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update extract_content action for BrowserUseTool

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This commit is contained in:
liangxinbing 2025-03-19 13:27:08 +08:00
parent 402355533c
commit b7dcbfecb3
1 changed files with 48 additions and 14 deletions
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62
app/tool/browser_use_tool.py
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@ -418,17 +418,7 @@ class BrowserUseTool(BaseTool, Generic[Context]):
# Create prompt for LLM
prompt_text = """
Your task is to extract the content of the page. You will be given a page and a goal, and you should extract all relevant information around this goal from the page.
Examples of extraction goals:
- Extract all company names
- Extract specific descriptions
- Extract all information about a topic
- Extract links with companies in structured format
- Extract all links
If the goal is vague, summarize the page. Respond in JSON format.
Your task is to extract the content of the page. You will be given a page and a goal, and you should extract all relevant information around this goal from the page. If the goal is vague, summarize the page. Respond in json format.
Extraction goal: {goal}
Page content:
@ -445,10 +435,54 @@ Page content:
messages = [Message.user_message(formatted_prompt)]
# Use LLM to extract content based on the goal
response = await self.llm.ask(messages)
# Define extraction function for the tool
extraction_function = {
"type": "function",
"function": {
"name": "extract_content",
"description": "Extract specific information from a webpage based on a goal",
"parameters": {
"type": "object",
"properties": {
"extracted_content": {
"type": "object",
"description": "The content extracted from the page according to the goal",
}
},
"required": ["extracted_content"],
},
},
}
# Use LLM to extract content with required function calling
response = await self.llm.ask_tool(
messages,
tools=[extraction_function],
tool_choice="required",
)
# Extract content from function call response
if (
response
and response.tool_calls
and len(response.tool_calls) > 0
):
# Get the first tool call arguments
tool_call = response.tool_calls[0]
# Parse the JSON arguments
try:
args = json.loads(tool_call.function.arguments)
extracted_content = args.get("extracted_content", {})
# Format extracted content as JSON string
content_json = json.dumps(
extracted_content, indent=2, ensure_ascii=False
)
msg = f"Extracted from page:\n{content_json}\n"
except Exception as e:
msg = f"Error parsing extraction result: {str(e)}\nRaw response: {tool_call.function.arguments}"
else:
msg = "No content was extracted from the page."
msg = f"Extracted from page:\n{response}\n"
return ToolResult(output=msg)
except Exception as e:
# Provide a more helpful error message