Add Langfuse-based LLM observability (#86)

* Add Langfuse-based LLM observability

* Document Langfuse configuration

* Don't hardcode model in use

docs/hosting/langfuse.md

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+# Langfuse
+
+This app can send traces of all LLM interactions to [Langfuse](https://langfuse.com) for debugging and usage analytics.  Find them here [on
+GitHub](https://github.com/langfuse/langfuse) and look at their [Open
+Source statement](https://langfuse.com/open-source).
+
+## Prerequisites
+
+1. Create a Langfuse project (self‑hosted or using their cloud offering).
+2. Copy the **public key** and **secret key** from the project's settings.
+
+## Configuration
+
+Set the following environment variables for the Rails app:
+
+```bash
+LANGFUSE_PUBLIC_KEY=your_public_key
+LANGFUSE_SECRET_KEY=your_secret_key
+# Optional if self‑hosting or using a non‑default domain
+LANGFUSE_HOST=https://your-langfuse-domain.com
+```
+
+In Docker setups, add the variables to `compose.yml` and the accompanying `.env` file.
+
+The initializer reads these values on boot and automatically enables tracing. If the keys are absent, the app runs normally without Langfuse.
+
+## What Gets Tracked
+
+* `chat_response`
+* `auto_categorize`
+* `auto_detect_merchants`
+
+Each call records the prompt, model, response, and token usage when available.
+
+## Viewing Traces
+
+After starting the app with the variables set, visit your Langfuse dashboard to see traces and generations grouped under the `openai.*` traces.