From 4d9b0c6138841c46df9a717156ea497bc917a039 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Jo=C3=A3o=20Moura?= Date: Thu, 2 May 2024 02:21:42 -0300 Subject: [PATCH] smal fixes and better guardrail for parsing small models tools usage --- src/crewai/tools/tool_usage.py | 74 +- tests/cassettes/test_crew_verbose_output.yaml | 11997 ++++++++-------- tests/crew_test.py | 16 +- 3 files changed, 6180 insertions(+), 5907 deletions(-) diff --git a/src/crewai/tools/tool_usage.py b/src/crewai/tools/tool_usage.py index 954572328..b3bf3c0a3 100644 --- a/src/crewai/tools/tool_usage.py +++ b/src/crewai/tools/tool_usage.py @@ -26,13 +26,13 @@ class ToolUsage: Class that represents the usage of a tool by an agent. Attributes: - task: Task being executed. - tools_handler: Tools handler that will manage the tool usage. - tools: List of tools available for the agent. - original_tools: Original tools available for the agent before being converted to BaseTool. - tools_description: Description of the tools available for the agent. - tools_names: Names of the tools available for the agent. - function_calling_llm: Language model to be used for the tool usage. + task: Task being executed. + tools_handler: Tools handler that will manage the tool usage. + tools: List of tools available for the agent. + original_tools: Original tools available for the agent before being converted to BaseTool. + tools_description: Description of the tools available for the agent. + tools_names: Names of the tools available for the agent. + function_calling_llm: Language model to be used for the tool usage. """ def __init__( @@ -265,12 +265,12 @@ class ToolUsage: model=model, instructions=dedent( """\ - The schema should have the following structure, only two keys: - - tool_name: str - - arguments: dict (with all arguments being passed) + The schema should have the following structure, only two keys: + - tool_name: str + - arguments: dict (with all arguments being passed) - Example: - {"tool_name": "tool name", "arguments": {"arg_name1": "value", "arg_name2": 2}}""", + Example: + {"tool_name": "tool name", "arguments": {"arg_name1": "value", "arg_name2": 2}}""", ), max_attemps=1, ) @@ -282,7 +282,8 @@ class ToolUsage: tool_name = self.action.tool tool = self._select_tool(tool_name) try: - arguments = ast.literal_eval(self.action.tool_input) + tool_input = self._validate_tool_input(self.action.tool_input) + arguments = ast.literal_eval(tool_input) except Exception: return ToolUsageErrorException( f'{self._i18n.errors("tool_arguments_error")}' @@ -308,3 +309,50 @@ class ToolUsage: return self._tool_calling(tool_string) return calling + + def _validate_tool_input(self, tool_input: str) -> dict: + try: + ast.literal_eval(tool_input) + return tool_input + except Exception: + # Clean and ensure the string is properly enclosed in braces + tool_input = tool_input.strip() + if not tool_input.startswith("{"): + tool_input = "{" + tool_input + if not tool_input.endswith("}"): + tool_input += "}" + + # Manually split the input into key-value pairs + entries = tool_input.strip("{} ").split(",") + formatted_entries = [] + + for entry in entries: + if ":" not in entry: + continue # Skip malformed entries + key, value = entry.split(":", 1) + + key = key.strip().strip( + '"' + ) # Remove extraneous white spaces and quotes + value = value.strip() + + # Check and format the value based on its type + if value.isdigit(): # Check if value is a digit, hence integer + formatted_value = value + elif value.lower() in [ + "true", + "false", + "null", + ]: # Check for boolean and null values + formatted_value = value.lower() + else: + # Assume the value is a string and needs quotes + formatted_value = '"' + value.strip('"').replace('"', '\\"') + '"' + + # Rebuild the entry with proper quoting + formatted_entry = f'"{key}": {formatted_value}' + formatted_entries.append(formatted_entry) + + # Reconstruct the JSON string + new_json_string = "{" + ", ".join(formatted_entries) + "}" + return new_json_string diff --git a/tests/cassettes/test_crew_verbose_output.yaml b/tests/cassettes/test_crew_verbose_output.yaml index 49ad8b9e1..2d3ff0b39 100644 --- a/tests/cassettes/test_crew_verbose_output.yaml +++ b/tests/cassettes/test_crew_verbose_output.yaml @@ -1,33 +1,379 @@ interactions: - request: body: !!binary | - CuILCiQKIgoMc2VydmljZS5uYW1lEhIKEGNyZXdBSS10ZWxlbWV0cnkSuQsKEgoQY3Jld2FpLnRl - bGVtZXRyeRKiCwoQSso0hby6M/hauvpCMZt92hII9MRJi+96UX8qDENyZXcgQ3JlYXRlZDABOaha - 1Gtb/7gXQUAM1mtb/7gXShoKDmNyZXdhaV92ZXJzaW9uEggKBjAuMTYuM0oaCg5weXRob25fdmVy - 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Notably, Deep Learning, + a subfield of ML, has made great strides, enabling machines to process and understand + human language, recognize images, and play complex games.\n\n2. Natural Language + Processing (NLP):\n\nSubstantial progress has been made in NLP. OpenAI''s GPT-3, + a language-generating AI, can produce human-like text, which signifies a major + leap in the field. Further, NLP is being used in sentiment analysis, chatbots, + and customer service, revolutionizing the way businesses interact with customers.\n\n3. + Reinforcement Learning:\n\nReinforcement Learning (RL) is another notable AI + advancement. RL algorithms learn optimal actions through trial and error. AlphaGo, + developed by Google''s DeepMind, used RL to defeat a world champion in the game + of Go, a feat previously considered impossible for AI.\n\n4. AI in Healthcare:\n\nAI + advancements have transformed healthcare. AI tools like predictive analytics, + precision medicine, and robotic surgeries are enhancing patient care. Moreover, + AI has been pivotal in managing and predicting COVID-19 trends.\n\n5. AI in + Finance:\n\nAI is reshaping the financial sector. Automated trading, risk management, + fraud detection, and robo-advisors are some ways AI is employed in finance.\n\n6. + Ethical Implications and Challenges:\n\nDespite these advancements, AI poses + ethical challenges. Issues like job displacement, privacy concerns, and decision-making + transparency are still unresolved. \n\n7. Leading AI Companies and Startups:\n\nLeading + companies in AI include Google, Microsoft, and IBM. Noteworthy startups like + OpenAI, DeepMind, and Neuralink are pushing the AI boundaries.\n\nIn conclusion, + AI advancements are revolutionizing various sectors while posing significant + ethical challenges. The future of AI, while promising, calls for careful and + ethical implementation.\n\nBegin! 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Content-Type: - - text/event-stream + - text/event-stream; charset=utf-8 Date: - - Sat, 02 Mar 2024 16:28:12 GMT + - Thu, 02 May 2024 05:12:18 GMT Server: - cloudflare Transfer-Encoding: - chunked - access-control-allow-origin: - - '*' alt-svc: - h3=":443"; ma=86400 - openai-model: - - gpt-4-0613 openai-organization: - crewai-iuxna1 openai-processing-ms: - - '289' + - '259' openai-version: - '2020-10-01' strict-transport-security: @@ -6333,13 +6558,13 @@ interactions: x-ratelimit-remaining-requests: - '9999' x-ratelimit-remaining-tokens: - - '299205' + - '299220' x-ratelimit-reset-requests: - 6ms x-ratelimit-reset-tokens: - - 159ms + - 155ms x-request-id: - - req_9ef5183d113f9ac49c7d9fbcffb0c038 + - req_cf0bba0655e4b076b43197db6dea3330 status: code: 200 message: OK diff --git a/tests/crew_test.py b/tests/crew_test.py index d054de382..f120612ec 100644 --- a/tests/crew_test.py +++ b/tests/crew_test.py @@ -648,10 +648,10 @@ def test_agent_usage_metrics_are_captured_for_sequential_process(): result = crew.kickoff() assert result == "Howdy!" assert crew.usage_metrics == { - "completion_tokens": 51, - "prompt_tokens": 483, - "successful_requests": 3, - "total_tokens": 534, + "completion_tokens": 17, + "prompt_tokens": 160, + "successful_requests": 1, + "total_tokens": 177, } @@ -678,10 +678,10 @@ def test_agent_usage_metrics_are_captured_for_hierarchical_process(): result = crew.kickoff() assert result == '"Howdy!"' assert crew.usage_metrics == { - "total_tokens": 2592, - "prompt_tokens": 2048, - "completion_tokens": 544, - "successful_requests": 6, + "total_tokens": 1650, + "prompt_tokens": 1367, + "completion_tokens": 283, + "successful_requests": 3, }