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Build error
Build error
Add concurrency
Browse files- app.py +8 -6
- fromage/models.py +0 -2
app.py
CHANGED
@@ -73,14 +73,14 @@ def generate_for_prompt(input_text, state, ret_scale_factor, max_nm_rets, num_wo
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elif type(output) == list:
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for image in output:
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filename = save_image_to_local(image)
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response += f'<img src="/file={filename}">'
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elif type(output) == Image.Image:
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# TODO(jykoh): Persist image inputs.
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chat_history = model_inputs + [' '.join([s for s in model_outputs if type(s) == str]) + '\n']
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conversation.append((input_text, response))
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# Set input image to None.
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print('state', state, flush=True)
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@@ -98,7 +98,7 @@ with gr.Blocks() as demo:
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with gr.Row():
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with gr.Column(scale=0.3, min_width=0):
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ret_scale_factor = gr.Slider(minimum=0.0, maximum=3.0, value=1.
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max_ret_images = gr.Number(minimum=0, maximum=3, value=1, precision=1, interactive=True, label="Max images to return")
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gr_max_len = gr.Number(value=32, precision=1, label="Max # of words returned", interactive=True)
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gr_temperature = gr.Number(value=0.0, label="Temperature", interactive=True)
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@@ -113,4 +113,6 @@ with gr.Blocks() as demo:
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image_btn.upload(upload_image, [gr_state, image_btn], [gr_state, chatbot])
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clear_btn.click(reset, [], [gr_state, chatbot])
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demo.launch(share=False, debug=True, server_name="0.0.0.0")
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elif type(output) == list:
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for image in output:
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filename = save_image_to_local(image)
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response += f'<br/><img src="/file={filename}">'
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elif type(output) == Image.Image:
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filename = save_image_to_local(output)
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response += f'<br/><img src="/file={filename}">'
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# TODO(jykoh): Persist image inputs.
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chat_history = model_inputs + [' '.join([s for s in model_outputs if type(s) == str]) + '\n']
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conversation.append((input_text, response.replace('[RET]', ''))) # Remove [RET] from outputs.
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# Set input image to None.
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print('state', state, flush=True)
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with gr.Row():
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with gr.Column(scale=0.3, min_width=0):
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ret_scale_factor = gr.Slider(minimum=0.0, maximum=3.0, value=1.3, step=0.1, interactive=True, label="Multiplier for returning images (higher means more frequent)")
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max_ret_images = gr.Number(minimum=0, maximum=3, value=1, precision=1, interactive=True, label="Max images to return")
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gr_max_len = gr.Number(value=32, precision=1, label="Max # of words returned", interactive=True)
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gr_temperature = gr.Number(value=0.0, label="Temperature", interactive=True)
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image_btn.upload(upload_image, [gr_state, image_btn], [gr_state, chatbot])
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clear_btn.click(reset, [], [gr_state, chatbot])
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# demo.launch(share=False, debug=True, server_name="0.0.0.0")
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demo.queue(concurrency_count=5)
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demo.launch(debug=True)
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fromage/models.py
CHANGED
@@ -634,8 +634,6 @@ def load_fromage(embeddings_dir: str, model_args_path: str, model_ckpt_path: str
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ret_token_idx = tokenizer('[RET]', add_special_tokens=False).input_ids
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assert len(ret_token_idx) == 1, ret_token_idx
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model_kwargs['retrieval_token_idx'] = ret_token_idx[0]
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# model_kwargs['opt_version'] = 'facebook/opt-125m'
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# model_kwargs['visual_encoder'] = 'openai/clip-vit-base-patch32'
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args = namedtuple('args', model_kwargs)(**model_kwargs)
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# Initialize model for inference.
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ret_token_idx = tokenizer('[RET]', add_special_tokens=False).input_ids
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assert len(ret_token_idx) == 1, ret_token_idx
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model_kwargs['retrieval_token_idx'] = ret_token_idx[0]
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args = namedtuple('args', model_kwargs)(**model_kwargs)
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# Initialize model for inference.
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