mirror of
https://github.com/trustgraph-ai/trustgraph.git
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310a2deb06
* Tidy up duplicate tech specs in doc directory * Streaming LLM text-completion service tech spec. * text-completion and prompt interfaces * streaming change applied to all LLMs, so far tested with VertexAI * Skip Pinecone unit tests, upstream module issue is affecting things, tests are passing again * Added agent streaming, not working and has broken tests
147 lines
4.3 KiB
Python
147 lines
4.3 KiB
Python
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import json
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import asyncio
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from . request_response_spec import RequestResponse, RequestResponseSpec
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from .. schema import PromptRequest, PromptResponse
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class PromptClient(RequestResponse):
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async def prompt(self, id, variables, timeout=600, streaming=False, chunk_callback=None):
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if not streaming:
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# Non-streaming path
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resp = await self.request(
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PromptRequest(
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id = id,
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terms = {
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k: json.dumps(v)
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for k, v in variables.items()
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},
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streaming = False
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),
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timeout=timeout
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)
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if resp.error:
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raise RuntimeError(resp.error.message)
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if resp.text: return resp.text
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return json.loads(resp.object)
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else:
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# Streaming path - collect all chunks
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full_text = ""
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full_object = None
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async def collect_chunks(resp):
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nonlocal full_text, full_object
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if resp.error:
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raise RuntimeError(resp.error.message)
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if resp.text:
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full_text += resp.text
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# Call chunk callback if provided
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if chunk_callback:
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if asyncio.iscoroutinefunction(chunk_callback):
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await chunk_callback(resp.text)
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else:
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chunk_callback(resp.text)
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elif resp.object:
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full_object = resp.object
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return getattr(resp, 'end_of_stream', False)
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await self.request(
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PromptRequest(
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id = id,
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terms = {
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k: json.dumps(v)
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for k, v in variables.items()
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},
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streaming = True
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),
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recipient=collect_chunks,
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timeout=timeout
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)
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if full_text: return full_text
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return json.loads(full_object)
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async def extract_definitions(self, text, timeout=600):
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return await self.prompt(
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id = "extract-definitions",
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variables = { "text": text },
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timeout = timeout,
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)
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async def extract_relationships(self, text, timeout=600):
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return await self.prompt(
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id = "extract-relationships",
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variables = { "text": text },
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timeout = timeout,
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)
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async def extract_objects(self, text, schema, timeout=600):
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return await self.prompt(
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id = "extract-rows",
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variables = { "text": text, "schema": schema, },
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timeout = timeout,
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)
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async def kg_prompt(self, query, kg, timeout=600):
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return await self.prompt(
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id = "kg-prompt",
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variables = {
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"query": query,
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"knowledge": [
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{ "s": v[0], "p": v[1], "o": v[2] }
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for v in kg
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]
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},
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timeout = timeout,
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)
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async def document_prompt(self, query, documents, timeout=600):
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return await self.prompt(
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id = "document-prompt",
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variables = {
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"query": query,
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"documents": documents,
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},
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timeout = timeout,
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)
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async def agent_react(self, variables, timeout=600, streaming=False, chunk_callback=None):
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return await self.prompt(
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id = "agent-react",
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variables = variables,
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timeout = timeout,
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streaming = streaming,
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chunk_callback = chunk_callback,
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)
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async def question(self, question, timeout=600):
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return await self.prompt(
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id = "question",
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variables = {
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"question": question,
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},
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timeout = timeout,
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)
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class PromptClientSpec(RequestResponseSpec):
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def __init__(
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self, request_name, response_name,
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):
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super(PromptClientSpec, self).__init__(
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request_name = request_name,
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request_schema = PromptRequest,
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response_name = response_name,
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response_schema = PromptResponse,
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impl = PromptClient,
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)
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