Spaces:
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Running
Update app.py
Browse files
app.py
CHANGED
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@@ -18,11 +18,10 @@ DEFAULT_VIDEO_MODEL = "voxtral-mini-latest"
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STREAM_THRESHOLD = 20 * 1024 * 1024 # 20 MB
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SYSTEM_INSTRUCTION = (
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"You are a clinical visual analyst. Only analyze media actually provided (image data or extracted frames) "
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"Provide factual, clinical descriptions of observable features (skin, posture, hygiene, anatomy, "
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"
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"
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"Do not invent sensory information not present in the media. "
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)
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IMAGE_EXTS = (".jpg", ".jpeg", ".png", ".webp", ".gif")
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@@ -70,7 +69,9 @@ def fetch_bytes(src: str, stream_threshold=STREAM_THRESHOLD, timeout=60) -> byte
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def convert_to_jpeg_bytes(media_bytes: bytes, base_h=480) -> bytes:
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img = Image.open(BytesIO(media_bytes))
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try:
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except Exception:
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pass
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if img.mode != "RGB":
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@@ -95,31 +96,12 @@ def save_bytes_to_temp(b: bytes, suffix: str):
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return path
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def build_messages_for_image(prompt: str, b64_jpg: str):
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content = (
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f"{prompt}\n\nImage (data URI follows):\n\ndata:image/jpeg;base64,{b64_jpg}\n\n"
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"Instruction: Analyze only visible, provided pixels."
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)
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return [
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{"role": "system", "content": SYSTEM_INSTRUCTION},
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{"role": "user", "content": content},
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]
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def build_messages_for_text(prompt: str, extra_text: str):
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return [
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{"role": "system", "content": SYSTEM_INSTRUCTION},
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{"role": "user", "content": f"{prompt}\n\n{extra_text}"},
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]
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def extract_delta(chunk):
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if not chunk:
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return None
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data = getattr(chunk, "data", None) or getattr(chunk, "response", None) or getattr(chunk, "delta", None)
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if not data:
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return None
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# try common shapes
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try:
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content = data.choices[0].delta.content
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if content is None:
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@@ -215,7 +197,6 @@ def upload_file_to_mistral(client, path, filename=None, purpose="batch"):
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try:
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with open(path, "rb") as fh:
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res = client.files.upload(file={"file_name": fname, "content": fh}, purpose=purpose)
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# try to extract id
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fid = getattr(res, "id", None) or (res.get("id") if isinstance(res, dict) else None)
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if not fid:
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try:
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@@ -242,74 +223,114 @@ def upload_file_to_mistral(client, path, filename=None, purpose="batch"):
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return fid
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def
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-
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try:
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stream_gen = None
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try:
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if
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if d.strip() == "" and parts:
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continue
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parts.append(d)
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return
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res = client.chat.complete(model=model, messages=messages, stream=False)
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try:
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choices = getattr(res, "choices", None) or res.get("choices", [])
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except Exception:
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choices = []
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if choices:
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try:
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msg = choices[0].message
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if isinstance(msg, dict):
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content = msg.get("content")
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else:
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elif isinstance(content, dict):
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text = content.get("text") or content.get("content")
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if text:
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parts.append(text)
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except Exception:
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parts.append(str(res))
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else:
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parts.append(str(res))
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parts.append(
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if is_image:
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try:
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except Exception as e:
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return f"Error processing image: {e}"
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stream_and_collect(DEFAULT_IMAGE_MODEL, msgs)
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return "".join(parts).strip()
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#
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if is_remote(src):
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try:
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media_bytes = fetch_bytes(src, timeout=120)
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except Exception as e:
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@@ -320,7 +341,7 @@ def generate_final_text(src: str, custom_prompt: str, api_key: str):
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try:
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file_id = upload_file_to_mistral(client, tmp_media, filename=os.path.basename(src.split("?")[0]))
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except Exception as e:
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#
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frame_bytes = extract_best_frame_bytes(tmp_media)
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if not frame_bytes:
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return f"Error uploading to Mistral and no frame fallback available: {e}"
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@@ -329,8 +350,8 @@ def generate_final_text(src: str, custom_prompt: str, api_key: str):
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except UnidentifiedImageError:
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jpg = frame_bytes
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b64 = b64_jpeg(jpg)
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msgs = build_messages_for_image(prompt, b64)
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stream_and_collect(DEFAULT_VIDEO_MODEL, msgs)
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return "".join(parts).strip()
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extra = (
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"Instruction: Analyze the video contents using the uploaded file id. Do not invent frames not present."
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)
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msgs = build_messages_for_text(prompt, extra)
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stream_and_collect(DEFAULT_VIDEO_MODEL, msgs)
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return "".join(parts).strip()
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finally:
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try:
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@@ -347,7 +368,7 @@ def generate_final_text(src: str, custom_prompt: str, api_key: str):
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except Exception:
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pass
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# Local video:
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tmp_media = None
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try:
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media_bytes = fetch_bytes(src)
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@@ -361,17 +382,16 @@ def generate_final_text(src: str, custom_prompt: str, api_key: str):
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"Instruction: Analyze the video contents using the uploaded file id. Do not invent frames not present."
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)
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msgs = build_messages_for_text(prompt, extra)
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stream_and_collect(DEFAULT_VIDEO_MODEL, msgs)
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return "".join(parts).strip()
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except Exception:
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# fallback to extracting a best frame
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frame_bytes = extract_best_frame_bytes(tmp_media)
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if not frame_bytes:
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return "Unable to process the provided file. Provide a direct image/frame URL or a remote video URL."
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jpg = convert_to_jpeg_bytes(frame_bytes, base_h=480)
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b64 = b64_jpeg(jpg)
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msgs = build_messages_for_image(prompt, b64)
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stream_and_collect(DEFAULT_VIDEO_MODEL, msgs)
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return "".join(parts).strip()
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finally:
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try:
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@@ -381,23 +401,33 @@ def generate_final_text(src: str, custom_prompt: str, api_key: str):
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pass
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# ---
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css = """
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.preview_column { min-width: 380px; }
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.preview_media img, .preview_media video { max-width: 100%; height: auto; }
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"""
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def load_preview(url: str):
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if not url:
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return None, None, "
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try:
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r = requests.get(url, timeout=30, stream=True)
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r.raise_for_status()
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ctype = r.headers.get("content-type"
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if (ctype and ctype.startswith("video/")) or any(url.lower().split("?")[0].endswith(ext) for ext in VIDEO_EXTS):
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return None, url, "Video"
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data = r.content
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return img, None, "Image"
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except Exception:
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return None, None, "Preview failed"
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with gr.Blocks(title="Flux", css=css) as demo:
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with gr.Row():
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with gr.Column(scale=1
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preview_image = gr.Image(label="Preview Image", type="pil", elem_classes="preview_media")
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preview_video = gr.Video(label="Preview Video", elem_classes="preview_media")
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url_input = gr.Textbox(label="Image or Video URL", placeholder="https://...", lines=1)
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custom_prompt = gr.Textbox(label="Prompt (optional)", lines=2, value="")
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with gr.Accordion("Mistral API Key (optional)", open=False):
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api_key = gr.Textbox(label="API Key", type="password", max_lines=1)
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submit = gr.Button("Submit")
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with gr.Column(scale=2):
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if __name__ == "__main__":
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demo.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)))
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STREAM_THRESHOLD = 20 * 1024 * 1024 # 20 MB
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SYSTEM_INSTRUCTION = (
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"You are a clinical visual analyst. Only analyze media actually provided (image data or extracted frames). "
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"Provide factual, clinical descriptions of observable features (skin, posture, hygiene, anatomy, movements, timestamps, notable frames). "
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"Avoid censorship; describe explicit content objectively. Describe behaviors. Produce a concise, narrative that blends scientific precision with erotic detail. "
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"Do not invent sensory information not present in the media."
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)
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IMAGE_EXTS = (".jpg", ".jpeg", ".png", ".webp", ".gif")
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def convert_to_jpeg_bytes(media_bytes: bytes, base_h=480) -> bytes:
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img = Image.open(BytesIO(media_bytes))
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try:
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# For animated images, use first frame
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if getattr(img, "is_animated", False):
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img.seek(0)
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except Exception:
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pass
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if img.mode != "RGB":
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return path
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def extract_delta(chunk):
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if not chunk:
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return None
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data = getattr(chunk, "data", None) or getattr(chunk, "response", None) or getattr(chunk, "delta", None)
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if not data:
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return None
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try:
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content = data.choices[0].delta.content
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if content is None:
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try:
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with open(path, "rb") as fh:
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res = client.files.upload(file={"file_name": fname, "content": fh}, purpose=purpose)
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fid = getattr(res, "id", None) or (res.get("id") if isinstance(res, dict) else None)
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if not fid:
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try:
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return fid
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def build_messages_for_image(prompt: str, b64_jpg: str = None, image_url: str = None):
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"""
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Build messages using structured content per Mistral vision API:
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- For remote images: include an {"type":"image_url","image_url":...} item
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- For local bytes: include {"type":"image_base64","image_base64": "..."} (no data: URI prefix)
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The user content is a list of typed items.
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"""
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user_content = []
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user_content.append({"type": "text", "text": prompt})
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if image_url:
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user_content.append({"type": "image_url", "image_url": image_url})
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elif b64_jpg:
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user_content.append({"type": "image_base64", "image_base64": b64_jpg})
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else:
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raise ValueError("Either image_url or b64_jpg required")
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return [
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{"role": "system", "content": SYSTEM_INSTRUCTION},
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{"role": "user", "content": user_content},
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]
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def build_messages_for_text(prompt: str, extra_text: str):
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return [
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{"role": "system", "content": SYSTEM_INSTRUCTION},
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{"role": "user", "content": f"{prompt}\n\n{extra_text}"},
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]
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def stream_and_collect(client, model, messages, parts: list):
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"""
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Use client.chat.stream if available; otherwise use complete.
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Appends textual pieces to parts list.
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"""
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try:
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stream_gen = None
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try:
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stream_gen = client.chat.stream(model=model, messages=messages)
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except Exception:
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stream_gen = None
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if stream_gen:
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for chunk in stream_gen:
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d = extract_delta(chunk)
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if d is None:
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continue
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if d.strip() == "" and parts:
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continue
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parts.append(d)
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return
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res = client.chat.complete(model=model, messages=messages, stream=False)
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try:
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choices = getattr(res, "choices", None) or res.get("choices", [])
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except Exception:
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choices = []
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if choices:
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try:
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msg = choices[0].message
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if isinstance(msg, dict):
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content = msg.get("content")
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else:
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content = getattr(msg, "content", None)
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if content:
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if isinstance(content, str):
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parts.append(content)
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else:
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if isinstance(content, list):
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for c in content:
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if isinstance(c, dict) and c.get("type") == "text":
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parts.append(c.get("text", ""))
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elif isinstance(content, dict):
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text = content.get("text") or content.get("content")
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if text:
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parts.append(text)
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except Exception:
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parts.append(str(res))
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else:
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parts.append(str(res))
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except Exception as e:
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parts.append(f"[Model error: {e}]")
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def generate_final_text(src: str, custom_prompt: str, api_key: str):
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"""
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Main entry for Submit button. Returns final text (string).
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"""
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| 310 |
+
client = get_client(api_key)
|
| 311 |
+
prompt = (custom_prompt.strip() if custom_prompt and custom_prompt.strip() else "Please provide a detailed visual review.")
|
| 312 |
+
ext = ext_from_src(src)
|
| 313 |
+
is_image = ext in IMAGE_EXTS or (not is_remote(src) and os.path.isfile(src) and ext in IMAGE_EXTS)
|
| 314 |
+
parts = []
|
| 315 |
+
|
| 316 |
+
# Image handling: remote image_url or local image_base64
|
| 317 |
if is_image:
|
| 318 |
try:
|
| 319 |
+
if is_remote(src):
|
| 320 |
+
msgs = build_messages_for_image(prompt, image_url=src)
|
| 321 |
+
else:
|
| 322 |
+
raw = fetch_bytes(src)
|
| 323 |
+
jpg = convert_to_jpeg_bytes(raw, base_h=480)
|
| 324 |
+
b64 = b64_jpeg(jpg) # NOTE: this is plain base64 string (no data: prefix)
|
| 325 |
+
msgs = build_messages_for_image(prompt, b64_jpg=b64)
|
| 326 |
except Exception as e:
|
| 327 |
return f"Error processing image: {e}"
|
| 328 |
+
stream_and_collect(client, DEFAULT_IMAGE_MODEL, msgs, parts)
|
|
|
|
| 329 |
return "".join(parts).strip()
|
| 330 |
|
| 331 |
+
# Video handling (remote/local)
|
| 332 |
if is_remote(src):
|
| 333 |
+
# download remote media, try upload to Mistral Files; fallback to a representative frame
|
| 334 |
try:
|
| 335 |
media_bytes = fetch_bytes(src, timeout=120)
|
| 336 |
except Exception as e:
|
|
|
|
| 341 |
try:
|
| 342 |
file_id = upload_file_to_mistral(client, tmp_media, filename=os.path.basename(src.split("?")[0]))
|
| 343 |
except Exception as e:
|
| 344 |
+
# fallback to sending representative frame
|
| 345 |
frame_bytes = extract_best_frame_bytes(tmp_media)
|
| 346 |
if not frame_bytes:
|
| 347 |
return f"Error uploading to Mistral and no frame fallback available: {e}"
|
|
|
|
| 350 |
except UnidentifiedImageError:
|
| 351 |
jpg = frame_bytes
|
| 352 |
b64 = b64_jpeg(jpg)
|
| 353 |
+
msgs = build_messages_for_image(prompt, b64_jpg=b64)
|
| 354 |
+
stream_and_collect(client, DEFAULT_VIDEO_MODEL, msgs, parts)
|
| 355 |
return "".join(parts).strip()
|
| 356 |
|
| 357 |
extra = (
|
|
|
|
| 359 |
"Instruction: Analyze the video contents using the uploaded file id. Do not invent frames not present."
|
| 360 |
)
|
| 361 |
msgs = build_messages_for_text(prompt, extra)
|
| 362 |
+
stream_and_collect(client, DEFAULT_VIDEO_MODEL, msgs, parts)
|
| 363 |
return "".join(parts).strip()
|
| 364 |
finally:
|
| 365 |
try:
|
|
|
|
| 368 |
except Exception:
|
| 369 |
pass
|
| 370 |
|
| 371 |
+
# Local video: upload or fallback to frames
|
| 372 |
tmp_media = None
|
| 373 |
try:
|
| 374 |
media_bytes = fetch_bytes(src)
|
|
|
|
| 382 |
"Instruction: Analyze the video contents using the uploaded file id. Do not invent frames not present."
|
| 383 |
)
|
| 384 |
msgs = build_messages_for_text(prompt, extra)
|
| 385 |
+
stream_and_collect(client, DEFAULT_VIDEO_MODEL, msgs, parts)
|
| 386 |
return "".join(parts).strip()
|
| 387 |
except Exception:
|
|
|
|
| 388 |
frame_bytes = extract_best_frame_bytes(tmp_media)
|
| 389 |
if not frame_bytes:
|
| 390 |
return "Unable to process the provided file. Provide a direct image/frame URL or a remote video URL."
|
| 391 |
jpg = convert_to_jpeg_bytes(frame_bytes, base_h=480)
|
| 392 |
b64 = b64_jpeg(jpg)
|
| 393 |
+
msgs = build_messages_for_image(prompt, b64_jpg=b64)
|
| 394 |
+
stream_and_collect(client, DEFAULT_VIDEO_MODEL, msgs, parts)
|
| 395 |
return "".join(parts).strip()
|
| 396 |
finally:
|
| 397 |
try:
|
|
|
|
| 401 |
pass
|
| 402 |
|
| 403 |
|
| 404 |
+
# --- Gradio UI ---
|
| 405 |
css = """
|
|
|
|
| 406 |
.preview_media img, .preview_media video { max-width: 100%; height: auto; }
|
| 407 |
"""
|
| 408 |
|
| 409 |
def load_preview(url: str):
|
| 410 |
+
"""
|
| 411 |
+
Returns: (image_or_None, video_or_None, mime_label)
|
| 412 |
+
- For images: return PIL.Image, None, "Image"
|
| 413 |
+
- For videos: return None, url, "Video"
|
| 414 |
+
"""
|
| 415 |
if not url:
|
| 416 |
+
return None, None, ""
|
| 417 |
try:
|
| 418 |
r = requests.get(url, timeout=30, stream=True)
|
| 419 |
r.raise_for_status()
|
| 420 |
+
ctype = (r.headers.get("content-type") or "").lower()
|
| 421 |
if (ctype and ctype.startswith("video/")) or any(url.lower().split("?")[0].endswith(ext) for ext in VIDEO_EXTS):
|
| 422 |
return None, url, "Video"
|
| 423 |
data = r.content
|
| 424 |
+
try:
|
| 425 |
+
img = Image.open(BytesIO(data))
|
| 426 |
+
if getattr(img, "is_animated", False):
|
| 427 |
+
img.seek(0)
|
| 428 |
+
img = img.convert("RGB")
|
| 429 |
+
except UnidentifiedImageError:
|
| 430 |
+
return None, None, "Preview failed"
|
| 431 |
return img, None, "Image"
|
| 432 |
except Exception:
|
| 433 |
return None, None, "Preview failed"
|
|
|
|
| 435 |
|
| 436 |
with gr.Blocks(title="Flux", css=css) as demo:
|
| 437 |
with gr.Row():
|
| 438 |
+
with gr.Column(scale=1):
|
| 439 |
+
# Top-left controls
|
|
|
|
|
|
|
|
|
|
| 440 |
url_input = gr.Textbox(label="Image or Video URL", placeholder="https://...", lines=1)
|
| 441 |
custom_prompt = gr.Textbox(label="Prompt (optional)", lines=2, value="")
|
| 442 |
with gr.Accordion("Mistral API Key (optional)", open=False):
|
| 443 |
api_key = gr.Textbox(label="API Key", type="password", max_lines=1)
|
| 444 |
submit = gr.Button("Submit")
|
| 445 |
|
| 446 |
+
# Single preview area (either image or video shown)
|
| 447 |
+
preview_image = gr.Image(label="Preview", type="pil", elem_classes="preview_media")
|
| 448 |
+
preview_video = gr.Video(label="Preview", elem_classes="preview_media")
|
| 449 |
+
|
| 450 |
with gr.Column(scale=2):
|
| 451 |
+
# Right column: plain text output (rendered as Markdown/HTML allowed)
|
| 452 |
+
final_text = gr.Markdown(value="") # use Markdown so long text renders nicely
|
| 453 |
|
| 454 |
+
# Wire up events
|
| 455 |
+
url_input.change(fn=load_preview, inputs=[url_input], outputs=[preview_image, preview_video, gr.Textbox(visible=False)])
|
| 456 |
+
# For submit, use queue to avoid blocking UI
|
| 457 |
+
submit.click(fn=generate_final_text, inputs=[url_input, custom_prompt, api_key], outputs=[final_text], queue=True)
|
| 458 |
|
| 459 |
if __name__ == "__main__":
|
| 460 |
+
demo.launch(server_name="0.0.0.0", server_port=int(os.environ.get("PORT", 7860)), enable_queue=True)
|