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feat:单个agent配置各自的apiurl、apimodel、apikey

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This commit is contained in:
liailing1026
2025-12-18 09:43:15 +08:00
parent 5ef86c6fa9
commit b42ab5aedd
7 changed files with 145 additions and 911 deletions
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99
backend/AgentCoord/LLMAPI/LLMAPI.py
View File

@@ -1,5 +1,7 @@
import asyncio
from openai import OpenAI, AsyncOpenAI
import httpx
from openai import OpenAI, AsyncOpenAI, max_retries
import yaml
from termcolor import colored
import os
@@ -21,6 +23,9 @@ OPENAI_API_BASE = os.getenv("OPENAI_API_BASE") or yaml_data.get(
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY") or yaml_data.get(
"OPENAI_API_KEY", ""
)
OPENAI_API_MODEL = os.getenv("OPENAI_API_MODEL") or yaml_data.get(
"OPENAI_API_MODEL", ""
)
# Initialize OpenAI clients
client = OpenAI(api_key=OPENAI_API_KEY, base_url=OPENAI_API_BASE)
@@ -41,8 +46,11 @@ MISTRAL_API_KEY = os.getenv("MISTRAL_API_KEY") or yaml_data.get(
# for LLM completion
def LLM_Completion(
messages: list[dict], stream: bool = True, useGroq: bool = True
messages: list[dict], stream: bool = True, useGroq: bool = True,model_config: dict = None
) -> str:
if model_config:
print_colored(f"Using model config: {model_config}", "blue")
return _call_with_custom_config(messages,stream,model_config)
if not useGroq or not FAST_DESIGN_MODE:
force_gpt4 = True
useGroq = False
@@ -75,6 +83,82 @@ def LLM_Completion(
return _chat_completion(messages=messages)
def _call_with_custom_config(messages: list[dict], stream: bool, model_config: dict) ->str:
"使用自定义配置调用API"
api_url = model_config.get("apiUrl", OPENAI_API_BASE)
api_key = model_config.get("apiKey", OPENAI_API_KEY)
api_model = model_config.get("apiModel", OPENAI_API_MODEL)
temp_client = OpenAI(api_key=api_key, base_url=api_url)
temp_async_client = AsyncOpenAI(api_key=api_key, base_url=api_url)
try:
if stream:
try:
loop = asyncio.get_event_loop()
except RuntimeError as ex:
if "There is no current event loop in thread" in str(ex):
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
return loop.run_until_complete(
_achat_completion_stream_custom(messages=messages, temp_async_client=temp_async_client, api_model=api_model)
)
else:
response = temp_client.chat.completions.create(
messages=messages,
model=api_model,
temperature=0.3,
max_tokens=4096,
timeout=180
)
full_reply_content = response.choices[0].message.content
print(colored(full_reply_content, "blue", "on_white"), end="")
return full_reply_content
except Exception as e:
print_colored(f"Custom API error for model {api_model} :{str(e)}","red")
raise
async def _achat_completion_stream_custom(messages:list[dict], temp_async_client, api_model: str ) -> str:
max_retries=3
for attempt in range(max_retries):
try:
response = await temp_async_client.chat.completions.create(
messages=messages,
model=api_model,
temperature=0.3,
max_tokens=4096,
stream=True,
timeout=180
)
collected_chunks = []
collected_messages = []
async for chunk in response:
collected_chunks.append(chunk)
choices = chunk.choices
if len(choices) > 0:
chunk_message = chunk.choices[0].delta
collected_messages.append(chunk_message)
if chunk_message.content:
print(colored(chunk_message.content, "blue", "on_white"), end="")
print()
full_reply_content = "".join(
[m.content or "" for m in collected_messages if m is not None]
)
return full_reply_content
except httpx.RemoteProtocolError as e:
if attempt < max_retries - 1:
wait_time = (attempt + 1) *2
print_colored(f"⚠️ Stream connection interrupted (attempt {attempt+1}/{max_retries}). Retrying in {wait_time}s...", text_color="yellow")
await asyncio.sleep(wait_time)
continue
except Exception as e:
print_colored(f"Custom API stream error for model {api_model} :{str(e)}","red")
raise
async def _achat_completion_stream_groq(messages: list[dict]) -> str:
from groq import AsyncGroq
groq_client = AsyncGroq(api_key=GROQ_API_KEY)
@@ -144,7 +228,7 @@ async def _achat_completion_stream_gpt35(messages: list[dict]) -> str:
messages=messages,
max_tokens=4096,
temperature=0.3,
timeout=30,
timeout=600,
model="gpt-3.5-turbo-16k",
stream=True,
)
@@ -172,16 +256,15 @@ async def _achat_completion_stream_gpt35(messages: list[dict]) -> str:
return full_reply_content
async def _achat_completion_json(messages: list[dict]) -> str:
def _achat_completion_json(messages: list[dict] ) -> str:
max_attempts = 5
for attempt in range(max_attempts):
try:
response = await async_client.chat.completions.create(
response = async_client.chat.completions.create(
messages=messages,
max_tokens=4096,
temperature=0.3,
timeout=30,
timeout=600,
model=MODEL,
response_format={"type": "json_object"},
)
@@ -245,7 +328,7 @@ def _cons_kwargs(messages: list[dict]) -> dict:
"messages": messages,
"max_tokens": 2000,
"temperature": 0.3,
"timeout": 60,
"timeout": 600,
}
kwargs_mode = {"model": MODEL}
kwargs.update(kwargs_mode)

25
backend/AgentCoord/RehearsalEngine_V2/Action/baseAction.py
View File

@@ -81,16 +81,33 @@ class BaseAction():
action_Record += PROMPT_TEMPLATE_ACTION_RECORD.format(AgentName = actionInfo["AgentName"], Action_Description = actionInfo["AgentName"], Action_Result = actionInfo["Action_Result"], Important_Mark = Important_Mark)
# Handle missing agent profiles gracefully
model_config = None
if agentName not in AgentProfile_Dict:
print_colored(text=f"Warning: Agent '{agentName}' not found in AgentProfile_Dict. Using default profile.", text_color="yellow")
agentProfile = f"AI Agent named {agentName}"
else:
agentProfile = AgentProfile_Dict[agentName]
prompt = PROMPT_TEMPLATE_TAKE_ACTION_BASE.format(agentName = agentName, agentProfile = agentProfile, General_Goal = General_Goal, Current_Task_Description = TaskDescription, Input_Objects = inputObject_Record, History_Action = action_Record, Action_Description = self.info["Description"], Action_Custom_Note = self.Action_Custom_Note)
# agentProfile = AgentProfile_Dict[agentName]
agent_config = AgentProfile_Dict[agentName]
agentProfile = agent_config.get("profile",f"AI Agent named {agentName}")
if agent_config.get("useCustomAPI",False):
model_config = {
"apiModel":agent_config.get("apiModel"),
"apiUrl":agent_config.get("apiUrl"),
"apiKey":agent_config.get("apiKey"),
}
prompt = PROMPT_TEMPLATE_TAKE_ACTION_BASE.format(
agentName = agentName,
agentProfile = agentProfile,
General_Goal = General_Goal,
Current_Task_Description = TaskDescription,
Input_Objects = inputObject_Record,
History_Action = action_Record,
Action_Description = self.info["Description"],
Action_Custom_Note = self.Action_Custom_Note
)
print_colored(text = prompt, text_color="red")
messages = [{"role":"system", "content": prompt}]
ActionResult = LLM_Completion(messages,True,False)
ActionResult = LLM_Completion(messages,True,False,model_config=model_config)
ActionInfo_with_Result = copy.deepcopy(self.info)
ActionInfo_with_Result["Action_Result"] = ActionResult

8
backend/config/config.yaml
View File

@@ -1,10 +1,10 @@
## config for default LLM
OPENAI_API_BASE: ""
OPENAI_API_KEY: ""
OPENAI_API_MODEL: "gpt-4-turbo-preview"
OPENAI_API_BASE: "https://ai.gitee.com/v1"
OPENAI_API_KEY: "HYCNGM39GGFNSB1F8MBBMI9QYJR3P1CRSYS2PV1A"
OPENAI_API_MODEL: "DeepSeek-V3"
## config for fast mode
FAST_DESIGN_MODE: True
FAST_DESIGN_MODE: False
GROQ_API_KEY: ""
MISTRAL_API_KEY: ""

22
backend/server.py
View File

@@ -271,13 +271,29 @@ def Handle_saveRequestCashe():
@app.route("/setAgents", methods=["POST"])
def set_agents():
global AgentBoard, AgentProfile_Dict
global AgentBoard, AgentProfile_Dict,yaml_data
AgentBoard = request.json
AgentProfile_Dict = {}
for item in AgentBoard:
name = item["Name"]
profile = item["Profile"]
AgentProfile_Dict[name] = profile
if all(item.get(field) for field in ["apiUrl","apiKey","apiModel"]):
agent_config = {
"profile": item["Profile"],
"apiUrl": item["apiUrl"],
"apiKey": item["apiKey"],
"apiModel": item["apiModel"],
"useCustomAPI":True
}
else:
agent_config = {
"profile": item["Profile"],
"apiUrl": yaml_data.get("OPENAI_API_BASE"),
"apiKey": yaml_data.get("OPENAI_API_KEY"),
"apiModel": yaml_data.get("OPENAI_API_MODEL"),
"useCustomAPI":False
}
AgentProfile_Dict[name] = agent_config
return jsonify({"code": 200, "content": "set agentboard successfully"})