ChenyuRabbitLove
commited on
Commit
•
203f861
1
Parent(s):
006b3a2
feature: add api calling demo
Browse files- __pycache__/app.cpython-311.pyc +0 -0
- __pycache__/functions_definition.cpython-311.pyc +0 -0
- app.py +40 -52
- functions_definition.py +81 -19
__pycache__/app.cpython-311.pyc
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__pycache__/functions_definition.cpython-311.pyc
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app.py
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@@ -3,25 +3,20 @@ import json
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import gradio as gr
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from openai import OpenAI
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from huggingface_hub import InferenceClient
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from tenacity import retry, wait_random_exponential, stop_after_attempt
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OPENAI_KEY = os.getenv("OPENAI_KEY")
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client = OpenAI(api_key=OPENAI_KEY)
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def get_current_weather(location, unit="celsius"):
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"""Get the current weather in a given location"""
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if "taipei" in location.lower():
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return json.dumps({"location": "Taipei", "temperature": "10", "unit": unit})
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else:
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return json.dumps({"location": location, "temperature": "unknown"})
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@retry(wait=wait_random_exponential(multiplier=1, max=40), stop=stop_after_attempt(3))
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def chat_completion_request(messages, tools=None, tool_choice=None):
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print(f
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try:
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response = client.chat.completions.create(
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model=
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messages=messages,
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tools=tools,
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tool_choice=tool_choice,
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print("Unable to generate ChatCompletion response")
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print(f"Exception: {e}")
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return e
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_current_weather",
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"description": "Get the current weather",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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},
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"unit": {
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"type": "string",
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"enum": ["celsius", "fahrenheit"],
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"description": "The temperature unit to use. Infer this from the users location.",
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},
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},
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"required": ["location", "unit"],
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},
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}
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}
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]
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def respond(
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message,
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history: list[tuple[str, str]],
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):
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messages = [
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for val in history:
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if val[0]:
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messages.append(
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if val[1]:
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messages.append(
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messages.append({"role": "user", "content": [{
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response = chat_completion_request(
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response_message = response.choices[0].message
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tool_calls = response_message.tool_calls
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if tool_calls:
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available_functions =
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"get_current_weather": get_current_weather,
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}
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messages.append(response_message)
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for tool_call in tool_calls:
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function_name = tool_call.function.name
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function_to_call = available_functions[function_name]
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function_args = json.loads(tool_call.function.arguments)
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function_response = function_to_call(
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unit=function_args.get("unit"),
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)
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messages.append(
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{
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"name": function_name,
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"content": function_response,
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}
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)
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second_response = chat_completion_request(messages)
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messages.append(
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return second_response.choices[0].message.content
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messages.append(
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return response.choices[0].message.content
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"""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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demo = gr.ChatInterface(
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respond,
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title='Function Calling Demo'
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)
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if __name__ == "__main__":
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demo.launch()
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import gradio as gr
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from openai import OpenAI
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from tenacity import retry, wait_random_exponential, stop_after_attempt
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from functions_definition import get_functions, get_openai_function_tools
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OPENAI_KEY = os.getenv("OPENAI_KEY")
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client = OpenAI(api_key=OPENAI_KEY)
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@retry(wait=wait_random_exponential(multiplier=1, max=40), stop=stop_after_attempt(3))
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def chat_completion_request(messages, tools=None, tool_choice=None):
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print(f"query message {messages}")
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try:
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response = client.chat.completions.create(
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model="gpt-4o",
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messages=messages,
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tools=tools,
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tool_choice=tool_choice,
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print("Unable to generate ChatCompletion response")
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print(f"Exception: {e}")
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return e
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def respond(
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message,
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history: list[tuple[str, str]],
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):
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messages = [
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{
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"role": "system",
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"content": [{"type": "text", "text": "You are a helpful agent"}],
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}
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]
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for val in history:
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if val[0]:
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messages.append(
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{"role": "user", "content": [{"type": "text", "text": val[0]}]}
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)
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if val[1]:
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messages.append(
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{"role": "assistant", "content": [{"type": "text", "text": val[1]}]}
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)
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messages.append({"role": "user", "content": [{"type": "text", "text": message}]})
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response = chat_completion_request(
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messages, tools=get_openai_function_tools(), tool_choice="auto"
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)
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response_message = response.choices[0].message
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tool_calls = response_message.tool_calls
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if tool_calls:
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available_functions = get_functions()
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messages.append(response_message)
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for tool_call in tool_calls:
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function_name = tool_call.function.name
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function_to_call = available_functions[function_name]
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function_args = json.loads(tool_call.function.arguments)
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function_response = function_to_call(
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type=function_args.get("type"),
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)
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messages.append(
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{
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"name": function_name,
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"content": function_response,
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}
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)
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second_response = chat_completion_request(messages)
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messages.append(
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{
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"role": "assistant",
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"content": [
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{"type": "text", "text": second_response.choices[0].message.content}
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],
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}
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)
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return second_response.choices[0].message.content
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messages.append(
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{
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"role": "assistant",
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"content": [{"type": "text", "text": response.choices[0].message.content}],
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}
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)
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return response.choices[0].message.content
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"""
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For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
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"""
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demo = gr.ChatInterface(respond, title="Function Calling Demo")
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if __name__ == "__main__":
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demo.launch()
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functions_definition.py
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},
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"
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},
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},
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"required": ["location", "unit"],
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},
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}
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}
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]
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import json
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import requests
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def get_current_weather(location, unit="celsius"):
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"""Get the current weather in a given location"""
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if "taipei" in location.lower():
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return json.dumps({"location": "Taipei", "temperature": "10", "unit": unit})
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else:
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return json.dumps({"location": location, "temperature": "unknown"})
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def get_junyi_content(type):
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print(f"Fetching Junyi content of type {type}")
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base_url = "https://www.junyiacademy.org/api/v2/open/content/topicpage/"
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topic_id = "knsh-7a"
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url = f"{base_url}{topic_id}"
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response = requests.get(url)
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if response.status_code == 200:
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data = response.json()
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print(data)
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else:
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print(f"Request failed with status code {response.status_code}")
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if type == "english":
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return json.dumps(
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{
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"content": "英文",
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"url": "https://www.junyiacademy.org/junyi-english/eng-junior/eng-junior07/eng-junior07-knsh/knsh-7a",
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}
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)
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def get_openai_function_tools():
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tools = [
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{
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"type": "function",
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"function": {
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"name": "get_current_weather",
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"description": "Get the current weather",
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"parameters": {
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"type": "object",
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"properties": {
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"location": {
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"type": "string",
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"description": "The city and state, e.g. San Francisco, CA",
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},
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"unit": {
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"type": "string",
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"enum": ["celsius", "fahrenheit"],
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"description": "The temperature unit to use. Infer this from the users location.",
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},
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},
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"required": ["location", "unit"],
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},
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},
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},
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{
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"type": "function",
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"function": {
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"name": "get_junyi_content",
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"description": "Get the content from Junyi Academy",
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"parameters": {
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"type": "object",
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"properties": {
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"type": {
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"type": "string",
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"enum": ["english", "math"],
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"description": "The type of content to fetch",
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},
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},
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"required": ["type"],
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},
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},
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},
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]
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return tools
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def get_functions():
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return {
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"get_current_weather": get_current_weather,
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"get_junyi_content": get_junyi_content,
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}
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