fix(llm): handle reasoning models, bump token limits to 20k

deepseek-v4-pro is a reasoning model that burns tokens on
reasoning_content before producing content. When max_tokens was too low
(400/1500), all tokens went to reasoning and content was empty.

- parse_response now falls back to reasoning_content when content is blank
- max_tokens raised to 20_000 across all call sites and default
- improved parse logging shows raw/cleaned byte sizes

lib/towerops/llm/deepseek.ex

@@ -46,7 +46,7 @@ defmodule Towerops.LLM.DeepSeek do
       model: model,
       messages: messages,
       temperature: opts[:temperature] || 0.2,
-      max_tokens: opts[:max_tokens] || 400
+      max_tokens: opts[:max_tokens] || 20_000
     }
 
     req_opts =
@@ -83,9 +83,19 @@ defmodule Towerops.LLM.DeepSeek do
     end
   end
 
-  defp parse_response(%{"choices" => [%{"message" => %{"content" => content}} | _]} = body) do
+  defp parse_response(%{"choices" => [%{"message" => message} | _]} = body) do
     usage = body["usage"] || %{}
 
+    content =
+      case message do
+        %{"content" => c} when is_binary(c) and c != "" -> c
+        # Reasoning models (deepseek-v4-pro) may exhaust max_tokens during
+        # reasoning and leave content empty; fall back to reasoning_content.
+        %{"reasoning_content" => rc} when is_binary(rc) -> rc
+        %{"content" => c} when is_binary(c) -> c
+        _ -> ""
+      end
+
     {:ok,
      %{
        content: content,

lib/towerops/llm/network_insight_prompt.ex

@@ -85,7 +85,7 @@ defmodule Towerops.LLM.NetworkInsightPrompt do
 
         _ ->
           Logger.warning(
-            "AI network insight: could not decode LLM response, content preview: #{String.slice(cleaned, 0, 200)}"
+            "AI network insight: could not decode LLM response, raw_bytes=#{byte_size(content)} cleaned_bytes=#{byte_size(cleaned)}, raw preview: #{String.slice(String.trim(content), 0, 300)}"
           )
 
           []

lib/towerops/workers/ai_network_insight_worker.ex

@@ -46,7 +46,7 @@ defmodule Towerops.Workers.AiNetworkInsightWorker do
     snapshot = NetworkSnapshot.build(organization_id)
     messages = NetworkInsightPrompt.build(snapshot)
 
-    case LLM.complete(messages, max_tokens: 1500, temperature: 0.3) do
+    case LLM.complete(messages, max_tokens: 20_000, temperature: 0.3) do
       {:ok, %{content: content, model: model} = response} ->
         {:ok, observations} = NetworkInsightPrompt.parse(content)
 

lib/towerops/workers/insight_llm_enrichment_worker.ex

@@ -31,7 +31,7 @@ defmodule Towerops.Workers.InsightLlmEnrichmentWorker do
   defp enrich_one(insight) do
     messages = InsightPrompt.build(insight)
 
-    case LLM.complete(messages, max_tokens: 400, temperature: 0.2) do
+    case LLM.complete(messages, max_tokens: 20_000, temperature: 0.2) do
       {:ok, %{content: content, model: model} = response} ->
         {:ok, parsed} = InsightPrompt.parse(content)