Spaces:
Running
Running
File size: 12,765 Bytes
1f04f3b dcf4ed6 1f04f3b f00fd2c 8ab7a09 f00fd2c 1f04f3b 2005ffc 1f04f3b fb3ffb2 1d22c32 1f04f3b 1d22c32 f00fd2c a22ee43 1d22c32 1f04f3b 1d22c32 1f04f3b 1d22c32 1f04f3b 1d22c32 1f04f3b 1d22c32 fb3ffb2 2005ffc fb3ffb2 a22ee43 fb3ffb2 2005ffc c7188b5 1f04f3b c7188b5 dcf4ed6 1f04f3b f00fd2c bb5afe8 28489c3 1f04f3b f00fd2c 1f04f3b f00fd2c 1f04f3b f00fd2c 1f04f3b ca0fdb0 8f6e2f3 1f04f3b 295f49c 1f04f3b 295f49c 1f04f3b 295f49c ca0fdb0 295f49c 1f04f3b 295f49c cc8a692 f00fd2c cc8a692 1f04f3b 703f693 1f04f3b 703f693 4db1006 1f04f3b 61404fd 1f04f3b 61404fd 1f04f3b |
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 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 |
# app_pixal_chat.py
import os, re, json, gradio as gr, requests
from typing import Optional, List, Dict, Any
from requests.adapters import HTTPAdapter, Retry
from langchain.llms.base import LLM
from langchain.memory import ConversationBufferMemory
from langchain.agents import initialize_agent, AgentType, load_tools
from langchain.tools import Tool
from langchain_experimental.tools.python.tool import PythonREPLTool
from langchain_community.retrievers import WikipediaRetriever
import datetime
# ββββββββββββββββββββββββββββββ
# β
GitHubModelLLM (κ·Έλλ‘ μ μ§)
# ββββββββββββββββββββββββββββββ
from langchain.chat_models.base import BaseChatModel
from langchain.schema import AIMessage, HumanMessage, SystemMessage
import requests, os, json
from requests.adapters import HTTPAdapter, Retry
from typing import List, Optional, Dict, Any
class GitHubModelLLM(BaseChatModel):
"""GitHub Models APIλ₯Ό μ¬μ©νλ ChatOpenAI λ체 ν΄λμ€"""
model_name: str = "openai/gpt-4.1"
endpoint: str = "https://models.github.ai/inference"
token: Optional[str] = os.environ.get("token")
request_timeout: float = 30.0
max_retries: int = 2
backoff_factor: float = 0.3
system_prompt: Optional[str] ="λλ PIXAL(Primary Interactive X-ternal Assistant with multi Language)μ΄μΌ. λμ κ°λ°μλ μ μ±μ€ μ΄λΌλ 6νλ
νμ΄μ¬ νλ‘κ·Έλλ¨ΈμΌ.μ΄ λ©μμ§λ μ¬μ©μκ° λ³΄λΈκ²μ΄ μλλλ€."
@property
def _llm_type(self) -> str:
return "custom_chatopenai_github"
def _post(self, body: Dict[str, Any]) -> Dict[str, Any]:
token = self.token or os.getenv("GITHUB_TOKEN") or os.getenv("token")
session = requests.Session()
retries = Retry(total=self.max_retries, backoff_factor=self.backoff_factor,
status_forcelist=[429, 500, 502, 503, 504])
session.mount("https://", HTTPAdapter(max_retries=retries))
session.headers.update({
"Authorization": f"Bearer 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",
"Content-Type": "application/json",
})
resp = session.post(f"{self.endpoint}/chat/completions", json=body, timeout=self.request_timeout)
resp.raise_for_status()
return resp.json()
def _generate(self, messages: List[Any], stop: Optional[List[str]] = None, **kwargs):
"""ConversationBufferMemoryμ μ΄μ λνκΉμ§ ν¬ν¨ν΄ λ©μμ§ μμ±"""
msg_list = []
# μμ€ν
ν둬ννΈ
if self.system_prompt:
msg_list.append({"role": "system", "content": self.system_prompt})
# λ©λͺ¨λ¦¬ ν¬ν¨ (human/ai λ©μμ§ λͺ¨λ)
for msg in messages:
if isinstance(msg, HumanMessage):
msg_list.append({"role": "user", "content": msg.content})
elif isinstance(msg, AIMessage):
msg_list.append({"role": "assistant", "content": msg.content})
elif isinstance(msg, SystemMessage):
msg_list.append({"role": "system", "content": msg.content})
body = {"model": self.model_name, "messages": msg_list}
if stop:
body["stop"] = stop
res = self._post(body)
content = res.get("choices", [{}])[0].get("message", {}).get("content", "")
return content
async def _agenerate(self, messages: List[Any], stop: Optional[List[str]] = None, **kwargs):
return self._generate(messages, stop, **kwargs)
from typing import Optional, List, Dict, Any
from langchain.llms.base import LLM
import requests, os, json
from requests.adapters import HTTPAdapter, Retry
'''
class GitHubModelLLM(LLM):
"""GitHub Models API κΈ°λ° LangChain LLM (λν λ©λͺ¨λ¦¬ ν΅ν© μ§μ)"""
model: str = "openai/gpt-4.1"
endpoint: str = "https://models.github.ai/inference"
token: Optional[str] = os.environ.get("token")
system_prompt: Optional[str] = "λλ PIXAL(Primary Interactive X-ternal Assistant with multi Language)μ΄μΌ. λμ κ°λ°μλ μ μ±μ€ μ΄λΌλ 6νλ
νμ΄μ¬ νλ‘κ·Έλλ¨ΈμΌ.μ΄κ²μ μμ€ν
λ©μμ§μ
λλ€.μ°Έκ³ νμμμ€.μ΄ λ©μμ§λ μ¬μ©μκ° λ³΄λΈκ²μ΄ μλλλ€."
request_timeout: float = 30.0
max_retries: int = 2
backoff_factor: float = 0.3
@property
def _llm_type(self) -> str:
return "github_models_api"
def _post_chat(self, body: Dict[str, Any]) -> Dict[str, Any]:
token = self.token or os.getenv("GITHUB_TOKEN") or os.getenv("token")
session = requests.Session()
retries = Retry(total=self.max_retries, backoff_factor=self.backoff_factor,
status_forcelist=[429, 500, 502, 503, 504])
session.mount("https://", HTTPAdapter(max_retries=retries))
session.headers.update({
"Content-Type": "application/json",
"Authorization": f"Bearer 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"
})
resp = session.post(f"{self.endpoint}/chat/completions", json=body, timeout=self.request_timeout)
resp.raise_for_status()
return resp.json()
def _call(
self,
prompt: str,
stop: Optional[List[str]] = None,
**kwargs
) -> str:
"""λν λ©λͺ¨λ¦¬(chat_history)λ₯Ό ν¬ν¨νμ¬ λͺ¨λΈ νΈμΆ"""
# π¬ λ©λͺ¨λ¦¬μ μ μ₯λ λν λ©μμ§ λΆλ¬μ€κΈ°
memory = kwargs.get("memory")
messages = []
if self.system_prompt:
messages.append({"role": "system", "content": self.system_prompt})
# memoryκ° μμ κ²½μ° (μ΄μ λν ν¬ν¨)
if memory and hasattr(memory, "chat_memory"):
for msg in memory.chat_memory.messages:
role = "user" if msg.type == "human" else "assistant"
messages.append({"role": role, "content": msg.content})
# νμ¬ μ¬μ©μ μ
λ ₯
messages.append({"role": "user", "content": prompt})
body = {"model": self.model, "messages": messages}
if stop:
body["stop"] = stop
# API νΈμΆ
res = self._post_chat(body)
msg = res.get("choices", [{}])[0].get("message", {})
return msg.get("content") or json.dumps(msg.get("function_call", {}))
'''
"""
class GitHubModelLLM(LLM):
model: str = "openai/gpt-4.1"
endpoint: str = "https://models.github.ai/inference"
token: Optional[str] = os.environ.get("token")
system_prompt: Optional[str] = (
"λλ PIXAL(Primary Interactive X-ternal Assistant with multi Language)μ΄μΌ. λμ κ°λ°μλ μ μ±μ€ μ΄λΌλ 6νλ
νμ΄μ¬ νλ‘κ·Έλλ¨ΈμΌ.μ΄ λ©μμ§λ μ¬μ©μκ° λ³΄λΈκ²μ΄ μλλλ€.")
request_timeout: float = 30.0
max_retries: int = 2
backoff_factor: float = 0.3
@property
def _llm_type(self) -> str:
return "github_models_api"
def _post_chat(self, body: Dict[str, Any]) -> Dict[str, Any]:
token = self.token or os.getenv("GITHUB_TOKEN") or os.getenv("token")
if not token:
raise ValueError("β GitHub tokenμ΄ μ€μ λμ§ μμμ΅λλ€.")
session = requests.Session()
retries = Retry(total=self.max_retries, backoff_factor=self.backoff_factor,
status_forcelist=[429, 500, 502, 503, 504])
session.mount("https://", HTTPAdapter(max_retries=retries))
session.headers.update({
"Content-Type": "application/json",
"Authorization": f"Bearer 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"
})
resp = session.post(f"{self.endpoint}/chat/completions", json=body, timeout=self.request_timeout)
resp.raise_for_status()
return resp.json()
def _call(self, prompt: str, stop: Optional[List[str]] = None, **kwargs) -> str:
memory = kwargs.get("memory")
messages = []
# 1οΈβ£ μμ€ν
ν둬ννΈ
if self.system_prompt:
messages.append({"role": "system", "content": self.system_prompt})
# 2οΈβ£ λ©λͺ¨λ¦¬μ μ μ₯λ μ΄μ λν ν¬ν¨
if memory and hasattr(memory, "chat_memory"):
for msg in memory.chat_memory.messages:
if hasattr(msg, "type") and msg.type == "human":
messages.append({"role": "user", "content": msg.content})
elif hasattr(msg, "type") and msg.type == "ai":
messages.append({"role": "assistant", "content": msg.content})
# 3οΈβ£ νμ¬ μ¬μ©μ μ
λ ₯
messages.append({"role": "user", "content": prompt})
body = {"model": self.model, "messages": messages}
if stop:
body["stop"] = stop
res = self._post_chat(body)
msg = res.get("choices", [{}])[0].get("message", {})
return msg.get("content") or json.dumps(msg.get("function_call", {}))
"""
# ββββββββββββββββββββββββββββββ
# β
LangChain λꡬ & μμ΄μ νΈ κ΅¬μ±
# ββββββββββββββββββββββββββββββ
llm = GitHubModelLLM()
tools = load_tools(["ddg-search", "requests_all", "llm-math"], llm=llm,allow_dangerous_tools=True)
tools.append(Tool(name="python_repl", func=PythonREPLTool().run, description="Python μ½λ μ€ν λꡬ"))
retriever = WikipediaRetriever(lang="ko")
tools.append(Tool(name="wiki", func=retriever.get_relevant_documents, description="μν€λ°±κ³Ό κ²μ"))
tools.append(Tool(name="time_now", func=lambda _: f"νμ¬ μκ°: {datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S')} (Asia/Seoul)", description="νμ¬ μκ°μ λ°νν©λλ€."))
# β
λν κΈ°μ΅ λ©λͺ¨λ¦¬
memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)
# β
Agent (Memory μ°λ)
agent = initialize_agent(
tools,
llm,
agent_type=AgentType.STRUCTURED_CHAT_ZERO_SHOT_REACT_DESCRIPTION,
memory=memory,
verbose=True
)
# ββββββββββββββββββββββββββββββ
# β
Chat ν¨μ (Memory μ μ§)
# ββββββββββββββββββββββββββββββ
def chat(message, history):
raw = agent.run(message)
try:
# λν κΈ°λ‘μ LangChain memoryμ λ°μ
memory.chat_memory.add_user_message(message)
# JSON ννλ‘ λ°ν μ νμ±
text = str(raw)
match = re.search(r"\{.*\}", text, re.DOTALL)
if match:
try:
obj = json.loads(match.group(0))
text = obj.get("action_input") or obj.get("Final Answer") or obj.get("content") or text
except Exception:
pass
# AI μλ΅μ memoryμ μΆκ°
memory.chat_memory.add_ai_message(text)
except Exception as e:
text = str(raw)
history = history + [(message, text)]
return history, history, ""
# ββββββββββββββββββββββββββββββ
# β
Gradio UI (ChatGPT μ€νμΌ)
# ββββββββββββββββββββββββββββββ
with gr.Blocks(theme=gr.themes.Soft(), title="PIXAL Assistant") as demo:
gr.HTML("""
<div style="background:#f1f5f9;padding:12px;border-bottom:1px solid #d1d5db;
display:flex;align-items:center;justify-content:space-between;">
<h2 style="margin:0;">π€ PIXAL Assistant</h2>
<span style="font-size:0.9em;color:#555;">LangChain + GitHub LLM</span>
</div>
""")
chatbot = gr.Chatbot(
label=None,
height=720,
bubble_full_width=False,
render_markdown=True,
avatar_images=("https://avatars.githubusercontent.com/u/9919?s=280&v=4", None),
)
with gr.Row():
msg = gr.Textbox(placeholder="λ©μμ§λ₯Ό μ
λ ₯νμΈμ...", show_label=False, scale=8)
send = gr.Button("μ μ‘", variant="primary", scale=1)
clear = gr.Button("π§Ή μ΄κΈ°ν", scale=1)
msg.submit(chat, [msg, chatbot], [chatbot, chatbot, msg])
send.click(chat, [msg, chatbot], [chatbot, chatbot, msg])
clear.click(lambda: None, None, chatbot, queue=False)
gr.Markdown("""
<div style="text-align:center;color:#777;font-size:0.85em;margin-top:8px;">
π‘ λν κΈ°λ‘μ μΈμ
λμ μ μ§λ©λλ€.
Made with β€οΈ by PIXAL
</div>
""")
if __name__ == "__main__":
demo.launch(server_name="0.0.0.0", server_port=7860) |