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Glitch University
2026-05-03 08:45:58 +02:00
parent 1deb1d2521
commit e8301fb2bf
118 changed files with 2324 additions and 196 deletions
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plugins/festinger/config.yaml
+1 -1
View File
@@ -10,7 +10,7 @@ upstream_anthropic: "https://api.anthropic.com"
# Where the real OpenAI-compatible API is running (for /v1/chat/completions).
# For LM Studio set this to its local address, e.g. "http://host.docker.internal:1234"
# Override via UPSTREAM_OPENAI env var if needed
upstream_openai: "http://host.docker.internal:1234"
upstream_openai: "http://host.docker.internal:11434"
# Port this proxy listens on inside the container (exposed as 11434 on the docker network)
proxy_port: 11434
plugins/festinger/festinger/main.py
+126 -70
View File
@@ -70,6 +70,12 @@ def load_yaml_config() -> dict:
return yaml.safe_load(f)
async def _feature_enabled(pool, key: str, default: bool = True) -> bool:
"""Read a feature flag from the DB config table. Truthy unless explicitly disabled."""
val = await get_config(pool, key, "true" if default else "false")
return val.strip().lower() not in ("false", "0", "off", "no", "disabled")
# ---------------------------------------------------------------------------
# Lifespan — startup / shutdown
# ---------------------------------------------------------------------------
@@ -876,24 +882,24 @@ async def _route_agent_chat(
return text, raw_o
text, raw = await _call(body)
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning(
"loop_detected (agent routed) agent_model=%s session=%s count=%d",
agent_model.model_name, sess[1], count,
)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["choices"] = [{
"index": 0,
"message": {"role": "assistant", "content": override},
"finish_reason": "stop",
}]
raw["loop_detected"] = True
else:
text, raw = await _call(body)
record_and_check(sess, text, min_len)
if await _feature_enabled(pool, "feature_loop_detection"):
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning(
"loop_detected (agent routed) agent_model=%s session=%s count=%d",
agent_model.model_name, sess[1], count,
)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["choices"] = [{
"index": 0,
"message": {"role": "assistant", "content": override},
"finish_reason": "stop",
}]
raw["loop_detected"] = True
else:
text, raw = await _call(body)
record_and_check(sess, text, min_len)
if original_stream:
return Response(content=_openai_sse_from_response(raw), media_type="text/event-stream")
@@ -944,6 +950,9 @@ async def process_prompt(
agent_name may be passed in directly (e.g. extracted from the URL path) to
avoid re-parsing the body/headers; falls back to _extract_agent_name if empty.
"""
if not await _feature_enabled(pool, "feature_recollection"):
return body
read_threshold = float(await get_config(pool, "saliency_read_threshold", "0.5"))
conf_floor = float(await get_config(pool, "recollection_confidence_floor", "0.6"))
recency_days = int(await get_config(pool, "recollection_recency_days", "90"))
@@ -1076,17 +1085,18 @@ async def _handle_ollama_chat(request: Request, agent_name: str = "") -> Respons
try:
body = await process_prompt(body, "/api/chat", pool, cfg, dict(request.headers), agent_name=agent_name)
text, raw = await call_ollama("/api/chat", body, upstream)
sess = session_key(model, body.get("messages", []))
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["message"] = {"role": "assistant", "content": override}
raw["loop_detected"] = True
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_ollama("/api/chat", body, upstream)
record_and_check(sess, text, min_len)
if await _feature_enabled(pool, "feature_loop_detection"):
sess = session_key(model, body.get("messages", []))
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["message"] = {"role": "assistant", "content": override}
raw["loop_detected"] = True
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_ollama("/api/chat", body, upstream)
record_and_check(sess, text, min_len)
raw["message"] = {"role": "assistant", "content": text}
return Response(content=json.dumps(raw), media_type="application/json")
except UpstreamError as exc:
@@ -1111,19 +1121,20 @@ async def _handle_ollama_generate(request: Request, agent_name: str = "") -> Res
log.info("chat route=/api/generate model=%s agent=%s", model, agent_name or "—")
try:
body = await process_prompt(body, "/api/generate", pool, cfg, dict(request.headers), agent_name=agent_name)
messages = [{"role": "user", "content": body.get("prompt", "")}]
sess = session_key(model, messages)
text, raw = await call_ollama("/api/generate", body, upstream)
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["response"] = override
raw["loop_detected"] = True
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_ollama("/api/generate", body, upstream)
record_and_check(sess, text, min_len)
if await _feature_enabled(pool, "feature_loop_detection"):
messages = [{"role": "user", "content": body.get("prompt", "")}]
sess = session_key(model, messages)
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["response"] = override
raw["loop_detected"] = True
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_ollama("/api/generate", body, upstream)
record_and_check(sess, text, min_len)
raw["response"] = text
return Response(content=json.dumps(raw), media_type="application/json")
except UpstreamError as exc:
@@ -1172,21 +1183,22 @@ async def _handle_anthropic_messages(request: Request, agent_name: str = "") ->
if "anthropic-version" not in {k.lower() for k in headers}:
headers["anthropic-version"] = "2023-06-01"
body = await process_prompt(body, "/v1/messages", pool, cfg, headers, agent_name=agent_name)
messages = body.get("messages", [])
sess = session_key(model, messages)
text, raw = await call_anthropic(body, upstream, headers)
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["content"] = [{"type": "text", "text": override}]
raw["loop_detected"] = True
if original_stream:
return Response(content=_anthropic_to_sse(raw), media_type="text/event-stream")
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_anthropic(body, upstream, headers)
record_and_check(sess, text, min_len)
if await _feature_enabled(pool, "feature_loop_detection"):
messages = body.get("messages", [])
sess = session_key(model, messages)
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
raw["content"] = [{"type": "text", "text": override}]
raw["loop_detected"] = True
if original_stream:
return Response(content=_anthropic_to_sse(raw), media_type="text/event-stream")
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_anthropic(body, upstream, headers)
record_and_check(sess, text, min_len)
if original_stream:
sse_bytes = _anthropic_to_sse(raw)
log.info(
@@ -1250,22 +1262,23 @@ async def _handle_openai_chat(request: Request, agent_name: str = "") -> Respons
# Standard path — forward to configured upstream unchanged
headers = _relay_headers(request, OPENAI_RELAY_HEADERS)
body = await process_prompt(body, "/v1/chat/completions", pool, cfg, hdrs, agent_name=agent_name)
messages = body.get("messages", [])
sess = session_key(model, messages)
text, raw = await call_openai(body, upstream, headers)
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
if raw.get("choices"):
raw["choices"][0]["message"]["content"] = override
raw["loop_detected"] = True
if original_stream:
return Response(content=_openai_sse_from_response(raw), media_type="text/event-stream")
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_openai(body, upstream, headers)
record_and_check(sess, text, min_len)
if await _feature_enabled(pool, "feature_loop_detection"):
messages = body.get("messages", [])
sess = session_key(model, messages)
count = record_and_check(sess, text, min_len)
if count >= 2:
log.warning("loop_detected model=%s session=%s count=%d", model, sess[1], count)
body, override = apply_mitigations(body, count, cfg)
if override is not None:
if raw.get("choices"):
raw["choices"][0]["message"]["content"] = override
raw["loop_detected"] = True
if original_stream:
return Response(content=_openai_sse_from_response(raw), media_type="text/event-stream")
return Response(content=json.dumps(raw), media_type="application/json")
text, raw = await call_openai(body, upstream, headers)
record_and_check(sess, text, min_len)
if original_stream:
return Response(content=_openai_sse_from_response(raw), media_type="text/event-stream")
return Response(content=json.dumps(raw), media_type="application/json")
@@ -3245,6 +3258,22 @@ ADMIN_HTML = """<!DOCTYPE html>
&nbsp;&mdash;&nbsp;<a href="/models-ui" style="color:#1a1a2e">Model Manager</a>
</p>
<h2>Pipeline features</h2>
<p style="font-size:0.83em;color:#666;margin-bottom:0.8em">
Toggle enrichment steps on/off without restarting. Changes take effect immediately.
</p>
<div style="display:flex;flex-direction:column;gap:0.7em;margin-bottom:1em" id="features-section">
<label style="display:flex;align-items:center;gap:0.6em;cursor:pointer;font-size:0.9em">
<input type="checkbox" id="feat-recollection" onchange="setFeature('feature_recollection', this.checked)" style="width:16px;height:16px;cursor:pointer">
<span><b>Recollection</b> — inject knowledge-graph context into prompts</span>
</label>
<label style="display:flex;align-items:center;gap:0.6em;cursor:pointer;font-size:0.9em">
<input type="checkbox" id="feat-loop-detection" onchange="setFeature('feature_loop_detection', this.checked)" style="width:16px;height:16px;cursor:pointer">
<span><b>Loop detection</b> — retry with mitigations on repeated identical responses</span>
</label>
</div>
<div id="features-status" style="font-size:0.8em;color:#666;margin-bottom:1.5em"></div>
<h2>World model stats</h2>
<div class="stats" id="stats">
<div class="stat"><div class="stat-label">SOAS tokens</div><div class="stat-value" id="s-soas">…</div></div>
@@ -3406,6 +3435,32 @@ ADMIN_HTML = """<!DOCTYPE html>
: 'never';
}}
async function loadFeatures() {{
const r = await fetch('/config');
const cfg = (await r.json()).config;
const isEnabled = key => (cfg[key] || 'true').trim().toLowerCase() !== 'false'
&& (cfg[key] || 'true').trim().toLowerCase() !== '0'
&& (cfg[key] || 'true').trim().toLowerCase() !== 'off'
&& (cfg[key] || 'true').trim().toLowerCase() !== 'no';
document.getElementById('feat-recollection').checked = isEnabled('feature_recollection');
document.getElementById('feat-loop-detection').checked = isEnabled('feature_loop_detection');
}}
async function setFeature(key, enabled) {{
const val = enabled ? 'true' : 'false';
const r = await fetch('/config', {{method:'POST', headers:{{'Content-Type':'application/json'}}, body:JSON.stringify({{key, value:val}})}});
const d = await r.json();
const status = document.getElementById('features-status');
if (d.status === 'ok') {{
status.textContent = `${{key}} set to ${{val}}`;
status.style.color = '#2a7a2a';
}} else {{
status.textContent = `Error: ${{JSON.stringify(d)}}`;
status.style.color = '#b00';
}}
setTimeout(() => {{ status.textContent = ''; }}, 3000);
}}
let _cfg = {{}};
async function loadModels() {{
@@ -3790,6 +3845,7 @@ ADMIN_HTML = """<!DOCTYPE html>
}}
loadStats();
loadFeatures();
loadConflicts();
loadLog(0);
loadModels();