Merge pull request #18 from heiko-braun/remove_assistant_api

Remove legacy implementation

README.md

@@ -32,7 +32,6 @@ export OPENAI_API_KEY="..."
 export QDRANT_KEY="..."
 export QDRANT_URL="..."
 export PG_URL="..."
-export ASSISTANT_ID="..." (used with legacy impl)
 ```
 
 For the slack bot, you also need these:
@@ -76,10 +75,17 @@ Once the process completes, you should have a meta data and vector embeddings in
 
 ## Using the assistant
 
+Web based:
+
 ```
 streamlit run agent-ui.py
 ```
 
+CLI based:
+
+```
+python agent-cli.py [-f QUESTION.txt]
+```
 [...]
 
 #### Results

agent-cli.py

@@ -0,0 +1,148 @@
+import sys
+
+from prompt_toolkit import PromptSession
+from prompt_toolkit.completion import WordCompleter
+from prompt_toolkit.lexers import PygmentsLexer
+from prompt_toolkit.styles import Style
+
+from langchain.agents.openai_functions_agent.agent_token_buffer_memory import (
+    AgentTokenBufferMemory,
+)
+
+from langchain.callbacks.base import AsyncCallbackHandler
+from langchain.schema import LLMResult
+from langchain_core.messages import BaseMessage
+from uuid import UUID
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Sequence, TypeVar, Union
+
+from core.costs import TokenCostProcess, CostCalcAsyncHandler
+
+from core.agent import agent_executor, agent_llm
+
+import argparse
+
+# ---
+
+style = Style.from_dict(
+    {
+        "completion-menu.completion": "bg:#008888 #ffffff",
+        "completion-menu.completion.current": "bg:#00aaaa #000000",
+        "scrollbar.background": "bg:#88aaaa",
+        "scrollbar.button": "bg:#222222",
+    }
+)
+
+class CLIAsyncHandler(AsyncCallbackHandler):
+
+    def on_llm_start( self, serialized: Dict[str, Any], prompts: List[str], **kwargs: Any) -> None:        
+        pass
+
+    async def on_llm_new_token(self, token: str, **kwargs) -> None:
+      pass
+
+    def on_llm_end(self, response: LLMResult, **kwargs: Any) -> None:      
+      pass
+
+    async def on_tool_start(
+        self,
+        serialized: Dict[str, Any],
+        input_str: str,
+        *,
+        run_id: UUID,
+        parent_run_id: Optional[UUID] = None,
+        tags: Optional[List[str]] = None,
+        metadata: Optional[Dict[str, Any]] = None,
+        **kwargs: Any,
+    ) -> None:
+        """Run when tool starts running."""
+        tool_name = serialized["name"]
+        print(f"{tool_name} : {input_str}")                
+
+    async def on_tool_end(
+        self,
+        output: str,
+        color: Optional[str] = None,
+        observation_prefix: Optional[str] = None,
+        llm_prefix: Optional[str] = None,
+        **kwargs: Any,
+    ) -> None:        
+        pass
+
+    async def on_chat_model_start(
+        self,
+        serialized: Dict[str, Any],
+        messages: List[List[BaseMessage]],
+        *,
+        run_id: UUID,
+        parent_run_id: Optional[UUID] = None,
+        tags: Optional[List[str]] = None,
+        metadata: Optional[Dict[str, Any]] = None,
+        **kwargs: Any,
+    ) -> Any:
+        """Run when a chat model starts running."""
+        print("Thinking ...")
+
+
+def main(args):
+
+    memory = AgentTokenBufferMemory(llm=agent_llm)
+
+    session = PromptSession(
+        lexer=None, completer=None, style=style
+    )
+
+    if(args.filename == None):
+
+        # enter QA loop
+
+        print("How can I help you?")
+
+        while True:
+            try:            
+                prompt_text = session.prompt("> ")
+            except KeyboardInterrupt:
+                continue  # Control-C pressed. Try again.
+            except EOFError:
+                break  # Control-D pressed.
+
+            # request chat completion
+            try:
+                response_handle = agent_executor(
+                    {"input": prompt_text, "history": memory.buffer},
+                    callbacks=[CLIAsyncHandler()],
+                    include_run_info=True,
+                )
+
+                memory.save_context({"input": prompt_text}, response_handle)
+
+                print(f"\n{response_handle['output']}")
+
+            except Exception as e:
+                print("Failed to call Openai API: ", str(e))                
+
+        print("GoodBye!")
+
+    else:
+
+        # enter one-shot prompting from file
+
+        with open(args.filename) as f:
+            prompt = f.read()        
+        prompt_text = prompt.replace('\n', ' ').replace('\r', '')        
+
+        response_handle = agent_executor(
+                {"input": prompt_text, "history": []},
+                callbacks=[CLIAsyncHandler()],
+                include_run_info=True,
+            )
+
+        print(f"\n{response_handle['output']}")
+
+
+
+if __name__ == "__main__":    
+    parser = argparse.ArgumentParser(description='Camel Quickstart Assistant')
+    parser.add_argument('-f', '--filename', help='The input file that will be taken as a prompt', required=False)
+    args = parser.parse_args()
+
+    main(args)