ayrisdev/crawl4ai
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

refactor(llm): rename LlmConfig to LLMConfig for consistency

Browse Source 
Rename LlmConfig to LLMConfig across the codebase to follow consistent naming conventions.
Update all imports and usages to use the new name.
Update documentation and examples to reflect the change.

BREAKING CHANGE: LlmConfig has been renamed to LLMConfig. Users need to update their imports and usage.
This commit is contained in:
UncleCode
2025-03-05 14:17:04 +08:00
parent e896c08f9c
commit baee4949d3
33 changed files with 362 additions and 174 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
docs/md_v2/core/quickstart.md
View File

@@ -128,7 +128,7 @@ Crawl4AI can also extract structured data (JSON) using CSS or XPath selectors. B
```python
from crawl4ai.extraction_strategy import JsonCssExtractionStrategy
from crawl4ai.async_configs import LlmConfig
from crawl4ai.types import LLMConfig
# Generate a schema (one-time cost)
html = "<div class='product'><h2>Gaming Laptop</h2><span class='price'>$999.99</span></div>"
@@ -136,13 +136,13 @@ html = "<div class='product'><h2>Gaming Laptop</h2><span class='price'>$999.99</
# Using OpenAI (requires API token)
schema = JsonCssExtractionStrategy.generate_schema(
html,
llmConfig = LlmConfig(provider="openai/gpt-4o",api_token="your-openai-token") # Required for OpenAI
llm_config = LLMConfig(provider="openai/gpt-4o",api_token="your-openai-token") # Required for OpenAI
)
# Or using Ollama (open source, no token needed)
schema = JsonCssExtractionStrategy.generate_schema(
html,
llmConfig = LlmConfig(provider="ollama/llama3.3", api_token=None) # Not needed for Ollama
llm_config = LLMConfig(provider="ollama/llama3.3", api_token=None) # Not needed for Ollama
)
# Use the schema for fast, repeated extractions
@@ -211,7 +211,7 @@ import os
import json
import asyncio
from pydantic import BaseModel, Field
from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, LlmConfig
from crawl4ai import AsyncWebCrawler, CrawlerRunConfig, LLMConfig
from crawl4ai.extraction_strategy import LLMExtractionStrategy
class OpenAIModelFee(BaseModel):
@@ -241,7 +241,7 @@ async def extract_structured_data_using_llm(
word_count_threshold=1,
page_timeout=80000,
extraction_strategy=LLMExtractionStrategy(
llmConfig = LlmConfig(provider=provider,api_token=api_token),
llm_config = LLMConfig(provider=provider,api_token=api_token),
schema=OpenAIModelFee.model_json_schema(),
extraction_type="schema",
instruction="""From the crawled content, extract all mentioned model names along with their fees for input and output tokens.