File size: 6,438 Bytes
7b5e29b a094782 7b5e29b 743176d a094782 92cd013 7b5e29b a094782 7b5e29b 743176d |
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 |
import gradio as gr
import google.generativeai as genai
import base64
from PIL import Image
import io
import time
def encode_image(image):
if isinstance(image, dict) and 'path' in image:
image_path = image['path']
elif isinstance(image, str):
image_path = image
else:
raise ValueError("Unsupported image format")
with open(image_path, "rb") as image_file:
return base64.b64encode(image_file.read()).decode('utf-8')
def bot_streaming(message, history, api_key, model, system_prompt, temperature, max_tokens, top_p, top_k, harassment, hate_speech, sexually_explicit, dangerous_content):
genai.configure(api_key=api_key)
messages = []
images = []
if system_prompt:
messages.append({"role": "system", "content": system_prompt})
for i, msg in enumerate(history):
if isinstance(msg[0], tuple):
# This is a message with an image
image, text = msg[0]
base64_image = encode_image(image)
messages.append({
"role": "user",
"parts": [
{"text": text},
{"inline_data": {"mime_type": "image/jpeg", "data": base64_image}}
]
})
images.append(Image.open(image['path'] if isinstance(image, dict) else image).convert("RGB"))
else:
# This is a text-only message
messages.append({"role": "user", "parts": [{"text": str(msg[0])}]})
# Add the model's response
messages.append({"role": "model", "parts": [{"text": str(msg[1])}]})
# Handle the current message
if isinstance(message, dict) and "files" in message and message["files"]:
# This is a message with an image
image = message["files"][0]
base64_image = encode_image(image)
content = [
{"text": message["text"]},
{"inline_data": {"mime_type": "image/jpeg", "data": base64_image}}
]
images.append(Image.open(image['path'] if isinstance(image, dict) else image).convert("RGB"))
else:
# This is a text-only message
content = [{"text": message["text"] if isinstance(message, dict) else str(message)}]
messages.append({"role": "user", "parts": content})
model = genai.GenerativeModel(model_name=model)
safety_settings = [
{"category": genai.types.HarmCategory.HARM_CATEGORY_HARASSMENT, "threshold": getattr(genai.types.HarmBlockThreshold, harassment)},
{"category": genai.types.HarmCategory.HARM_CATEGORY_HATE_SPEECH, "threshold": getattr(genai.types.HarmBlockThreshold, hate_speech)},
{"category": genai.types.HarmCategory.HARM_CATEGORY_SEXUALLY_EXPLICIT, "threshold": getattr(genai.types.HarmBlockThreshold, sexually_explicit)},
{"category": genai.types.HarmCategory.HARM_CATEGORY_DANGEROUS_CONTENT, "threshold": getattr(genai.types.HarmBlockThreshold, dangerous_content)}
]
chat = model.start_chat(history=messages)
response = chat.send_message(
content,
stream=True,
generation_config=genai.types.GenerationConfig(
temperature=temperature,
max_output_tokens=max_tokens,
top_p=top_p,
top_k=top_k
),
safety_settings=safety_settings
)
buffer = ""
for chunk in response:
if hasattr(chunk, 'text') and chunk.text:
buffer += chunk.text
yield buffer
time.sleep(0.01)
if hasattr(chunk, 'finish_reason') and chunk.finish_reason:
break
if buffer:
yield buffer
with gr.Blocks(theme=gr.themes.Soft()) as demo:
gr.Markdown("#💬 Chat with Google Gemini AI ")
gr.Markdown("### Upload images or type your message to start the conversation.")
api_key = gr.Textbox(label="API Key", type="password", placeholder="Enter your Google AI API key")
model = gr.Dropdown(
label="Select Model",
choices=[
"gemini-1.5-pro",
"gemini-1.5-pro-001",
"gemini-1.5-pro-vision-latest",
"gemini-1.5-pro-latest",
"gemini-1.5-flash",
"gemini-1.5-flash-002",
"gemini-1.0-pro",
"gemini-1.0-pro-001",
"gemini-1.0-pro-vision-latest",
"gemini-1.0-pro-latest"
],
value="gemini-1.5-pro",
)
system_prompt = gr.Textbox(label="System Prompt", placeholder="Enter a system prompt (optional)")
chatbot = gr.ChatInterface(
fn=bot_streaming,
additional_inputs=[
api_key, model, system_prompt, gr.Slider(minimum=0, maximum=1, value=0.7, step=0.1, label="Temperature"),
gr.Slider(minimum=1, maximum=2048, value=1000, step=1, label="Max Tokens"), gr.Slider(minimum=0, maximum=1, value=0.95, step=0.01, label="Top P"),
gr.Slider(minimum=1, maximum=40, value=40, step=1, label="Top K"),
gr.Dropdown(label="Harassment", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE"),
gr.Dropdown(label="Hate Speech", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE"),
gr.Dropdown(label="Sexually Explicit", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE"),
gr.Dropdown(label="Dangerous Content", choices=["BLOCK_NONE", "BLOCK_ONLY_HIGH", "BLOCK_MEDIUM_AND_ABOVE", "BLOCK_LOW_AND_ABOVE"], value="BLOCK_MEDIUM_AND_ABOVE")
],
retry_btn="🔄 Retry",
undo_btn="↩️ Undo",
clear_btn="🗑️ Clear",
multimodal=True,
cache_examples=False,
fill_height=True,
)
gr.Markdown("""
# 🤖 Google Gemini API Multimodal Chat
Chat with Google Gemini AI models. Supports text and image interactions.
## 🚀 Quick Start:
1. Enter your Google AI API key
2. Choose a model
3. Start chatting!
Enjoy your AI-powered conversation!
""")
gr.Markdown("""
## 🔧 Settings:
- Adjust basic parameters in the "Common Settings" section
- Fine-tune safety options in the "Safety Settings" section
- Upload images for multimodal interactions
""")
demo.launch(debug=True, share=True)
|