File size: 6,157 Bytes
2a88707
 
34d0739
f68537f
a05fede
34d0739
a05fede
34d0739
 
92d7276
2a88707
34d0739
442574e
 
 
 
 
174910b
 
 
 
 
 
 
 
 
 
2a88707
 
 
f068886
92d7276
2a88707
34d0739
174910b
 
 
 
 
 
 
e88412a
 
174910b
 
2a88707
34d0739
 
 
 
e88412a
2a88707
 
 
e88412a
 
174910b
 
e88412a
77ae47f
174910b
77ae47f
174910b
 
 
 
 
 
 
 
 
 
 
2a88707
34d0739
2a88707
174910b
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
import streamlit as st
import cohere
import os
import base64

st.set_page_config(page_title="Cohere Chat", layout="wide")

AI_PFP = "media/pfps/cohere-pfp.png"
USER_PFP = "media/pfps/user-pfp.jpg"
BANNER = "media/banner.png"

model_info = {
    "c4ai-aya-expanse-8b": {"description": "Aya Expanse is a highly performant 8B multilingual model, designed to rival monolingual performance through innovations in instruction tuning with data arbitrage, preference training, and model merging. Serves 23 languages.", "context": "4K", "output": "4K"},
    "c4ai-aya-expanse-32b": {"description": "Aya Expanse is a highly performant 32B multilingual model, designed to rival monolingual performance through innovations in instruction tuning with data arbitrage, preference training, and model merging. Serves 23 languages.", "context": "128K", "output": "4K"},
    "command-a-03-2025": {"description": "Command A is our most performant model to date, excelling at tool use, agents, retrieval augmented generation (RAG), and multilingual use cases. Command A has a context length of 256K, only requires two GPUs to run, and has 150% higher throughput compared to Command R+ 08-2024.", "context": "256K", "output": "8K"},
    "command-r7b-12-2024": {"description": "command-r7b-12-2024 is a small, fast update delivered in December 2024. It excels at RAG, tool use, agents, and similar tasks requiring complex reasoning and multiple steps.", "context": "128K", "output": "4K"},
    "command-r-plus-04-2024": {"description": "Command R+ is an instruction-following conversational model that performs language tasks at a higher quality, more reliably, and with a longer context than previous models. It is best suited for complex RAG workflows and multi-step tool use.", "context": "128K", "output": "4K"},
    "command-r-plus": {"description": "command-r-plus is an alias for command-r-plus-04-2024, so if you use command-r-plus in the API, that's the model you're pointing to.", "context": "128K", "output": "4K"},
    "command-r-08-2024": {"description": "Updated Command R model from August 2024.", "context": "128K", "output": "4K"},
    "command-r-03-2024": {"description": "Instruction-following model for code generation, RAG, and agents.", "context": "128K", "output": "4K"},
    "command-r": {"description": "Alias for command-r-03-2024.", "context": "128K", "output": "4K"},
    "command": {"description": "Conversational model with long context capabilities.", "context": "4K", "output": "4K"},
    "command-nightly": {"description": "Experimental nightly build (not for production).", "context": "128K", "output": "4K"},
    "command-light": {"description": "Faster lightweight version of command.", "context": "4K", "output": "4K"},
    "command-light-nightly": {"description": "Experimental nightly build of command-light.", "context": "128K", "output": "4K"},
    "c4ai-aya-vision-8b": {"description": "Aya Vision is an 8B vision-language model enabling image-based chat and analysis.", "context": "4K", "output": "4K"},
    "c4ai-aya-vision-32b": {"description": "Aya Vision is a 32B vision-language model with advanced image understanding and reasoning.", "context": "128K", "output": "4K"}
}

with st.sidebar:
    st.image(BANNER, use_container_width=True)
    st.title("Settings")
    api_key = st.text_input("Cohere API Key", type="password")
    selected_model = st.selectbox("Model", options=list(model_info.keys()))
    if selected_model.startswith("c4ai-aya-vision"):
        uploaded = st.file_uploader("Upload image", type=["png","jpg","jpeg"])
        if uploaded:
            data = uploaded.read()
            session_image = base64.b64encode(data).decode('utf-8')
            st.session_state.image_data = session_image
    if st.button("Clear Chat"):
        st.session_state.messages = []
        st.session_state.first_message_sent = False
        st.session_state.image_data = None
        st.rerun()
    st.divider()
    st.subheader(selected_model)
    st.markdown(model_info[selected_model]["description"])
    st.caption(f"Context: {model_info[selected_model]['context']}")
    st.caption(f"Output: {model_info[selected_model]['output']}")
    st.markdown("Powered by Cohere's API")

if "messages" not in st.session_state:
    st.session_state.messages = []
if "first_message_sent" not in st.session_state:
    st.session_state.first_message_sent = False
if "image_data" not in st.session_state:
    st.session_state.image_data = None

if not st.session_state.first_message_sent:
    st.markdown("<h1 style='text-align: center; color: #4a4a4a; margin-top: 100px;'>How can Cohere help you today?</h1>", unsafe_allow_html=True)
for msg in st.session_state.messages:
    with st.chat_message(msg["role"], avatar=USER_PFP if msg["role"]=="user" else AI_PFP):
        content = msg["content"]
        if isinstance(content, list):
            for item in content:
                if item.get("type")=="text":
                    st.markdown(item.get("text"))
                if item.get("type")=="image_url":
                    st.image(item.get("image_url").get("url"))
        else:
            st.markdown(content)
if prompt := st.chat_input("Message..."):
    if not api_key:
        st.error("API key required")
        st.stop()
    st.session_state.first_message_sent = True
    st.session_state.messages.append({"role":"user","content":prompt})
    with st.chat_message("user", avatar=USER_PFP):
        st.markdown(prompt)
    co = cohere.ClientV2(api_key)
    content = [{"type":"text","text":prompt}]
    if st.session_state.image_data and selected_model.startswith("c4ai-aya-vision"):
        data_url = f"data:image/jpeg;base64,{st.session_state.image_data}"
        content.append({"type":"image_url","image_url":{"url":data_url}})
    response = co.chat(model=selected_model, messages=[*st.session_state.messages, {"role":"user","content":content}], temperature=0.3)
    items = response.message.content
    reply = "".join([getattr(i,'text','') for i in items])
    with st.chat_message("assistant", avatar=AI_PFP):
        st.markdown(reply)
    st.session_state.messages.append({"role":"assistant","content":items})