diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/.gitignore b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/.gitignore new file mode 100644 index 0000000000000..990c18de22908 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/.gitignore @@ -0,0 +1,153 @@ +llama_index/_static +.DS_Store +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +bin/ +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +etc/ +include/ +lib/ +lib64/ +parts/ +sdist/ +share/ +var/ +wheels/ +pip-wheel-metadata/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +.ruff_cache + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# Sphinx documentation +docs/_build/ + +# PyBuilder +target/ + +# Jupyter Notebook +.ipynb_checkpoints +notebooks/ + +# IPython +profile_default/ +ipython_config.py + +# pyenv +.python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ +pyvenv.cfg + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# Jetbrains +.idea +modules/ +*.swp + +# VsCode +.vscode + +# pipenv +Pipfile +Pipfile.lock + +# pyright +pyrightconfig.json diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/BUILD b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/BUILD new file mode 100644 index 0000000000000..0896ca890d8bf --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/BUILD @@ -0,0 +1,3 @@ +poetry_requirements( + name="poetry", +) diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/Makefile b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/Makefile new file mode 100644 index 0000000000000..b9eab05aa3706 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/Makefile @@ -0,0 +1,17 @@ +GIT_ROOT ?= $(shell git rev-parse --show-toplevel) + +help: ## Show all Makefile targets. + @grep -E '^[a-zA-Z_-]+:.*?## .*$$' $(MAKEFILE_LIST) | awk 'BEGIN {FS = ":.*?## "}; {printf "\033[33m%-30s\033[0m %s\n", $$1, $$2}' + +format: ## Run code autoformatters (black). + pre-commit install + git ls-files | xargs pre-commit run black --files + +lint: ## Run linters: pre-commit (black, ruff, codespell) and mypy + pre-commit install && git ls-files | xargs pre-commit run --show-diff-on-failure --files + +test: ## Run tests via pytest. + pytest tests + +watch-docs: ## Build and watch documentation. + sphinx-autobuild docs/ docs/_build/html --open-browser --watch $(GIT_ROOT)/llama_index/ diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/README.md b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/README.md new file mode 100644 index 0000000000000..e10552f751ba4 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/README.md @@ -0,0 +1,146 @@ +# LlamaIndex Readers Integration: + +## ChatGPT Conversations Reader and Message Node Parser + +[![License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE) + +A custom reader and node parser for processing exported ChatGPT conversation JSON files using [LlamaIndex](https://github.com/jerryjliu/llama_index). This package allows you to load and parse your ChatGPT conversation data, enabling advanced querying and analysis using LlamaIndex's indexing and querying capabilities. + +## **Table of Contents** + +- [Installation](#installation) +- [Features](#features) +- [Usage](#usage) + - [Loading Conversations](#loading-conversations) + - [Parsing Messages](#parsing-messages) + - [Building an Index](#building-an-index) +- [Examples](#examples) +- [Tests](#tests) +- [Contributing](#contributing) +- [License](#license) + +## **Installation** + +```bash +pip install llama-index-readers-chatgpt-conversations +``` + +## **Features** + +- **ChatGPT Conversation Reader**: Load exported ChatGPT conversation JSON files into LlamaIndex `Document` objects. +- **Message Parser**: Parse conversation documents into structured nodes with speaker identities and metadata. +- **Markdown Support**: Process Markdown content within messages, including headers, code blocks, and inline code. +- **Node Relationships**: Maintain relationships between nodes for contextual understanding. + +## **Usage** + +### **1. Loading Conversations** + +Use the `ChatGPTConversationsReader` to load your exported ChatGPT conversation JSON file. + +```python +from llama_index.readers.chatgpt_conversation_json import ( + ChatGPTConversationsReader, +) + +# Initialize the reader with the path to your conversations.json file +reader = ChatGPTConversationsReader(input_file="path/to/conversations.json") + +# Load documents +documents = reader.load_data() +print(f"Loaded {len(documents)} documents.") +``` + +### **2. Parsing Messages** + +Use the `ChatGPTMessageNodeParser` to parse the loaded documents into nodes. + +```python +from llama_index.readers.chatgpt_conversation_json import ( + ChatGPTMessageNodeParser, +) + +# Initialize the message parser +parser = ChatGPTMessageNodeParser() + +# Parse documents into nodes +nodes = parser(documents) +print(f"Parsed {len(nodes)} nodes.") +``` + +### **3. Building an Index** + +Leverage LlamaIndex to build an index over the parsed nodes for querying. + +```python +from llama_index import VectorStoreIndex, StorageContext + +# Create a storage context (e.g., using a default in-memory store) +storage_context = StorageContext.from_defaults() + +# Build the index +index = VectorStoreIndex(nodes, storage_context=storage_context) + +# (Optional) Persist the index for later use +storage_context.persist(persist_dir="./storage") +``` + +## **Examples** + +Here's a full example combining all steps: + +```python +from llama_index.readers.chatgpt_conversation_json import ( + ChatGPTConversationsReader, + ChatGPTMessageNodeParser, +) +from llama_index.core import VectorStoreIndex, StorageContext + +# Step 1: Load conversations +reader = ChatGPTConversationsReader(input_file="path/to/conversations.json") +documents = reader.load_data() + +# Step 2: Parse messages into nodes +parser = ChatGPTMessageNodeParser() +nodes = parser(documents) + +# Step 3: Build an index over the nodes +storage_context = StorageContext.from_defaults() +index = VectorStoreIndex(nodes, storage_context=storage_context) + +# Step 4: Query the index +query_engine = index.as_query_engine() +response = query_engine.query("What did I ask about data export?") +print(response) +``` + +## **Tests** + +To run the tests, navigate to the project root directory and execute: + +```bash +pytest tests +``` + +## **License** + +This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details. + +--- + +## **Additional Notes** + +- **Dependencies**: + + - `llama_index_core` + - `markdown-it-py` + +- **Compatibility**: The package is compatible with Python 3.8 and above. + +- **Publishing**: Update the `pyproject.toml` with the appropriate package name, version, and author information before publishing to PyPI. + +--- + +## **Happy Coding!** + +Feel free to reach out if you have any questions or need further assistance. diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/examples/BUILD b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/examples/BUILD new file mode 100644 index 0000000000000..db46e8d6c978c --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/examples/BUILD @@ -0,0 +1 @@ +python_sources() diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/examples/main.py b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/examples/main.py new file mode 100644 index 0000000000000..0075c8689342a --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/examples/main.py @@ -0,0 +1,27 @@ +from llama_index.readers.chatgpt_conversations import ( + ChatGPTConversationsReader, + ChatGPTMessageNodeParser, +) + +# Specify the path to your conversations.json file +conversations_file = "path/to/your/conversations.json" # Update this path + +# Initialize the ChatGPTConversationsReader +reader = ChatGPTConversationsReader(input_file=conversations_file) + +# Load conversations as Documents +documents = reader.load_data() +print(f"Number of documents loaded: {len(documents)}") + +# Initialize the ChatGPTMessageNodeParser +parser = ChatGPTMessageNodeParser() + +# Parse documents into nodes +nodes = parser(documents) +print(f"Number of nodes parsed: {len(nodes)}") + +# Optionally, print out some information about the first few nodes +for i, node in enumerate(nodes[:5]): + print(f"\nNode {i + 1}:") + print(f"Text: {node.text}") + print(f"Metadata: {node.metadata}") diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/BUILD b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/BUILD new file mode 100644 index 0000000000000..db46e8d6c978c --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/BUILD @@ -0,0 +1 @@ +python_sources() diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/__init__.py b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/__init__.py new file mode 100644 index 0000000000000..0478db1cead37 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/__init__.py @@ -0,0 +1,6 @@ +from llama_index.readers.chatgpt_conversations.base import ChatGPTConversationsReader +from llama_index.readers.chatgpt_conversations.message_node_parser import ( + ChatGPTMessageNodeParser, +) + +__all__ = ["ChatGPTConversationsReader", "ChatGPTMessageNodeParser"] diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/base.py b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/base.py new file mode 100644 index 0000000000000..d5698da0f2bc1 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/base.py @@ -0,0 +1,172 @@ +import json +from typing import Any, Dict, List, Tuple, Optional, Union +from datetime import datetime +from pathlib import Path +from llama_index.core.readers.base import BaseReader +from llama_index.core.schema import Document + + +class ChatGPTConversationsReader(BaseReader): + """Custom JSON Reader for structured ChatGPT conversation data.""" + + def __init__( + self, + input_file: Union[str, Path], + ensure_ascii: bool = False, + is_jsonl: Optional[bool] = False, + max_items: Optional[int] = None, + ) -> None: + """Initialize with arguments.""" + super().__init__() + self.input_file = Path(input_file) + self.ensure_ascii = ensure_ascii + self.is_jsonl = is_jsonl + self.max_items = max_items + + def load_data(self, extra_info: Optional[Dict] = {}) -> List[Document]: + """Load data from the input file.""" + with open(self.input_file, encoding="utf-8") as f: + data = ( + json.load(f) + if not self.is_jsonl + else [json.loads(line.strip()) for line in f] + ) + + # Ensure data is a list of conversations + if isinstance(data, dict): + load_data = [data] + elif isinstance(data, list): + load_data = data + else: + raise ValueError("Invalid JSON format: Expected a dict or list.") + + documents = [] + processed_count = 0 + + # Loop through each conversation in the JSON array + for conversation in load_data: + if self.max_items is not None and processed_count >= self.max_items: + break + + # Extract the conversation_id + conversation_id = conversation.get( + "conversation_id", f"doc_{processed_count}" + ) + + # Basic metadata for each conversation + metadata = { + "title": conversation.get("title", "No Title"), + "conversation_id": conversation_id, + "create_time": datetime.fromtimestamp( + conversation.get("create_time", 0) + ).isoformat(), + "update_time": datetime.fromtimestamp( + conversation.get("update_time", 0) + ).isoformat(), + **extra_info, + } + + # Convert the conversation into plain text with speaker identities + ( + conversation_text, + messages_metadata, + ) = self._convert_conversation_to_text(conversation) + + # Add messages metadata to the document metadata + metadata["messages"] = messages_metadata + + # Add the conversation as a Document + documents.append( + Document( + text=conversation_text, + metadata=metadata, + id_=conversation_id, # Use conversation_id as id_ + ) + ) + processed_count += 1 + + print(f"Number of documents created: {len(documents)}") # Debug statement + + return documents + + def _convert_conversation_to_text( + self, conversation: Dict + ) -> Tuple[str, List[Dict[str, Any]]]: + """Convert conversation JSON to plain text with speaker identities and collect message metadata.""" + mapping = conversation.get("mapping", {}) + if not mapping: + print("No 'mapping' found in conversation") + return "", [] # Return empty string if no messages + + # Identify the root node and start processing messages from the root + root_node_id = next( + ( + node_id + for node_id, node in mapping.items() + if node.get("parent") is None + ), + None, + ) + messages = [] + messages_metadata = [] + + def traverse_messages(node_id): + node_data = mapping.get(node_id) + if not node_data: + return + message = node_data.get("message") + if message and "content" in message and "parts" in message["content"]: + message_content = message["content"]["parts"] + # Adjusted this section to handle non-string items + message_text = "" + for part in message_content: + if isinstance(part, str): + message_text += part + elif isinstance(part, dict): + # Convert dict to string (e.g., via JSON) + message_text += json.dumps(part) + else: + # Convert other types to string + message_text += str(part) + author_role = message.get("author", {}).get("role", "unknown") + message_id = node_id # Use node_id as the message_id + + create_time = message.get("create_time") or message.get("update_time") + # Adjust for milliseconds if needed + if create_time and create_time > 1e12: # Timestamp in milliseconds + create_time = create_time / 1000.0 + timestamp = ( + datetime.fromtimestamp(create_time).strftime("%H:%M") + if create_time + else "Unknown time" + ) + message_date = ( + datetime.fromtimestamp(create_time).strftime("%Y-%m-%d") + if create_time + else None + ) + + # Append message text with speaker identity + messages.append(f"{author_role}: {message_text}") + + # Collect message metadata + message_metadata = { + "message_id": message_id, + "author_role": author_role, + "timestamp": timestamp, + "date": message_date, + "text": message_text, + # Include other metadata as needed + } + messages_metadata.append(message_metadata) + for child_id in node_data.get("children", []): + traverse_messages(child_id) + + if root_node_id: + traverse_messages(root_node_id) + else: + print("No root node found in conversation mapping") + + # Join messages into a single text + conversation_text = "\n".join(messages) + return conversation_text, messages_metadata diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/message_node_parser.py b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/message_node_parser.py new file mode 100644 index 0000000000000..2d9cac743d7c7 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/llama_index/readers/chatgpt_conversations/message_node_parser.py @@ -0,0 +1,261 @@ +from typing import Any, Dict, List, Sequence +from markdown_it import MarkdownIt +from llama_index.core.schema import ( + BaseNode, + TextNode, + NodeRelationship, + TransformComponent, +) +from pydantic import Field, ConfigDict + + +class ChatGPTMessageNodeParser(TransformComponent): + """Processes messages from the document text, leveraging speaker identities.""" + + model_config = ConfigDict(arbitrary_types_allowed=True) + md: MarkdownIt = Field(default_factory=MarkdownIt, exclude=True) + + def __call__( + self, + nodes: Sequence[BaseNode], + **kwargs: Any, + ) -> List[TextNode]: + """Process nodes into TextNodes.""" + all_nodes = [] + for doc in nodes: + if not isinstance(doc, BaseNode): + continue + # Split the document text into messages based on speaker identity + messages = self._split_text_into_messages(doc.text) + messages_metadata = doc.metadata.get("messages", []) + # Process messages + doc_nodes = self._process_messages(messages, messages_metadata, doc) + all_nodes.extend(doc_nodes) + return all_nodes + + def _split_text_into_messages(self, text: str) -> List[Dict[str, str]]: + """Split text into messages using speaker identities.""" + # Assuming each message starts with 'user:' or 'assistant:' + messages = [] + lines = text.strip().split("\n") + for line in lines: + if line.startswith(("user:", "assistant:")): + author_role, message_text = line.split(":", 1) + messages.append( + {"author_role": author_role.strip(), "text": message_text.strip()} + ) + return messages + + def _process_messages( + self, + messages: List[Dict[str, str]], + messages_metadata: List[Dict[str, Any]], + doc: BaseNode, + ) -> List[TextNode]: + """Process messages and return TextNodes.""" + nodes = [] + prev_node = None + for idx, message in enumerate(messages): + message_text = message["text"] + author_role = message["author_role"] + # Find metadata for this message + message_metadata = next( + ( + m + for m in messages_metadata + if m["author_role"] == author_role and m["text"] == message_text + ), + {}, + ) + metadata = { + **doc.metadata, + **message_metadata, + } + ref_doc_id = doc.id_ + source_node = doc + + # Process Markdown content + tokens = self.md.parse(message_text) + message_nodes = self._process_tokens( + tokens, metadata, ref_doc_id, source_node + ) + + # Include previous user message for context in assistant messages + if author_role == "assistant" and idx > 0: + # Find the last user message + context_message = messages[idx - 1] + if context_message["author_role"] == "user": + context_text = context_message["text"] + context_metadata = { + **doc.metadata, + **next( + ( + m + for m in messages_metadata + if m["author_role"] == "user" + and m["text"] == context_text + ), + {}, + ), + } + # Process context message + context_tokens = self.md.parse(context_text) + context_nodes = self._process_tokens( + context_tokens, context_metadata, ref_doc_id, source_node + ) + # Set up relationships between context and message nodes + if context_nodes and message_nodes: + for i in range(len(context_nodes) - 1): + context_nodes[i].relationships[ + NodeRelationship.NEXT + ] = context_nodes[i + 1].as_related_node_info() + context_nodes[i + 1].relationships[ + NodeRelationship.PREVIOUS + ] = context_nodes[i].as_related_node_info() + context_nodes[-1].relationships[ + NodeRelationship.NEXT + ] = message_nodes[0].as_related_node_info() + message_nodes[0].relationships[ + NodeRelationship.PREVIOUS + ] = context_nodes[-1].as_related_node_info() + message_nodes = context_nodes + message_nodes + elif context_nodes: + message_nodes = context_nodes + + # Set up relationships within message nodes + for i in range(len(message_nodes) - 1): + message_nodes[i].relationships[NodeRelationship.NEXT] = message_nodes[ + i + 1 + ].as_related_node_info() + message_nodes[i + 1].relationships[ + NodeRelationship.PREVIOUS + ] = message_nodes[i].as_related_node_info() + + # Set up relationships with previous node + if prev_node and message_nodes: + message_nodes[0].relationships[ + NodeRelationship.PREVIOUS + ] = prev_node.as_related_node_info() + prev_node.relationships[NodeRelationship.NEXT] = message_nodes[ + 0 + ].as_related_node_info() + + if message_nodes: + prev_node = message_nodes[-1] + nodes.extend(message_nodes) + else: + # Optionally, handle the case where message_nodes is empty + # For example, log a warning or skip to the next message + pass + + return nodes + + def _process_tokens( + self, + tokens: List[Any], + metadata: Dict[str, Any], + ref_doc_id: str, + source_node: BaseNode, + ) -> List[TextNode]: + """Process Markdown tokens into nodes with structure.""" + nodes = [] + current_text = "" + header_path = [] + for idx, token in enumerate(tokens): + # Header handling + if token.type == "heading_open": + if current_text.strip(): + nodes.append( + self._build_text_node( + current_text, + metadata, + "/".join(header_path), + ref_doc_id, + source_node, + ) + ) + current_text = "" + header_level = int(token.tag[1]) + next_token = tokens[idx + 1] if idx + 1 < len(tokens) else None + header_text = next_token.content if next_token else "" + header_path = header_path[: header_level - 1] + [header_text] + # Code block handling + elif token.type == "fence": + if current_text.strip(): + nodes.append( + self._build_text_node( + current_text, + metadata, + "/".join(header_path), + ref_doc_id, + source_node, + ) + ) + current_text = "" + code_language = token.info.strip() or "plain" + code_block = token.content + code_node = TextNode( + text=code_block.strip(), + metadata={ + **metadata, + "Content Type": "code", + "Language": code_language, + "Header Path": "/".join(header_path), + }, + ref_doc_id=ref_doc_id, + source_node=source_node, + ) + nodes.append(code_node) + # Inline code + elif token.type == "code_inline": + inline_code = token.content + current_text += f"`{inline_code}`" + # Paragraph handling + elif token.type == "paragraph_open": + continue + elif token.type == "paragraph_close": + if current_text.strip(): + nodes.append( + self._build_text_node( + current_text, + metadata, + "/".join(header_path), + ref_doc_id, + source_node, + ) + ) + current_text = "" + elif token.type == "inline": + current_text += token.content + " " + # Text + elif token.type == "text": + current_text += token.content + # Handle other token types as needed + + if current_text.strip(): + nodes.append( + self._build_text_node( + current_text, + metadata, + "/".join(header_path), + ref_doc_id, + source_node, + ) + ) + return nodes + + def _build_text_node( + self, + text: str, + metadata: Dict[str, Any], + header_path: str, + ref_doc_id: str, + source_node: BaseNode, + ) -> TextNode: + """Build a text node with metadata.""" + return TextNode( + text=text.strip(), + metadata={**metadata, "Content Type": "text", "Header Path": header_path}, + ref_doc_id=ref_doc_id, + source_node=source_node, + ) diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/poetry.lock 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b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/pyproject.toml @@ -0,0 +1,61 @@ +[build-system] +build-backend = "poetry.core.masonry.api" +requires = ["poetry-core"] + +[tool.codespell] +check-filenames = true +check-hidden = true +# Feel free to un-skip examples, and experimental, you will just need to +# work through many typos (--write-changes and --interactive will help) +skip = "*.csv,*.html,*.json,*.jsonl,*.pdf,*.txt,*.ipynb" + +[tool.llamahub] +contains_example = true +import_path = "llama_index.readers.chatgpt_conversations" + +[tool.llamahub.class_authors] +ChatGPTConversationsReader = "jasonnathan" +ChatGPTMessageNodeParser = "jasonnathan" + +[tool.mypy] +disallow_untyped_defs = true +# Remove venv skip when integrated with pre-commit +exclude = ["_static", "build", "examples", "notebooks", "venv"] +ignore_missing_imports = true +python_version = "3.8" + +[tool.poetry] +authors = ["Jason Joseph Nathan "] +description = "A custom JSON reader for LlamaIndex, parsing ChatGPT-style conversation data." +license = "MIT" +name = "llama-index-readers-chatgpt-conversations" +packages = [{include = "llama_index"}] +readme = "README.md" +version = "0.1.0" + +[tool.poetry.dependencies] +markdown-it-py = "^3.0.0" +python = ">=3.8.1,<4.0" +llama-index-core = "^0.11.21" +pytest = "^6.2" +pytest-asyncio = "^0.18" +llama-index = "^0.11.21" + +[tool.poetry.group.dev.dependencies] +black = {extras = ["jupyter"], version = "<=23.9.1,>=23.7.0"} +codespell = {extras = ["toml"], version = ">=v2.2.6"} +ipython = "8.10.0" +jupyter = "^1.0.0" +mypy = "0.991" +pre-commit = "3.2.0" +pylint = "2.15.10" +pytest = ">=6.2,<7.0" +pytest-mock = "3.11.1" +ruff = "0.0.292" +tree-sitter-languages = "^1.8.0" +types-Deprecated = ">=0.1.0" +types-PyYAML = "^6.0.12.12" +types-protobuf = "^4.24.0.4" +types-redis = "4.5.5.0" +types-requests = "2.28.11.8" # TODO: unpin when mypy>0.991 +types-setuptools = "67.1.0.0" diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/BUILD b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/BUILD new file mode 100644 index 0000000000000..dabf212d7e716 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/BUILD @@ -0,0 +1 @@ +python_tests() diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/__init__.py b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/__init__.py new file mode 100644 index 0000000000000..e69de29bb2d1d diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/test_message_parser.py b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/test_message_parser.py new file mode 100644 index 0000000000000..1485f3b05d678 --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/test_message_parser.py @@ -0,0 +1,39 @@ +from llama_index.readers.chatgpt_conversations import ChatGPTMessageNodeParser +from llama_index.core.schema import Document + + +def test_message_parser(): + # Create a sample document + doc_text = "user: Hello, how can I export my data?\nassistant: You can export your data by..." + metadata = { + "conversation_id": "test_convo_1", + "messages": [ + { + "message_id": "node1", + "author_role": "user", + "text": "Hello, how can I export my data?", + }, + { + "message_id": "node2", + "author_role": "assistant", + "text": "You can export your data by...", + }, + ], + } + doc = Document(text=doc_text, metadata=metadata) + + # Initialize the parser + parser = ChatGPTMessageNodeParser() + + # Parse the document + nodes = parser([doc]) + assert len(nodes) > 0 + + # Check node content + user_node = nodes[0] + assert user_node.metadata["author_role"] == "user" + assert "export my data" in user_node.text + + assistant_node = nodes[-1] + assert assistant_node.metadata["author_role"] == "assistant" + assert "You can export your data" in assistant_node.text diff --git a/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/test_readers_chatgpt-conversation.py b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/test_readers_chatgpt-conversation.py new file mode 100644 index 0000000000000..ea996119d274f --- /dev/null +++ b/llama-index-integrations/readers/llama-index-readers-chatgpt-conversations/tests/test_readers_chatgpt-conversation.py @@ -0,0 +1,56 @@ +from llama_index.readers.chatgpt_conversations import ChatGPTConversationsReader +import json +from pathlib import Path + + +def test_load_data(): + # Prepare a sample conversation JSON + sample_conversation = { + "title": "Sample Conversation", + "create_time": 1690000000, + "update_time": 1690003600, + "conversation_id": "test_convo_1", + "mapping": { + "node1": { + "parent": None, + "children": ["node2"], + "message": { + "id": "node1", + "author": {"role": "user"}, + "create_time": 1690000000, + "content": {"parts": ["Hello, how can I export my data?"]}, + }, + }, + "node2": { + "parent": "node1", + "children": [], + "message": { + "id": "node2", + "author": {"role": "assistant"}, + "create_time": 1690000100, + "content": {"parts": ["You can export your data by..."]}, + }, + }, + }, + } + + # Write sample data to a temporary JSON file + temp_file = Path("temp_conversation.json") + with temp_file.open("w", encoding="utf-8") as f: + json.dump([sample_conversation], f) + + # Initialize the reader + reader = ChatGPTConversationsReader(input_file=str(temp_file)) + + # Load data + documents = reader.load_data() + assert len(documents) == 1 + + # Check document content + doc = documents[0] + assert doc.metadata["title"] == "Sample Conversation" + assert "user: Hello, how can I export my data?" in doc.text + assert "assistant: You can export your data by..." in doc.text + + # Clean up + temp_file.unlink()