fix: add support for pydantic v1 users

README.md

@@ -1,7 +1,7 @@
 <div align="center">
 
-<img src="assets/logo-light-mode.png#gh-light-mode-only" alt="lanarky-logo-light-mode" width="500">
-<img src="assets/logo-dark-mode.png#gh-dark-mode-only" alt="lanarky-logo-dark-mode" width="500">
+<img src="https://raw.githubusercontent.com/ajndkr/lanarky/main/assets/logo-light-mode.png#gh-light-mode-only" alt="lanarky-logo-light-mode" width="500">
+<img src="https://raw.githubusercontent.com/ajndkr/lanarky/main/assets/logo-dark-mode.png#gh-dark-mode-only" alt="lanarky-logo-dark-mode" width="500">
 
 <h4>The web framework for building LLM microservices.</h4>
 

README.pypi.md

@@ -0,0 +1,53 @@
+<div align="center">
+
+<img src="https://raw.githubusercontent.com/ajndkr/lanarky/main/assets/logo-light-mode.png#gh-light-mode-only" alt="lanarky-logo-light-mode" width="500">
+
+<h4>The web framework for building LLM microservices.</h4>
+
+[![Stars](https://img.shields.io/github/stars/ajndkr/lanarky)](https://github.com/ajndkr/lanarky/stargazers)
+[![License](https://img.shields.io/badge/License-MIT-yellow.svg)](https://github.com/ajndkr/lanarky/blob/main/LICENSE)
+[![Twitter](https://img.shields.io/twitter/follow/LanarkyAPI?style=social)](https://twitter.com/intent/follow?screen_name=LanarkyAPI)
+[![Discord](https://img.shields.io/badge/join-Discord-7289da.svg)](https://discord.gg/6qUfrQAEeE)
+
+[![Python](https://img.shields.io/pypi/pyversions/lanarky.svg)](https://pypi.org/project/lanarky/)
+[![Coverage](https://coveralls.io/repos/github/ajndkr/lanarky/badge.svg?branch=main)](https://coveralls.io/github/ajndkr/lanarky?branch=main)
+[![Version](https://badge.fury.io/py/lanarky.svg)](https://pypi.org/project/lanarky/)
+[![Stats](https://img.shields.io/pypi/dm/lanarky.svg)](https://pypistats.org/packages/lanarky)
+
+</div>
+
+Lanarky is a **python (3.9+)** web framework for developers who want to build microservices using LLMs.
+Here are some of its key features:
+
+- **LLM-first**: Unlike other web frameworks, lanarky is built specifically for LLM developers.
+  It's unopinionated in terms of how you build your microservices and guarantees zero vendor lock-in
+  with any LLM tooling frameworks or cloud providers
+- **Fast & Modern**: Built on top of FastAPI, lanarky offers all the FastAPI features you know and love.
+  If you are new to FastAPI, visit [fastapi.tiangolo.com](https://fastapi.tiangolo.com) to learn more
+- **Streaming**: Streaming is essential for many real-time LLM applications, like chatbots. Lanarky has
+  got you covered with built-in streaming support over **HTTP** and **WebSockets**.
+- **Open-source**: Lanarky is open-source and free to use. Forever.
+
+To learn more about lanarky and get started, you can find the full documentation on [lanarky.ajndkr.com](https://lanarky.ajndkr.com)
+
+## Installation
+
+The library is available on PyPI and can be installed via `pip`:
+
+```bash
+pip install lanarky
+```
+
+## Contributing
+
+[![Code check](https://github.com/ajndkr/lanarky/actions/workflows/code-check.yaml/badge.svg)](https://github.com/ajndkr/lanarky/actions/workflows/code-check.yaml)
+[![Publish](https://github.com/ajndkr/lanarky/actions/workflows/publish.yaml/badge.svg)](https://github.com/ajndkr/lanarky/actions/workflows/publish.yaml)
+
+Contributions are more than welcome! If you have an idea for a new feature or want to help improve lanarky,
+please create an issue or submit a pull request on [GitHub](https://github.com/ajndkr/lanarky).
+
+See [CONTRIBUTING.md](https://github.com/ajndkr/lanarky/blob/main/CONTRIBUTING.md) for more information.
+
+## License
+
+The library is released under the [MIT License](https://github.com/ajndkr/lanarky/blob/main/LICENSE).

lanarky/adapters/langchain/callbacks.py

@@ -1,5 +1,5 @@
 from enum import Enum
-from typing import Any, Optional, Union
+from typing import Any, Optional
 
 from fastapi.websockets import WebSocket
 from langchain.callbacks.base import AsyncCallbackHandler
@@ -12,6 +12,7 @@
 from starlette.types import Message, Send
 
 from lanarky.events import Events, ServerSentEvent, ensure_bytes
+from lanarky.utils import model_dump_json
 
 
 class LangchainEvents(str, Enum):
@@ -88,7 +89,7 @@ class TokenEventData(BaseModel):
     token: str = ""
 
 
-def get_token_data(token: str, mode: TokenStreamMode) -> Union[str, dict[str, Any]]:
+def get_token_data(token: str, mode: TokenStreamMode) -> str:
     """Get token data based on mode.
 
     Args:
@@ -101,7 +102,7 @@ def get_token_data(token: str, mode: TokenStreamMode) -> Union[str, dict[str, An
     if mode == TokenStreamMode.TEXT:
         return token
     else:
-        return TokenEventData(token=token).model_dump_json()
+        return model_dump_json(TokenEventData(token=token))
 
 
 class TokenStreamingCallbackHandler(StreamingCallbackHandler):
@@ -188,9 +189,9 @@ async def on_chain_end(
                 document.dict() for document in outputs["source_documents"]
             ]
             message = self._construct_message(
-                data=SourceDocumentsEventData(
-                    source_documents=source_documents
-                ).model_dump_json(),
+                data=model_dump_json(
+                    SourceDocumentsEventData(source_documents=source_documents)
+                ),
                 event=LangchainEvents.SOURCE_DOCUMENTS,
             )
             await self.send(message)
@@ -374,9 +375,9 @@ async def on_chain_end(
                 document.dict() for document in outputs["source_documents"]
             ]
             message = self._construct_message(
-                data=SourceDocumentsEventData(
-                    source_documents=source_documents
-                ).model_dump_json(),
+                data=model_dump_json(
+                    SourceDocumentsEventData(source_documents=source_documents)
+                ),
                 event=LangchainEvents.SOURCE_DOCUMENTS,
             )
             await self.websocket.send_json(message)

lanarky/adapters/langchain/dependencies.py

@@ -4,6 +4,7 @@
 from langchain.chains.base import Chain
 
 from lanarky.adapters.langchain.utils import create_request_model, create_response_model
+from lanarky.utils import model_dump
 
 
 def Depends(
@@ -34,6 +35,6 @@ async def chain_dependency(
         request: request_model,
         chain: Chain = params.Depends(dependency, use_cache=use_cache),
     ) -> response_model:
-        return await chain.acall(inputs=request.model_dump(), **dependency_kwargs)
+        return await chain.acall(inputs=model_dump(request), **dependency_kwargs)
 
     return params.Depends(chain_dependency, use_cache=use_cache)

lanarky/adapters/langchain/utils.py

@@ -19,6 +19,7 @@
 from lanarky.adapters.langchain.responses import HTTPStatusDetail, StreamingResponse
 from lanarky.events import Events
 from lanarky.logging import logger
+from lanarky.utils import model_dump
 from lanarky.websockets import WebSocket, WebsocketSession
 
 
@@ -43,7 +44,7 @@ async def factory_endpoint(
         request: request_model, chain: Chain = Depends(endpoint)
     ):
         return StreamingResponse(
-            chain=chain, config={"inputs": request.model_dump(), "callbacks": callbacks}
+            chain=chain, config={"inputs": model_dump(request), "callbacks": callbacks}
         )
 
     return factory_endpoint
@@ -70,7 +71,7 @@ async def factory_endpoint(websocket: WebSocket, chain: Chain = Depends(endpoint
             async for data in session:
                 try:
                     await chain.acall(
-                        inputs=request_model(**data).model_dump(),
+                        inputs=model_dump(request_model(**data)),
                         callbacks=callbacks,
                     )
                 except Exception as e:

lanarky/adapters/openai/dependencies.py

@@ -2,6 +2,8 @@
 
 from fastapi import params
 
+from lanarky.utils import model_dump
+
 from .resources import OpenAIResource
 from .utils import create_request_model, create_response_model
 
@@ -34,7 +36,7 @@ async def resource_dependency(
         request: request_model,
         resource: OpenAIResource = params.Depends(dependency, use_cache=use_cache),
     ) -> response_model:
-        resource_kwargs = {**request.model_dump(), **dependency_kwargs}
+        resource_kwargs = {**model_dump(request), **dependency_kwargs}
 
         return await resource(**resource_kwargs)
 

lanarky/adapters/openai/resources.py

@@ -5,6 +5,8 @@
 from openai.types.chat import ChatCompletion, ChatCompletionChunk
 from pydantic import BaseModel, Field
 
+from lanarky.utils import model_dump
+
 
 class Message(BaseModel):
     role: str = Field(pattern=r"^(user|assistant)$")
@@ -105,5 +107,5 @@ async def __call__(self, messages: list[dict]) -> ChatCompletion:
 
     def _prepare_messages(self, messages: list[dict]) -> list[dict]:
         if self.system is not None:
-            messages = [self.system.model_dump()] + messages
+            messages = [model_dump(self.system)] + messages
         return messages

lanarky/adapters/openai/utils.py

@@ -7,6 +7,7 @@
 
 from lanarky.events import Events
 from lanarky.logging import logger
+from lanarky.utils import model_dump, model_fields
 from lanarky.websockets import WebSocket, WebsocketSession
 
 from .resources import ChatCompletion, ChatCompletionResource, Message, OpenAIResource
@@ -31,7 +32,7 @@ def build_factory_api_endpoint(
     async def factory_endpoint(
         request: request_model, resource: OpenAIResource = Depends(endpoint)
     ):
-        return StreamingResponse(resource=resource, **request.model_dump())
+        return StreamingResponse(resource=resource, **model_dump(request))
 
     return factory_endpoint
 
@@ -58,7 +59,7 @@ async def factory_endpoint(
             async for data in session:
                 try:
                     async for chunk in resource.stream_response(
-                        **request_model(**data).model_dump()
+                        **model_dump(request_model(**data))
                     ):
                         await websocket.send_json(
                             dict(
@@ -153,7 +154,7 @@ def create_response_model(
         raise TypeError("resource must be a ChatCompletion instance")
 
     response_fields = {
-        k: (v.annotation, ...) for k, v in ChatCompletion.model_fields.items()
+        k: (v.annotation, ...) for k, v in model_fields(ChatCompletion).items()
     }
 
     prefix = prefix or resource.__class__.__name__

lanarky/utils.py

@@ -0,0 +1,42 @@
+from typing import Any
+
+import pydantic
+from pydantic.fields import FieldInfo
+
+PYDANTIC_V2 = pydantic.VERSION.startswith("2.")
+
+
+def model_dump(model: pydantic.BaseModel, **kwargs) -> dict[str, Any]:
+    """Dump a pydantic model to a dictionary.
+
+    Args:
+        model: A pydantic model.
+    """
+    if PYDANTIC_V2:
+        return model.model_dump(**kwargs)
+    else:
+        return model.dict(**kwargs)
+
+
+def model_dump_json(model: pydantic.BaseModel, **kwargs) -> str:
+    """Dump a pydantic model to a JSON string.
+
+    Args:
+        model: A pydantic model.
+    """
+    if PYDANTIC_V2:
+        return model.model_dump_json(**kwargs)
+    else:
+        return model.json(**kwargs)
+
+
+def model_fields(model: pydantic.BaseModel) -> dict[str, FieldInfo]:
+    """Get the fields of a pydantic model.
+
+    Args:
+        model: A pydantic model.
+    """
+    if PYDANTIC_V2:
+        return model.model_fields
+    else:
+        return model.__fields__

pyproject.toml

@@ -1,11 +1,12 @@
 [tool.poetry]
 name = "lanarky"
-version = "0.8.0"
+version = "0.8.1"
 description = "The web framework for building LLM microservices"
 authors = ["Ajinkya Indulkar <ajndkr@gmail.com>"]
-readme = "README.md"
-homepage = "https://github.com/ajndkr/lanarky"
+readme = "README.pypi.md"
+homepage = "https://lanarky.ajndkr.com/"
 repository = "https://github.com/ajndkr/lanarky"
+documentation = "https://lanarky.ajndkr.com/"
 license = "MIT"
 packages = [{include = "lanarky"}]