mirror of
https://github.com/csunny/DB-GPT.git
synced 2025-07-30 23:28:35 +00:00
插件输出结果到对话框
This commit is contained in:
tuyang.yhj
parent
8afee1070e
commit
96c8d14cf1
@ -42,7 +42,7 @@ def execute_ai_response_json(
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cfg = Config()
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try:
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assistant_reply_json = fix_json_using_multiple_techniques(ai_response)
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except (json.JSONDecodeError, ValueError) as e:
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except (json.JSONDecodeError, ValueError, AttributeError) as e:
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raise NotCommands("非可执行命令结构")
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command_name, arguments = get_command(assistant_reply_json)
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if cfg.speak_mode:
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@ -1,4 +1,3 @@
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class NotCommands(Exception):
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def __init__(self, message, error_code):
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def __init__(self, message):
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super().__init__(message)
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self.error_code = error_code
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@ -90,8 +90,8 @@ class FirstPrompt:
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for i, goal in enumerate(self.ai_goals):
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full_prompt += f"{i+1}. {goal}\n"
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if db_schemes:
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full_prompt += f"DB SCHEME:\n\n"
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full_prompt += f"{db_schemes}\n"
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full_prompt += f"\nDB SCHEME:\n\n"
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full_prompt += f"{db_schemes}"
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# if self.api_budget > 0.0:
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# full_prompt += f"\nIt takes money to let you run. Your API budget is ${self.api_budget:.3f}"
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@ -42,7 +42,7 @@ def build_default_prompt_generator() -> PromptGenerator:
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)
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prompt_generator.add_resource("Long Term memory management.")
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prompt_generator.add_resource(
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"GPT-3.5 powered Agents for delegation of simple tasks."
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"DB-GPT powered Agents for delegation of simple tasks."
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)
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# prompt_generator.add_resource("File output.")
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@ -225,69 +225,72 @@ def http_bot(state, mode, sql_mode, db_selector, temperature, max_new_tokens, re
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"stop": state.sep if state.sep_style == SeparatorStyle.SINGLE else state.sep2,
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}
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logger.info(f"Requert: \n{payload}")
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if sql_mode == conversation_sql_mode["auto_execute_ai_response"]:
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auto_db_gpt_response(first_prompt.prompt_generator, payload)
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response = requests.post(urljoin(VICUNA_MODEL_SERVER, "generate"),
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headers=headers, json=payload, timeout=30)
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print(response.json())
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print(str(response))
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try:
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# response = """{"thoughts":{"text":"thought","reasoning":"reasoning","plan":"- short bulleted\n- list that conveys\n- long-term plan","criticism":"constructive self-criticism","speak":"thoughts summary to say to user"},"command":{"name":"db_sql_executor","args":{"sql":"select count(*) as user_count from users u where create_time >= DATE_SUB(NOW(), INTERVAL 1 MONTH);"}}}"""
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# response = response.replace("\n", "\\n")
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plugin_resp = execute_ai_response_json(first_prompt.prompt_generator, response)
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print(plugin_resp)
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state.messages[-1][-1] = "DB-GPT执行结果:\n" + plugin_resp
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yield (state, state.to_gradio_chatbot()) + (no_change_btn,) * 5
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except NotCommands as e:
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print("命令执行:" + str(e))
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state.messages[-1][-1] = "命令执行:" + str(e) +"\n模型输出:\n" + str(response)
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yield (state, state.to_gradio_chatbot()) + (no_change_btn,) * 5
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else:
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stream_ai_response(payload)
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# 流式输出
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state.messages[-1][-1] = "▌"
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yield (state, state.to_gradio_chatbot()) + (disable_btn,) * 5
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def stream_ai_response(payload):
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# 流式输出
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state.messages[-1][-1] = "▌"
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yield (state, state.to_gradio_chatbot()) + (disable_btn,) * 5
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try:
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# Stream output
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response = requests.post(urljoin(VICUNA_MODEL_SERVER, "generate_stream"),
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headers=headers, json=payload, stream=True, timeout=20)
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for chunk in response.iter_lines(decode_unicode=False, delimiter=b"\0"):
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if chunk:
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data = json.loads(chunk.decode())
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if data["error_code"] == 0:
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output = data["text"][skip_echo_len:].strip()
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output = post_process_code(output)
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state.messages[-1][-1] = output + "▌"
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yield (state, state.to_gradio_chatbot()) + (disable_btn,) * 5
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else:
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output = data["text"] + f" (error_code: {data['error_code']})"
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state.messages[-1][-1] = output
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yield (state, state.to_gradio_chatbot()) + (
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disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)
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return
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try:
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# Stream output
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response = requests.post(urljoin(VICUNA_MODEL_SERVER, "generate_stream"),
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headers=headers, json=payload, stream=True, timeout=20)
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for chunk in response.iter_lines(decode_unicode=False, delimiter=b"\0"):
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if chunk:
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data = json.loads(chunk.decode())
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if data["error_code"] == 0:
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output = data["text"][skip_echo_len:].strip()
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output = post_process_code(output)
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state.messages[-1][-1] = output + "▌"
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yield (state, state.to_gradio_chatbot()) + (disable_btn,) * 5
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else:
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output = data["text"] + f" (error_code: {data['error_code']})"
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state.messages[-1][-1] = output
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yield (state, state.to_gradio_chatbot()) + (disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)
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return
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except requests.exceptions.RequestException as e:
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state.messages[-1][-1] = server_error_msg + f" (error_code: 4)"
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yield (state, state.to_gradio_chatbot()) + (disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)
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return
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except requests.exceptions.RequestException as e:
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state.messages[-1][-1] = server_error_msg + f" (error_code: 4)"
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yield (state, state.to_gradio_chatbot()) + (disable_btn, disable_btn, disable_btn, enable_btn, enable_btn)
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return
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state.messages[-1][-1] = state.messages[-1][-1][:-1]
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yield (state, state.to_gradio_chatbot()) + (enable_btn,) * 5
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state.messages[-1][-1] = state.messages[-1][-1][:-1]
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yield (state, state.to_gradio_chatbot()) + (enable_btn,) * 5
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# 记录运行日志
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finish_tstamp = time.time()
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logger.info(f"{output}")
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# 记录运行日志
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finish_tstamp = time.time()
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logger.info(f"{output}")
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with open(get_conv_log_filename(), "a") as fout:
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data = {
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"tstamp": round(finish_tstamp, 4),
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"type": "chat",
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"model": model_name,
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"start": round(start_tstamp, 4),
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"finish": round(start_tstamp, 4),
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"state": state.dict(),
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"ip": request.client.host,
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}
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fout.write(json.dumps(data) + "\n")
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with open(get_conv_log_filename(), "a") as fout:
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data = {
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"tstamp": round(finish_tstamp, 4),
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"type": "chat",
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"model": model_name,
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"start": round(start_tstamp, 4),
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"finish": round(start_tstamp, 4),
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"state": state.dict(),
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"ip": request.client.host,
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}
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fout.write(json.dumps(data) + "\n")
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def auto_db_gpt_response( prompt: PromptGenerator, payload)->str:
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response = requests.post(urljoin(VICUNA_MODEL_SERVER, "generate"),
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headers=headers, json=payload, timeout=30)
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print(response)
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try:
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plugin_resp = execute_ai_response_json(prompt, response)
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print(plugin_resp)
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except NotCommands as e:
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print(str(e))
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return "auto_db_gpt_response!"
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block_css = (
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code_highlight_css
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