run throught pipeline (InternLM#4)

Co-authored-by: liujiangning <[email protected]>

Author: Harold-lkk

app.py

@@ -13,8 +13,6 @@
 
 from src.agent import init_agent
 
-# agent = os.environ.get('agent_cfg', dict())
-
 app = FastAPI(docs_url='/')
 
 app.add_middleware(CORSMiddleware,
@@ -95,10 +93,10 @@ async def async_generator_wrapper():
             # yield f'data: {response_json}\n\n'
 
     inputs = request.inputs
-    agent = init_agent(request.agent_cfg)
+    agent = init_agent(**request.agent_cfg)
     return EventSourceResponse(generate())
 
 
 if __name__ == '__main__':
     import uvicorn
-    uvicorn.run(app, host='0.0.0.0', port=8090, log_level='info')
+    uvicorn.run(app, host='0.0.0.0', port=8002, log_level='info')

src/agent/__init__.py

@@ -2,48 +2,48 @@
 from datetime import datetime
 
 from lagent.actions import ActionExecutor, BingBrowser
-from lagent.llms import LMDeployPipeline
 
-from .mindsearch_agent import MindSearchAgent, MindSearchProtocol
-from .mindsearch_prompt import (FINAL_RESPONSE_CN, GRAPH_PROMPT_CN,
-                                searcher_context_template_cn,
-                                searcher_input_template_cn,
-                                searcher_system_prompt_cn)
+import src.agent.models as llm_factory
+from src.agent.mindsearch_agent import MindSearchAgent, MindSearchProtocol
+from src.agent.mindsearch_prompt import (
+    FINAL_RESPONSE_CN, FINAL_RESPONSE_EN, GRAPH_PROMPT_CN, GRAPH_PROMPT_EN,
+    searcher_context_template_cn, searcher_context_template_en,
+    searcher_input_template_cn, searcher_input_template_en,
+    searcher_system_prompt_cn, searcher_system_prompt_en)
 
-llm = LMDeployPipeline(path='internlm/internlm2_5-7b',
-                       model_name='internlm2',
-                       meta_template=[
-                           dict(role='system', api_role='system'),
-                           dict(role='user', api_role='user'),
-                           dict(role='assistant', api_role='assistant'),
-                           dict(role='environment', api_role='environment')
-                       ],
-                       top_p=0.8,
-                       top_k=1,
-                       temperature=0,
-                       max_new_tokens=8192,
-                       repetition_penalty=1.02,
-                       stop_words=['<|im_end|>'])
+LLM = {}
 
 
-def init_agent(lang='cn', model_format='pipeline'):
+def init_agent(lang='cn', model_format='internlm_server'):
+    llm = LLM.get(model_format, None)
+    if llm is None:
+        llm_cfg = getattr(llm_factory, model_format)
+        if llm_cfg is None:
+            raise NotImplementedError
+        llm = llm_cfg.pop('type')(**llm_cfg)
+        LLM[model_format] = llm
 
     agent = MindSearchAgent(
         llm=llm,
         protocol=MindSearchProtocol(meta_prompt=datetime.now().strftime(
             'The current date is %Y-%m-%d.'),
-                                    interpreter_prompt=GRAPH_PROMPT_CN,
-                                    response_prompt=FINAL_RESPONSE_CN),
+                                    interpreter_prompt=GRAPH_PROMPT_CN
+                                    if lang == 'cn' else GRAPH_PROMPT_EN,
+                                    response_prompt=FINAL_RESPONSE_CN
+                                    if lang == 'cn' else FINAL_RESPONSE_EN),
         searcher_cfg=dict(
             llm=llm,
-            plugin=ActionExecutor(
+            plugin_executor=ActionExecutor(
                 BingBrowser(
                     api_key=os.environ.get('BING_API_KEY', 'YOUR_BING_API'))),
             protocol=MindSearchProtocol(
                 meta_prompt=datetime.now().strftime(
                     'The current date is %Y-%m-%d.'),
-                plugin_prompt=searcher_system_prompt_cn,
+                plugin_prompt=searcher_system_prompt_cn
+                if lang == 'cn' else searcher_system_prompt_en,
             ),
-            template=dict(input=searcher_input_template_cn,
-                          context=searcher_context_template_cn)))
+            template=dict(input=searcher_input_template_cn
+                          if lang == 'cn' else searcher_input_template_en,
+                          context=searcher_context_template_cn
+                          if lang == 'cn' else searcher_context_template_en)))
     return agent

src/agent/mindsearch_agent.py

@@ -322,8 +322,7 @@ def _generate_reference(self, agent_return, code, as_dict):
     def execute_code(self, command: str):
 
         def extract_code(text: str) -> str:
-            text = re.sub(r'from ([\w.]+) import',
-                          'from lagent.agents.mindsearch_agent import', text)
+            text = re.sub(r'from ([\w.]+) import WebSearchGraph', '', text)
             triple_match = re.search(r'```[^\n]*\n(.+?)```', text, re.DOTALL)
             single_match = re.search(r'`([^`]*)`', text, re.DOTALL)
             if triple_match:

src/agent/models.py

@@ -0,0 +1,29 @@
+import os
+
+from lagent.llms import GPTAPI, INTERNLM2_META, LMDeployClient, LMDeployServer
+
+internlm_server = dict(type=LMDeployServer,
+                       path='internlm/internlm2_5-7b',
+                       model_name='internlm2',
+                       meta_template=INTERNLM2_META,
+                       top_p=0.8,
+                       top_k=1,
+                       temperature=0,
+                       max_new_tokens=8192,
+                       repetition_penalty=1.02,
+                       stop_words=['<|im_end|>'])
+
+internlm_client = dict(type=LMDeployClient,
+                       model_name='internlm2_5-7b',
+                       url='http://127.0.0.1:23333',
+                       meta_template=INTERNLM2_META,
+                       top_p=0.8,
+                       top_k=1,
+                       temperature=0,
+                       max_new_tokens=8192,
+                       repetition_penalty=1.02,
+                       stop_words=['<|im_end|>'])
+
+gpt4 = dict(type=GPTAPI,
+            model_type='gpt-4-turbo',
+            key=os.environ.get('OPENAI_API_KEY', 'YOUR OPENAI API KEY'))