General
PromptBeginner5 minmarkdown
tool_calls=json.dumps(result[tool_calls]
indent=2)
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General
PromptBeginner5 minmarkdown
def parse_headers(header_list: list[str]) -> dict[str
str]:
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General
PromptBeginner5 minmarkdown
for i
(qa_pair
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General
PromptBeginner5 minmarkdown
for i
qa_pair in enumerate(qa_pairs):
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Productivity
PromptBeginner5 minmarkdown
result = await evaluate_single_task(client
model
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General
PromptBeginner5 minmarkdown
response
tool_metrics = await agent_loop(client
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General
PromptBeginner5 minmarkdown
) -> dict[str
Any]:
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General
PromptBeginner5 minmarkdown
qa_pair: dict[str
Any]
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General
PromptBeginner5 minmarkdown
tools: list[dict[str
Any]]
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General
PromptBeginner5 minmarkdown
return response_text
tool_metrics
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General
PromptBeginner5 minmarkdown
tool_result = await connection.call_tool(tool_name
tool_input)
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General
PromptBeginner5 minmarkdown
tool_metrics[tool_name] = {count: 0
durations: []}
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General
PromptBeginner5 minmarkdown
tool_response = json.dumps(tool_result) if isinstance(tool_result
(dict
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General
PromptBeginner5 minmarkdown
) -> tuple[str
dict[str
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General
PromptBeginner5 minmarkdown
tools: list[dict[str
Any]]
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General
PromptBeginner5 minmarkdown
matches = re.findall(pattern
text
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General
PromptBeginner5 minmarkdown
def parse_evaluation_file(file_path: Path) -> list[dict[str
Any]]:
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General
PromptBeginner5 minmarkdown
- For IDs
provide just the ID
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General
PromptBeginner5 minmarkdown
- For names or text
provide the exact text requested
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General
PromptBeginner5 minmarkdown
- In your <feedback> tags
provide constructive feedback on the tools:
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General
PromptBeginner5 minmarkdown
- Which tools you used
in what order
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General
PromptBeginner5 minmarkdown
- For numeric responses
provide just the number
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General
PromptBeginner5 minmarkdown
3. Provide feedback on the tools provided
wrapped in <feedback> tags
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General
PromptBeginner5 minmarkdown
4. Provide your final response
wrapped in <response> tags
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