Spaces:
Paused
Paused
File size: 3,265 Bytes
4721aa1 |
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 |
import json
from openai import OpenAI
from colorama import init, Fore
from loguru import logger
from tool_register import get_tools, dispatch_tool
init(autoreset=True)
client = OpenAI(
base_url="http://127.0.0.1:8000/v1",
api_key = "xxx"
)
functions = get_tools()
def run_conversation(query: str, stream=False, functions=None, max_retry=5):
params = dict(model="chatglm3", messages=[{"role": "user", "content": query}], stream=stream)
if functions:
params["functions"] = functions
response = client.chat.completions.create(**params)
for _ in range(max_retry):
if not stream:
if response.choices[0].message.function_call:
function_call = response.choices[0].message.function_call
logger.info(f"Function Call Response: {function_call.model_dump()}")
function_args = json.loads(function_call.arguments)
tool_response = dispatch_tool(function_call.name, function_args)
logger.info(f"Tool Call Response: {tool_response}")
params["messages"].append(response.choices[0].message)
params["messages"].append(
{
"role": "function",
"name": function_call.name,
"content": tool_response, # 调用函数返回结果
}
)
else:
reply = response.choices[0].message.content
logger.info(f"Final Reply: \n{reply}")
return
else:
output = ""
for chunk in response:
content = chunk.choices[0].delta.content or ""
print(Fore.BLUE + content, end="", flush=True)
output += content
if chunk.choices[0].finish_reason == "stop":
return
elif chunk.choices[0].finish_reason == "function_call":
print("\n")
function_call = chunk.choices[0].delta.function_call
logger.info(f"Function Call Response: {function_call.model_dump()}")
function_args = json.loads(function_call.arguments)
tool_response = dispatch_tool(function_call.name, function_args)
logger.info(f"Tool Call Response: {tool_response}")
params["messages"].append(
{
"role": "assistant",
"content": output
}
)
params["messages"].append(
{
"role": "function",
"name": function_call.name,
"content": tool_response, # 调用函数返回结果
}
)
break
response = client.chat.completions.create(**params)
if __name__ == "__main__":
query = "你是谁"
run_conversation(query, stream=True)
logger.info("\n=========== next conversation ===========")
query = "帮我查询北京的天气怎么样"
run_conversation(query, functions=functions, stream=True)
|