claw/diarization-ui
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

fix(diarization-ui): capture thinking tokens in debug stream (Qwen3)

Browse Source 
Ollama streaming chunks for thinking models use a separate "thinking"
field. Previously only "response" was captured, leaving the debug
window empty while the model reasoned. Now both fields are tracked
independently: thinking is shown in blue above the final answer,
both are persisted to new llm_thinking / existing llm_response columns.

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
Wolf G. Beckmann
2026-05-06 15:50:40 +02:00
parent 405c3e798d
commit 4f651fac12
1 changed files with 25 additions and 9 deletions
Download Patch File Download Diff File Expand all files Collapse all files

34
app.py
View File

@@ -110,6 +110,10 @@ def init_db():
c.execute("ALTER TABLE jobs ADD COLUMN llm_response TEXT") c.execute("ALTER TABLE jobs ADD COLUMN llm_response TEXT")
except Exception: except Exception:
pass pass
try:
c.execute("ALTER TABLE jobs ADD COLUMN llm_thinking TEXT")
except Exception:
pass
# defaults # defaults
c.execute("INSERT OR IGNORE INTO projects(name, created_at) VALUES (?,?)", ("Default", now_iso())) c.execute("INSERT OR IGNORE INTO projects(name, created_at) VALUES (?,?)", ("Default", now_iso()))
@@ -369,7 +373,7 @@ def _process_analysis_job(job_id: int):
_job_set(job_id, llm_prompt=llm_prompt) _job_set(job_id, llm_prompt=llm_prompt)
with _JOB_STREAM_LOCK: with _JOB_STREAM_LOCK:
_JOB_STREAMS[job_id] = "" _JOB_STREAMS[job_id] = {"thinking": "", "response": ""}
r = requests.post( r = requests.post(
f"{OLLAMA_BASE_URL}/api/generate", f"{OLLAMA_BASE_URL}/api/generate",
@@ -379,16 +383,18 @@ def _process_analysis_job(job_id: int):
) )
r.raise_for_status() r.raise_for_status()
accumulated = "" acc_thinking = ""
acc_response = ""
ollama_final = {} ollama_final = {}
chunk_count = 0 chunk_count = 0
for line in r.iter_lines(): for line in r.iter_lines():
if not line: if not line:
continue continue
chunk = json.loads(line) chunk = json.loads(line)
accumulated += chunk.get("response", "") acc_thinking += chunk.get("thinking") or ""
acc_response += chunk.get("response") or ""
with _JOB_STREAM_LOCK: with _JOB_STREAM_LOCK:
_JOB_STREAMS[job_id] = accumulated _JOB_STREAMS[job_id] = {"thinking": acc_thinking, "response": acc_response}
chunk_count += 1 chunk_count += 1
if chunk_count % 100 == 0: if chunk_count % 100 == 0:
j_check = _job_get(job_id) j_check = _job_get(job_id)
@@ -398,7 +404,7 @@ def _process_analysis_job(job_id: int):
ollama_final = chunk ollama_final = chunk
break break
answer = accumulated answer = acc_response
j = _job_get(job_id) j = _job_get(job_id)
if not j or j["status"] == "cancelled": if not j or j["status"] == "cancelled":
@@ -423,7 +429,7 @@ def _process_analysis_job(job_id: int):
) )
new_doc_id = cur.lastrowid new_doc_id = cur.lastrowid
_job_set(job_id, status="done", result_document_id=new_doc_id, finished_at=now_iso(), llm_response=answer) _job_set(job_id, status="done", result_document_id=new_doc_id, finished_at=now_iso(), llm_response=answer, llm_thinking=acc_thinking or None)
except Exception as e: except Exception as e:
_job_set(job_id, status="error", error=str(e), finished_at=now_iso()) _job_set(job_id, status="error", error=str(e), finished_at=now_iso())
finally: finally:
@@ -1302,12 +1308,13 @@ def job_debug_data(job_id: int):
if not j: if not j:
raise HTTPException(404, "job not found") raise HTTPException(404, "job not found")
with _JOB_STREAM_LOCK: with _JOB_STREAM_LOCK:
live = _JOB_STREAMS.get(job_id) live = dict(_JOB_STREAMS[job_id]) if job_id in _JOB_STREAMS else None
return { return {
"status": j["status"], "status": j["status"],
"kind": j["kind"], "kind": j["kind"],
"llm_prompt": j.get("llm_prompt"), "llm_prompt": j.get("llm_prompt"),
"llm_response": live if live is not None else j.get("llm_response"), "llm_thinking": live["thinking"] if live is not None else j.get("llm_thinking"),
"llm_response": live["response"] if live is not None else j.get("llm_response"),
"streaming": live is not None, "streaming": live is not None,
} }
@@ -1530,7 +1537,16 @@ async function refreshDebug() {{
document.getElementById('debug-prompt-content').textContent = d.llm_prompt || '(kein Prompt gespeichert)'; document.getElementById('debug-prompt-content').textContent = d.llm_prompt || '(kein Prompt gespeichert)';
const respEl = document.getElementById('debug-response-content'); const respEl = document.getElementById('debug-response-content');
const atBottom = respEl.scrollHeight - respEl.scrollTop <= respEl.clientHeight + 20; const atBottom = respEl.scrollHeight - respEl.scrollTop <= respEl.clientHeight + 20;
respEl.textContent = d.llm_response || '(noch keine Antwort)'; const thinking = d.llm_thinking || '';
const response = d.llm_response || '';
if (thinking) {{
respEl.innerHTML =
`<span style='color:#94a3b8;font-size:.75rem;letter-spacing:.06em'>▶ THINKING</span>\n` +
`<span style='color:#7dd3fc'>${{thinking.replace(/</g,'&lt;')}}</span>` +
(response ? `\n\n<span style='color:#94a3b8;font-size:.75rem;letter-spacing:.06em'>▶ ANTWORT</span>\n<span style='color:#c7f9cc'>${{response.replace(/</g,'&lt;')}}</span>` : '');
}} else {{
respEl.textContent = response || '(noch keine Antwort)';
}}
if (atBottom) respEl.scrollTop = respEl.scrollHeight; if (atBottom) respEl.scrollTop = respEl.scrollHeight;
const badge = document.getElementById('debug-streaming-badge'); const badge = document.getElementById('debug-streaming-badge');
badge.classList.toggle('d-none', !d.streaming); badge.classList.toggle('d-none', !d.streaming);