API Agent Reference
Here we handle the connection to external software tools via the parameterisation of API calls by the LLM.
Base classes
The abstract base classes
Abstract base classes for API interaction components.
Provides base classes for query builders, fetchers, and interpreters used in API interactions and result processing.
BaseAPIModel
Bases: BaseModel
A base class for all API models.
Includes default fields uuid
and method_name
.
Source code in biochatter/api_agent/base/agent_abc.py
BaseFetcher
Bases: ABC
Abstract base class for fetchers.
A fetcher is responsible for submitting queries (in systems where
submission and fetching are separate) and fetching and saving results of
queries. It has to implement a fetch_results()
method, which can wrap a
multi-step procedure to submit and retrieve. Should implement retry method to
account for connectivity issues or processing times.
Source code in biochatter/api_agent/base/agent_abc.py
fetch_results(query_models, retries=3)
abstractmethod
Fetch results by submitting a query.
Can implement a multi-step procedure if submitting and fetching are distinct processes (e.g., in the case of long processing times as in the case of BLAST).
query_models: list of Pydantic models describing the parameterised
queries
Source code in biochatter/api_agent/base/agent_abc.py
BaseInterpreter
Bases: ABC
Abstract base class for result interpreters.
The interpreter is aware of the nature and structure of the results and can extract and summarise information from them.
Source code in biochatter/api_agent/base/agent_abc.py
summarise_results(question, conversation_factory, response_text)
abstractmethod
Summarise an answer based on the given parameters.
question (str): The question that was asked.
conversation_factory (Callable): A function that creates a
BioChatter conversation.
response_text (str): The response.text returned from the request.
A summary of the answer.
Todo:
Genericise (remove file path and n_lines parameters, and use a
generic way to get the results). The child classes should manage the
specifics of the results.
Source code in biochatter/api_agent/base/agent_abc.py
BaseQueryBuilder
Bases: ABC
An abstract base class for query builders.
Source code in biochatter/api_agent/base/agent_abc.py
structured_output_prompt
property
Define a structured output prompt template.
This provides a default implementation for an API agent that can be overridden by subclasses to return a ChatPromptTemplate-compatible object.
create_runnable(query_parameters, conversation)
abstractmethod
Create a runnable object for executing queries.
Must be implemented by subclasses. Should use the LangChain
create_structured_output_runnable
method to generate the Callable.
query_parameters: A Pydantic data model that specifies the fields of
the API that should be queried.
conversation: A BioChatter conversation object.
A Callable object that can execute the query.
Source code in biochatter/api_agent/base/agent_abc.py
parameterise_query(question, conversation)
abstractmethod
Parameterise a query object.
Parameterises a Pydantic model with the fields of the API based on the given question using a BioChatter conversation instance. Must be implemented by subclasses.
question (str): The question to be answered.
conversation: The BioChatter conversation object containing the LLM
that should parameterise the query.
A list containing one or more parameterised instance(s) of the query
object (Pydantic BaseModel).
Source code in biochatter/api_agent/base/agent_abc.py
BaseTools
Abstract base class for tools.
Source code in biochatter/api_agent/base/agent_abc.py
make_pydantic_tools()
Uses pydantics create_model to create a list of pydantic tools from a dictionary of parameters
Source code in biochatter/api_agent/base/agent_abc.py
The API Agent
Base API agent module.
APIAgent
Source code in biochatter/api_agent/base/api_agent.py
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__init__(conversation_factory, query_builder, fetcher, interpreter)
API agent class to interact with a tool's API for querying and fetching
results. The query fields have to be defined in a Pydantic model
(BaseModel
) and used (i.e., parameterised by the LLM) in the query
builder. Specific API agents are defined in submodules of this directory
(api_agent
). The agent's logic is implemented in the execute
method.
Attributes
conversation_factory (Callable): A function used to create a
BioChatter conversation, providing LLM access.
query_builder (BaseQueryBuilder): An instance of a child of the
BaseQueryBuilder class.
result_fetcher (BaseFetcher): An instance of a child of the
BaseFetcher class.
result_interpreter (BaseInterpreter): An instance of a child of the
BaseInterpreter class.
Source code in biochatter/api_agent/base/api_agent.py
execute(question)
Wrapper that uses class methods to execute the API agent logic. Consists of 1) query generation, 2) query submission, 3) results fetching, and 4) answer extraction. The final answer is stored in the final_answer attribute.
question (str): The question to be answered.
Source code in biochatter/api_agent/base/api_agent.py
fetch_results(query_models)
Fetch the results of the query using the individual API's implementation (either single-step or submit-retrieve).
query_models: list of parameterised query Pydantic models
Source code in biochatter/api_agent/base/api_agent.py
parameterise_query(question)
Use LLM to parameterise a query (a list of Pydantic models) based on the given question using a BioChatter conversation instance.
Source code in biochatter/api_agent/base/api_agent.py
summarise_results(question, response_text)
Summarise the retrieved results to extract the answer to the question.
Source code in biochatter/api_agent/base/api_agent.py
Web APIs
The BLAST tool
Module for handling BLAST API interactions.
Provides functionality for building queries, fetching results, and interpreting BLAST (Basic Local Alignment Search Tool) sequence alignment data.
BlastFetcher
Bases: BaseFetcher
A class for retrieving API results from BLAST.
Retrieves results from BLAST given a parameterised BlastQuery.
TODO add a limit of characters to be returned from the response.text?
Source code in biochatter/api_agent/web/blast.py
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fetch_results(query_models, retries=20)
Submit request and fetch results from BLAST API.
Wraps individual submission and retrieval of results.
query_models: list of Pydantic models of the queries
retries: the number of maximum retries
str: the result from the BLAST API
Source code in biochatter/api_agent/web/blast.py
BlastInterpreter
Bases: BaseInterpreter
A class for interpreting BLAST results.
Source code in biochatter/api_agent/web/blast.py
summarise_results(question, conversation_factory, response_text)
Extract the answer from the BLAST results.
question (str): The question to be answered.
conversation_factory: A BioChatter conversation object.
response_text (str): The response.text returned by NCBI.
str: The extracted answer from the BLAST results.
Source code in biochatter/api_agent/web/blast.py
BlastQueryBuilder
Bases: BaseQueryBuilder
A class for building a BlastQuery object.
Source code in biochatter/api_agent/web/blast.py
create_runnable(query_parameters, conversation)
Create a runnable object for executing queries.
Creates a runnable using the LangChain
create_structured_output_runnable
method.
query_parameters: A Pydantic data model that specifies the fields of
the API that should be queried.
conversation: A BioChatter conversation object.
A Callable object that can execute the query.
Source code in biochatter/api_agent/web/blast.py
parameterise_query(question, conversation)
Generate a BlastQuery object.
Generates the object based on the given question, prompt, and BioChatter conversation. Uses a Pydantic model to define the API fields. Creates a runnable that can be invoked on LLMs that are qualified to parameterise functions.
question (str): The question to be answered.
conversation: The conversation object used for parameterising the
BlastQuery.
BlastQuery: the parameterised query object (Pydantic model)
Source code in biochatter/api_agent/web/blast.py
BlastQueryParameters
Bases: BaseModel
Pydantic model for the parameters of a BLAST query request.
The class is used for configuring and sending a request to the NCBI BLAST query API. The fields are dynamically configured by the LLM based on the user's question.
Source code in biochatter/api_agent/web/blast.py
The OncoKB tool
OncoKB API agent.
OncoKBFetcher
Bases: BaseFetcher
A class for retrieving API results.
Retrieve from OncoKB given a parameterized OncoKBQuery.
Source code in biochatter/api_agent/web/oncokb.py
fetch_results(request_data, retries=3)
Submit the OncoKB query and fetch the results directly.
No multi-step procedure, thus no wrapping of submission and retrieval in this case.
request_data: List of OncoKBQuery objects (Pydantic models)
containing the OncoKB query parameters.
retries: The number of retries to fetch the results.
str: The results of the OncoKB query.
Source code in biochatter/api_agent/web/oncokb.py
OncoKBInterpreter
Bases: BaseInterpreter
Source code in biochatter/api_agent/web/oncokb.py
summarise_results(question, conversation_factory, response_text)
Extract the answer from the BLAST results.
question (str): The question to be answered.
conversation_factory: A BioChatter conversation object.
response_text (str): The response.text returned by OncoKB.
str: The extracted answer from the BLAST results.
Source code in biochatter/api_agent/web/oncokb.py
OncoKBQueryBuilder
Bases: BaseQueryBuilder
A class for building an OncoKBQuery object.
Source code in biochatter/api_agent/web/oncokb.py
create_runnable(query_parameters, conversation)
Creates a runnable object for executing queries using the LangChain
create_structured_output_runnable
method.
query_parameters: A Pydantic data model that specifies the fields of
the API that should be queried.
conversation: A BioChatter conversation object.
A Callable object that can execute the query.
Source code in biochatter/api_agent/web/oncokb.py
parameterise_query(question, conversation)
Generate an OncoKBQuery object.
Generate based on the given question, prompt, and BioChatter conversation. Uses a Pydantic model to define the API fields. Creates a runnable that can be invoked on LLMs that are qualified to parameterise functions.
question (str): The question to be answered.
conversation: The conversation object used for parameterising the
OncoKBQuery.
OncoKBQueryParameters: the parameterised query object (Pydantic model)
Source code in biochatter/api_agent/web/oncokb.py
The bio.tools API
Module for interacting with the bio.tools API.
BioToolsFetcher
Bases: BaseFetcher
A class for retrieving API results from BioTools.
Retrieves API results given a parameterized BioToolsQuery.
Source code in biochatter/api_agent/web/bio_tools.py
__init__(api_token='demo')
Initialise the BioToolsFetcher.
api_token: The API token for the BioTools API.
Source code in biochatter/api_agent/web/bio_tools.py
fetch_results(request_data, retries=3)
Submit the BioTools query and fetch the results directly.
No multi-step procedure, thus no wrapping of submission and retrieval in this case.
request_data: List of BioToolsQuery objects (Pydantic models)
containing the BioTools query parameters.
retries: The number of retries to fetch the results.
str: The results of the BioTools query.
Source code in biochatter/api_agent/web/bio_tools.py
BioToolsInterpreter
Bases: BaseInterpreter
A class for interpreting BioTools results.
Source code in biochatter/api_agent/web/bio_tools.py
summarise_results(question, conversation_factory, response_text)
Extract the answer from the BLAST results.
question (str): The question to be answered.
conversation_factory: A BioChatter conversation object.
response_text (str): The response.text returned by bio.tools.
str: The extracted answer from the BLAST results.
Source code in biochatter/api_agent/web/bio_tools.py
BioToolsQueryBuilder
Bases: BaseQueryBuilder
A class for building an BioToolsQuery object.
Source code in biochatter/api_agent/web/bio_tools.py
create_runnable(query_parameters, conversation)
Create a runnable object for executing queries.
Create runnable using the LangChain create_structured_output_runnable
method.
query_parameters: A Pydantic data model that specifies the fields of
the API that should be queried.
conversation: A BioChatter conversation object.
A Callable object that can execute the query.
Source code in biochatter/api_agent/web/bio_tools.py
parameterise_query(question, conversation)
Generate an BioToolsQuery object.
Generate a BioToolsQuery object based on the given question, prompt, and BioChatter conversation. Uses a Pydantic model to define the API fields. Creates a runnable that can be invoked on LLMs that are qualified to parameterise functions.
question (str): The question to be answered.
conversation: The conversation object used for parameterising the
BioToolsQuery.
BioToolsQueryParameters: the parameterised query object (Pydantic
model)
Source code in biochatter/api_agent/web/bio_tools.py
BioToolsQueryParameters
Bases: BaseModel
Parameters for querying the bio.tools API.
Source code in biochatter/api_agent/web/bio_tools.py
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Python APIs
Generic Python API ingestion
Module for ingesting any Python module and generating a query builder.
GenericQueryBuilder
Bases: BaseQueryBuilder
A class for building a generic query using LLM tools.
The query builder works by ingesting a Python module and generating a list of Pydantic classes for each callable in the module. It then uses these classes to parameterise a query using LLM tool binding.
Source code in biochatter/api_agent/python/generic_agent.py
create_runnable(query_parameters, conversation)
Create a runnable object for the query builder.
query_parameters: The list of Pydantic classes to be used for the
query.
conversation: The conversation object used for parameterising the
query.
The runnable object for the query builder.
Source code in biochatter/api_agent/python/generic_agent.py
parameterise_query(question, prompt, conversation, module, generated_classes=None)
Parameterise tool calls for any Python module.
Generate a list of parameterised BaseModel instances based on the given question, prompt, and BioChatter conversation. Uses a Pydantic model to define the API fields.
Using langchain's bind_tools
method to allow the LLM to parameterise
the function call, based on the functions available in the module.
Relies on defined structure and annotation of the passed module.
question (str): The question to be answered.
prompt (str): The prompt to be used for the query, instructing the
LLM of its task and the module context.
conversation: The conversation object used for parameterising the
query.
module: The Python module to be used for the query.
generated_classes: The list of Pydantic classes to be used for the
query. If not provided, the classes will be generated from the
module. Allows for external injection of classes for testing
purposes.
list[BaseAPIModel]: the parameterised query object (Pydantic
model)
Source code in biochatter/api_agent/python/generic_agent.py
AutoGenerate Pydantic classes for each callable.
This module provides a function to generate Pydantic classes for each callable (function/method) in a given module. It extracts parameters from docstrings using docstring-parser and creates Pydantic models with fields corresponding to the parameters. If a parameter name conflicts with BaseModel attributes, it is aliased.
Examples
import scanpy as sc generated_classes = generate_pydantic_classes(sc.tl) for model in generated_classes: ... print(model.schema())
generate_pydantic_classes(module)
Generate Pydantic classes for each callable.
For each callable (function/method) in a given module. Extracts parameters from docstrings using docstring-parser. Each generated class has fields corresponding to the parameters of the function. If a parameter name conflicts with BaseModel attributes, it is aliased.
Params:
module : ModuleType The Python module from which to extract functions and generate models.
Returns
list[Type[BaseModel]]
A list of Pydantic model classes corresponding to each function found in
module
.
Notes
- For now, all parameter types are set to
Any
to avoid complications with complex or external classes that are not easily JSON-serializable. - Optional parameters (those with a None default) are represented as
Optional[Any]
. - Required parameters (no default) use
...
to indicate that the field is required.
Source code in biochatter/api_agent/python/autogenerate_model.py
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Scanpy modules
Module for generating anndata queries using LLM tools.
AnnDataIOQueryBuilder
Bases: BaseQueryBuilder
A class for building a AnndataIO query object.
Source code in biochatter/api_agent/python/anndata_agent.py
create_runnable(query_parameters, conversation)
Create a runnable object for executing queries.
Create runnable using the LangChain create_structured_output_runnable
method.
query_parameters: A Pydantic data model that specifies the fields of
the API that should be queried.
conversation: A BioChatter conversation object.
A Callable object that can execute the query.
Source code in biochatter/api_agent/python/anndata_agent.py
parameterise_query(question, conversation)
Generate a AnnDataIOQuery object.
Generates the object based on the given question, prompt, and BioChatter conversation. Uses a Pydantic model to define the API fields. Creates a runnable that can be invoked on LLMs that are qualified to parameterise functions.
question (str): The question to be answered.
conversation: The conversation object used for parameterising the
AnnDataIOQuery.
AnnDataIOQuery: the parameterised query object (Pydantic model)
Source code in biochatter/api_agent/python/anndata_agent.py
ConcatenateAnnData
Bases: BaseAPIModel
Concatenate AnnData objects along an axis.
Source code in biochatter/api_agent/python/anndata_agent.py
MapAnnData
Bases: BaseAPIModel
Apply mapping functions to elements of AnnData.
Source code in biochatter/api_agent/python/anndata_agent.py
ReadCSV
Bases: BaseAPIModel
Read .csv file.
Source code in biochatter/api_agent/python/anndata_agent.py
ReadExcel
Bases: BaseAPIModel
Read .xlsx (Excel) file.
Source code in biochatter/api_agent/python/anndata_agent.py
ReadH5AD
Bases: BaseAPIModel
Read .h5ad-formatted hdf5 file.
Source code in biochatter/api_agent/python/anndata_agent.py
ReadHDF
Bases: BaseAPIModel
Read .h5 (hdf5) file.
Source code in biochatter/api_agent/python/anndata_agent.py
ReadLoom
Bases: BaseAPIModel
Read .loom-formatted hdf5 file.
Source code in biochatter/api_agent/python/anndata_agent.py
ReadMTX
ReadText
Bases: BaseAPIModel
Read .txt, .tab, .data (text) file.
Source code in biochatter/api_agent/python/anndata_agent.py
ReadZarr
Bases: BaseAPIModel
Read from a hierarchical Zarr array store.
Source code in biochatter/api_agent/python/anndata_agent.py
Module for interacting with the scanpy
API for plotting (pl
).
ScanpyPlDrawGraphQueryParameters
Bases: BaseModel
Parameters for querying the Scanpy pl.draw_graph
API.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
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ScanpyPlPcaQueryParameters
Bases: BaseModel
Parameters for querying the scanpy pl.pca
API.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
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ScanpyPlQueryBuilder
Bases: BaseQueryBuilder
A class for building a AnndataIO query object.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
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create_runnable(query_parameters, conversation)
Create a runnable object for executing queries.
Create runnable using the LangChain create_structured_output_runnable
method.
query_parameters: A Pydantic data model that specifies the fields of
the API that should be queried.
conversation: A BioChatter conversation object.
A Callable object that can execute the query.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
parameterise_query(question, conversation)
Generate a AnnDataIOQuery object.
Generates the object based on the given question, prompt, and BioChatter conversation. Uses a Pydantic model to define the API fields. Creates a runnable that can be invoked on LLMs that are qualified to parameterise functions.
question (str): The question to be answered.
conversation: The conversation object used for parameterising the
ScanpyPlQuery.
ScanpyPlQuery: the parameterised query object (Pydantic model)
Source code in biochatter/api_agent/python/scanpy_pl_full.py
ScanpyPlScatterQueryParameters
Bases: BaseModel
Parameters for querying the scanpy pl.scatter
API.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
ScanpyPlSpatialQueryParameters
Bases: BaseModel
Parameters for querying the Scanpy pl.spatial
API.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
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ScanpyPlTsneQueryParameters
Bases: BaseModel
Parameters for querying the Scanpy pl.tsne
API.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
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ScanpyPlUmapQueryParameters
Bases: BaseModel
Parameters for querying the Scanpy pl.umap
API.
Source code in biochatter/api_agent/python/scanpy_pl_full.py
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