docs: langchain + modal examples

.pre-commit-config.yaml

@@ -72,7 +72,7 @@ repos:
       - id: deptry
         pass_filenames: false
         always_run: true
-        entry: bash -c "uv run --frozen --all-extras --dev deptry src --ignore DEP001"
+        entry: bash -c "uv run --frozen --all-extras --dev deptry src --ignore DEP001 --extend-exclude 'codegen-examples/.*'"
 
   - repo: https://github.com/renovatebot/pre-commit-hooks
     rev: 39.164.1

codegen-examples/examples/langchain_agent/README.md

@@ -0,0 +1,82 @@
+# Codegen LangChain Agent Example
+
+<p align="center">
+  <a href="https://docs.codegen.com/tutorials/build-code-agent">
+    <img src="https://i.imgur.com/6RF9W0z.jpeg" />
+  </a>
+</p>
+
+<h2 align="center">
+  Build an intelligent code agent with LangChain and Codegen
+</h2>
+
+<div align="center">
+
+[![Documentation](https://img.shields.io/badge/Docs-docs.codegen.com-purple?style=flat-square)](https://docs.codegen.com/tutorials/build-code-agent)
+[![License](https://img.shields.io/badge/Code%20License-Apache%202.0-gray?&color=gray)](https://github.com/codegen-sh/codegen-sdk/tree/develop?tab=Apache-2.0-1-ov-file)
+
+</div>
+
+This example demonstrates how to build an intelligent code agent using Codegen's LangChain integration. The agent can analyze and manipulate codebases using natural language commands.
+
+## Quick Start
+
+```python
+from codegen import Codebase
+from codegen.extensions.langchain import create_codebase_agent
+
+# Initialize codebase
+codebase = Codebase.from_repo("fastapi/fastapi")
+
+# Create the agent
+agent = create_codebase_agent(codebase=codebase, model_name="gpt-4", verbose=True)
+
+# Ask the agent to analyze code
+result = agent.invoke({"input": "What are the dependencies of the FastAPI class?", "config": {"configurable": {"session_id": "demo"}}})
+print(result["output"])
+```
+
+## Installation
+
+```bash
+# Install dependencies
+pip install modal-client codegen langchain langchain-openai
+
+# Run the example
+python run.py
+```
+
+## Available Tools
+
+The agent comes with several built-in tools for code operations:
+
+- `ViewFileTool`: View file contents and metadata
+- `ListDirectoryTool`: List directory contents
+- `SearchTool`: Search code using regex
+- `EditFileTool`: Edit file contents
+- `CreateFileTool`: Create new files
+- `DeleteFileTool`: Delete files
+- `RenameFileTool`: Rename files and update imports
+- `MoveSymbolTool`: Move functions/classes between files
+- `RevealSymbolTool`: Analyze symbol dependencies
+- `SemanticEditTool`: Make semantic code edits
+- `CommitTool`: Commit changes to disk
+
+## Example Operations
+
+The agent can perform various code analysis and manipulation tasks:
+
+```python
+# Analyze dependencies
+agent.invoke({"input": "What are the dependencies of the reveal_symbol function?", "config": {"configurable": {"session_id": "demo"}}})
+
+# Find usage patterns
+agent.invoke({"input": "Show me examples of dependency injection in the codebase", "config": {"configurable": {"session_id": "demo"}}})
+
+# Move code
+agent.invoke({"input": "Move the validate_email function to validation_utils.py", "config": {"configurable": {"session_id": "demo"}}})
+```
+
+## Learn More
+
+- [Full Tutorial](https://docs.codegen.com/tutorials/build-code-agent)

codegen-examples/examples/langchain_agent/run.py

@@ -0,0 +1,107 @@
+"""Demo implementation of an agent with Codegen tools."""
+
+from codegen import Codebase
+from codegen.extensions.langchain.tools import (
+    CommitTool,
+    CreateFileTool,
+    DeleteFileTool,
+    EditFileTool,
+    ListDirectoryTool,
+    MoveSymbolTool,
+    RenameFileTool,
+    RevealSymbolTool,
+    SearchTool,
+    SemanticEditTool,
+    ViewFileTool,
+)
+from codegen.sdk.enums import ProgrammingLanguage
+from langchain import hub
+from langchain.agents import AgentExecutor
+from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
+from langchain_core.chat_history import ChatMessageHistory
+from langchain_core.runnables.history import RunnableWithMessageHistory
+from langchain_openai import ChatOpenAI
+
+
+def create_codebase_agent(
+    codebase: Codebase,
+    model_name: str = "gpt-4o",
+    temperature: float = 0,
+    verbose: bool = True,
+) -> RunnableWithMessageHistory:
+    """Create an agent with all codebase tools.
+
+    Args:
+        codebase: The codebase to operate on
+        model_name: Name of the model to use (default: gpt-4)
+        temperature: Model temperature (default: 0)
+        verbose: Whether to print agent's thought process (default: True)
+
+    Returns:
+        Initialized agent with message history
+    """
+    # Initialize language model
+    llm = ChatOpenAI(
+        model_name=model_name,
+        temperature=temperature,
+    )
+
+    # Get all codebase tools
+    tools = [
+        ViewFileTool(codebase),
+        ListDirectoryTool(codebase),
+        SearchTool(codebase),
+        EditFileTool(codebase),
+        CreateFileTool(codebase),
+        DeleteFileTool(codebase),
+        RenameFileTool(codebase),
+        MoveSymbolTool(codebase),
+        RevealSymbolTool(codebase),
+        SemanticEditTool(codebase),
+        CommitTool(codebase),
+    ]
+
+    # Get the prompt to use
+    prompt = hub.pull("hwchase17/openai-functions-agent")
+
+    # Create the agent
+    agent = OpenAIFunctionsAgent(
+        llm=llm,
+        tools=tools,
+        prompt=prompt,
+    )
+
+    # Create the agent executor
+    agent_executor = AgentExecutor(
+        agent=agent,
+        tools=tools,
+        verbose=verbose,
+    )
+
+    # Create message history handler
+    message_history = ChatMessageHistory()
+
+    # Wrap with message history
+    return RunnableWithMessageHistory(
+        agent_executor,
+        lambda session_id: message_history,
+        input_messages_key="input",
+        history_messages_key="chat_history",
+    )
+
+
+if __name__ == "__main__":
+    # Initialize codebase
+    print("Initializing codebase...")
+    codebase = Codebase.from_repo("fastapi/fastapi", programming_language=ProgrammingLanguage.PYTHON)
+
+    # Create agent with history
+    print("Creating agent...")
+    agent = create_codebase_agent(codebase)
+
+    print("\nAsking agent to analyze symbol relationships...")
+    result = agent.invoke(
+        {"input": "What are the dependencies of the reveal_symbol function?"},
+        config={"configurable": {"session_id": "demo"}},
+    )
+    print("Messages:", result["messages"])

pyproject.toml

@@ -151,6 +151,7 @@ dev-dependencies = [
   "loguru>=0.7.3",
   "httpx<0.28.2,>=0.28.1",
   "jupyterlab>=4.3.5",
+  "modal>=0.73.25",
 ]
 
 

src/codegen/extensions/langchain/agent.py

@@ -3,12 +3,11 @@
 from langchain import hub
 from langchain.agents import AgentExecutor
 from langchain.agents.openai_functions_agent.base import OpenAIFunctionsAgent
 from langchain_core.chat_history import ChatMessageHistory
 from langchain_core.runnables.history import RunnableWithMessageHistory
 from langchain_openai import ChatOpenAI
 
 from codegen import Codebase
-from codegen.sdk.enums import ProgrammingLanguage
 
 from .tools import (
     CommitTool,
@@ -27,7 +26,7 @@
 
 def create_codebase_agent(
     codebase: Codebase,
-    model_name: str = "gpt-4",
+    model_name: str = "gpt-4o",
     temperature: float = 0,
     verbose: bool = True,
 ) -> RunnableWithMessageHistory:
@@ -85,25 +84,8 @@
 
     # Wrap with message history
     return RunnableWithMessageHistory(
         agent_executor,
         lambda session_id: message_history,
         input_messages_key="input",
         history_messages_key="chat_history",
     )
-
-
-if __name__ == "__main__":
-    # Initialize codebase
-    print("Initializing codebase...")
-    codebase = Codebase.from_repo("fastapi/fastapi", programming_language=ProgrammingLanguage.PYTHON)
-
-    # Create agent with history
-    print("Creating agent...")
-    agent = create_codebase_agent(codebase)
-
-    print("\nAsking agent to analyze symbol relationships...")
-    result = agent.invoke(
-        {"input": "What are the dependencies of the reveal_symbol function?"},
-        config={"configurable": {"session_id": "demo"}},
-    )
-    print("Messages:", result["messages"])