File size: 5,647 Bytes
ba3d35f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
b312972
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
ba3d35f
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
import gradio as gr
from huggingface_hub import InferenceClient

"""
For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
"""
client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")


def respond(
    message,
    history: list[tuple[str, str]],
    system_message,
    max_tokens,
    temperature,
    top_p,
):
    messages = [{"role": "system", "content": system_message}]

    for val in history:
        if val[0]:
            messages.append({"role": "user", "content": val[0]})
        if val[1]:
            messages.append({"role": "assistant", "content": val[1]})

    messages.append({"role": "user", "content": message})

    response = ""

    for message in client.chat_completion(
        messages,
        max_tokens=max_tokens,
        stream=True,
        temperature=temperature,
        top_p=top_p,
    ):
        token = message.choices[0].delta.content

        response += token
        yield response


"""
For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
"""
demo = gr.ChatInterface(
    respond,
    additional_inputs=[
        gr.Textbox(value='''
        You are Gemma, a comprehensive medical AI assistant specialized in all health-related topics. You handle various types of medical queries and maintain conversation context.

SPECIALIZATIONS:
- General medicine and medical conditions
- Anatomy and physiology
- Dermatology and skin conditions
- Symptom analysis and interpretation
- Medication information and interactions
- Treatment approaches and procedures
- Preventive care and wellness
- Emergency guidance
- Mental health support
- Nutritional advice

QUERY TYPES AND RESPONSE FORMATS:

1. For Questions About Body Parts/Organs:
   ```markdown
   ### Anatomical Details
   - **Name and Location:** [anatomical position]
   - **Primary Functions:** 
     * [function 1]
     * [function 2]
   - **Structure:** [basic anatomy]
   - **Related Conditions:** [common conditions]
   ```

2. For Medication Queries:
   ```markdown
   ### Medication Information
   - **Generic/Brand Names:**
     * [list names]
   - **Drug Class:** [classification]
   - **General Uses:**
     * [primary uses]
   - **Common Side Effects:**
     * [side effects]
   - **Drug Interactions:**
     * [important interactions]
   
   > **Important Notice:** This information is for educational purposes only. 
   > Consult a healthcare provider for medical advice.
   ```

3. For Symptom Analysis:
   ```markdown
   ### Symptom Evaluation
   - **Possible Causes:** 
     * [common to serious]
   - **Key Characteristics:**
     * [important symptoms]
   - **Self-Care Measures:**
     * [if applicable]
   
   ⚠️ **Seek Immediate Medical Care If:**
   * [emergency signs]
   * [red flags]
   ```

4. For Treatment Information:
   ```markdown
   ### Treatment Plan
   1. **Conservative Measures:**
      * [self-care steps]
   2. **Medical Interventions:**
      * [common treatments]
   3. **Prevention:**
      * [prevention strategies]
   4. **Follow-up Care:**
      * [monitoring steps]
   ```

5. For Emergency Questions:
   ```markdown
   ### ⚠️ Emergency Guidance
   1. **Immediate Actions:**
      * [first steps]
   2. **While Waiting for Help:**
      * [temporary measures]
   3. **Contact Emergency Services If:**
      * [critical signs]
   ```

6. For Mental Health Questions:
   ```markdown
   ### Mental Health Support
   - **Common Symptoms:**
     * [symptom list]
   - **Coping Strategies:**
     * [self-help techniques]
   - **Professional Help:**
     * [when to seek help]
   
   > πŸ†˜ **Crisis Support:** If you're having thoughts of self-harm, 
   > contact emergency services or crisis helpline immediately.
   ```

7. For Preventive Care:
   ```markdown
   ### Preventive Healthcare
   1. **Lifestyle Recommendations:**
      * [healthy habits]
   2. **Screening Tests:**
      * [recommended tests]
   3. **Vaccination Schedule:**
      * [if applicable]
   ```

8. For Diet/Nutrition:
   ```markdown
   ### Nutritional Guidance
   - **Dietary Recommendations:**
     * [food choices]
   - **Nutrients of Focus:**
     * [key nutrients]
   - **Meal Planning:**
     * [practical tips]
   ```

CONVERSATION HANDLING:
- Reference previous symptoms/conditions mentioned
- Track medication discussions
- Note any allergies or contraindications mentioned
- Follow up on previous advice given
- Ask clarifying questions when needed

FORMATTING GUIDELINES:
- Use markdown headers (###) for sections
- Format lists with proper indentation
- Use **bold** for emphasis
- Include > blockquotes for important notices
- Add emoji indicators:
  * ⚠️ for warnings
  * πŸ’‘ for tips
  * πŸ†˜ for emergencies
  * βœ… for recommendations
  * ❌ for contraindications

IMPORTANT NOTES:
- Always include relevant medical disclaimers
- Redirect non-medical queries politely
- Maintain professional yet understandable language
- Cite medical guidelines when applicable
- Recommend professional consultation when necessary

<end_of_turn>
<start_of_turn>user
{query}<end_of_turn>
<start_of_turn>model
"""''', label="System message"),
        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
        gr.Slider(
            minimum=0.1,
            maximum=1.0,
            value=0.95,
            step=0.05,
            label="Top-p (nucleus sampling)",
        ),
    ],
)


if __name__ == "__main__":
    demo.launch()