added langroid instructions and script

Author: pchalasani

langroid-llm-agents/README.md

@@ -0,0 +1,54 @@
+### Langroid + Groq
+[Langroid](https://github.com/langroid/langroid) is an
+open-source Python framework that simplifies building LLM applications, 
+using a Multi-Agent paradigm.
+
+You can now use Langroid with Groq, by setting the model name to 
+`groq/<model>`, e.g., `groq/llama3-70b-8192`.
+
+To get started, create a virtual environment using Python 3.11: 
+
+
+```bash
+python3 -m venv .venv
+. ./.venv/bin/activate
+pip install --upgrade langroid
+````
+Place your `GROQ_API_KEY` in a `.env` file in the root directory of this project,
+it should have a line that looks like:
+```
+GROQ_API_KEY=gsk_...
+```
+Or you can set explicitly set this key in your environment before 
+running the scripts.
+
+```bash
+Below is a bare-bones code example.
+
+```python
+import langroid as lr
+import langroid.language_models as lm
+
+llm_config = lm.OpenAIGPTConfig(
+ chat_model="groq/llama3-70b-8192",
+ chat_context_length=8192,
+)
+
+llm = lm.OpenAIGPT(llm_config)
+
+llm.chat("3+4=?").message
+
+agent_config = lr.ChatAgentConfig(
+ llm=llm_config,
+ system_message="""Be nice but concise""",
+)
+
+agent = lr.ChatAgent(agent_config)
+task = lr.Task(agent, interactive=True)
+```
+
+An example script showing a 2-agent assistant is included in this folder.
+The langroid repo has numerous example scripts as well, and you can run them 
+against a groq-hosted LLM by changing `chat_model` to `groq/llama3-70b-8192` (as an 
+example). Many of the scripts also take a command-line argument `-m` to specify the 
+model, e.g. `-m groq/llama3-70b-8192`.

langroid-llm-agents/search-assistant.py

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+"""
+2-Agent system where:
+- Assistant takes user's (complex) question, breaks it down into smaller pieces
+ if needed
+- WebSearcher takes Assistant's question, uses the Search tool to search the web
+ (using DuckDuckGo), and returns a coherent answer to the Assistant.
+
+Once the Assistant thinks it has enough info to answer the user's question, it
+says DONE and presents the answer to the user.
+
+Run like this:
+
+python3 search-assistant.py
+"""
+
+from dotenv import load_dotenv
+from rich import print
+from rich.prompt import Prompt
+from fire import Fire
+import langroid as lr
+import langroid.language_models as lm
+from langroid.agent.tools.duckduckgo_search_tool import DuckduckgoSearchTool
+
+MODEL = "groq/llama3-70b-8192"
+
+def main() -> None:
+ print(
+ """
+ [blue]Welcome to the Web Search Assistant chatbot!
+ I will try to answer your complex questions. 
+ 
+ Enter x or q to quit at any point.
+ """
+ )
+ load_dotenv()
+
+ llm_config = lm.OpenAIGPTConfig(
+ chat_model=MODEL, # or lr.OpenAIChatModel.GPT4_TURBO
+ chat_context_length=8192,
+ temperature=0,
+ max_output_tokens=200,
+ timeout=45,
+ )
+
+ assistant_config = lr.ChatAgentConfig(
+ system_message="""
+ You are a resourceful assistant, able to think step by step to answer
+ complex questions from the user. You must break down complex questions into
+ simpler questions that can be answered by a web search. You must ask me 
+ (the user) each question ONE BY ONE, and I will do a web search and send you
+ a brief answer. Once you have enough information to answer my original
+ (complex) question, you MUST say DONE and present the answer to me.
+ """,
+ llm=llm_config,
+ vecdb=None,
+ )
+ assistant_agent = lr.ChatAgent(assistant_config)
+ search_tool_handler_method = DuckduckgoSearchTool.default_value("request")
+
+ search_agent_config = lr.ChatAgentConfig(
+ llm=llm_config,
+ vecdb=None,
+ system_message=f"""
+ You are a web-searcher. For any question you get, you must use the
+ `{search_tool_handler_method}` tool/function-call to get up to 5 results.
+ I WILL SEND YOU THE RESULTS; DO NOT MAKE UP THE RESULTS!!
+ Once you receive the results, you must compose a CONCISE answer 
+ based on the search results and say DONE and show the answer to me,
+ in this format:
+ DONE [... your CONCISE answer here ...]
+ IMPORTANT: YOU MUST WAIT FOR ME TO SEND YOU THE 
+ SEARCH RESULTS BEFORE saying you're DONE.
+ """,
+ )
+ search_agent = lr.ChatAgent(search_agent_config)
+ search_agent.enable_message(DuckduckgoSearchTool)
+
+ assistant_task = lr.Task(
+ assistant_agent,
+ name="Assistant",
+ llm_delegate=True,
+ single_round=False,
+ interactive=False,
+ )
+ search_task = lr.Task(
+ search_agent,
+ name="Searcher",
+ llm_delegate=True,
+ single_round=False,
+ interactive=False,
+ )
+ assistant_task.add_sub_task(search_task)
+ question = Prompt.ask("What do you want to know?")
+ assistant_task.run(question)
+
+
+if __name__ == "__main__":
+ Fire(main)