+      maxOutput?: number;
+    },
+  ) {
+    super(config);
+
+    this.defaultModel =
+      config.model ?? process.env.MISTRAL_MODEL ?? "ministral-8b-latest";
+    this.defaultTemperature = config.temperature ?? 0.0;
+    this.maxOutput = config.maxOutput ?? 4096;
+
+    const apiKey = config.apiKey ?? process.env.MISTRAL_TOKEN;
+    if (!apiKey) throw new Error("Mistral API key not specified");
+
+    this.client = new Mistral({ apiKey });
+
+    console.log("[Mistral] LLM service initialized");
+  }
+
+  async generateContent(
+    system: string,
+    prompt: string,
+    model?: string,
+    temperature?: number,
+  ): Promise<LlmResult> {
+    const modelName = model ?? this.defaultModel;
+    const temp = temperature ?? this.defaultTemperature;
+
+    try {
+      const resp = await this.client.chat.complete({
+        model: modelName,
+        messages: [
+          { role: "system", content: system },
+          { role: "user", content: prompt },
+        ],
+        temperature: temp,
+        maxTokens: this.maxOutput,
+      });
+
+      return {
+        text: (resp.choices?.[0]?.message?.content as string) ?? "",
+        inToken: resp.usage?.promptTokens ?? 0,
+        outToken: resp.usage?.completionTokens ?? 0,
+        model: modelName,
+      };
+    } catch (err) {
+      if ((err as any)?.statusCode === 429 || (err as any)?.status === 429) {
+        throw new TooManyRequestsError();
+      }
+      throw err;
+    }
+  }
+
+  override supportsStreaming(): boolean {
+    return true;
+  }
+
+  async *generateContentStream(
+    system: string,
+    prompt: string,
+    model?: string,
+    temperature?: number,
+  ): AsyncGenerator<LlmChunk> {
+    const modelName = model ?? this.defaultModel;
+    const temp = temperature ?? this.defaultTemperature;
+
+    try {
+      const stream = await this.client.chat.stream({
+        model: modelName,
+        messages: [
+          { role: "system", content: system },
+          { role: "user", content: prompt },
+        ],
+        temperature: temp,
+        maxTokens: this.maxOutput,
+      });
+
+      let totalInputTokens = 0;
+      let totalOutputTokens = 0;
+
+      for await (const chunk of stream) {
+        const delta = chunk.data?.choices?.[0]?.delta;
+        if (delta?.content) {
+          yield {
+            text: delta.content as string,
+            inToken: null,
+            outToken: null,
+            model: modelName,
+            isFinal: false,
+          };
+        }
+
+        if (chunk.data?.usage) {
+          totalInputTokens = chunk.data.usage.promptTokens ?? 0;
+          totalOutputTokens = chunk.data.usage.completionTokens ?? 0;
+        }
+      }
+
+      yield {
+        text: "",
+        inToken: totalInputTokens,
+        outToken: totalOutputTokens,
+        model: modelName,
+        isFinal: true,
+      };
+    } catch (err) {
+      if ((err as any)?.statusCode === 429 || (err as any)?.status === 429) {
+        throw new TooManyRequestsError();
+      }
+      throw err;
+    }
+  }
+}
+
+export async function run(): Promise<void> {
+  await MistralProcessor.launch("text-completion");
+}