Datasets:
File size: 4,327 Bytes
371b96b | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 | diff --git a/ambient/agent.py b/ambient/agent.py
index 0113473..743774d 100644
--- a/ambient/agent.py
+++ b/ambient/agent.py
@@ -354,8 +354,13 @@ async def run_agent(
print(f"Turn {turn}")
turn_trajectory: dict = {"turn": turn, "messages": list(messages)}
+ # Agent (orchestrator) endpoint may differ from the vision endpoint:
+ # vision tools use llm_base_url (e.g. local vLLM); the agent uses agent_base_url
+ # (e.g. OpenRouter/deepseek) when set, falling back to the llm_* pair.
+ _agent_base = settings.agent_base_url or settings.llm_base_url
+ _agent_key = settings.agent_api_key or settings.llm_api_key
resp = await _send_request(
- settings.llm_base_url, settings.llm_api_key, model, messages
+ _agent_base, _agent_key, model, messages
)
if "content" not in resp:
print(f"No content in response: {resp}")
diff --git a/ambient/llm.py b/ambient/llm.py
index 68e356a..ebd2d5c 100644
--- a/ambient/llm.py
+++ b/ambient/llm.py
@@ -28,6 +28,22 @@ def video_to_data_url(path: str, mime="video/mp4") -> str:
return f"data:{mime};base64,{b64}"
+def _clip_to_frame_urls(mp4: str, fps: float = 0.5, cap: int = 28, dim: int = 768) -> list:
+ """Sample chronological frames from a clip mp4 as base64 image data-URLs.
+ Used for image-only vision models (e.g. qwen) that reject video_url input."""
+ import subprocess, tempfile, glob as _glob
+ d = tempfile.mkdtemp(prefix="clipfr_")
+ subprocess.run(
+ ["ffmpeg", "-nostdin", "-loglevel", "error", "-i", mp4, "-vf",
+ f"fps={fps},scale='if(gt(iw,ih),{dim},-2)':'if(gt(iw,ih),-2,{dim})'", "-q:v", "4",
+ os.path.join(d, "f%04d.jpg")], check=False)
+ out = []
+ for p in sorted(_glob.glob(os.path.join(d, "*.jpg")))[:cap]:
+ with open(p, "rb") as f:
+ out.append("data:image/jpeg;base64," + base64.b64encode(f.read()).decode())
+ return out
+
+
def construct_payload(clips: Optional[List[Clip]] = None, frames: Optional[List[Frame]] = None):
payload = []
if clips is None and frames is None:
@@ -38,28 +54,26 @@ def construct_payload(clips: Optional[List[Clip]] = None, frames: Optional[List[
is_clip_url = clip.clip_url is not None
is_clip_file_path = clip.clip_file_path is not None and os.path.exists(clip.clip_file_path)
- if is_clip_url:
- url = clip.clip_url
- elif is_clip_file_path:
- url = video_to_data_url(clip.clip_file_path)
- else:
- raise ValueError(f"Clip {clip.id} has no valid url or file path")
-
-
timestamp = f"Timestamp: {clip.start_time} seconds to {clip.end_time} seconds"
-
- payload.extend(
- [
- {
- "type": "text",
- "text": f"Clip ID: {clip.id}\n{timestamp}",
- },
- {
- "type": "video_url",
- "video_url": {"url": url},
- },
- ]
- )
+ image_only = "gemini" not in (settings.llm_model or "").lower()
+
+ if is_clip_file_path and image_only:
+ # image-only vision model (e.g. qwen3.6-27b): send sampled frames, not video_url
+ payload.append({"type": "text",
+ "text": f"Clip ID: {clip.id}\n{timestamp}\n(chronological sampled frames)"})
+ for u in _clip_to_frame_urls(clip.clip_file_path):
+ payload.append({"type": "image_url", "image_url": {"url": u}})
+ else:
+ if is_clip_url:
+ url = clip.clip_url
+ elif is_clip_file_path:
+ url = video_to_data_url(clip.clip_file_path)
+ else:
+ raise ValueError(f"Clip {clip.id} has no valid url or file path")
+ payload.extend([
+ {"type": "text", "text": f"Clip ID: {clip.id}\n{timestamp}"},
+ {"type": "video_url", "video_url": {"url": url}},
+ ])
if frames is not None:
start_time = frames[0].timestamp
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