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Python Examples for Context SDK
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‎examples/python-sdk/README.md‎

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This directory contains examples demonstrating how to use the Augment Python SDK.
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The SDK has two main components:
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1. **Auggie SDK** - An agent-based interface for AI-powered workflows with typed responses, sessions, and function calling
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2. **Context SDK** - Semantic search and AI-powered code analysis via `FileSystemContext` and `DirectContext`
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## Quick Links
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- **[User Examples](user_examples/)** - Numbered tutorial examples (01-09) with a comprehensive [user guide](user_examples/user_guide.md)
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- **[Context Examples](context/)** - Semantic search and AI-powered code analysis examples
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- **[Documentation](docs/)** - Detailed guides on specific features
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- **Basic Examples** - See below for standalone example scripts
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For ClaudeCodeACPClient documentation, see:
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- [Claude Code Client Guide](docs/CLAUDE_CODE_CLIENT.md)
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## Context SDK Examples
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The **[context](context/)** directory contains examples demonstrating the Auggie SDK's context modes for semantic search and AI-powered code analysis:
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- **[Direct Context](context/direct_context/)** - API-based indexing with semantic search and AI Q&A
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- **[FileSystem Context](context/filesystem_context/)** - Local directory search via MCP protocol
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- **[File Search Server](context/file_search_server/)** - REST API for semantic file search with AI summarization
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- **[Prompt Enhancer Server](context/prompt_enhancer_server/)** - HTTP server that enhances prompts with codebase context
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- **[GitHub Action Indexer](context/github_action_indexer/)** - Index GitHub repositories for semantic search
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See the [context README](context/README.md) for prerequisites and detailed usage instructions.
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## Prompt-to-SDK Conversion
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### `example_complex_prompt.txt`

‎examples/python-sdk/context/README.md‎

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# Context Examples
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Examples demonstrating the Auggie SDK's context modes and AI-powered code analysis.
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## Prerequisites
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1. **Python 3.10+** - Required to run the examples
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2. **Auggie CLI** - Required for FileSystem Context examples
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```bash
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npm install -g @augmentcode/auggie@prerelease
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```
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3. **Authentication** - Required for all examples
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```bash
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auggie login
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```
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This creates a session file at `~/.augment/session.json` with your API token.
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Alternatively, you can set environment variables:
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```bash
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export AUGMENT_API_TOKEN=your_token_here
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export AUGMENT_API_URL=https://staging-shard-0.api.augmentcode.com/
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```
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## Examples
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### [Direct Context](./direct_context/)
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API-based indexing with semantic search and AI Q&A.
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**Run it:**
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```bash
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python -m direct_context
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```
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### [FileSystem Context](./filesystem_context/)
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Local directory search via MCP protocol.
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**Important:** The FileSystem Context indexes all files in the workspace directory. To avoid timeouts when indexing large directories (like `node_modules/`), consider adding a `.gitignore` or `.augmentignore` file that excludes them. The auggie CLI respects both `.gitignore` and `.augmentignore` patterns during indexing.
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**Run it:**
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```bash
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python -m filesystem_context
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```
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### [File Search Server](./file_search_server/)
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REST API for semantic file search with AI summarization.
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**Run it:**
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```bash
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python -m file_search_server .
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```
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Then query the API:
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```bash
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curl "http://localhost:3000/search?q=python"
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```
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### [Prompt Enhancer Server](./prompt_enhancer_server/)
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HTTP server that enhances prompts with codebase context.
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**Run it:**
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```bash
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python -m prompt_enhancer_server .
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```
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Then enhance prompts:
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```bash
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curl -X POST http://localhost:3001/enhance \
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-H "Content-Type: application/json" \
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-d '{"prompt": "fix the login bug"}'
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```
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### [GitHub Action Indexer](./github_action_indexer/)
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Index GitHub repositories for semantic search.
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This example has its own requirements.txt and dependencies.
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**Setup:**
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```bash
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pip install -r github_action_indexer/requirements.txt
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```
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**Run it:**
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```bash
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python -m github_action_indexer index
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python -m github_action_indexer search "your query"
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```
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See [github_action_indexer/README.md](./github_action_indexer/README.md) for more details.
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## Troubleshooting
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### MCP Timeout in FileSystem Context
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**Problem:** The FileSystem Context example times out during indexing.
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**Cause:** The workspace directory contains too many files (e.g., `node_modules/` with 45,000+ files).
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**Solution:** Create a `.gitignore` or `.augmentignore` file in the workspace directory to exclude large directories:
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```bash
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# .gitignore or .augmentignore
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node_modules/
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dist/
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*.log
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.DS_Store
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__pycache__/
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*.pyc
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```
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The auggie CLI respects both `.gitignore` and `.augmentignore` patterns and will skip excluded files during indexing.
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### Authentication Errors
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**Problem:** `Error: API key is required for search_and_ask()`
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**Cause:** The SDK cannot find your authentication credentials.
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**Solution:** Run `auggie login` to authenticate, or set the `AUGMENT_API_TOKEN` and `AUGMENT_API_URL` environment variables.
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‎examples/python-sdk/context/direct_context/README.md‎

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# Direct Context Example
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API-based indexing with semantic search, AI Q&A, and state persistence.
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## Usage
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```bash
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# Authenticate
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auggie login
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# Run the example (from the context directory)
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cd examples/python-sdk/context
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python -m direct_context
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# Or run directly
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python direct_context/main.py
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```
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## What It Does
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- Creates a Direct Context instance
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- Adds sample files to the index
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- Performs semantic searches
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- Uses `search_and_ask()` for AI-powered Q&A
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- Generates documentation
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- Exports/imports context state
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## Key Features
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- **`search()`**: Semantic search returning formatted code snippets
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- **`search_and_ask()`**: One-step AI Q&A about indexed code
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- **State persistence**: Export/import index for reuse
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‎examples/python-sdk/context/direct_context/__init__.py‎

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# direct_context package
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‎examples/python-sdk/context/direct_context/__main__.py‎

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"""Allow running as: python -m direct_context"""
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from .main import main
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main()
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‎examples/python-sdk/context/direct_context/main.py‎

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"""
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Sample: Direct Context - API-based indexing with import/export state
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This sample demonstrates:
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- Creating a Direct Context instance
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- Adding files to the index
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- Searching the indexed files
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- Using Generation API to ask questions about indexed code
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- Generating documentation from indexed code
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- Exporting state to a file
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- Importing state from a file
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"""
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import json
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import sys
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import tempfile
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from pathlib import Path
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from auggie_sdk.context import DirectContext, File
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# Sample files are in the samples/ subdirectory
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SAMPLES_DIR = Path(__file__).parent / "samples"
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def load_sample_files() -> list[File]:
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"""Load sample Python files from the samples directory."""
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files = []
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for file_path in SAMPLES_DIR.rglob("*.py"):
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relative_path = file_path.relative_to(SAMPLES_DIR)
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contents = file_path.read_text()
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files.append(File(path=str(relative_path), contents=contents))
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return files
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def main():
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print("=== Direct Context Sample ===\n")
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# Create a Direct Context instance
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# Authentication is automatic via:
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# 1. AUGMENT_API_TOKEN / AUGMENT_API_URL env vars, or
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# 2. ~/.augment/session.json (created by `auggie login`)
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print("Creating Direct Context...")
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context = DirectContext.create(debug=True)
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# Load sample files from the samples/ directory
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print("\nAdding files to index...")
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file_objects = load_sample_files()
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print(f" Found {len(file_objects)} sample files")
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result = context.add_to_index(file_objects)
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print("\nIndexing result:")
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print(f" Newly uploaded: {result.newly_uploaded}")
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print(f" Already uploaded: {result.already_uploaded}")
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# Search the codebase - returns formatted string ready for LLM use or display
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# Using queries that work well with our realistic content
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print("\n--- Search 1: Find string utility functions ---")
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results1 = context.search("string utility functions for text formatting")
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print("Search results:")
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print(results1)
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print("\n--- Search 2: Find user management service ---")
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results2 = context.search("user management service with CRUD operations")
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print("Search results:")
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print(results2)
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print("\n--- Search 3: Find HTTP client for API requests ---")
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http_results = context.search("HTTP client for making API requests")
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print("Search results:")
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print(http_results)
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# Use search_and_ask to ask questions about the indexed code
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print("\n--- search_and_ask Example 1: Ask questions about the code ---")
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question = "How does the UserService class handle user creation and validation?"
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print(f"Question: {question}")
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answer = context.search_and_ask(
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"user creation and validation in UserService",
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question,
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)
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print(f"\nAnswer: {answer}")
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# Use search_and_ask to generate documentation
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print("\n--- search_and_ask Example 2: Generate documentation ---")
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documentation = context.search_and_ask(
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"string utility functions",
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"Generate API documentation in markdown format for the string utility functions",
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)
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print("\nGenerated Documentation:")
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print(documentation)
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# Use search_and_ask to explain code patterns
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print("\n--- search_and_ask Example 3: Explain code patterns ---")
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explanation = context.search_and_ask(
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"utility functions",
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"Explain what these utility functions do and when they would be useful",
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)
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print(f"\nExplanation: {explanation}")
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# Export state to a file
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state_file = Path(tempfile.gettempdir()) / "direct-context-state.json"
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print(f"\nExporting state to {state_file}...")
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context.export_to_file(state_file)
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print("State exported successfully")
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# Show the exported state
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with open(state_file, "r") as f:
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exported_state = json.load(f)
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print("\nExported state:")
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print(json.dumps(exported_state, indent=2))
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# Import state in a new context
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print("\n--- Testing state import ---")
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context2 = DirectContext.import_from_file(state_file, debug=False)
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print("State imported successfully")
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# Verify we can still search
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results3 = context2.search("string utility functions")
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print("\nSearch after importing state:")
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print(results3)
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print("\n=== Sample Complete ===")
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if __name__ == "__main__":
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try:
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main()
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except Exception as error:
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print(f"Error: {error}")
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sys.exit(1)
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