File size: 7,899 Bytes
5e1f2b6
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
import gradio as gr
import httpx
import json
import asyncio
import os
from chat_state import chat_state
from config import OLLAMA_URL, DEFAULT_TEMPERATURE, DEFAULT_SYSTEM_MESSAGE

theme = gr.themes.Soft(
    primary_hue="yellow",
    neutral_hue="neutral",
    text_size="md",
    spacing_size="md",
    radius_size="md",
    font=[gr.themes.GoogleFont('Montserrat'), gr.themes.GoogleFont('ui-sans-serif'), 'system-ui', 'sans-serif'],
)


async def fetch_available_models():
    async with httpx.AsyncClient() as client:
        try:
            response = await client.get(f"{OLLAMA_URL}/api/tags")
            response.raise_for_status()
            data = response.json()
            return [model["name"] for model in data.get("models", [])]
        except httpx.HTTPStatusError as e:
            print(f"Error fetching models: {e}")
            return []

async def get_model_info(model_name):
    async with httpx.AsyncClient() as client:
        try:
            response = await client.post(f"{OLLAMA_URL}/api/show", json={"name": model_name})
            response.raise_for_status()
            return response.json()
        except httpx.HTTPStatusError as e:
            print(f"Error fetching model info: {e}")
            return {}

async def call_ollama_api(prompt, history):
    messages = [{"role": "system", "content": chat_state.system_message}]
    for user_msg, assistant_msg in history:
        if user_msg:
            messages.append({"role": "user", "content": user_msg})
        if assistant_msg:
            messages.append({"role": "assistant", "content": assistant_msg})
    messages.append({"role": "user", "content": prompt})

    payload = {
        "model": chat_state.model,
        "messages": messages,
        "stream": True,
        "temperature": chat_state.temperature
    }
    
    async with httpx.AsyncClient() as client:
        try:
            async with client.stream("POST", f"{OLLAMA_URL}/api/chat", json=payload, timeout=30.0) as response:
                response.raise_for_status()
                full_response = ""
                async for line in response.aiter_lines():
                    if line:
                        json_line = json.loads(line)
                        message_content = json_line.get('message', {}).get('content', '')
                        if message_content:
                            full_response += message_content
                            yield full_response
                        if json_line.get('done'):
                            break
        except httpx.HTTPStatusError as e:
            yield f"An error occurred: {e}"
        except asyncio.TimeoutError:
            yield "The request timed out. Please try again."

async def user(user_message, history):
    return "", history + [[user_message, None]]

async def bot(history):
    user_message = history[-1][0]
    bot_message_generator = call_ollama_api(user_message, history[:-1])
    async for message_content in bot_message_generator:
        history[-1][1] = message_content
        yield history

def clear_chat():
    return None

def save_chat_history(history, filename="chat_history.json"):
    with open(filename, "w") as f:
        json.dump(history, f)
    return f"Chat history saved to {filename}"

def load_chat_history(filename="chat_history.json"):
    try:
        with open(filename, "r") as f:
            return json.load(f)
    except FileNotFoundError:
        return None

async def change_model(model_name):
    chat_state.model = model_name
    model_info = await get_model_info(model_name)
    info_text = f"Model: {model_name}\n"
    info_text += f"Parameter Size: {model_info.get('details', {}).get('parameter_size', 'Unknown')}\n"
    info_text += f"Quantization: {model_info.get('details', {}).get('quantization_level', 'Unknown')}\n"
    info_text += f"Format: {model_info.get('details', {}).get('format', 'Unknown')}"
    return f"Model changed to {chat_state.model}", info_text

def update_temperature(new_temp):
    chat_state.temperature = float(new_temp)
    return f"Temperature set to {chat_state.temperature}"

def update_system_message(new_message):
    chat_state.system_message = new_message
    return f"System message updated: {chat_state.system_message}"

async def initialize_interface():
    chat_state.available_models = await fetch_available_models()
    
    with gr.Blocks(theme=theme) as demo:
        gr.Markdown("# 🤖 Enhanced Ollama Chatbot Interface")
        
        with gr.Row():
            with gr.Column(scale=7):
                chatbot = gr.Chatbot(height=600, elem_id="chatbot")
                with gr.Row():
                    msg = gr.Textbox(
                        label="Message",
                        placeholder="Type your message here...",
                        scale=4,
                        elem_id="user-input"
                    )
                    send = gr.Button("Send", scale=1, elem_id="send-btn")
            
            with gr.Column(scale=3):
                with gr.Accordion("Model Settings", open=True):
                    model_dropdown = gr.Dropdown(
                        choices=chat_state.available_models,
                        label="Select Model",
                        value=chat_state.available_models[0] if chat_state.available_models else None,
                        elem_id="model-dropdown"
                    )
                    model_info = gr.Textbox(label="Model Information", interactive=False, lines=4)
                    temp_slider = gr.Slider(
                        minimum=0, maximum=1, value=DEFAULT_TEMPERATURE, step=0.1,
                        label="Temperature",
                        elem_id="temp-slider"
                    )
                
                with gr.Accordion("System Message", open=False):
                    system_message_input = gr.Textbox(
                        label="System Message",
                        value=DEFAULT_SYSTEM_MESSAGE,
                        lines=3,
                        elem_id="system-message"
                    )
                    update_system_button = gr.Button("Update System Message", elem_id="update-system-btn")
                
                with gr.Accordion("Chat Management", open=False):
                    with gr.Row():
                        clear = gr.Button("Clear Chat", elem_id="clear-btn")
                        save_button = gr.Button("Save Chat", elem_id="save-btn")
                        load_button = gr.Button("Load Chat", elem_id="load-btn")
                
                status_box = gr.Textbox(label="Status", interactive=False, elem_id="status-box")
        
        # Event handlers
        send_event = msg.submit(user, [msg, chatbot], [msg, chatbot], queue=False).then(
            bot, chatbot, chatbot
        )
        send.click(user, [msg, chatbot], [msg, chatbot], queue=False).then(
            bot, chatbot, chatbot
        )
        clear.click(clear_chat, outputs=[chatbot])
        model_dropdown.change(change_model, inputs=[model_dropdown], outputs=[status_box, model_info])
        temp_slider.change(update_temperature, inputs=[temp_slider], outputs=[status_box])
        update_system_button.click(update_system_message, inputs=[system_message_input], outputs=[status_box])
        save_button.click(save_chat_history, inputs=[chatbot], outputs=[status_box])
        load_button.click(load_chat_history, outputs=[chatbot])

        # Initialize the first model
        if chat_state.available_models:
            chat_state.model = chat_state.available_models[0]

    return demo

if __name__ == "__main__":
    demo = asyncio.run(initialize_interface())
    demo.launch(share=True)