subconscious: lift continuation gen + render helpers into shared homes

- context.rs gains is_assistant, render_branch_text, render_prior_context
  alongside memory_key / is_memory_node. They're pure AST helpers, used
  by both the finetune pipeline and the forthcoming compare screen.

- new subconscious/generate.rs holds gen_continuation(context, entry_idx,
  skip, client): build the prompt from a context prefix with an arbitrary
  skip predicate, send to the model, decode the completion. Takes both
  the predicate and the client so callers can aim it at memory-stripped
  contexts (finetune), same-context-different-model (F7 compare), or
  whatever else.

- learn.rs drops its private copies of those helpers and the inline
  generate_alternate; the finetune path now reads as
  gen_continuation(context, idx, is_memory_node, client).

Pure refactor, no behavior change.

Co-Authored-By: Proof of Concept <poc@bcachefs.org>

src/subconscious/generate.rs

@@ -0,0 +1,46 @@
+// generate.rs — Continuation generation for scoring / comparison flows.
+//
+// Shared by the finetune pipeline (learn.rs) and the compare screen:
+// given a context prefix and a skip predicate, generate what the model
+// would say as the next assistant turn.
+
+use crate::agent::api::{ApiClient, SamplingParams, StreamToken};
+use crate::agent::context::{AstNode, ContextState};
+use crate::agent::tokenizer;
+
+/// Generate an assistant continuation from the context up to `entry_idx`,
+/// with `skip` applied to identity + conversation entries during prompt
+/// assembly. The model is whichever `client` points at — the default
+/// runtime client for memory-ablation alternates, a test-model client
+/// for F7 comparison.
+pub async fn gen_continuation<F>(
+    context: &ContextState,
+    entry_idx: usize,
+    skip: F,
+    client: &ApiClient,
+) -> anyhow::Result<String>
+where F: FnMut(&AstNode) -> bool,
+{
+    let (mut prompt, images, _) = context.wire_prompt(0..entry_idx, skip);
+
+    prompt.push(tokenizer::IM_START);
+    prompt.extend(tokenizer::encode("assistant\n"));
+
+    let sampling = SamplingParams {
+        temperature: 0.6,
+        top_p: 0.95,
+        top_k: 20,
+    };
+    let (mut rx, _guard) = client.stream_completion_mm(&prompt, &images, sampling, Some(-5));
+
+    let mut tokens = Vec::new();
+    while let Some(tok) = rx.recv().await {
+        match tok {
+            StreamToken::Token(id) => tokens.push(id),
+            StreamToken::Done { .. } => break,
+            StreamToken::Error(e) => anyhow::bail!("generation error: {}", e),
+        }
+    }
+
+    Ok(tokenizer::decode(&tokens))
+}