diff --git a/README.md b/README.md index 28c38b7..084bea4 100644 --- a/README.md +++ b/README.md @@ -1,10 +1,9 @@ # UiPath Developer Console -[![PyPI downloads](https://img.shields.io/pypi/dm/uipath-dev.svg)](https://pypi.org/project/uipath-dev/) [![PyPI - Version](https://img.shields.io/pypi/v/uipath-dev)](https://pypi.org/project/uipath-dev/) +[![PyPI downloads](https://img.shields.io/pypi/dm/uipath-dev.svg)](https://pypi.org/project/uipath-dev/) [![Python versions](https://img.shields.io/pypi/pyversions/uipath-dev.svg)](https://pypi.org/project/uipath-dev/) - Interactive terminal application for building, testing, and debugging UiPath Python runtimes, agents, and automation scripts. ## Overview @@ -50,3 +49,11 @@ To run tests: ```bash pytest ``` + +### :heart: Special Thanks + +A huge thank-you to the open-source community and the maintainers of the libraries that make this project possible: + +- [OpenTelemetry](https://github.com/open-telemetry/opentelemetry-python) for observability and tracing. +- [Pyperclip](https://github.com/asweigart/pyperclip) for cross-platform clipboard operations. +- [Textual](https://github.com/Textualize/textual) for the powerful TUI framework that powers the developer console. diff --git a/demo/chat_agent/entry-points.json b/demo/chat_agent/entry-points.json new file mode 100644 index 0000000..ebc1ea4 --- /dev/null +++ b/demo/chat_agent/entry-points.json @@ -0,0 +1,2204 @@ +{ + "$schema": "https://cloud.uipath.com/draft/2024-12/entry-point", + "$id": "entry-points.json", + "entryPoints": [ + { + "filePath": "agent", + "uniqueId": "1c20b39b-c92f-46b4-8f12-d26badd55809", + "type": "agent", + "input": { + "type": "object", + "properties": { + "messages": { + "items": { + "oneOf": [ + { + "additionalProperties": true, + "description": "Message from an AI.\n\nAn `AIMessage` is returned from a chat model as a response to a prompt.\n\nThis message represents the output of the model and consists of both\nthe raw output as returned by the model and standardized fields\n(e.g., tool calls, usage metadata) added by the LangChain framework.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "ai", + "default": "ai", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Represents an AI's request to call a tool.\n\nExample:\n ```python\n {\"name\": \"foo\", \"args\": {\"a\": 1}, \"id\": \"123\"}\n ```\n\n This represents a request to call the tool named `'foo'` with arguments\n `{\"a\": 1}` and an identifier of `'123'`.", + "properties": { + "name": { + "title": "Name", + "type": "string" + }, + "args": { + "additionalProperties": true, + "title": "Args", + "type": "object" + }, + "id": { + "type": "string" + }, + "type": { + "const": "tool_call", + "title": "Type", + "type": "string" + } + }, + "required": [ + "name", + "args", + "id" + ], + "title": "ToolCall", + "type": "object" + }, + "title": "Tool Calls", + "type": "array" + }, + "invalid_tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Allowance for errors made by LLM.\n\nHere we add an `error` key to surface errors made during generation\n(e.g., invalid JSON arguments.)", + "properties": { + "type": { + "const": "invalid_tool_call", + "title": "Type", + "type": "string" + }, + "id": { + "type": "string" + }, + "name": { + "type": "string" + }, + "args": { + "type": "string" + }, + "error": { + "type": "string" + }, + "index": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "string" + } + ], + "title": "Index" + }, + "extras": { + "additionalProperties": true, + "title": "Extras", + "type": "object" + } + }, + "required": [ + "type", + "id", + "name", + "args", + "error" + ], + "title": "InvalidToolCall", + "type": "object" + }, + "title": "Invalid Tool Calls", + "type": "array" + }, + "usage_metadata": { + "additionalProperties": true, + "description": "Usage metadata for a message, such as token counts.\n\nThis is a standard representation of token usage that is consistent across models.\n\nExample:\n ```python\n {\n \"input_tokens\": 350,\n \"output_tokens\": 240,\n \"total_tokens\": 590,\n \"input_token_details\": {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n },\n \"output_token_details\": {\n \"audio\": 10,\n \"reasoning\": 200,\n },\n }\n ```\n\n!!! warning \"Behavior changed in `langchain-core` 0.3.9\"\n Added `input_token_details` and `output_token_details`.\n\n!!! note \"LangSmith SDK\"\n The LangSmith SDK also has a `UsageMetadata` class. While the two share fields,\n LangSmith's `UsageMetadata` has additional fields to capture cost information\n used by the LangSmith platform.", + "properties": { + "input_tokens": { + "title": "Input Tokens", + "type": "integer" + }, + "output_tokens": { + "title": "Output Tokens", + "type": "integer" + }, + "total_tokens": { + "title": "Total Tokens", + "type": "integer" + }, + "input_token_details": { + "additionalProperties": true, + "description": "Breakdown of input token counts.\n\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "cache_creation": { + "title": "Cache Creation", + "type": "integer" + }, + "cache_read": { + "title": "Cache Read", + "type": "integer" + } + }, + "title": "InputTokenDetails", + "type": "object" + }, + "output_token_details": { + "additionalProperties": true, + "description": "Breakdown of output token counts.\n\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"reasoning\": 200,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "reasoning": { + "title": "Reasoning", + "type": "integer" + } + }, + "title": "OutputTokenDetails", + "type": "object" + } + }, + "required": [ + "input_tokens", + "output_tokens", + "total_tokens" + ], + "title": "UsageMetadata", + "type": "object" + } + }, + "required": [ + "content" + ], + "title": "AIMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message from the user.\n\nA `HumanMessage` is a message that is passed in from a user to the model.\n\nExample:\n ```python\n from langchain_core.messages import HumanMessage, SystemMessage\n\n messages = [\n SystemMessage(content=\"You are a helpful assistant! Your name is Bob.\"),\n HumanMessage(content=\"What is your name?\"),\n ]\n\n # Instantiate a chat model and invoke it with the messages\n model = ...\n print(model.invoke(messages))\n ```", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "human", + "default": "human", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "HumanMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message that can be assigned an arbitrary speaker (i.e. role).", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "chat", + "default": "chat", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "role": { + "title": "Role", + "type": "string" + } + }, + "required": [ + "content", + "role" + ], + "title": "ChatMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message for priming AI behavior.\n\nThe system message is usually passed in as the first of a sequence\nof input messages.\n\nExample:\n ```python\n from langchain_core.messages import HumanMessage, SystemMessage\n\n messages = [\n SystemMessage(content=\"You are a helpful assistant! Your name is Bob.\"),\n HumanMessage(content=\"What is your name?\"),\n ]\n\n # Define a chat model and invoke it with the messages\n print(model.invoke(messages))\n ```", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "system", + "default": "system", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "SystemMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message for passing the result of executing a tool back to a model.\n\n`FunctionMessage` are an older version of the `ToolMessage` schema, and\ndo not contain the `tool_call_id` field.\n\nThe `tool_call_id` field is used to associate the tool call request with the\ntool call response. Useful in situations where a chat model is able\nto request multiple tool calls in parallel.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "function", + "default": "function", + "title": "Type", + "type": "string" + }, + "name": { + "title": "Name", + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content", + "name" + ], + "title": "FunctionMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message for passing the result of executing a tool back to a model.\n\n`ToolMessage` objects contain the result of a tool invocation. Typically, the result\nis encoded inside the `content` field.\n\nExample: A `ToolMessage` representing a result of `42` from a tool call with id\n\n```python\nfrom langchain_core.messages import ToolMessage\n\nToolMessage(content=\"42\", tool_call_id=\"call_Jja7J89XsjrOLA5r!MEOW!SL\")\n```\n\nExample: A `ToolMessage` where only part of the tool output is sent to the model\nand the full output is passed in to artifact.\n\n```python\nfrom langchain_core.messages import ToolMessage\n\ntool_output = {\n \"stdout\": \"From the graph we can see that the correlation between \"\n \"x and y is ...\",\n \"stderr\": None,\n \"artifacts\": {\"type\": \"image\", \"base64_data\": \"/9j/4gIcSU...\"},\n}\n\nToolMessage(\n content=tool_output[\"stdout\"],\n artifact=tool_output,\n tool_call_id=\"call_Jja7J89XsjrOLA5r!MEOW!SL\",\n)\n```\n\nThe `tool_call_id` field is used to associate the tool call request with the\ntool call response. Useful in situations where a chat model is able\nto request multiple tool calls in parallel.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "tool", + "default": "tool", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "tool_call_id": { + "title": "Tool Call Id", + "type": "string" + }, + "artifact": { + "default": null, + "title": "Artifact" + }, + "status": { + "default": "success", + "enum": [ + "success", + "error" + ], + "title": "Status", + "type": "string" + } + }, + "required": [ + "content", + "tool_call_id" + ], + "title": "ToolMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message chunk from an AI (yielded when streaming).", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "AIMessageChunk", + "default": "AIMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Represents an AI's request to call a tool.\n\nExample:\n ```python\n {\"name\": \"foo\", \"args\": {\"a\": 1}, \"id\": \"123\"}\n ```\n\n This represents a request to call the tool named `'foo'` with arguments\n `{\"a\": 1}` and an identifier of `'123'`.", + "properties": { + "name": { + "title": "Name", + "type": "string" + }, + "args": { + "additionalProperties": true, + "title": "Args", + "type": "object" + }, + "id": { + "type": "string" + }, + "type": { + "const": "tool_call", + "title": "Type", + "type": "string" + } + }, + "required": [ + "name", + "args", + "id" + ], + "title": "ToolCall", + "type": "object" + }, + "title": "Tool Calls", + "type": "array" + }, + "invalid_tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Allowance for errors made by LLM.\n\nHere we add an `error` key to surface errors made during generation\n(e.g., invalid JSON arguments.)", + "properties": { + "type": { + "const": "invalid_tool_call", + "title": "Type", + "type": "string" + }, + "id": { + "type": "string" + }, + "name": { + "type": "string" + }, + "args": { + "type": "string" + }, + "error": { + "type": "string" + }, + "index": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "string" + } + ], + "title": "Index" + }, + "extras": { + "additionalProperties": true, + "title": "Extras", + "type": "object" + } + }, + "required": [ + "type", + "id", + "name", + "args", + "error" + ], + "title": "InvalidToolCall", + "type": "object" + }, + "title": "Invalid Tool Calls", + "type": "array" + }, + "usage_metadata": { + "additionalProperties": true, + "description": "Usage metadata for a message, such as token counts.\n\nThis is a standard representation of token usage that is consistent across models.\n\nExample:\n ```python\n {\n \"input_tokens\": 350,\n \"output_tokens\": 240,\n \"total_tokens\": 590,\n \"input_token_details\": {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n },\n \"output_token_details\": {\n \"audio\": 10,\n \"reasoning\": 200,\n },\n }\n ```\n\n!!! warning \"Behavior changed in `langchain-core` 0.3.9\"\n Added `input_token_details` and `output_token_details`.\n\n!!! note \"LangSmith SDK\"\n The LangSmith SDK also has a `UsageMetadata` class. While the two share fields,\n LangSmith's `UsageMetadata` has additional fields to capture cost information\n used by the LangSmith platform.", + "properties": { + "input_tokens": { + "title": "Input Tokens", + "type": "integer" + }, + "output_tokens": { + "title": "Output Tokens", + "type": "integer" + }, + "total_tokens": { + "title": "Total Tokens", + "type": "integer" + }, + "input_token_details": { + "additionalProperties": true, + "description": "Breakdown of input token counts.\n\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "cache_creation": { + "title": "Cache Creation", + "type": "integer" + }, + "cache_read": { + "title": "Cache Read", + "type": "integer" + } + }, + "title": "InputTokenDetails", + "type": "object" + }, + "output_token_details": { + "additionalProperties": true, + "description": "Breakdown of output token counts.\n\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"reasoning\": 200,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "reasoning": { + "title": "Reasoning", + "type": "integer" + } + }, + "title": "OutputTokenDetails", + "type": "object" + } + }, + "required": [ + "input_tokens", + "output_tokens", + "total_tokens" + ], + "title": "UsageMetadata", + "type": "object" + }, + "tool_call_chunks": { + "default": [], + "items": { + "additionalProperties": true, + "description": "A chunk of a tool call (yielded when streaming).\n\nWhen merging `ToolCallChunk`s (e.g., via `AIMessageChunk.__add__`),\nall string attributes are concatenated. Chunks are only merged if their\nvalues of `index` are equal and not None.\n\nExample:\n```python\nleft_chunks = [ToolCallChunk(name=\"foo\", args='{\"a\":', index=0)]\nright_chunks = [ToolCallChunk(name=None, args=\"1}\", index=0)]\n\n(\n AIMessageChunk(content=\"\", tool_call_chunks=left_chunks)\n + AIMessageChunk(content=\"\", tool_call_chunks=right_chunks)\n).tool_call_chunks == [ToolCallChunk(name=\"foo\", args='{\"a\":1}', index=0)]\n```", + "properties": { + "name": { + "type": "string" + }, + "args": { + "type": "string" + }, + "id": { + "type": "string" + }, + "index": { + "type": "integer" + }, + "type": { + "const": "tool_call_chunk", + "title": "Type", + "type": "string" + } + }, + "required": [ + "name", + "args", + "id", + "index" + ], + "title": "ToolCallChunk", + "type": "object" + }, + "title": "Tool Call Chunks", + "type": "array" + }, + "chunk_position": { + "const": "last", + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "AIMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Human Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "HumanMessageChunk", + "default": "HumanMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "HumanMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Chat Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "ChatMessageChunk", + "default": "ChatMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "role": { + "title": "Role", + "type": "string" + } + }, + "required": [ + "content", + "role" + ], + "title": "ChatMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "System Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "SystemMessageChunk", + "default": "SystemMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "SystemMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Function Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "FunctionMessageChunk", + "default": "FunctionMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "title": "Name", + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content", + "name" + ], + "title": "FunctionMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Tool Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "ToolMessageChunk", + "default": "ToolMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "tool_call_id": { + "title": "Tool Call Id", + "type": "string" + }, + "artifact": { + "default": null, + "title": "Artifact" + }, + "status": { + "default": "success", + "enum": [ + "success", + "error" + ], + "title": "Status", + "type": "string" + } + }, + "required": [ + "content", + "tool_call_id" + ], + "title": "ToolMessageChunk", + "type": "object" + } + ] + }, + "title": "Messages", + "type": "array" + } + }, + "required": [ + "messages" + ] + }, + "output": { + "type": "object", + "properties": { + "messages": { + "default": null, + "items": { + "oneOf": [ + { + "additionalProperties": true, + "description": "Message from an AI.\n\nAn `AIMessage` is returned from a chat model as a response to a prompt.\n\nThis message represents the output of the model and consists of both\nthe raw output as returned by the model and standardized fields\n(e.g., tool calls, usage metadata) added by the LangChain framework.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "ai", + "default": "ai", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Represents an AI's request to call a tool.\n\nExample:\n ```python\n {\"name\": \"foo\", \"args\": {\"a\": 1}, \"id\": \"123\"}\n ```\n\n This represents a request to call the tool named `'foo'` with arguments\n `{\"a\": 1}` and an identifier of `'123'`.", + "properties": { + "name": { + "title": "Name", + "type": "string" + }, + "args": { + "additionalProperties": true, + "title": "Args", + "type": "object" + }, + "id": { + "type": "string" + }, + "type": { + "const": "tool_call", + "title": "Type", + "type": "string" + } + }, + "required": [ + "name", + "args", + "id" + ], + "title": "ToolCall", + "type": "object" + }, + "title": "Tool Calls", + "type": "array" + }, + "invalid_tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Allowance for errors made by LLM.\n\nHere we add an `error` key to surface errors made during generation\n(e.g., invalid JSON arguments.)", + "properties": { + "type": { + "const": "invalid_tool_call", + "title": "Type", + "type": "string" + }, + "id": { + "type": "string" + }, + "name": { + "type": "string" + }, + "args": { + "type": "string" + }, + "error": { + "type": "string" + }, + "index": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "string" + } + ], + "title": "Index" + }, + "extras": { + "additionalProperties": true, + "title": "Extras", + "type": "object" + } + }, + "required": [ + "type", + "id", + "name", + "args", + "error" + ], + "title": "InvalidToolCall", + "type": "object" + }, + "title": "Invalid Tool Calls", + "type": "array" + }, + "usage_metadata": { + "additionalProperties": true, + "description": "Usage metadata for a message, such as token counts.\n\nThis is a standard representation of token usage that is consistent across models.\n\nExample:\n ```python\n {\n \"input_tokens\": 350,\n \"output_tokens\": 240,\n \"total_tokens\": 590,\n \"input_token_details\": {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n },\n \"output_token_details\": {\n \"audio\": 10,\n \"reasoning\": 200,\n },\n }\n ```\n\n!!! warning \"Behavior changed in `langchain-core` 0.3.9\"\n Added `input_token_details` and `output_token_details`.\n\n!!! note \"LangSmith SDK\"\n The LangSmith SDK also has a `UsageMetadata` class. While the two share fields,\n LangSmith's `UsageMetadata` has additional fields to capture cost information\n used by the LangSmith platform.", + "properties": { + "input_tokens": { + "title": "Input Tokens", + "type": "integer" + }, + "output_tokens": { + "title": "Output Tokens", + "type": "integer" + }, + "total_tokens": { + "title": "Total Tokens", + "type": "integer" + }, + "input_token_details": { + "additionalProperties": true, + "description": "Breakdown of input token counts.\n\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "cache_creation": { + "title": "Cache Creation", + "type": "integer" + }, + "cache_read": { + "title": "Cache Read", + "type": "integer" + } + }, + "title": "InputTokenDetails", + "type": "object" + }, + "output_token_details": { + "additionalProperties": true, + "description": "Breakdown of output token counts.\n\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"reasoning\": 200,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "reasoning": { + "title": "Reasoning", + "type": "integer" + } + }, + "title": "OutputTokenDetails", + "type": "object" + } + }, + "required": [ + "input_tokens", + "output_tokens", + "total_tokens" + ], + "title": "UsageMetadata", + "type": "object" + } + }, + "required": [ + "content" + ], + "title": "AIMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message from the user.\n\nA `HumanMessage` is a message that is passed in from a user to the model.\n\nExample:\n ```python\n from langchain_core.messages import HumanMessage, SystemMessage\n\n messages = [\n SystemMessage(content=\"You are a helpful assistant! Your name is Bob.\"),\n HumanMessage(content=\"What is your name?\"),\n ]\n\n # Instantiate a chat model and invoke it with the messages\n model = ...\n print(model.invoke(messages))\n ```", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "human", + "default": "human", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "HumanMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message that can be assigned an arbitrary speaker (i.e. role).", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "chat", + "default": "chat", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "role": { + "title": "Role", + "type": "string" + } + }, + "required": [ + "content", + "role" + ], + "title": "ChatMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message for priming AI behavior.\n\nThe system message is usually passed in as the first of a sequence\nof input messages.\n\nExample:\n ```python\n from langchain_core.messages import HumanMessage, SystemMessage\n\n messages = [\n SystemMessage(content=\"You are a helpful assistant! Your name is Bob.\"),\n HumanMessage(content=\"What is your name?\"),\n ]\n\n # Define a chat model and invoke it with the messages\n print(model.invoke(messages))\n ```", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "system", + "default": "system", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "SystemMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message for passing the result of executing a tool back to a model.\n\n`FunctionMessage` are an older version of the `ToolMessage` schema, and\ndo not contain the `tool_call_id` field.\n\nThe `tool_call_id` field is used to associate the tool call request with the\ntool call response. Useful in situations where a chat model is able\nto request multiple tool calls in parallel.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "function", + "default": "function", + "title": "Type", + "type": "string" + }, + "name": { + "title": "Name", + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content", + "name" + ], + "title": "FunctionMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message for passing the result of executing a tool back to a model.\n\n`ToolMessage` objects contain the result of a tool invocation. Typically, the result\nis encoded inside the `content` field.\n\nExample: A `ToolMessage` representing a result of `42` from a tool call with id\n\n```python\nfrom langchain_core.messages import ToolMessage\n\nToolMessage(content=\"42\", tool_call_id=\"call_Jja7J89XsjrOLA5r!MEOW!SL\")\n```\n\nExample: A `ToolMessage` where only part of the tool output is sent to the model\nand the full output is passed in to artifact.\n\n```python\nfrom langchain_core.messages import ToolMessage\n\ntool_output = {\n \"stdout\": \"From the graph we can see that the correlation between \"\n \"x and y is ...\",\n \"stderr\": None,\n \"artifacts\": {\"type\": \"image\", \"base64_data\": \"/9j/4gIcSU...\"},\n}\n\nToolMessage(\n content=tool_output[\"stdout\"],\n artifact=tool_output,\n tool_call_id=\"call_Jja7J89XsjrOLA5r!MEOW!SL\",\n)\n```\n\nThe `tool_call_id` field is used to associate the tool call request with the\ntool call response. Useful in situations where a chat model is able\nto request multiple tool calls in parallel.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "tool", + "default": "tool", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "tool_call_id": { + "title": "Tool Call Id", + "type": "string" + }, + "artifact": { + "default": null, + "title": "Artifact" + }, + "status": { + "default": "success", + "enum": [ + "success", + "error" + ], + "title": "Status", + "type": "string" + } + }, + "required": [ + "content", + "tool_call_id" + ], + "title": "ToolMessage", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Message chunk from an AI (yielded when streaming).", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "AIMessageChunk", + "default": "AIMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Represents an AI's request to call a tool.\n\nExample:\n ```python\n {\"name\": \"foo\", \"args\": {\"a\": 1}, \"id\": \"123\"}\n ```\n\n This represents a request to call the tool named `'foo'` with arguments\n `{\"a\": 1}` and an identifier of `'123'`.", + "properties": { + "name": { + "title": "Name", + "type": "string" + }, + "args": { + "additionalProperties": true, + "title": "Args", + "type": "object" + }, + "id": { + "type": "string" + }, + "type": { + "const": "tool_call", + "title": "Type", + "type": "string" + } + }, + "required": [ + "name", + "args", + "id" + ], + "title": "ToolCall", + "type": "object" + }, + "title": "Tool Calls", + "type": "array" + }, + "invalid_tool_calls": { + "default": [], + "items": { + "additionalProperties": true, + "description": "Allowance for errors made by LLM.\n\nHere we add an `error` key to surface errors made during generation\n(e.g., invalid JSON arguments.)", + "properties": { + "type": { + "const": "invalid_tool_call", + "title": "Type", + "type": "string" + }, + "id": { + "type": "string" + }, + "name": { + "type": "string" + }, + "args": { + "type": "string" + }, + "error": { + "type": "string" + }, + "index": { + "anyOf": [ + { + "type": "integer" + }, + { + "type": "string" + } + ], + "title": "Index" + }, + "extras": { + "additionalProperties": true, + "title": "Extras", + "type": "object" + } + }, + "required": [ + "type", + "id", + "name", + "args", + "error" + ], + "title": "InvalidToolCall", + "type": "object" + }, + "title": "Invalid Tool Calls", + "type": "array" + }, + "usage_metadata": { + "additionalProperties": true, + "description": "Usage metadata for a message, such as token counts.\n\nThis is a standard representation of token usage that is consistent across models.\n\nExample:\n ```python\n {\n \"input_tokens\": 350,\n \"output_tokens\": 240,\n \"total_tokens\": 590,\n \"input_token_details\": {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n },\n \"output_token_details\": {\n \"audio\": 10,\n \"reasoning\": 200,\n },\n }\n ```\n\n!!! warning \"Behavior changed in `langchain-core` 0.3.9\"\n Added `input_token_details` and `output_token_details`.\n\n!!! note \"LangSmith SDK\"\n The LangSmith SDK also has a `UsageMetadata` class. While the two share fields,\n LangSmith's `UsageMetadata` has additional fields to capture cost information\n used by the LangSmith platform.", + "properties": { + "input_tokens": { + "title": "Input Tokens", + "type": "integer" + }, + "output_tokens": { + "title": "Output Tokens", + "type": "integer" + }, + "total_tokens": { + "title": "Total Tokens", + "type": "integer" + }, + "input_token_details": { + "additionalProperties": true, + "description": "Breakdown of input token counts.\n\nDoes *not* need to sum to full input token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"cache_creation\": 200,\n \"cache_read\": 100,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "cache_creation": { + "title": "Cache Creation", + "type": "integer" + }, + "cache_read": { + "title": "Cache Read", + "type": "integer" + } + }, + "title": "InputTokenDetails", + "type": "object" + }, + "output_token_details": { + "additionalProperties": true, + "description": "Breakdown of output token counts.\n\nDoes *not* need to sum to full output token count. Does *not* need to have all keys.\n\nExample:\n ```python\n {\n \"audio\": 10,\n \"reasoning\": 200,\n }\n ```\n\nMay also hold extra provider-specific keys.\n\n!!! version-added \"Added in `langchain-core` 0.3.9\"", + "properties": { + "audio": { + "title": "Audio", + "type": "integer" + }, + "reasoning": { + "title": "Reasoning", + "type": "integer" + } + }, + "title": "OutputTokenDetails", + "type": "object" + } + }, + "required": [ + "input_tokens", + "output_tokens", + "total_tokens" + ], + "title": "UsageMetadata", + "type": "object" + }, + "tool_call_chunks": { + "default": [], + "items": { + "additionalProperties": true, + "description": "A chunk of a tool call (yielded when streaming).\n\nWhen merging `ToolCallChunk`s (e.g., via `AIMessageChunk.__add__`),\nall string attributes are concatenated. Chunks are only merged if their\nvalues of `index` are equal and not None.\n\nExample:\n```python\nleft_chunks = [ToolCallChunk(name=\"foo\", args='{\"a\":', index=0)]\nright_chunks = [ToolCallChunk(name=None, args=\"1}\", index=0)]\n\n(\n AIMessageChunk(content=\"\", tool_call_chunks=left_chunks)\n + AIMessageChunk(content=\"\", tool_call_chunks=right_chunks)\n).tool_call_chunks == [ToolCallChunk(name=\"foo\", args='{\"a\":1}', index=0)]\n```", + "properties": { + "name": { + "type": "string" + }, + "args": { + "type": "string" + }, + "id": { + "type": "string" + }, + "index": { + "type": "integer" + }, + "type": { + "const": "tool_call_chunk", + "title": "Type", + "type": "string" + } + }, + "required": [ + "name", + "args", + "id", + "index" + ], + "title": "ToolCallChunk", + "type": "object" + }, + "title": "Tool Call Chunks", + "type": "array" + }, + "chunk_position": { + "const": "last", + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "AIMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Human Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "HumanMessageChunk", + "default": "HumanMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + } + }, + "required": [ + "content" + ], + "title": "HumanMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "Chat Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + "additionalProperties": true, + "type": "object" + } + ] + }, + "type": "array" + } + ], + "title": "Content" + }, + "additional_kwargs": { + "additionalProperties": true, + "title": "Additional Kwargs", + "type": "object" + }, + "response_metadata": { + "additionalProperties": true, + "title": "Response Metadata", + "type": "object" + }, + "type": { + "const": "ChatMessageChunk", + "default": "ChatMessageChunk", + "title": "Type", + "type": "string" + }, + "name": { + "type": "string" + }, + "id": { + "type": "string" + }, + "role": { + "title": "Role", + "type": "string" + } + }, + "required": [ + "content", + "role" + ], + "title": "ChatMessageChunk", + "type": "object" + }, + { + "additionalProperties": true, + "description": "System Message chunk.", + "properties": { + "content": { + "anyOf": [ + { + "type": "string" + }, + { + "items": { + "anyOf": [ + { + "type": "string" + }, + { + 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detail?", + "citation": null + }, + "meta_event": null + }, + "tool_call": null, + "meta_event": null + } + }, + { + "event_type": "runtime_message", + "execution_id": null, + "metadata": null, + "payload": { + "message_id": "lc_run--146a93d8-60d4-4f53-8e6f-cf688427e050", + "start": null, + "end": { + "metadata": null + }, + "content_part": { + "content_part_id": "chunk-lc_run--146a93d8-60d4-4f53-8e6f-cf688427e050-0", + "start": null, + "end": { + "last_chunk_content_part_sequence": null, + "interrupted": null, + "metadata": null + }, + "chunk": null, + "meta_event": null + }, + "tool_call": null, + "meta_event": null + } + }, + { + "event_type": "runtime_state", + "execution_id": null, + "metadata": null, + "payload": { + "messages": [ + { + "content": [ + { + "text": "# Fight Club (1999)\n\n## Overview\nFight Club is a 1999 American film directed by David Fincher and based on Chuck Palahniuk's 1996 novel of the same name. The film has become one of the most iconic and culturally significant movies of its era, known for its raw intensity, psychological depth, and social commentary.\n\n## Plot\nThe film follows an unnamed narrator (played by Edward Norton), an insomniac office worker who is deeply dissatisfied with his sterile, consumer-driven existence. He meets the charismatic and enigmatic Tyler Durden (Brad Pitt), and together they form \"Fight Club,\" an underground community where men release their suppressed anger through bare-knuckle fighting. What begins as a form of personal catharsis evolves into a cult-like movement called Project Mayhem, which aims to disrupt the social order. The film features a shocking twist that has become one of the most famous in cinema history.\n\n## Cast and Crew\n- **Director**: David Fincher\n- **Main Cast**:\n - Edward Norton as the Narrator\n - Brad Pitt as Tyler Durden\n - Helena Bonham Carter as Marla Singer\n- **Based on**: The novel by Chuck Palahniuk\n- **Studio**: 20th Century Fox\n\n## Reception and Impact\nUpon its initial release, Fight Club received polarized reviews and was considered a box office disappointment. It was even reportedly booed at its 1999 Venice Film Festival premiere. The film failed to meet the studio's financial expectations during its theatrical run.\n\nHowever, Fight Club has since experienced one of the most remarkable post-theatrical transformations in film history:\n\n1. **Cult Classic Status**: The film gained a massive cult following after its home video release, eventually earning over $100 million worldwide.\n\n2. **Critical Reassessment**: Over time, critics have largely reassessed the film, and it is now widely regarded as a masterpiece of 1990s cinema.\n\n3. **Cultural Impact**: The movie has had a profound influence on popular culture, with its quotes (particularly \"The first rule of Fight Club is: you don't talk about Fight Club\") becoming part of the cultural lexicon.\n\n4. **Artistic Recognition**: David Fincher's direction is lauded for creating a visually striking and psychologically intense atmosphere. The performances, particularly by Norton and Pitt, are considered career-defining.\n\n5. **Thematic Significance**: The film is recognized for its exploration of themes including masculinity in crisis, anti-consumerism, identity, and societal alienation\u2014topics that have only become more relevant over time.\n\n## Legacy\nFight Club is now considered one of the most influential films of the late 20th century. Its unique visual style, narrative structure, and unflinching examination of modern society continue to resonate with audiences. The film has inspired countless analyses, academic papers, and discussions about its deeper meanings and social commentary.\n\nFor many viewers, Fight Club represents more than entertainment\u2014it's seen as a film that challenges conventional thinking and provokes meaningful reflection on consumer culture, personal identity, and societal norms.\n\nWould you like me to explore any specific aspect of Fight Club in more detail?", + "type": "text", + "index": 0 + } + ], + "additional_kwargs": {}, + "response_metadata": { + "model_name": "claude-3-7-sonnet-20250219", + "model_provider": "anthropic", + "stop_reason": "end_turn", + "stop_sequence": {} + }, + "type": "ai", + "name": {}, + "id": "lc_run--146a93d8-60d4-4f53-8e6f-cf688427e050", + "tool_calls": [], + "invalid_tool_calls": [], + "usage_metadata": { + "input_tokens": 5029, + "output_tokens": 713, + "total_tokens": 5742, + "input_token_details": { + "cache_creation": 0, + "cache_read": 0 + } + } + } + ] + }, + "node_name": "model" + }, + { + "event_type": "runtime_result", + "execution_id": null, + "metadata": null, + "output": { + "messages": [ + { + "content": [ + { + "text": "# Fight Club (1999)\n\n## Overview\nFight Club is a 1999 American film directed by David Fincher and based on Chuck Palahniuk's 1996 novel of the same name. The film has become one of the most iconic and culturally significant movies of its era, known for its raw intensity, psychological depth, and social commentary.\n\n## Plot\nThe film follows an unnamed narrator (played by Edward Norton), an insomniac office worker who is deeply dissatisfied with his sterile, consumer-driven existence. He meets the charismatic and enigmatic Tyler Durden (Brad Pitt), and together they form \"Fight Club,\" an underground community where men release their suppressed anger through bare-knuckle fighting. What begins as a form of personal catharsis evolves into a cult-like movement called Project Mayhem, which aims to disrupt the social order. The film features a shocking twist that has become one of the most famous in cinema history.\n\n## Cast and Crew\n- **Director**: David Fincher\n- **Main Cast**:\n - Edward Norton as the Narrator\n - Brad Pitt as Tyler Durden\n - Helena Bonham Carter as Marla Singer\n- **Based on**: The novel by Chuck Palahniuk\n- **Studio**: 20th Century Fox\n\n## Reception and Impact\nUpon its initial release, Fight Club received polarized reviews and was considered a box office disappointment. It was even reportedly booed at its 1999 Venice Film Festival premiere. The film failed to meet the studio's financial expectations during its theatrical run.\n\nHowever, Fight Club has since experienced one of the most remarkable post-theatrical transformations in film history:\n\n1. **Cult Classic Status**: The film gained a massive cult following after its home video release, eventually earning over $100 million worldwide.\n\n2. **Critical Reassessment**: Over time, critics have largely reassessed the film, and it is now widely regarded as a masterpiece of 1990s cinema.\n\n3. **Cultural Impact**: The movie has had a profound influence on popular culture, with its quotes (particularly \"The first rule of Fight Club is: you don't talk about Fight Club\") becoming part of the cultural lexicon.\n\n4. **Artistic Recognition**: David Fincher's direction is lauded for creating a visually striking and psychologically intense atmosphere. The performances, particularly by Norton and Pitt, are considered career-defining.\n\n5. **Thematic Significance**: The film is recognized for its exploration of themes including masculinity in crisis, anti-consumerism, identity, and societal alienation\u2014topics that have only become more relevant over time.\n\n## Legacy\nFight Club is now considered one of the most influential films of the late 20th century. Its unique visual style, narrative structure, and unflinching examination of modern society continue to resonate with audiences. The film has inspired countless analyses, academic papers, and discussions about its deeper meanings and social commentary.\n\nFor many viewers, Fight Club represents more than entertainment\u2014it's seen as a film that challenges conventional thinking and provokes meaningful reflection on consumer culture, personal identity, and societal norms.\n\nWould you like me to explore any specific aspect of Fight Club in more detail?", + "type": "text", + "index": 0 + } + ], + "additional_kwargs": {}, + "response_metadata": { + "model_name": "claude-3-7-sonnet-20250219", + "model_provider": "anthropic", + "stop_reason": "end_turn", + "stop_sequence": {} + }, + "type": "ai", + "name": {}, + "id": "lc_run--146a93d8-60d4-4f53-8e6f-cf688427e050", + "tool_calls": [], + "invalid_tool_calls": [], + "usage_metadata": { + "input_tokens": 5029, + "output_tokens": 713, + "total_tokens": 5742, + "input_token_details": { + "cache_creation": 0, + "cache_read": 0 + } + } + } + ] + }, + "status": "successful", + "trigger": null, + "error": null + } +] \ No newline at end of file diff --git a/src/uipath/dev/_demo/mock_runtime.py b/demo/mock_factory.py similarity index 53% rename from src/uipath/dev/_demo/mock_runtime.py rename to demo/mock_factory.py index 1e36759..5115b06 100644 --- a/src/uipath/dev/_demo/mock_runtime.py +++ b/demo/mock_factory.py @@ -1,31 +1,50 @@ """Minimal demo script to run UiPathDevTerminal with mock runtimes.""" import logging +from pathlib import Path from uipath.runtime import ( UiPathRuntimeProtocol, ) -from uipath.dev._demo.mock_context_runtime import ENTRYPOINT_CONTEXT, MockContextRuntime -from uipath.dev._demo.mock_greeting_runtime import ( +from demo.mock_greeting_runtime import ( ENTRYPOINT_GREETING, MockGreetingRuntime, ) -from uipath.dev._demo.mock_numbers_runtime import ( +from demo.mock_numbers_runtime import ( ENTRYPOINT_ANALYZE_NUMBERS, MockNumberAnalyticsRuntime, ) -from uipath.dev._demo.mock_support_runtime import ( +from demo.mock_support_runtime import ( ENTRYPOINT_SUPPORT_CHAT, MockSupportChatRuntime, ) +from demo.mock_telemetry_runtime import ( + ENTRYPOINT_TELEMETRY, + MockTelemetryRuntime, +) +from demo.mock_template_runtime import ( + create_template_runtime, +) logger = logging.getLogger(__name__) +# Template mappings: entrypoint -> (events_file, schema_file) +TEMPLATE_RUNTIMES = { + "chat/movies.py:graph": ( + "chat_agent/events.json", + "chat_agent/entry-points.json", + ), +} + class MockRuntimeFactory: """Runtime factory compatible with UiPathRuntimeFactoryProtocol.""" + def __init__(self): + """Initialize the mock runtime factory.""" + self.demo_dir = Path(__file__).parent + async def new_runtime( self, entrypoint: str, runtime_id: str ) -> UiPathRuntimeProtocol: @@ -36,8 +55,19 @@ async def new_runtime( return MockNumberAnalyticsRuntime(entrypoint=entrypoint) if entrypoint == ENTRYPOINT_SUPPORT_CHAT: return MockSupportChatRuntime(entrypoint=entrypoint) - if entrypoint == ENTRYPOINT_CONTEXT: - return MockContextRuntime(entrypoint=entrypoint) + if entrypoint == ENTRYPOINT_TELEMETRY: + return MockTelemetryRuntime(entrypoint=entrypoint) + + if entrypoint in TEMPLATE_RUNTIMES: + events_file, schema_file = TEMPLATE_RUNTIMES[entrypoint] + + events_path = self.demo_dir / events_file + schema_path = self.demo_dir / schema_file + + return create_template_runtime( + events_json=events_path, + schema_json=schema_path, + ) # Fallback: still return something so the demo doesn't explode logger.warning( @@ -47,20 +77,32 @@ async def new_runtime( async def discover_runtimes(self) -> list[UiPathRuntimeProtocol]: """Return prototype instances for discovery (not really used by the UI).""" - return [ + runtimes: list[UiPathRuntimeProtocol] = [ MockGreetingRuntime(entrypoint=ENTRYPOINT_GREETING), MockNumberAnalyticsRuntime(entrypoint=ENTRYPOINT_ANALYZE_NUMBERS), MockSupportChatRuntime(entrypoint=ENTRYPOINT_SUPPORT_CHAT), - MockContextRuntime(entrypoint=ENTRYPOINT_CONTEXT), + MockTelemetryRuntime(entrypoint=ENTRYPOINT_TELEMETRY), ] + for entrypoint in TEMPLATE_RUNTIMES.keys(): + try: + runtime: UiPathRuntimeProtocol = await self.new_runtime( + entrypoint, runtime_id="discovery" + ) + runtimes.append(runtime) + except Exception as e: + logger.error(f"Failed to load template runtime '{entrypoint}': {e}") + + return runtimes + def discover_entrypoints(self) -> list[str]: """Return all available entrypoints.""" return [ - ENTRYPOINT_CONTEXT, + ENTRYPOINT_TELEMETRY, ENTRYPOINT_GREETING, ENTRYPOINT_ANALYZE_NUMBERS, ENTRYPOINT_SUPPORT_CHAT, + *TEMPLATE_RUNTIMES.keys(), ] async def dispose(self) -> None: diff --git a/src/uipath/dev/_demo/mock_greeting_runtime.py b/demo/mock_greeting_runtime.py similarity index 93% rename from src/uipath/dev/_demo/mock_greeting_runtime.py rename to demo/mock_greeting_runtime.py index 54ed7d7..e6c1017 100644 --- a/src/uipath/dev/_demo/mock_greeting_runtime.py +++ b/demo/mock_greeting_runtime.py @@ -1,3 +1,5 @@ +"""Mock Greeting Runtime for demonstration purposes.""" + import asyncio import logging from typing import Any, AsyncGenerator @@ -21,10 +23,12 @@ class MockGreetingRuntime: """Mock runtime that builds a greeting and simulates a small pipeline.""" def __init__(self, entrypoint: str = ENTRYPOINT_GREETING) -> None: + """Initialize the MockGreetingRuntime.""" self.entrypoint = entrypoint self.tracer = trace.get_tracer("uipath.dev.mock.greeting") async def get_schema(self) -> UiPathRuntimeSchema: + """Get the schema for the greeting runtime.""" return UiPathRuntimeSchema( filePath=self.entrypoint, uniqueId="mock-greeting-runtime", @@ -62,6 +66,7 @@ async def execute( input: dict[str, Any] | None = None, options: UiPathExecuteOptions | None = None, ) -> UiPathRuntimeResult: + """Execute the greeting runtime.""" payload = input or {} name = str(payload.get("name", "world")).strip() or "world" excited = bool(payload.get("excited", True)) @@ -124,8 +129,10 @@ async def stream( input: dict[str, Any] | None = None, options: UiPathStreamOptions | None = None, ) -> AsyncGenerator[UiPathRuntimeEvent, None]: + """Stream events from the greeting runtime.""" logger.info("GreetingRuntime: stream() invoked") yield await self.execute(input=input, options=options) async def dispose(self) -> None: + """Dispose of any resources used by the greeting runtime.""" logger.info("GreetingRuntime: dispose() invoked") diff --git a/src/uipath/dev/_demo/mock_numbers_runtime.py b/demo/mock_numbers_runtime.py similarity index 92% rename from src/uipath/dev/_demo/mock_numbers_runtime.py rename to demo/mock_numbers_runtime.py index ff54500..4e61512 100644 --- a/src/uipath/dev/_demo/mock_numbers_runtime.py +++ b/demo/mock_numbers_runtime.py @@ -1,3 +1,5 @@ +"""An example mock runtime that analyzes numbers.""" + import asyncio import logging from typing import Any, AsyncGenerator @@ -12,7 +14,7 @@ ) from uipath.runtime.schema import UiPathRuntimeSchema -ENTRYPOINT_ANALYZE_NUMBERS = "analytics/numbers.py:analyze" +ENTRYPOINT_ANALYZE_NUMBERS = "agent/numbers.py:analyze" logger = logging.getLogger(__name__) @@ -21,10 +23,12 @@ class MockNumberAnalyticsRuntime: """Mock runtime that analyzes a list of numbers.""" def __init__(self, entrypoint: str = ENTRYPOINT_ANALYZE_NUMBERS) -> None: + """Initialize the MockNumberAnalyticsRuntime.""" self.entrypoint = entrypoint self.tracer = trace.get_tracer("uipath.dev.mock.number-analytics") async def get_schema(self) -> UiPathRuntimeSchema: + """Get the schema for the number analytics runtime.""" return UiPathRuntimeSchema( filePath=self.entrypoint, uniqueId="mock-number-analytics-runtime", @@ -61,6 +65,7 @@ async def execute( input: dict[str, Any] | None = None, options: UiPathExecuteOptions | None = None, ) -> UiPathRuntimeResult: + """Execute the number analytics runtime.""" payload = input or {} numbers = payload.get("numbers") or [] operation = str(payload.get("operation", "sum")).lower() @@ -137,8 +142,10 @@ async def stream( input: dict[str, Any] | None = None, options: UiPathStreamOptions | None = None, ) -> AsyncGenerator[UiPathRuntimeEvent, None]: + """Stream events from the number analytics runtime.""" logger.info("NumberAnalyticsRuntime: stream() invoked") yield await self.execute(input=input, options=options) async def dispose(self) -> None: + """Dispose of any resources used by the number analytics runtime.""" logger.info("NumberAnalyticsRuntime: dispose() invoked") diff --git a/src/uipath/dev/_demo/mock_support_runtime.py b/demo/mock_support_runtime.py similarity index 92% rename from src/uipath/dev/_demo/mock_support_runtime.py rename to demo/mock_support_runtime.py index a417001..93bde6b 100644 --- a/src/uipath/dev/_demo/mock_support_runtime.py +++ b/demo/mock_support_runtime.py @@ -1,3 +1,5 @@ +"""Mock runtime that simulates a support chat agent.""" + import asyncio import logging from typing import Any, AsyncGenerator @@ -12,7 +14,7 @@ ) from uipath.runtime.schema import UiPathRuntimeSchema -ENTRYPOINT_SUPPORT_CHAT = "agent/support.py:chat" +ENTRYPOINT_SUPPORT_CHAT = "agent/support.py:main" logger = logging.getLogger(__name__) @@ -21,10 +23,12 @@ class MockSupportChatRuntime: """Mock runtime that simulates a tiny support agent.""" def __init__(self, entrypoint: str = ENTRYPOINT_SUPPORT_CHAT) -> None: + """Initialize the MockSupportChatRuntime.""" self.entrypoint = entrypoint self.tracer = trace.get_tracer("uipath.dev.mock.support-chat") async def get_schema(self) -> UiPathRuntimeSchema: + """Get the schema for the support chat runtime.""" return UiPathRuntimeSchema( filePath=self.entrypoint, uniqueId="mock-support-chat-runtime", @@ -60,6 +64,7 @@ async def execute( input: dict[str, Any] | None = None, options: UiPathExecuteOptions | None = None, ) -> UiPathRuntimeResult: + """Execute the support chat runtime.""" payload = input or {} message = str(payload.get("message", "")).strip() previous = payload.get("previousIssues") or [] @@ -139,8 +144,10 @@ async def stream( input: dict[str, Any] | None = None, options: UiPathStreamOptions | None = None, ) -> AsyncGenerator[UiPathRuntimeEvent, None]: + """Stream events from the support chat runtime.""" logger.info("SupportChatRuntime: stream() invoked") yield await self.execute(input=input, options=options) async def dispose(self) -> None: + """Dispose of any resources used by the support chat runtime.""" logger.info("SupportChatRuntime: dispose() invoked") diff --git a/src/uipath/dev/_demo/mock_context_runtime.py b/demo/mock_telemetry_runtime.py similarity index 97% rename from src/uipath/dev/_demo/mock_context_runtime.py rename to demo/mock_telemetry_runtime.py index 22c2cf4..8f2c44a 100644 --- a/src/uipath/dev/_demo/mock_context_runtime.py +++ b/demo/mock_telemetry_runtime.py @@ -1,3 +1,5 @@ +"""Mock runtime that simulates a multi-step workflow with rich telemetry.""" + import asyncio import logging from typing import Any, AsyncGenerator @@ -10,17 +12,19 @@ UiPathRuntimeStatus, UiPathStreamOptions, ) +from uipath.runtime.debug import UiPathBreakpointResult from uipath.runtime.schema import UiPathRuntimeSchema -ENTRYPOINT_CONTEXT = "agent/context.py:run" +ENTRYPOINT_TELEMETRY = "agent/telemetry.py:run" logger = logging.getLogger(__name__) -class MockContextRuntime: +class MockTelemetryRuntime: """A mock runtime that simulates a multi-step workflow with rich telemetry.""" - def __init__(self, entrypoint: str = ENTRYPOINT_CONTEXT) -> None: + def __init__(self, entrypoint: str = ENTRYPOINT_TELEMETRY) -> None: + """Initialize the MockTelemetryRuntime.""" self.entrypoint = entrypoint self.tracer = trace.get_tracer("uipath.dev.mock.context") # State tracking for breakpoints @@ -39,6 +43,7 @@ def __init__(self, entrypoint: str = ENTRYPOINT_CONTEXT) -> None: ] async def get_schema(self) -> UiPathRuntimeSchema: + """Get the schema for the mock telemetry runtime.""" return UiPathRuntimeSchema( filePath=self.entrypoint, uniqueId="mock-runtime", @@ -60,8 +65,7 @@ async def execute( input: dict[str, Any] | None = None, options: UiPathExecuteOptions | None = None, ) -> UiPathRuntimeResult: - from uipath.runtime.debug import UiPathBreakpointResult - + """Execute the mock telemetry runtime.""" payload = input or {} entrypoint = "mock-entrypoint" message = str(payload.get("message", "")) @@ -454,10 +458,12 @@ async def stream( input: dict[str, Any] | None = None, options: UiPathStreamOptions | None = None, ) -> AsyncGenerator[UiPathRuntimeEvent, None]: + """Stream events from the mock telemetry runtime.""" logger.info("MockRuntime: stream() invoked") print("[MockRuntime] stream() invoked") yield await self.execute(input=input, options=options) async def dispose(self) -> None: + """Dispose of any resources used by the mock telemetry runtime.""" logger.info("MockRuntime: dispose() invoked") print("[MockRuntime] dispose() invoked") diff --git a/demo/mock_template_runtime.py b/demo/mock_template_runtime.py new file mode 100644 index 0000000..25984b9 --- /dev/null +++ b/demo/mock_template_runtime.py @@ -0,0 +1,193 @@ +"""Mock runtime that replays events from a JSON file.""" + +import asyncio +import json +import logging +from pathlib import Path +from typing import Any, AsyncGenerator, cast + +from opentelemetry import trace +from uipath.core.chat import UiPathConversationMessageEvent +from uipath.runtime import ( + UiPathExecuteOptions, + UiPathRuntimeEvent, + UiPathRuntimeResult, + UiPathRuntimeStatus, + UiPathStreamOptions, +) +from uipath.runtime.events import ( + UiPathRuntimeMessageEvent, + UiPathRuntimeStateEvent, +) +from uipath.runtime.schema import ( + UiPathRuntimeEdge, + UiPathRuntimeGraph, + UiPathRuntimeNode, + UiPathRuntimeSchema, +) + +logger = logging.getLogger(__name__) + + +class MockTemplateRuntime: + """Mock runtime that replays events from a JSON file.""" + + def __init__( + self, + events_file: str | Path, + schema_file: str | Path, + ) -> None: + """Initialize the MockTemplateRuntime.""" + self.events_file = Path(events_file) + self.schema_file = Path(schema_file) + self.tracer = trace.get_tracer("uipath.dev.mock.template") + self._events: list[dict[str, Any]] = [] + self._schema_data: dict[str, Any] | None = None + self._load_events() + self._load_schema() + + def _load_events(self) -> None: + """Load events from JSON file.""" + with open(self.events_file, "r", encoding="utf-8") as f: + data = json.load(f) + + if isinstance(data, list): + self._events = data + else: + raise ValueError("Expected JSON array of events") + + def _load_schema(self) -> None: + """Load schema from separate JSON file if provided.""" + with open(self.schema_file, "r", encoding="utf-8") as f: + self._schema_data = json.load(f) + + async def get_schema(self) -> UiPathRuntimeSchema: + """Get runtime schema from the loaded data or build default.""" + assert self._schema_data is not None + entry_points = self._schema_data.get("entryPoints", []) + assert entry_points is not None and len(entry_points) > 0 + ep = entry_points[0] + + # Build graph if present + graph = None + if "graph" in ep and ep["graph"]: + graph_data = ep["graph"] + nodes = [UiPathRuntimeNode(**node) for node in graph_data.get("nodes", [])] + edges = [UiPathRuntimeEdge(**edge) for edge in graph_data.get("edges", [])] + graph = UiPathRuntimeGraph(nodes=nodes, edges=edges) + + return UiPathRuntimeSchema( + filePath=ep["filePath"], + uniqueId=ep["uniqueId"], + type=ep["type"], + input=ep["input"], + output=ep["output"], + graph=graph, + ) + + async def execute( + self, + input: dict[str, Any] | None = None, + options: UiPathExecuteOptions | None = None, + ) -> UiPathRuntimeResult: + """Execute by replaying all events and returning final result.""" + logger.info("MockTemplateRuntime: starting execution") + + # Stream all events and capture the final result + final_result = None + async for event in self.stream( + input=input, options=cast(UiPathStreamOptions, options) + ): + if isinstance(event, UiPathRuntimeResult): + final_result = event + + return final_result or UiPathRuntimeResult( + output={}, + status=UiPathRuntimeStatus.SUCCESSFUL, + ) + + async def stream( + self, + input: dict[str, Any] | None = None, + options: UiPathStreamOptions | None = None, + ) -> AsyncGenerator[UiPathRuntimeEvent, None]: + """Stream events from the JSON file.""" + logger.info(f"MockTemplateRuntime: streaming {len(self._events)} events") + + with self.tracer.start_as_current_span( + "template.stream", + attributes={ + "uipath.runtime.name": "MockTemplateRuntime", + "uipath.event.count": len(self._events), + }, + ): + for i, event_data in enumerate(self._events): + event_type = event_data.get("event_type") + + # Add small delay between events for realistic streaming + if i > 0: + await asyncio.sleep(0.01) + + try: + if event_type == "runtime_message": + payload_data = event_data.get("payload", {}) + + conversation_event = ( + UiPathConversationMessageEvent.model_validate(payload_data) + ) + + yield UiPathRuntimeMessageEvent( + payload=conversation_event, + execution_id=event_data.get("execution_id"), + metadata=event_data.get("metadata"), + ) + + elif event_type == "runtime_state": + yield UiPathRuntimeStateEvent( + payload=event_data.get("payload", {}), + node_name=event_data.get("node_name"), + execution_id=event_data.get("execution_id"), + metadata=event_data.get("metadata"), + ) + + elif event_type == "runtime_result": + yield UiPathRuntimeResult( + output=event_data.get("output"), + status=UiPathRuntimeStatus( + event_data.get("status", "successful") + ), + execution_id=event_data.get("execution_id"), + metadata=event_data.get("metadata"), + ) + + else: + logger.warning(f"Unknown event type: {event_type}") + + except Exception as e: + logger.error(f"Error processing event {i}: {e}", exc_info=True) + continue + + logger.info("MockTemplateRuntime: streaming completed") + + async def dispose(self) -> None: + """Cleanup resources.""" + logger.info("MockTemplateRuntime: dispose() invoked") + + +def create_template_runtime( + events_json: str | Path, + schema_json: str | Path, +) -> MockTemplateRuntime: + """Create a template runtime from JSON files. + + Args: + events_json: Path to JSON file containing events array + schema_json: Path to entry-points.json schema file + + Returns: + MockTemplateRuntime instance + """ + return MockTemplateRuntime( + events_file=events_json, + schema_file=schema_json, + ) diff --git a/pyproject.toml b/pyproject.toml index 64b6ad9..f74c963 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -27,7 +27,7 @@ Repository = "https://github.com/UiPath/uipath-dev-python" Documentation = "https://uipath.github.io/uipath-python/" [project.scripts] -uipath-dev = "uipath.dev._demo.run_dev_console:main" +uipath-dev = "uipath.dev.__mock__:main" [build-system] requires = ["hatchling"] @@ -51,6 +51,9 @@ dev = [ [tool.hatch.build.targets.wheel] packages = ["src/uipath"] +[tool.hatch.build.targets.sdist] +exclude = ["demo"] + [tool.ruff] line-length = 88 indent-width = 4 diff --git a/src/uipath/dev/__mock__.py b/src/uipath/dev/__mock__.py new file mode 100644 index 0000000..6da0f4e --- /dev/null +++ b/src/uipath/dev/__mock__.py @@ -0,0 +1,33 @@ +"""Run the UiPath Developer Console with a mock runtime factory.""" + +import sys +from pathlib import Path + +from uipath.core.tracing import UiPathTraceManager + +from uipath.dev import UiPathDeveloperConsole + +# Add demo to path for local development +demo_path = Path(__file__).parent.parent.parent.parent / "demo" +if demo_path.exists(): + sys.path.insert(0, str(demo_path.parent)) + + +def main(): + """Run the developer console with the mock runtime factory.""" + try: + # Import from demo (only works locally, not in published package) + from demo.mock_factory import MockRuntimeFactory + + trace_manager = UiPathTraceManager() + factory = MockRuntimeFactory() + app = UiPathDeveloperConsole( + runtime_factory=factory, trace_manager=trace_manager + ) + app.run() + except ImportError: + print("Demo not available in installed package") + + +if __name__ == "__main__": + main() diff --git a/src/uipath/dev/_demo/__init__.py b/src/uipath/dev/_demo/__init__.py deleted file mode 100644 index e69de29..0000000 diff --git a/src/uipath/dev/_demo/run_dev_console.py b/src/uipath/dev/_demo/run_dev_console.py deleted file mode 100644 index 00033d2..0000000 --- a/src/uipath/dev/_demo/run_dev_console.py +++ /dev/null @@ -1,15 +0,0 @@ -from uipath.core.tracing import UiPathTraceManager - -from uipath.dev import UiPathDeveloperConsole -from uipath.dev._demo.mock_runtime import MockRuntimeFactory - - -def main(): - trace_manager = UiPathTraceManager() - factory = MockRuntimeFactory() - app = UiPathDeveloperConsole(runtime_factory=factory, trace_manager=trace_manager) - app.run() - - -if __name__ == "__main__": - main()