(message, history)
| 16 | |
| 17 | |
| 18 | def predict(message, history): |
| 19 | messages = [] |
| 20 | |
| 21 | for user_message, assistant_message in history: |
| 22 | messages.append({"role": "user", "content": user_message}) |
| 23 | messages.append({"role": "assistant", "content": assistant_message}) |
| 24 | |
| 25 | messages.append({"role": "user", "content": message}) |
| 26 | |
| 27 | response = llama.create_chat_completion_openai_v1( |
| 28 | model=model, messages=messages, stream=True |
| 29 | ) |
| 30 | |
| 31 | text = "" |
| 32 | for chunk in response: |
| 33 | content = chunk.choices[0].delta.content |
| 34 | if content: |
| 35 | text += content |
| 36 | yield text |
| 37 | |
| 38 | |
| 39 | js = """function () { |
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