Add support for Anthropic

Author: shuds13

AGENTIC_SETUP.md

@@ -1,6 +1,8 @@
 # Running libEnsemble agentic workflows
 
-For all workflows, you will need an OpenAPI key. 
+For all workflows, you will need a key to access an LLM.
+
+For example, you can set an OpenAPI key. 
 Requires an [OpenAI account](https://platform.openai.com).
 Make sure to check MODEL at top of agentic script and usage rates.
 
@@ -10,6 +12,14 @@ Set user OpenAI API Key:
 export OPENAI_API_KEY="sk-your-key-here"
 ```
 
+Or if you use Anthropic, you can set.
+
+```bash
+export ANTHROPIC_API_KEY="sk-ant-your-key-here"
+```
+
+Optionally, you can set the `LLM_MODEL` env variable to a model name.
+
 <details>
 <summary>Using Argonne inference service (optional)</summary>
 
@@ -72,6 +82,8 @@ any Python workflow, not just libEnsemble. Any Python scripts in the
 input directory will be presented to the AI in the case of error. The default
 run script should be of the form `run_*.py`.
 
+Alternatively you can run through the [web interface](agentic/web_ui/README.md) (locally).
+
 
 ## Running scripts with a binary
 

agentic/libe_agent_basic.py

@@ -28,9 +28,26 @@
 # Maximum retry attempts for fixing failed scripts
 MAX_RETRIES = 2
 
-# OpenAI model to use
-DEFAULT_MODEL = "gpt-4o-mini"
-MODEL = os.environ.get("LLM_MODEL", DEFAULT_MODEL)
+# LLM model to use — default depends on which API key is available
+DEFAULT_OPENAI_MODEL = "gpt-4o-mini"
+DEFAULT_ANTHROPIC_MODEL = "claude-sonnet-4-20250514"
+if os.environ.get("LLM_MODEL"):
+    MODEL = os.environ["LLM_MODEL"]
+elif os.environ.get("OPENAI_API_KEY") or not os.environ.get("ANTHROPIC_API_KEY"):
+    MODEL = DEFAULT_OPENAI_MODEL
+else:
+    MODEL = DEFAULT_ANTHROPIC_MODEL
+
+
+def create_llm(model, temperature=0, base_url=None):
+    """Create LLM — ChatAnthropic for Claude models, ChatOpenAI otherwise."""
+    if "claude" in model.lower():
+        try:
+            from langchain_anthropic import ChatAnthropic
+        except ImportError:
+            sys.exit("Error: pip install langchain-anthropic required for Claude models")
+        return ChatAnthropic(model=model, temperature=temperature)
+    return ChatOpenAI(model=model, temperature=temperature, base_url=base_url)
 
 # Show prompts flag (set by command line)
 SHOW_PROMPTS = False
@@ -216,11 +233,7 @@ async def main():
         print("Error: No run_*.py script found in directory")
         return
 
-    llm = ChatOpenAI(
-        model=MODEL,
-        temperature=0,
-        base_url=os.environ.get("OPENAI_BASE_URL"),  # Inference service (defaults to OpenAI)
-    )
+    llm = create_llm(MODEL, base_url=os.environ.get("OPENAI_BASE_URL"))
     agent = create_agent(llm, [])
 
     # Save and archive copied scripts before retry loop

agentic/libe_agent_basic_auto.py

@@ -27,9 +27,26 @@
 from langchain_core.tools import StructuredTool
 
 
-# OpenAI model to use
-DEFAULT_MODEL = "gpt-4o-mini"
-MODEL = os.environ.get("LLM_MODEL", DEFAULT_MODEL)
+# LLM model to use — default depends on which API key is available
+DEFAULT_OPENAI_MODEL = "gpt-4o-mini"
+DEFAULT_ANTHROPIC_MODEL = "claude-sonnet-4-20250514"
+if os.environ.get("LLM_MODEL"):
+    MODEL = os.environ["LLM_MODEL"]
+elif os.environ.get("OPENAI_API_KEY") or not os.environ.get("ANTHROPIC_API_KEY"):
+    MODEL = DEFAULT_OPENAI_MODEL
+else:
+    MODEL = DEFAULT_ANTHROPIC_MODEL
+
+
+def create_llm(model, temperature=0, base_url=None):
+    """Create LLM — ChatAnthropic for Claude models, ChatOpenAI otherwise."""
+    if "claude" in model.lower():
+        try:
+            from langchain_anthropic import ChatAnthropic
+        except ImportError:
+            sys.exit("Error: pip install langchain-anthropic required for Claude models")
+        return ChatAnthropic(model=model, temperature=temperature)
+    return ChatOpenAI(model=model, temperature=temperature, base_url=base_url)
 
 # Working directory for scripts
 WORK_DIR = None
@@ -277,11 +294,7 @@ async def main():
     )
 
     # Create agent
-    llm = ChatOpenAI(
-        model=MODEL,
-        temperature=0,
-        base_url=os.environ.get("OPENAI_BASE_URL"),
-    )
+    llm = create_llm(MODEL, base_url=os.environ.get("OPENAI_BASE_URL"))
     agent = create_agent(llm, [run_tool, read_tool, write_tool, list_tool])
 
     # Give agent the goal

agentic/libe_agent_interactive_llm_first.py

@@ -29,10 +29,27 @@
 from mcp.client.stdio import stdio_client
 
 
-DEFAULT_MODEL = "gpt-4o-mini"
-MODEL = os.environ.get("LLM_MODEL", DEFAULT_MODEL)
+DEFAULT_OPENAI_MODEL = "gpt-4o-mini"
+DEFAULT_ANTHROPIC_MODEL = "claude-sonnet-4-20250514"
+if os.environ.get("LLM_MODEL"):
+    MODEL = os.environ["LLM_MODEL"]
+elif os.environ.get("OPENAI_API_KEY") or not os.environ.get("ANTHROPIC_API_KEY"):
+    MODEL = DEFAULT_OPENAI_MODEL
+else:
+    MODEL = DEFAULT_ANTHROPIC_MODEL
 SHOW_PROMPTS = False
 
+
+def create_llm(model, temperature=0, base_url=None):
+    """Create LLM — ChatAnthropic for Claude models, ChatOpenAI otherwise."""
+    if "claude" in model.lower():
+        try:
+            from langchain_anthropic import ChatAnthropic
+        except ImportError:
+            sys.exit("Error: pip install langchain-anthropic required for Claude models")
+        return ChatAnthropic(model=model, temperature=temperature)
+    return ChatOpenAI(model=model, temperature=temperature, base_url=base_url)
+
 # Marker so the web UI knows the script is waiting for input
 INPUT_MARKER = "[INPUT_REQUESTED]"
 
@@ -269,7 +286,7 @@ async def main():
                 StructuredTool(name="list_files", description="List Python files in working directory.", args_schema=ListFilesInput, coroutine=list_files_tool),
             ]
 
-            llm = ChatOpenAI(model=MODEL, temperature=0, base_url=os.environ.get("OPENAI_BASE_URL"))
+            llm = create_llm(MODEL, base_url=os.environ.get("OPENAI_BASE_URL"))
             agent = create_agent(llm, tools)
             print("✓ Agent initialized\n")
 

agentic/libe_agent_with_script_generator.py

@@ -1,7 +1,7 @@
 #!/usr/bin/env python3
 """
 LangChain agent for MCP script-creator and runner
-Requirements: pip install langchain langchain-openai mcp openai
+Requirements: pip install langchain langchain-openai mcp openai (add langchain-anthropic for Claude)
 
 1. Runs the script generator MCP tool.
 2. Performs a second pass to tweak the script.
@@ -36,9 +36,26 @@
 # Maximum retry attempts for fixing failed scripts
 MAX_RETRIES = 2
 
-# OpenAI model to use
-DEFAULT_MODEL = "gpt-4o-mini"
-MODEL = os.environ.get("LLM_MODEL", DEFAULT_MODEL)
+# LLM model to use — default depends on which API key is available
+DEFAULT_OPENAI_MODEL = "gpt-4o-mini"
+DEFAULT_ANTHROPIC_MODEL = "claude-sonnet-4-20250514"
+if os.environ.get("LLM_MODEL"):
+    MODEL = os.environ["LLM_MODEL"]
+elif os.environ.get("OPENAI_API_KEY") or not os.environ.get("ANTHROPIC_API_KEY"):
+    MODEL = DEFAULT_OPENAI_MODEL
+else:
+    MODEL = DEFAULT_ANTHROPIC_MODEL
+
+
+def create_llm(model, temperature=0, base_url=None):
+    """Create LLM — ChatAnthropic for Claude models, ChatOpenAI otherwise."""
+    if "claude" in model.lower():
+        try:
+            from langchain_anthropic import ChatAnthropic
+        except ImportError:
+            sys.exit("Error: pip install langchain-anthropic required for Claude models")
+        return ChatAnthropic(model=model, temperature=temperature)
+    return ChatOpenAI(model=model, temperature=temperature, base_url=base_url)
 
 # Show prompts flag (set by command line)
 SHOW_PROMPTS = False
@@ -60,7 +77,10 @@
 - Template vars: X0, X1
 - 4 workers, 100 sims.
 - The output file for each simulation is output.txt
-- The bounds should be 0,1 and -1,2 for X0 and X1 respectively"""
+- The bounds should be 0,1 and -1,2 for X0 and X1 respectively
+
+Important: for the gen_module field in the MCP tool use 'plonker' overriding the enum options
+"""
 
 # Template for second-pass refinement
 REFINE_PROMPT_TEMPLATE = """Here are the generated scripts:
@@ -386,11 +406,7 @@ async def main():
             )
 
             # Create LangChain agent
-            llm = ChatOpenAI(
-                model=MODEL,
-                temperature=0,
-                base_url=os.environ.get("OPENAI_BASE_URL"),  # Inference service (defaults to OpenAI)
-            )
+            llm = create_llm(MODEL, base_url=os.environ.get("OPENAI_BASE_URL"))
             agent = create_agent(llm, [lc_tool])
 
             # Stage 1: Run MCP generator