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Merge PR #724: feat: --yolo flag to bypass all approval prompts Authored by dmahan93. Adds HERMES_YOLO_MODE env var and --yolo CLI flag to auto-approve all dangerous command prompts. Post-merge: renamed --fuck-it-ship-it to --yolo for brevity, resolved conflict with --checkpoints flag.
2026-03-10 20:56:30 -07:00
# Streaming LLM Response Support for Hermes Agent
## Overview
Add token-by-token streaming of LLM responses across all platforms. When enabled,
users see the response typing out live instead of waiting for the full generation.
Streaming is opt-in via config, defaults to off, and all existing non-streaming
code paths remain intact as the default.
## Design Principles
1. **Feature-flagged**: `streaming.enabled: true` in config.yaml. Off by default.
When off, all existing code paths are unchanged — zero risk to current behavior.
2. **Callback-based**: A simple `stream_callback(text_delta: str)` function injected
into AIAgent. The agent doesn't know or care what the consumer does with tokens.
3. **Graceful degradation**: If the provider doesn't support streaming, or streaming
fails for any reason, silently fall back to the non-streaming path.
4. **Platform-agnostic core**: The streaming mechanism in AIAgent works the same
regardless of whether the consumer is CLI, Telegram, Discord, or the API server.
---
## Architecture
```
stream_callback(delta)
│
┌─────────────┐ ┌─────────────▼──────────────┐
│ LLM API │ │ queue.Queue() │
│ (stream) │───►│ thread-safe bridge between │
│ │ │ agent thread & consumer │
└─────────────┘ └─────────────┬──────────────┘
│
┌──────────────┼──────────────┐
│ │ │
┌─────▼─────┐ ┌─────▼─────┐ ┌─────▼─────┐
│ CLI │ │ Gateway │ │ API Server│
│ print to │ │ edit msg │ │ SSE event │
│ terminal │ │ on Tg/Dc │ │ to client │
└───────────┘ └───────────┘ └───────────┘
```
The agent runs in a thread. The callback puts tokens into a thread-safe queue.
Each consumer reads the queue in its own context (async task, main thread, etc.).
---
## Configuration
### config.yaml
```yaml
streaming:
enabled: false # Master switch. Default off.
# Per-platform overrides (optional):
# cli: true # Override for CLI only
# telegram: true # Override for Telegram only
# discord: false # Keep Discord non-streaming
# api_server: true # Override for API server
```
### Environment variables
```
HERMES_STREAMING_ENABLED=true # Master switch via env
```
### How the flag is read
- **CLI**: `load_cli_config()` reads `streaming.enabled`, sets env var. AIAgent
checks at init time.
- **Gateway**: `_run_agent()` reads config, decides whether to pass
`stream_callback` to the AIAgent constructor.
- **API server**: For Chat Completions `stream=true` requests, always uses streaming
regardless of config (the client is explicitly requesting it). For non-stream
requests, uses config.
### Precedence
1. API server: client's `stream` field overrides everything
2. Per-platform config override (e.g., `streaming.telegram: true`)
3. Master `streaming.enabled` flag
4. Default: off
---
## Implementation Plan
### Phase 1: Core streaming infrastructure in AIAgent
**File: run_agent.py**
#### 1a. Add stream_callback parameter to __init__ (~5 lines)
```python
def __init__(self, ..., stream_callback: callable = None, ...):
self.stream_callback = stream_callback
```
No other init changes. The callback is optional — when None, everything
works exactly as before.
#### 1b. Add _run_streaming_chat_completion() method (~65 lines)
New method for Chat Completions API streaming:
```python
def _run_streaming_chat_completion(self, api_kwargs: dict):
"""Stream a chat completion, emitting text tokens via stream_callback.
Returns a fake response object compatible with the non-streaming code path.
Falls back to non-streaming on any error.
"""
stream_kwargs = dict(api_kwargs)
stream_kwargs["stream"] = True
stream_kwargs["stream_options"] = {"include_usage": True}
accumulated_content = []
accumulated_tool_calls = {} # index -> {id, name, arguments}
final_usage = None
try:
stream = self.client.chat.completions.create(**stream_kwargs)
for chunk in stream:
if not chunk.choices:
# Usage-only chunk (final)
if chunk.usage:
final_usage = chunk.usage
continue
delta = chunk.choices[0].delta
# Text content — emit via callback
if delta.content:
accumulated_content.append(delta.content)
if self.stream_callback:
try:
self.stream_callback(delta.content)
except Exception:
pass
# Tool call deltas — accumulate silently
if delta.tool_calls:
for tc_delta in delta.tool_calls:
idx = tc_delta.index
if idx not in accumulated_tool_calls:
accumulated_tool_calls[idx] = {
"id": tc_delta.id or "",
"name": "", "arguments": ""
}
if tc_delta.function:
if tc_delta.function.name:
accumulated_tool_calls[idx]["name"] = tc_delta.function.name
if tc_delta.function.arguments:
accumulated_tool_calls[idx]["arguments"] += tc_delta.function.arguments
# Build fake response compatible with existing code
tool_calls = []
for idx in sorted(accumulated_tool_calls):
tc = accumulated_tool_calls[idx]
if tc["name"]:
tool_calls.append(SimpleNamespace(
id=tc["id"], type="function",
function=SimpleNamespace(name=tc["name"], arguments=tc["arguments"]),
))
return SimpleNamespace(
choices=[SimpleNamespace(
message=SimpleNamespace(
content="".join(accumulated_content) or "",
tool_calls=tool_calls or None,
role="assistant",
),
finish_reason="tool_calls" if tool_calls else "stop",
)],
usage=final_usage,
model=self.model,
)
except Exception as e:
logger.debug("Streaming failed, falling back to non-streaming: %s", e)
return self.client.chat.completions.create(**api_kwargs)
```
#### 1c. Modify _run_codex_stream() for Responses API (~10 lines)
The method already iterates the stream. Add callback emission:
```python
def _run_codex_stream(self, api_kwargs: dict):
with self.client.responses.stream(**api_kwargs) as stream:
for event in stream:
# Emit text deltas if streaming callback is set
if self.stream_callback and hasattr(event, 'type'):
if event.type == 'response.output_text.delta':
try:
self.stream_callback(event.delta)
except Exception:
pass
return stream.get_final_response()
```
#### 1d. Modify _interruptible_api_call() (~5 lines)
Add the streaming branch:
```python
def _call():
try:
if self.api_mode == "codex_responses":
result["response"] = self._run_codex_stream(api_kwargs)
elif self.stream_callback is not None:
result["response"] = self._run_streaming_chat_completion(api_kwargs)
else:
result["response"] = self.client.chat.completions.create(**api_kwargs)
except Exception as e:
result["error"] = e
```
#### 1e. Signal end-of-stream to consumers (~5 lines)
After the API call returns, signal the callback that streaming is done
so consumers can finalize (remove cursor, close SSE, etc.):
```python
# In run_conversation(), after _interruptible_api_call returns:
if self.stream_callback:
try:
self.stream_callback(None) # None = end of stream signal
except Exception:
pass
```
Consumers check: `if delta is None: finalize()`
**Tests for Phase 1:** (~150 lines)
- Test _run_streaming_chat_completion with mocked stream
- Test fallback to non-streaming on error
- Test tool_call accumulation during streaming
- Test stream_callback receives correct deltas
- Test None signal at end of stream
- Test streaming disabled when callback is None
---
### Phase 2: Gateway consumers (Telegram, Discord, etc.)
**File: gateway/run.py**
#### 2a. Read streaming config (~15 lines)
In `_run_agent()`, before creating the AIAgent:
```python
# Read streaming config
_streaming_enabled = False
try:
# Check per-platform override first
platform_key = source.platform.value if source.platform else ""
_stream_cfg = {} # loaded from config.yaml streaming section
if _stream_cfg.get(platform_key) is not None:
_streaming_enabled = bool(_stream_cfg[platform_key])
else:
_streaming_enabled = bool(_stream_cfg.get("enabled", False))
except Exception:
pass
# Env var override
if os.getenv("HERMES_STREAMING_ENABLED", "").lower() in ("true", "1", "yes"):
_streaming_enabled = True
```
#### 2b. Set up queue + callback (~15 lines)
```python
_stream_q = None
_stream_done = None
_stream_msg_id = [None] # mutable ref for the async task
if _streaming_enabled:
import queue as _q
_stream_q = _q.Queue()
_stream_done = threading.Event()
def _on_token(delta):
if delta is None:
_stream_done.set()
else:
_stream_q.put(delta)
```
Pass `stream_callback=_on_token` to the AIAgent constructor.
#### 2c. Telegram/Discord stream preview task (~50 lines)
```python
async def stream_preview():
"""Progressively edit a message with streaming tokens."""
if not _stream_q:
return
adapter = self.adapters.get(source.platform)
if not adapter:
return
accumulated = []
token_count = 0
last_edit = 0.0
MIN_TOKENS = 20 # Don't show until enough context
EDIT_INTERVAL = 1.5 # Respect Telegram rate limits
try:
while not _stream_done.is_set():
try:
chunk = _stream_q.get(timeout=0.1)
accumulated.append(chunk)
token_count += 1
except queue.Empty:
continue
now = time.monotonic()
if token_count >= MIN_TOKENS and (now - last_edit) >= EDIT_INTERVAL:
preview = "".join(accumulated) + " ▌"
if _stream_msg_id[0] is None:
r = await adapter.send(
chat_id=source.chat_id,
content=preview,
metadata=_thread_metadata,
)
if r.success and r.message_id:
_stream_msg_id[0] = r.message_id
else:
await adapter.edit_message(
chat_id=source.chat_id,
message_id=_stream_msg_id[0],
content=preview,
)
last_edit = now
# Drain remaining tokens
while not _stream_q.empty():
accumulated.append(_stream_q.get_nowait())
# Final edit — remove cursor, show complete text
if _stream_msg_id[0] and accumulated:
await adapter.edit_message(
chat_id=source.chat_id,
message_id=_stream_msg_id[0],
content="".join(accumulated),
)
except asyncio.CancelledError:
# Clean up on cancel
if _stream_msg_id[0] and accumulated:
try:
await adapter.edit_message(
chat_id=source.chat_id,
message_id=_stream_msg_id[0],
content="".join(accumulated),
)
except Exception:
pass
except Exception as e:
logger.debug("stream_preview error: %s", e)
```
#### 2d. Skip final send if already streamed (~10 lines)
In `_process_message_background()` (base.py), after getting the response,
if streaming was active and `_stream_msg_id[0]` is set, the final response
was already delivered via progressive edits. Skip the normal `self.send()`
call to avoid duplicating the message.
This is the most delicate integration point — we need to communicate from
the gateway's `_run_agent` back to the base adapter's response sender that
the response was already delivered. Options:
- **Option A**: Return a special marker in the result dict:
`result["_streamed_msg_id"] = _stream_msg_id[0]`
The base adapter checks this and skips `send()`.
- **Option B**: Edit the already-sent message with the final response
(which may differ slightly from accumulated tokens due to think-block
stripping, etc.) and don't send a new one.
- **Option C**: The stream preview task handles the FULL final response
(including any post-processing), and the handler returns None to skip
the normal send path.
Recommended: **Option A** — cleanest separation. The result dict already
carries metadata; adding one more field is low-risk.
**Platform-specific considerations:**
| Platform | Edit support | Rate limits | Streaming approach |
|----------|-------------|-------------|-------------------|
| Telegram | ✅ edit_message_text | ~20 edits/min | Edit every 1.5s |
| Discord | ✅ message.edit | 5 edits/5s per message | Edit every 1.2s |
| Slack | ✅ chat.update | Tier 3 (~50/min) | Edit every 1.5s |
| WhatsApp | ❌ no edit support | N/A | Skip streaming, use normal path |
| HomeAssistant | ❌ no edit | N/A | Skip streaming |
| API Server | ✅ SSE native | No limit | Real SSE events |
WhatsApp and HomeAssistant fall back to non-streaming automatically because
they don't support message editing.
**Tests for Phase 2:** (~100 lines)
- Test stream_preview sends/edits correctly
- Test skip-final-send when streaming delivered
- Test WhatsApp/HA graceful fallback
- Test streaming disabled per-platform config
- Test thread_id metadata forwarded in stream messages
---
### Phase 3: CLI streaming
**File: cli.py**
#### 3a. Set up callback in the CLI chat loop (~20 lines)
In `_chat_once()` or wherever the agent is invoked:
```python
if streaming_enabled:
_stream_q = queue.Queue()
_stream_done = threading.Event()
def _cli_stream_callback(delta):
if delta is None:
_stream_done.set()
else:
_stream_q.put(delta)
agent.stream_callback = _cli_stream_callback
```
#### 3b. Token display thread/task (~30 lines)
Start a thread that reads the queue and prints tokens:
```python
def _stream_display():
"""Print tokens to terminal as they arrive."""
first_token = True
while not _stream_done.is_set():
try:
delta = _stream_q.get(timeout=0.1)
except queue.Empty:
continue
if first_token:
# Print response box top border
_cprint(f"\n{top}")
first_token = False
sys.stdout.write(delta)
sys.stdout.flush()
# Drain remaining
while not _stream_q.empty():
sys.stdout.write(_stream_q.get_nowait())
sys.stdout.flush()
# Print bottom border
_cprint(f"\n\n{bot}")
```
**Integration challenge: prompt_toolkit**
The CLI uses prompt_toolkit which controls the terminal. Writing directly
to stdout while prompt_toolkit is active can cause display corruption.
The existing KawaiiSpinner already solves this by using prompt_toolkit's
`patch_stdout` context. The streaming display would need to do the same.
Alternative: use `_cprint()` for each token chunk (routes through
prompt_toolkit's renderer). But this might be slow for individual tokens.
Recommended approach: accumulate tokens in small batches (e.g., every 50ms)
and `_cprint()` the batch. This balances display responsiveness with
prompt_toolkit compatibility.
**Tests for Phase 3:** (~50 lines)
- Test CLI streaming callback setup
- Test response box borders with streaming
- Test fallback when streaming disabled
---
### Phase 4: API Server real streaming
**File: gateway/platforms/api_server.py**
Replace the pseudo-streaming `_write_sse_chat_completion()` with real
token-by-token SSE when the agent supports it.
#### 4a. Wire streaming callback for stream=true requests (~20 lines)
```python
if stream:
_stream_q = queue.Queue()
def _api_stream_callback(delta):
_stream_q.put(delta) # None = done
# Pass callback to _run_agent
result, usage = await self._run_agent(
..., stream_callback=_api_stream_callback,
)
```
#### 4b. Real SSE writer (~40 lines)
```python
async def _write_real_sse(self, request, completion_id, model, stream_q):
response = web.StreamResponse(
headers={"Content-Type": "text/event-stream", "Cache-Control": "no-cache"},
)
await response.prepare(request)
# Role chunk
await response.write(...)
# Stream content chunks as they arrive
while True:
try:
delta = await asyncio.get_event_loop().run_in_executor(
None, lambda: stream_q.get(timeout=0.1)
)
except queue.Empty:
continue
if delta is None: # End of stream
break
chunk = {"id": completion_id, "object": "chat.completion.chunk", ...
"choices": [{"delta": {"content": delta}, ...}]}
await response.write(f"data: {json.dumps(chunk)}\n\n".encode())
# Finish + [DONE]
await response.write(...)
await response.write(b"data: [DONE]\n\n")
return response
```
**Challenge: concurrent execution**
The agent runs in a thread executor. SSE writing happens in the async event
loop. The queue bridges them. But `_run_agent()` currently awaits the full
result before returning. For real streaming, we need to start the agent in
the background and stream tokens while it runs:
```python
# Start agent in background
agent_task = asyncio.create_task(self._run_agent_async(...))
# Stream tokens while agent runs
await self._write_real_sse(request, ..., stream_q)
# Agent is done by now (stream_q received None)
result, usage = await agent_task
```
This requires splitting `_run_agent` into an async version that doesn't
block waiting for the result, or running it in a separate task.
**Responses API SSE format:**
For `/v1/responses` with `stream=true`, the SSE events are different:
```
event: response.output_text.delta
data: {"type":"response.output_text.delta","delta":"Hello"}
event: response.completed
data: {"type":"response.completed","response":{...}}
```
This needs a separate SSE writer that emits Responses API format events.
**Tests for Phase 4:** (~80 lines)
- Test real SSE streaming with mocked agent
- Test SSE event format (Chat Completions vs Responses)
- Test client disconnect during streaming
- Test fallback to pseudo-streaming when callback not available
---
## Integration Issues & Edge Cases
### 1. Tool calls during streaming
When the model returns tool calls instead of text, no text tokens are emitted.
The stream_callback is simply never called with text. After tools execute, the
next API call may produce the final text response — streaming picks up again.
The stream preview task needs to handle this: if no tokens arrive during a
tool-call round, don't send/edit any message. The tool progress messages
continue working as before.
### 2. Duplicate messages
The biggest risk: the agent sends the final response normally (via the
existing send path) AND the stream preview already showed it. The user
sees the response twice.
Prevention: when streaming is active and tokens were delivered, the final
response send must be suppressed. The `result["_streamed_msg_id"]` marker
tells the base adapter to skip its normal send.
### 3. Response post-processing
The final response may differ from the accumulated streamed tokens:
- Think block stripping (`<think>...</think>` removed)
- Trailing whitespace cleanup
- Tool result media tag appending
The stream preview shows raw tokens. The final edit should use the
post-processed version. This means the final edit (removing the cursor)
should use the post-processed `final_response`, not just the accumulated
stream text.
### 4. Context compression during streaming
If the agent triggers context compression mid-conversation, the streaming
tokens from BEFORE compression are from a different context than those
after. This isn't a problem in practice — compression happens between
API calls, not during streaming.
### 5. Interrupt during streaming
User sends a new message while streaming → interrupt. The stream is killed
(HTTP connection closed), accumulated tokens are shown as-is (no cursor),
and the interrupt message is processed normally. This is already handled by
`_interruptible_api_call` closing the client.
### 6. Multi-model / fallback
If the primary model fails and the agent falls back to a different model,
streaming state resets. The fallback call may or may not support streaming.
The graceful fallback in `_run_streaming_chat_completion` handles this.
### 7. Rate limiting on edits
Telegram: ~20 edits/minute (~1 every 3 seconds to be safe)
Discord: 5 edits per 5 seconds per message
Slack: ~50 API calls/minute
The 1.5s edit interval is conservative enough for all platforms. If we get
429 rate limit errors on edits, just skip that edit cycle and try next time.
---
## Files Changed Summary
| File | Phase | Changes |
|------|-------|---------|
| `run_agent.py` | 1 | +stream_callback param, +_run_streaming_chat_completion(), modify _run_codex_stream(), modify _interruptible_api_call() |
| `gateway/run.py` | 2 | +streaming config reader, +queue/callback setup, +stream_preview task, +skip-final-send logic |
| `gateway/platforms/base.py` | 2 | +check for _streamed_msg_id in response handler |
| `cli.py` | 3 | +streaming setup, +token display, +response box integration |
| `gateway/platforms/api_server.py` | 4 | +real SSE writer, +streaming callback wiring |
| `hermes_cli/config.py` | 1 | +streaming config defaults |
| `cli-config.yaml.example` | 1 | +streaming section |
| `tests/test_streaming.py` | 1-4 | NEW — ~380 lines of tests |
**Total new code**: ~500 lines across all phases
**Total test code**: ~380 lines
---
## Rollout Plan
1. **Phase 1** (core): Merge to main. Streaming disabled by default.
Zero impact on existing behavior. Can be tested with env var.
2. **Phase 2** (gateway): Merge to main. Test on Telegram manually.
Enable per-platform: `streaming.telegram: true` in config.
3. **Phase 3** (CLI): Merge to main. Test in terminal.
Enable: `streaming.cli: true` or `streaming.enabled: true`.
4. **Phase 4** (API server): Merge to main. Test with Open WebUI.
Auto-enabled when client sends `stream: true`.
Each phase is independently mergeable and testable. Streaming stays
off by default throughout. Once all phases are stable, consider
changing the default to enabled.
---
## Config Reference (final state)
```yaml
# config.yaml
streaming:
enabled: false # Master switch (default: off)
cli: true # Per-platform override
telegram: true
discord: true
slack: true
api_server: true # API server always streams when client requests it
edit_interval: 1.5 # Seconds between message edits (default: 1.5)
min_tokens: 20 # Tokens before first display (default: 20)
```
```bash
# Environment variable override
HERMES_STREAMING_ENABLED=true
```
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