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| import json | |
| import random | |
| from typing import List, Optional | |
| import pandas as pd | |
| def get_current_df(dfs: List[pd.DataFrame], current: int) -> pd.DataFrame: | |
| if len(dfs) == 0: | |
| return pd.DataFrame() | |
| else: | |
| return dfs[current] | |
| def query_llm_mock( | |
| messages, | |
| history: List, | |
| df: pd.DataFrame, | |
| llm_type: str, | |
| api_key: str, | |
| system_prompt: str, | |
| ): | |
| """Chat function that streams responses using mock llm. | |
| Args: | |
| messages (str or list): User input message(s). | |
| history (list): Conversation history. | |
| dfs (List[pd.DataFrame): a representation of the data already obtained | |
| system_prompt (str): The syste prompt | |
| openai_client (OpenAI): The OpenAI client | |
| Returns: | |
| str: The assistant's response. | |
| """ | |
| mock_json = json.dumps( | |
| { | |
| "Medications": [ | |
| { | |
| "Medication name": "Tamsulosin", | |
| "Passes_RBB": "Yes", | |
| "Random": random.random(), | |
| }, | |
| { | |
| "Medication name": "Metoprolol", | |
| "Passes_RBB": "Yes", | |
| "Random": random.random(), | |
| }, | |
| { | |
| "Medication name": "Bromocriptine", | |
| "Passes_RBB": "Yes", | |
| "Random": random.random(), | |
| }, | |
| { | |
| "Medication name": "Reserpine", | |
| "Passes_RBB": "Yes", | |
| "Random": random.random(), | |
| }, | |
| { | |
| "Medication name": "Rasagiline", | |
| "Passes_RBB": "Yes", | |
| "Random": random.random(), | |
| }, | |
| ] | |
| } | |
| ) | |
| yield ( | |
| f"Good question!\n" | |
| f"Here's the data frame in JSON format:\n" | |
| f"```json\n" | |
| f"{mock_json if random.random() > 0.5 else ''}\n" | |
| f"```\n\n" | |
| f"Hope this is useful." | |
| ) | |
| def llm_extract_table_mock(chat_output, llm_type, api_key) -> str: | |
| dic = { | |
| "Medications": [ | |
| { | |
| "Name": "Medication Name", | |
| "key1": "value1", | |
| "key2": "value2", | |
| "Random": random.random(), | |
| }, | |
| { | |
| "Name": "Medication Name", | |
| "key1": "value1", | |
| "key2": "value2", | |
| "Random": random.random(), | |
| }, | |
| ] | |
| } | |
| return json.dumps(dic) | |