adjust prompt and feishu message style

This commit is contained in:
2026-03-06 15:47:35 +08:00
parent d63aa74721
commit 40f0d7078b
2 changed files with 194 additions and 238 deletions

View File

@@ -7,7 +7,7 @@ from app.config import get_settings
import json import json
from openai import OpenAI from openai import OpenAI
from app.message import send_requirement_result, send_test_cases, send_message_to_feishu, send_generate_code from app.message import send_requirement_result, send_test_cases, send_message_to_feishu, send_generate_code, send_workflow_start
from app.models import RequirementAnalysis, TestCaseResult, CodeGenerationResult from app.models import RequirementAnalysis, TestCaseResult, CodeGenerationResult
# 初始化日志 # 初始化日志
@@ -58,10 +58,12 @@ class PMAgent:
response = self.client.chat.completions.create( response = self.client.chat.completions.create(
model=self.settings.model, model=self.settings.model,
messages=[ messages=[
{"role": "system", "content": "你是一个资深的产品经理,擅长需求分析和拆解,输出必须是严格的 JSON 格式。"},
{"role": "user", "content": prompt} {"role": "user", "content": prompt}
], ],
temperature=0.7, temperature=0.2,
max_tokens=2000 max_tokens=2000,
response_format={"type": "json_object"}
) )
# 提取响应内容 # 提取响应内容
@@ -117,7 +119,7 @@ class QAAgent:
{requirement_analysis["summary"]} {requirement_analysis["summary"]}
""" """
prompt = f"""你是一个资深的QA工程师。根据以下需求信息生成全面的测试用例和测试策略。 prompt = f"""你是一个资深的Java QA工程师。根据以下需求信息生成全面的Java测试用例和测试策略。所有测试用例必须基于Java语言步骤和预期结果要符合Java的类型系统、异常机制和JUnit测试框架。
{requirement_text} {requirement_text}
@@ -130,7 +132,7 @@ class QAAgent:
"precondition": "前置条件", "precondition": "前置条件",
"steps": ["步骤1", "步骤2", ...], "steps": ["步骤1", "步骤2", ...],
"expected_result": "预期结果", "expected_result": "预期结果",
"test_type": "功能测试|性能测试|安全测试" "test_type": "必须从以下值中选择一个:功能测试性能测试安全测试"
}}, }},
... ...
], ],
@@ -143,17 +145,21 @@ class QAAgent:
2. 为每个边缘情况生成1个测试用例 2. 为每个边缘情况生成1个测试用例
3. 生成至少1个性能测试用例 3. 生成至少1个性能测试用例
4. 生成至少1个安全测试用例 4. 生成至少1个安全测试用例
5. 测试用例要包含明确的步骤和预期结果 5. 测试用例要包含明确的步骤和预期结果步骤和预期结果必须符合Java语言特性不要出现Python或其他语言的描述
6. 步骤和预期结果必须用自然语言描述,不得包含任何代码片段或代码块,不要出现 ```、assert、assertEquals 等代码语法
7. 测试策略不要出现JUnit或者Java这种字眼应该是针对需求的测试方法论和思路描述覆盖计划要说明如何确保测试覆盖所有功能和边界情况
返回ONLY JSON内容不要有其他文字。""" 返回ONLY JSON内容不要有其他文字。"""
response = self.client.chat.completions.create( response = self.client.chat.completions.create(
model=self.settings.model, model=self.settings.model,
messages=[ messages=[
{"role": "system", "content": "你是一个资深的 Java QA 工程师,擅长为 Java 应用程序设计测试用例,所有测试步骤和预期结果必须基于 Java 语言特性(如 JUnit、强类型系统、异常机制等输出必须是严格的 JSON 格式。"},
{"role": "user", "content": prompt} {"role": "user", "content": prompt}
], ],
temperature=0.7, temperature=0.2,
max_tokens=3000 max_tokens=3000,
response_format={"type": "json_object"}
) )
content = response.choices[0].message.content content = response.choices[0].message.content
@@ -208,10 +214,17 @@ class DevAgent:
{requirement_analysis["summary"]} {requirement_analysis["summary"]}
""" """
test_cases_text = chr(10).join(
f"- [{c['test_id']}] {c['test_name']}(类型:{c.get('test_type', '未分类')})|预期结果:{c['expected_result']}"
for c in test_cases["test_cases"]
)
test_summary = f""" test_summary = f"""
测试用例数量: {len(test_cases["test_cases"])} 测试用例数量: {len(test_cases["test_cases"])}
测试策略: {test_cases["test_strategy"]} 测试策略: {test_cases["test_strategy"]}
覆盖计划: {test_cases["coverage_plan"]} 覆盖计划: {test_cases["coverage_plan"]}
关键测试用例列表:
{test_cases_text}
""" """
prompt = f"""你是一个资深的Java开发工程师。根据以下需求和测试用例生成高质量的Java实现代码和单元测试代码。 prompt = f"""你是一个资深的Java开发工程师。根据以下需求和测试用例生成高质量的Java实现代码和单元测试代码。
@@ -225,13 +238,13 @@ class DevAgent:
"java_code": "完整的Java实现代码包含主类和必要的辅助类", "java_code": "完整的Java实现代码包含主类和必要的辅助类",
"unit_tests": "使用JUnit的单元测试代码", "unit_tests": "使用JUnit的单元测试代码",
"implementation_notes": "实现说明和注意事项", "implementation_notes": "实现说明和注意事项",
"unit_tests_count": "生成的单元测试数量", "unit_tests_count": "生成的单元测试数量(整数)",
"passed_tests_count": "通过的单元测试数量" "passed_tests_count": "基于代码逻辑分析,预期可通过的单元测试数量(整数)"
}} }}
Java代码要求 Java代码要求
1. 遵循Java编码规范和最佳实践 1. 遵循Java编码规范和最佳实践
2. 包含详细的代码注释 2. 包含详细的代码注释,所有多行注释必须以 /* 开头、以 */ 结尾Javadoc注释以 /** 开头、以 */ 结尾,绝对不能用单独的 / 作为注释结尾
3. 包含异常处理 3. 包含异常处理
4. 支持所有的功能需求 4. 支持所有的功能需求
5. 考虑非功能需求(性能、安全等) 5. 考虑非功能需求(性能、安全等)
@@ -243,17 +256,17 @@ Java代码要求
4. 使用有意义的测试方法名称 4. 使用有意义的测试方法名称
5. 测试代码要清晰易读 5. 测试代码要清晰易读
通过的单元测试数量一定要是你真实运行了单元测试之后得到的真实数字,不能伪造
返回ONLY JSON内容不要有其他文字。""" 返回ONLY JSON内容不要有其他文字。"""
response = self.client.chat.completions.create( response = self.client.chat.completions.create(
model=self.settings.model, model=self.settings.model,
messages=[ messages=[
{"role": "system", "content": "你是一个资深的 Java 开发工程师,擅长编写高质量代码和单元测试,输出必须是严格的 JSON 格式。"},
{"role": "user", "content": prompt} {"role": "user", "content": prompt}
], ],
temperature=0.7, temperature=0.2,
max_tokens=8192 max_tokens=8192,
response_format={"type": "json_object"}
) )
content = response.choices[0].message.content content = response.choices[0].message.content
@@ -282,7 +295,7 @@ async def orchestrate_agents(simple_requirement: str) -> dict:
包含所有Agent结果的完整字典 包含所有Agent结果的完整字典
""" """
send_message_to_feishu(f"收到新需求: {simple_requirement}") send_workflow_start(simple_requirement)
# Step 1: PM Agent 分析需求 # Step 1: PM Agent 分析需求
pm_agent = PMAgent() pm_agent = PMAgent()
requirement_analysis = pm_agent.analyze_requirement(simple_requirement) requirement_analysis = pm_agent.analyze_requirement(simple_requirement)

View File

@@ -7,189 +7,164 @@ from app.models import RequirementAnalysis, TestCaseResult, CodeGenerationResult
webhook_url = "https://open.feishu.cn/open-apis/bot/v2/hook/0cd37406-31b8-424a-a3da-c11ce465ac29" webhook_url = "https://open.feishu.cn/open-apis/bot/v2/hook/0cd37406-31b8-424a-a3da-c11ce465ac29"
def send_message_to_feishu(message: str): _TYPE_EMOJI = {
data = { "功能测试": "🧩",
"msg_type": "text", "性能测试": "",
"content": { "安全测试": "🔒",
"text": message }
}
}
def _post(data: dict):
requests.post( requests.post(
webhook_url, webhook_url,
headers={"Content-Type": "application/json"}, headers={"Content-Type": "application/json"},
data=json.dumps(data) data=json.dumps(data, ensure_ascii=False)
) )
def _make_card(title: str, color: str, elements: list) -> dict:
return {
"msg_type": "interactive",
"card": {
"config": {"wide_screen_mode": True},
"header": {
"title": {"tag": "plain_text", "content": title},
"template": color
},
"elements": elements
}
}
def send_message_to_feishu(message: str):
_post({"msg_type": "text", "content": {"text": message}})
def send_workflow_start(requirement: str):
elements = [
{
"tag": "markdown",
"content": f"收到新需求:\n\n**{requirement}**"
},
{"tag": "hr"},
{
"tag": "markdown",
"content": "🤖 **AI 将按以下流程自动处理,请稍候...**"
},
{
"tag": "column_set",
"flex_mode": "stretch",
"background_style": "default",
"columns": [
{
"tag": "column",
"width": "weighted",
"weight": 1,
"background_style": "blue-300",
"elements": [{
"tag": "markdown",
"content": "\n **📌 需求分析**\n\n - 功能需求拆解\n - 非功能需求识别\n - 验收标准制定\n - 边界情况梳理\n "
}]
},
{
"tag": "column",
"width": "auto",
"elements": [{"tag": "markdown", "content": "\n\n\n\n**→**"}]
},
{
"tag": "column",
"width": "weighted",
"weight": 1,
"background_style": "sunflower-300",
"elements": [{
"tag": "markdown",
"content": "\n **🧪 测试用例生成**\n\n - 功能测试用例\n - 性能测试用例\n - 安全测试用例\n - 测试策略规划\n - 测试覆盖计划\n "
}]
},
{
"tag": "column",
"width": "auto",
"elements": [{"tag": "markdown", "content": "\n\n\n\n**→**"}]
},
{
"tag": "column",
"width": "weighted",
"weight": 1,
"background_style": "green-300",
"elements": [{
"tag": "markdown",
"content": "\n **💻 代码生成**\n\n - 实现思路\n - 业务代码\n - 单元测试代码\n - 测试执行报告\n "
}]
}
]
}
]
_post(_make_card("🚀 AI 全自动开发流程启动", "purple", elements))
def send_requirement_result(requirement_analysis: RequirementAnalysis): def send_requirement_result(requirement_analysis: RequirementAnalysis):
data = { elements = [
"msg_type": "interactive", {"tag": "markdown", "content": f"**📎 需求总结**\n\n{requirement_analysis['summary']}"},
"card": { {"tag": "hr"},
"config": { {"tag": "markdown", "content": "**🧩 功能需求**\n\n" + "\n".join(f"- {r}" for r in requirement_analysis["functional_requirements"])},
"wide_screen_mode": True {"tag": "hr"},
}, {"tag": "markdown", "content": "**🚀 非功能需求**\n\n" + "\n".join(f"- {r}" for r in requirement_analysis["non_functional_requirements"])},
"header": { {"tag": "hr"},
"title": { {"tag": "markdown", "content": "**⚠️ 边界情况**\n\n" + "\n".join(f"- {c}" for c in requirement_analysis["edge_cases"])},
"tag": "plain_text", {"tag": "hr"},
"content": "📌 需求分析结果" {"tag": "markdown", "content": "**✅ 验收标准**\n\n" + "\n".join(f"- {c}" for c in requirement_analysis["acceptance_criteria"])},
}, ]
"template": "blue" _post(_make_card("📌 需求分析结果", "blue", elements))
},
"elements": [
{
"tag": "markdown",
"content": f"---\n**📎 总结:**\n\n{requirement_analysis['summary']}"
},
{
"tag": "markdown",
"content": f"### 🧩 功能需求\n\n{chr(10).join([f'- {req}' for req in requirement_analysis['functional_requirements']])}"
},
{
"tag": "markdown",
"content": f"### 🚀 非功能需求\n\n{chr(10).join([f'- {req}' for req in requirement_analysis['non_functional_requirements']])}"
},
{
"tag": "markdown",
"content": f"### ⚠️ 边界情况\n\n{chr(10).join([f'- {case}' for case in requirement_analysis['edge_cases']])}"
},
{
"tag": "markdown",
"content": f"### ✅ 验收标准\n\n{chr(10).join([f'- {criteria}' for criteria in requirement_analysis['acceptance_criteria']])}"
}
]
}
}
requests.post(
webhook_url,
headers={"Content-Type": "application/json"},
data=json.dumps(data)
)
def send_generate_code(code_result: CodeGenerationResult): def send_generate_code(code_result: CodeGenerationResult):
implementation_notes_data = { # 实现思路
"msg_type": "interactive", _post(_make_card(
"card": { "📌 代码生成结果 — 实现思路", "green",
"config": { [{"tag": "markdown", "content": code_result["implementation_notes"]}]
"wide_screen_mode": True ))
},
"header": {
"title": {
"tag": "plain_text",
"content": "📌 代码生成结果 - 实现思路"
},
"template": "green"
},
"elements": [
{
"tag": "markdown",
"content": code_result['implementation_notes']
}
]
}
}
java_code_data = { # 业务代码
"msg_type": "interactive", _post(_make_card(
"card": { "💻 代码生成结果 — 业务代码", "green",
"config": { [{"tag": "markdown", "content": f"```java\n{code_result['java_code']}\n```"}]
"wide_screen_mode": True ))
},
"header": {
"title": {
"tag": "plain_text",
"content": "📌 代码生成结果 - 业务代码"
},
"template": "green"
},
"elements": [
{
"tag": "markdown",
"content": code_result['java_code']
}
]
}
}
unit_tests_data = { # 单元测试代码
"msg_type": "interactive", _post(_make_card(
"card": { "🧪 代码生成结果 — 单元测试代码", "green",
"config": { [{"tag": "markdown", "content": f"```java\n{code_result['unit_tests']}\n```"}]
"wide_screen_mode": True ))
},
"header": {
"title": {
"tag": "plain_text",
"content": "🚀 代码生成结果 - 测试代码"
},
"template": "green"
},
"elements": [
{
"tag": "markdown",
"content": code_result['unit_tests']
}
]
}
}
passed_tests_data = { # 单元测试执行结果
"msg_type": "interactive", try:
"card": { total = int(code_result["unit_tests_count"])
"config": { passed = int(code_result["passed_tests_count"])
"wide_screen_mode": True failed = total - passed
}, rate = f"{passed / total * 100:.0f}%" if total > 0 else ""
"header": { status = "✅ 全部通过" if failed == 0 else f"⚠️ {failed} 个未通过"
"title": { failed_display = f"{failed}" if failed > 0 else "0"
"tag": "plain_text", except (ValueError, TypeError):
"content": "🚀 代码生成结果 - 单元测试执行结果" total = code_result["unit_tests_count"]
}, passed = code_result["passed_tests_count"]
"template": "green" failed_display, rate, status = "", "", ""
},
"elements": [
{
"tag": "markdown",
"content": f"""
### 📊 测试统计
- **总用例数:** {code_result['unit_tests_count']} result_md = (
- **通过** {code_result['passed_tests_count']} f"**总用例数** {total}\n\n"
""" f"**通过:** {passed}\n\n"
} f"**未通过:** {failed_display}\n\n"
] f"**通过率:** {rate}\n\n"
} f"---\n\n"
} f"**整体状态:** {status}"
requests.post(
webhook_url,
headers={"Content-Type": "application/json"},
data=json.dumps(implementation_notes_data)
) )
_post(_make_card(
"📊 代码生成结果 — 单元测试执行结果", "green",
[{"tag": "markdown", "content": result_md}]
))
requests.post(
webhook_url,
headers={"Content-Type": "application/json"},
data=json.dumps(java_code_data)
)
requests.post(
webhook_url,
headers={"Content-Type": "application/json"},
data=json.dumps(unit_tests_data)
)
requests.post(
webhook_url,
headers={"Content-Type": "application/json"},
data=json.dumps(passed_tests_data)
)
def send_test_cases(test_case: TestCaseResult): def send_test_cases(test_case: TestCaseResult):
_post(build_full_feishu_card(test_case))
requests.post(
webhook_url,
headers={"Content-Type": "application/json"},
data=json.dumps(build_full_feishu_card(test_case))
)
def build_full_feishu_card(data: TestCaseResult) -> dict: def build_full_feishu_card(data: TestCaseResult) -> dict:
@@ -198,76 +173,44 @@ def build_full_feishu_card(data: TestCaseResult) -> dict:
type_counter = defaultdict(int) type_counter = defaultdict(int)
grouped_cases = defaultdict(list) grouped_cases = defaultdict(list)
# 分组 + 统计
for case in test_cases: for case in test_cases:
t_type = case.get("test_type", "未分类") t_type = case.get("test_type", "未分类")
type_counter[t_type] += 1 type_counter[t_type] += 1
grouped_cases[t_type].append(case) grouped_cases[t_type].append(case)
total = len(test_cases) total = len(test_cases)
elements = [] elements = []
# 📊 统计 # 测试统计
stats_text = "### 📊 测试统计\n\n" stats_lines = [f"**📊 测试用例统计**\n", f"- 总用例数:**{total}**"]
stats_text += f"- 总用例数:**{total}**\n" for t_type, count in type_counter.items():
for k, v in type_counter.items(): emoji = _TYPE_EMOJI.get(t_type, "📋")
stats_text += f"- {k}{v}\n" stats_lines.append(f"- {emoji} {t_type}**{count}**")
elements.append({"tag": "markdown", "content": "\n".join(stats_lines)})
elements.append({ # 分组展示
"tag": "markdown",
"content": stats_text
})
# 🗂 分组 + 全量展示
for test_type, cases in grouped_cases.items(): for test_type, cases in grouped_cases.items():
elements.append({ emoji = _TYPE_EMOJI.get(test_type, "📋")
"tag": "markdown", elements.append({"tag": "hr"})
"content": f"---\n## 🗂 {test_type}" elements.append({"tag": "markdown", "content": f"## {emoji} {test_type}"})
})
for case in cases: for case in cases:
steps_text = "\n".join([f" {i+1}. {s}" for i, s in enumerate(case.get("steps", []))]) steps_text = "\n".join(f" {i + 1}. {s}" for i, s in enumerate(case.get("steps", [])))
case_text = (
f"**{case.get('test_id')} · {case.get('test_name')}**\n\n"
f"- **前置条件:** {case.get('precondition')}\n"
f"- **执行步骤:**\n{steps_text}\n"
f"- **期望结果:** {case.get('expected_result')}"
)
elements.append({"tag": "markdown", "content": case_text})
case_text = f"""### {case.get('test_id')} - {case.get('test_name')} # 测试策略
elements.append({"tag": "hr"})
elements.append({"tag": "markdown", "content": f"**🧠 测试策略**\n\n{data.get('test_strategy')}"})
- **前置条件:** {case.get('precondition')} # 覆盖计划
- **执行步骤:** elements.append({"tag": "hr"})
{steps_text} elements.append({"tag": "markdown", "content": f"**🎯 覆盖计划**\n\n{data.get('coverage_plan')}"})
- **期望结果:** {case.get('expected_result')}
"""
elements.append({ return _make_card("🧪 自动化测试用例结果", "blue", elements)
"tag": "markdown",
"content": case_text
})
# 🧠 测试策略
elements.append({
"tag": "markdown",
"content": f"---\n### 🧠 测试策略\n\n{data.get('test_strategy')}"
})
# 🎯 覆盖计划
elements.append({
"tag": "markdown",
"content": f"---\n### 🎯 覆盖计划\n\n{data.get('coverage_plan')}"
})
return {
"msg_type": "interactive",
"card": {
"config": {
"wide_screen_mode": True
},
"header": {
"title": {
"tag": "plain_text",
"content": "🧪 自动化测试用例结果"
},
"template": "blue"
},
"elements": elements
}
}