"+f"[INST] {message} [/INST]"
return prompt
else:
prompt += f"[INST] {message} [/INST]"
return prompt
def run_gpt(in_prompt,history,model_drop,seed):
client = InferenceClient(c_models[int(model_drop)])
print(f'history :: {history}')
prompt=format_prompt(in_prompt,history,seed)
if seed == 0:
seed = random.randint(1,1111111111111111)
print (seed)
generate_kwargs = dict(
temperature=1.0,
max_new_tokens=1048,
top_p=0.99,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
content = agent.GENERATE_PROMPT + prompt
print(content)
stream = client.text_generation(content, **generate_kwargs, stream=True, details=True, return_full_text=False)
resp = ""
for response in stream:
resp += response.token.text
return resp
def run_idefics(in_prompt,history,model_drop,seed):
client = InferenceClient("HuggingFaceM4/idefics-9b-instruct")
print(f'history :: {history}')
prompt=format_prompt(in_prompt,history,seed)
seed = random.randint(1,1111111111111111)
print (seed)
generate_kwargs = dict(
temperature=1.0,
max_new_tokens=1048,
top_p=0.99,
repetition_penalty=1.0,
do_sample=True,
seed=seed,
)
content = agent.GENERATE_PROMPT + prompt
print(content)
stream = client.text_generation(content, **generate_kwargs, stream=True, details=True, return_full_text=False)
resp = ""
for response in stream:
resp += response.token.text
print (resp)
return resp
def generate(purpose,history,chat_drop,seed):
print (history)
out_prompt = run_gpt(purpose,history,chat_drop,seed)
return out_prompt
def describe(purpose,history,image,chat_drop,seed):
print (history)
purpose=f"{purpose},![]({image})"
out_prompt = run_idefics(purpose,history,chat_drop)
return out_prompt
def run(purpose,history,image,model_drop,chat_drop,choice,seed):
if choice == "Generate":
#out_img = infer(out_prompt)
out_prompt=generate(purpose,history,chat_drop,seed)
history.append((purpose,out_prompt))
yield (history,None)
model=loaded_model[int(model_drop)]
out_img=model(out_prompt)
#return (history,None)
print(out_img)
url=f'https://johann22-chat-diffusion-describe.hf.space/file={out_img}'
print(url)
uid = uuid.uuid4()
#urllib.request.urlretrieve(image, 'tmp.png')
#out=Image.open('tmp.png')
r = requests.get(url, stream=True)
if r.status_code == 200:
out = Image.open(io.BytesIO(r.content))
#yield ([(purpose,out_prompt)],out)
yield (history,out)
else:
yield ([(purpose,"an Error occured")],None)
if choice == "Describe":
#out_img = infer(out_prompt)
out_prompt=describe(purpose,history,image,model_drop,chat_drop,seed)
history.append((purpose,out_prompt))
yield (history,None)
################################################
style="""
.top_head{
background: no-repeat;
background-image: url(https://huggingface.co/spaces/johann22/chat-diffusion/resolve/main/image.png);
background-position-y: bottom;
height: 180px;
background-position-x: center;
}
.top_h1{
color: white!important;
-webkit-text-stroke-width: medium;
}
"""
with gr.Blocks(css=style) as iface:
gr.HTML("""
Mixtral Chat Diffusion
This chatbot will generate images