gramps/jarvisChat
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fix: resolve all critical runtime errors and bugs from audit

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- Add COMPLETIONS_API_KEY to config.py (env var + auto-generated fallback)
- Fix perplexity auto-search: upstream sends logprobs=true, parse_llama_stream_chunk
  extracts per-token logprobs, all_logprobs populated during streaming
- Fix all /api/models endpoints to target LLAMA_SERVER_BASE (port 8081) not OLLAMA_BASE
- Fix RAG embedding endpoint URL from port 11434 (Ollama) to 8081 (llama-server)
- Correct misleading error messages: 'inference server' not 'Ollama'
- Remove raw_results leak from SSE event stream in /api/search
- Fix weather query extractor: pattern-match instead of unconditional suffix append
- Escape FTS5 operator keywords (AND/OR/NOT/NEAR) in memory search
- Move auth.py BODY_LIMIT_DEFAULT_BYTES imports to module level
- Change RAG injection log level from warning to info
- Fix all 8 test files after modular refactor (rewire imports from correct modules)
- Update AGENTS.md and README.md to reflect v1.8.0 changes
This commit is contained in:
gramps
2026-06-27 15:10:32 -07:00
parent 41a8708c0d
commit 193829b7ff
20 changed files with 457 additions and 896 deletions
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29
routers/chat.py
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@@ -26,7 +26,7 @@ def parse_llama_stream_chunk(line: str) -> tuple:
if line.startswith("data: "):
line = line[6:]
if line.strip() == "[DONE]":
return None, True, {}
return None, True, {}, []
try:
chunk = json.loads(line)
choices = chunk.get("choices", [])
@@ -35,10 +35,17 @@ def parse_llama_stream_chunk(line: str) -> tuple:
token = delta.get("content")
finish = choices[0].get("finish_reason")
stats = {}
logprobs_list = []
logprobs_info = choices[0].get("logprobs")
if logprobs_info:
content_logprobs = logprobs_info.get("content", [])
for entry in content_logprobs:
if "logprob" in entry:
logprobs_list.append({"logprob": entry["logprob"]})
if finish == "stop":
usage = chunk.get("usage", {})
stats["tokens_per_sec"] = usage.get("tokens_per_second", 0.0)
return token, finish == "stop", stats
return token, finish == "stop", stats, logprobs_list
if "message" in chunk and "content" in chunk["message"]:
token = chunk["message"]["content"]
done = chunk.get("done", False)
@@ -47,10 +54,10 @@ def parse_llama_stream_chunk(line: str) -> tuple:
eval_count = chunk.get("eval_count", 0)
eval_duration = chunk.get("eval_duration", 0)
stats["tokens_per_sec"] = (eval_count / (eval_duration / 1e9)) if eval_duration > 0 else 0
return token, done, stats
return token, done, stats, []
except json.JSONDecodeError:
pass
return None, False, {}
return None, False, {}, []
@router.post("/api/chat")
@@ -97,7 +104,7 @@ async def chat(request: Request):
for row in history_rows:
messages.append({"role": row["role"], "content": row["content"]})
ollama_payload = {"model": model, "messages": messages, "stream": True}
upstream_payload = {"model": model, "messages": messages, "stream": True, "logprobs": True}
async def stream_response():
full_response = []
@@ -111,12 +118,14 @@ async def chat(request: Request):
try:
async with client.stream(
"POST", f"{LLAMA_SERVER_BASE}/v1/chat/completions",
json=ollama_payload,
json=upstream_payload,
timeout=httpx.Timeout(300.0, connect=10.0),
) as resp:
async for line in resp.aiter_lines():
if line.strip():
token, done, stats = parse_llama_stream_chunk(line)
token, done, stats, chunk_logprobs = parse_llama_stream_chunk(line)
if chunk_logprobs:
all_logprobs.extend(chunk_logprobs)
if token:
full_response.append(token)
yield f"data: {json.dumps({'token': token, 'conversation_id': conv_id})}\n\n"
@@ -153,7 +162,7 @@ async def chat(request: Request):
) as resp2:
async for line in resp2.aiter_lines():
if line.strip():
token2, done2, _ = parse_llama_stream_chunk(line)
token2, done2, _, _ = parse_llama_stream_chunk(line)
if token2:
augmented_response.append(token2)
if done2:
@@ -194,9 +203,9 @@ async def chat(request: Request):
except httpx.RemoteProtocolError:
pass
except httpx.ConnectError:
yield f"data: {json.dumps({'error': 'Cannot connect to Ollama. Is it running?'})}\n\n"
yield f"data: {json.dumps({'error': 'Cannot connect to inference server. Is it running?'})}\n\n"
except Exception as e:
incident_key = log_incident("chat_stream", message="Ollama stream failure during chat response",
incident_key = log_incident("chat_stream", message="Inference stream failure during chat response",
request=request, exc=e)
yield f"data: {json.dumps({'error': 'Chat response generation failed before completion. Use the incident key for support lookup.', 'error_key': incident_key})}\n\n"