Merge branch 'backend_refactor' into dev
This commit is contained in:
Ibis Prevedello
commit
329b3ca2d5
11 changed files with 527 additions and 331 deletions
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@ -1,186 +1,21 @@
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from fastapi import APIRouter
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from langflow_backend.api import signature
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from langflow_backend.api import list_endpoints
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from langflow_backend.utils import payload
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from langchain.agents.loading import load_agent_executor_from_config
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from langchain.chains.loading import load_chain_from_config
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from langchain.llms.loading import load_llm_from_config
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from langchain.prompts.loading import load_prompt_from_config
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from typing import Any
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import io
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import contextlib
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import re
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from fastapi import APIRouter, HTTPException
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from langflow_backend.interface.types import build_langchain_types_dict, get_type_list
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from langflow_backend.interface.loading import process_data_graph
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from typing import Any, Dict
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# build router
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router = APIRouter()
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def get_type_list():
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all_types = get_all()
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all_types.pop("tools")
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for key, value in all_types.items():
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all_types[key] = [item["template"]["_type"] for item in value.values()]
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return all_types
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@router.get("/all")
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def get_all():
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return {
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"chains": {
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chain: signature.get_chain(chain) for chain in list_endpoints.list_chains()
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},
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"agents": {
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agent: signature.get_agent(agent) for agent in list_endpoints.list_agents()
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},
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"prompts": {
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prompt: signature.get_prompt(prompt)
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for prompt in list_endpoints.list_prompts()
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},
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"llms": {llm: signature.get_llm(llm) for llm in list_endpoints.list_llms()},
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"tools": {
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tool: signature.get_tool(tool) for tool in list_endpoints.list_tools()
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},
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}
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return build_langchain_types_dict()
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@router.post("/predict")
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def get_load(data: dict[str, Any]):
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# Get type list
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type_list = get_type_list()
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# Substitute ZeroShotPromt with PromptTemplate
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for node in data["nodes"]:
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if node["data"]["type"] == "ZeroShotPrompt":
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# Build Prompt Template
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tools = [
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tool
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for tool in data["nodes"]
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if tool["type"] != "chatOutputNode"
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and "Tool" in tool["data"]["node"]["base_classes"]
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]
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node["data"] = build_prompt_template(prompt=node["data"], tools=tools)
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break
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# Add input variables
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data = payload.extract_input_variables(data)
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# Nodes, edges and root node
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message = data["message"]
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nodes = data["nodes"]
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edges = data["edges"]
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root = payload.get_root_node(data)
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extracted_json = payload.build_json(root, nodes, edges)
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# Build json
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if extracted_json["_type"] in type_list["agents"]:
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loaded = load_agent_executor_from_config(extracted_json)
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with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
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result = loaded.run(message)
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thought = output_buffer.getvalue()
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elif extracted_json["_type"] in type_list["chains"]:
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loaded = load_chain_from_config(extracted_json)
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with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
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result = loaded.run(message)
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thought = output_buffer.getvalue()
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elif extracted_json["_type"] in type_list["llms"]:
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loaded = load_llm_from_config(extracted_json)
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with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
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result = loaded(message)
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thought = output_buffer.getvalue()
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else:
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result = "Error: Type should be either agent, chain or llm"
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thought = ""
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# Remove unnecessary data from response
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begin = thought.rfind(message)
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thought = thought[(begin + len(message)) :]
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return {
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"result": result,
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"thought": re.sub(
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r"\x1b\[([0-9,A-Z]{1,2}(;[0-9,A-Z]{1,2})?)?[m|K]", "", thought
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).strip(),
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}
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def build_prompt_template(prompt, tools):
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prefix = prompt["node"]["template"]["prefix"]["value"]
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suffix = prompt["node"]["template"]["suffix"]["value"]
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format_instructions = prompt["node"]["template"]["format_instructions"]["value"]
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tool_strings = "\n".join(
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[
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f"{tool['data']['node']['name']}: {tool['data']['node']['description']}"
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for tool in tools
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]
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)
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tool_names = ", ".join([tool["data"]["node"]["name"] for tool in tools])
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format_instructions = format_instructions.format(tool_names=tool_names)
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value = "\n\n".join([prefix, tool_strings, format_instructions, suffix])
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prompt["type"] = "PromptTemplate"
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prompt["node"] = {
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"template": {
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"_type": "prompt",
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"input_variables": {
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"type": "str",
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"required": True,
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"placeholder": "",
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"list": True,
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"show": False,
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"multiline": False,
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},
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"output_parser": {
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"type": "BaseOutputParser",
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"required": False,
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"placeholder": "",
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"list": False,
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"show": False,
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"multline": False,
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"value": None,
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},
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"template": {
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"type": "str",
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"required": True,
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"placeholder": "",
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"list": False,
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"show": True,
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"multiline": True,
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"value": value,
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},
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"template_format": {
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"type": "str",
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"required": False,
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"placeholder": "",
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"list": False,
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"show": False,
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"multline": False,
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"value": "f-string",
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},
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"validate_template": {
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"type": "bool",
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"required": False,
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"placeholder": "",
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"list": False,
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"show": False,
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"multline": False,
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"value": True,
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},
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},
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"description": "Schema to represent a prompt for an LLM.",
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"base_classes": ["BasePromptTemplate"],
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}
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return prompt
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def get_load(data: Dict[str, Any]):
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try:
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return process_data_graph(data)
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except Exception as e:
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return HTTPException(status_code=500, detail=str(e))
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@ -1,14 +1,6 @@
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from fastapi import APIRouter
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from langchain import chains
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from langchain import agents
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from langchain import prompts
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from langchain import llms
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from langchain.chains.conversation import memory as memories
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from langchain.agents.load_tools import get_all_tool_names
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from langflow_backend.utils import util, allowed_components
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from langflow_backend.custom import customs
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from langflow_backend.interface.listing import list_type
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# build router
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router = APIRouter(
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@ -32,61 +24,35 @@ def read_items():
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@router.get("/chains")
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def list_chains():
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"""List all chain types"""
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return [
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chain.__annotations__["return"].__name__
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for chain in chains.loading.type_to_loader_dict.values()
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if chain.__annotations__["return"].__name__ in allowed_components.CHAINS
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]
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return list_type("chains")
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@router.get("/agents")
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def list_agents():
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"""List all agent types"""
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# return list(agents.loading.AGENT_TO_CLASS.keys())
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return [
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agent.__name__
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for agent in agents.loading.AGENT_TO_CLASS.values()
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if agent.__name__ in allowed_components.AGENTS
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]
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return list_type("agents")
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@router.get("/prompts")
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def list_prompts():
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"""List all prompt types"""
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custom_prompts = customs.get_custom_prompts()
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library_prompts = [
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prompt.__annotations__["return"].__name__
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for prompt in prompts.loading.type_to_loader_dict.values()
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if prompt.__annotations__["return"].__name__ in allowed_components.PROMPTS
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]
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return library_prompts + list(custom_prompts.keys())
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return list_type("prompts")
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@router.get("/llms")
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def list_llms():
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"""List all llm types"""
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return [
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llm.__name__
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for llm in llms.type_to_cls_dict.values()
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if llm.__name__ in allowed_components.LLMS
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]
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return list_type("llms")
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@router.get("/memories")
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def list_memories():
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"""List all memory types"""
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return [memory.__name__ for memory in memories.type_to_cls_dict.values()]
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return list_type("memories")
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@router.get("/tools")
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def list_tools():
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"""List all load tools"""
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tools = []
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for tool in get_all_tool_names():
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tool_params = util.get_tool_params(util.get_tools_dict(tool))
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if tool_params and tool_params["name"] in allowed_components.TOOLS:
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tools.append(tool_params["name"])
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return tools
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return list_type("tools")
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@ -1,17 +1,6 @@
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from typing import Any, Dict
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from fastapi import APIRouter, HTTPException
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from langchain import agents, chains, llms, prompts
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from langchain.agents.load_tools import (
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_BASE_TOOLS,
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_EXTRA_LLM_TOOLS,
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_EXTRA_OPTIONAL_TOOLS,
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_LLM_TOOLS,
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get_all_tool_names,
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)
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from langchain.chains.conversation import memory as memories
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from langflow_backend.utils import util
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from langflow_backend.custom import customs
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from langflow_backend.interface.signature import get_signature
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# build router
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router = APIRouter(
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@ -24,9 +13,7 @@ router = APIRouter(
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def get_chain(name: str):
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"""Get the signature of a chain."""
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try:
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return util.build_template_from_function(
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name, chains.loading.type_to_loader_dict
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)
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return get_signature(name, "chains")
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except ValueError as exc:
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raise HTTPException(status_code=404, detail="Chain not found") from exc
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@ -35,7 +22,7 @@ def get_chain(name: str):
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def get_agent(name: str):
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"""Get the signature of an agent."""
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try:
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return util.build_template_from_class(name, agents.loading.AGENT_TO_CLASS)
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return get_signature(name, "agents")
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except ValueError as exc:
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raise HTTPException(status_code=404, detail="Agent not found") from exc
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@ -44,11 +31,7 @@ def get_agent(name: str):
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def get_prompt(name: str):
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"""Get the signature of a prompt."""
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try:
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if name in customs.get_custom_prompts().keys():
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return customs.get_custom_prompts()[name]
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return util.build_template_from_function(
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name, prompts.loading.type_to_loader_dict
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)
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return get_signature(name, "prompts")
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except ValueError as exc:
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raise HTTPException(status_code=404, detail="Prompt not found") from exc
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@ -57,7 +40,7 @@ def get_prompt(name: str):
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def get_llm(name: str):
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"""Get the signature of an llm."""
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try:
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return util.build_template_from_class(name, llms.type_to_cls_dict)
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return get_signature(name, "llms")
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except ValueError as exc:
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raise HTTPException(status_code=404, detail="LLM not found") from exc
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@ -66,7 +49,7 @@ def get_llm(name: str):
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def get_memory(name: str):
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"""Get the signature of a memory."""
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try:
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return util.build_template_from_class(name, memories.type_to_cls_dict)
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return get_signature(name, "memories")
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except ValueError as exc:
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raise HTTPException(status_code=404, detail="Memory not found") from exc
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|
@ -74,51 +57,7 @@ def get_memory(name: str):
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@router.get("/tool")
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def get_tool(name: str):
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"""Get the signature of a tool."""
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all_tools = {}
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for tool in get_all_tool_names():
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if tool_params := util.get_tool_params(util.get_tools_dict(tool)):
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all_tools[tool_params["name"]] = tool
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# Raise error if name is not in tools
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if name not in all_tools.keys():
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raise HTTPException(status_code=404, detail=f"Tool {name} not found.")
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type_dict = {
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"str": {
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"type": "str",
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"required": False,
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"list": False,
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"show": True,
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"placeholder": "",
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"value": "",
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},
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"llm": {"type": "BaseLLM", "required": True, "list": False, "show": True},
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}
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tool_type = all_tools[name]
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if tool_type in _BASE_TOOLS:
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params = []
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elif tool_type in _LLM_TOOLS:
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params = ["llm"]
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elif tool_type in _EXTRA_LLM_TOOLS:
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_, extra_keys = _EXTRA_LLM_TOOLS[tool_type]
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params = ["llm"] + extra_keys
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elif tool_type in _EXTRA_OPTIONAL_TOOLS:
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_, extra_keys = _EXTRA_OPTIONAL_TOOLS[tool_type]
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params = extra_keys
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else:
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params = []
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template = {
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param: (type_dict[param] if param == "llm" else type_dict["str"])
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for param in params
|
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} # type: Dict[str, Any]
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template["_type"] = tool_type
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return {
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"template": template,
|
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**util.get_tool_params(util.get_tools_dict(tool_type)),
|
||||
"base_classes": ["Tool"],
|
||||
}
|
||||
try:
|
||||
return get_signature(name, "tools")
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except ValueError as exc:
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raise HTTPException(status_code=404, detail="Tool not found") from exc
|
||||
|
|
|
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0
langflow/backend/langflow_backend/interface/__init__.py
Normal file
0
langflow/backend/langflow_backend/interface/__init__.py
Normal file
74
langflow/backend/langflow_backend/interface/listing.py
Normal file
74
langflow/backend/langflow_backend/interface/listing.py
Normal file
|
|
@ -0,0 +1,74 @@
|
|||
from langchain import chains, agents, prompts, llms
|
||||
from langflow_backend.custom import customs
|
||||
from langflow_backend.utils import util, allowed_components
|
||||
from langchain.agents.load_tools import get_all_tool_names
|
||||
from langchain.chains.conversation import memory as memories
|
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|
||||
|
||||
def list_type(object_type: str):
|
||||
"""List all components"""
|
||||
return {
|
||||
"chains": list_chain_types,
|
||||
"agents": list_agents,
|
||||
"prompts": list_prompts,
|
||||
"llms": list_llms,
|
||||
"tools": list_tools,
|
||||
"memories": list_memories,
|
||||
}.get(object_type, lambda: "Invalid type")()
|
||||
|
||||
|
||||
def list_agents():
|
||||
"""List all agent types"""
|
||||
# return list(agents.loading.AGENT_TO_CLASS.keys())
|
||||
return [
|
||||
agent.__name__
|
||||
for agent in agents.loading.AGENT_TO_CLASS.values()
|
||||
if agent.__name__ in allowed_components.AGENTS
|
||||
]
|
||||
|
||||
|
||||
def list_prompts():
|
||||
"""List all prompt types"""
|
||||
custom_prompts = customs.get_custom_prompts()
|
||||
library_prompts = [
|
||||
prompt.__annotations__["return"].__name__
|
||||
for prompt in prompts.loading.type_to_loader_dict.values()
|
||||
if prompt.__annotations__["return"].__name__ in allowed_components.PROMPTS
|
||||
]
|
||||
return library_prompts + list(custom_prompts.keys())
|
||||
|
||||
|
||||
def list_tools():
|
||||
"""List all load tools"""
|
||||
|
||||
tools = []
|
||||
|
||||
for tool in get_all_tool_names():
|
||||
tool_params = util.get_tool_params(util.get_tools_dict(tool))
|
||||
if tool_params and tool_params["name"] in allowed_components.TOOLS:
|
||||
tools.append(tool_params["name"])
|
||||
|
||||
return tools
|
||||
|
||||
|
||||
def list_llms():
|
||||
"""List all llm types"""
|
||||
return [
|
||||
llm.__name__
|
||||
for llm in llms.type_to_cls_dict.values()
|
||||
if llm.__name__ in allowed_components.LLMS
|
||||
]
|
||||
|
||||
|
||||
def list_chain_types():
|
||||
"""List all chain types"""
|
||||
return [
|
||||
chain.__annotations__["return"].__name__
|
||||
for chain in chains.loading.type_to_loader_dict.values()
|
||||
if chain.__annotations__["return"].__name__ in allowed_components.CHAINS
|
||||
]
|
||||
|
||||
|
||||
def list_memories():
|
||||
"""List all memory types"""
|
||||
return [memory.__name__ for memory in memories.type_to_cls_dict.values()]
|
||||
152
langflow/backend/langflow_backend/interface/loading.py
Normal file
152
langflow/backend/langflow_backend/interface/loading.py
Normal file
|
|
@ -0,0 +1,152 @@
|
|||
import contextlib
|
||||
import re
|
||||
import io
|
||||
from typing import Any, Dict
|
||||
from langflow_backend.interface.types import get_type_list
|
||||
from langchain.agents.loading import load_agent_executor_from_config
|
||||
from langchain.chains.loading import load_chain_from_config
|
||||
from langchain.llms.loading import load_llm_from_config
|
||||
from langflow_backend.utils import payload
|
||||
|
||||
|
||||
def replace_zero_shot_prompt_with_prompt_template(nodes):
|
||||
for node in nodes:
|
||||
if node["data"]["type"] == "ZeroShotPrompt":
|
||||
# Build Prompt Template
|
||||
tools = [
|
||||
tool
|
||||
for tool in nodes
|
||||
if tool["type"] != "chatOutputNode"
|
||||
and "Tool" in tool["data"]["node"]["base_classes"]
|
||||
]
|
||||
node["data"] = build_prompt_template(prompt=node["data"], tools=tools)
|
||||
break
|
||||
return nodes
|
||||
|
||||
|
||||
def process_data_graph(data_graph: Dict[str, Any]):
|
||||
nodes = data_graph["nodes"]
|
||||
# Substitute ZeroShotPrompt with PromptTemplate
|
||||
nodes = replace_zero_shot_prompt_with_prompt_template(nodes)
|
||||
# Add input variables
|
||||
data_graph = payload.extract_input_variables(data_graph)
|
||||
# Nodes, edges and root node
|
||||
message = data_graph["message"]
|
||||
edges = data_graph["edges"]
|
||||
root = payload.get_root_node(data_graph)
|
||||
extracted_json = payload.build_json(root, nodes, edges)
|
||||
|
||||
# Process json
|
||||
result, thought = get_result_and_thought(extracted_json, message)
|
||||
|
||||
# Remove unnecessary data from response
|
||||
begin = thought.rfind(message)
|
||||
thought = thought[(begin + len(message)) :]
|
||||
|
||||
return {
|
||||
"result": result,
|
||||
"thought": re.sub(
|
||||
r"\x1b\[([0-9,A-Z]{1,2}(;[0-9,A-Z]{1,2})?)?[m|K]", "", thought
|
||||
).strip(),
|
||||
}
|
||||
|
||||
|
||||
def get_result_and_thought(extracted_json: Dict[str, Any], message: str):
|
||||
# Get type list
|
||||
type_list = get_type_list()
|
||||
if extracted_json["_type"] in type_list["agents"]:
|
||||
loaded = load_agent_executor_from_config(extracted_json)
|
||||
|
||||
with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
|
||||
result = loaded.run(message)
|
||||
thought = output_buffer.getvalue()
|
||||
|
||||
elif extracted_json["_type"] in type_list["chains"]:
|
||||
loaded = load_chain_from_config(extracted_json)
|
||||
|
||||
with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
|
||||
result = loaded.run(message)
|
||||
thought = output_buffer.getvalue()
|
||||
|
||||
elif extracted_json["_type"] in type_list["llms"]:
|
||||
loaded = load_llm_from_config(extracted_json)
|
||||
|
||||
with io.StringIO() as output_buffer, contextlib.redirect_stdout(output_buffer):
|
||||
result = loaded(message)
|
||||
thought = output_buffer.getvalue()
|
||||
else:
|
||||
result = "Error: Type should be either agent, chain or llm"
|
||||
thought = ""
|
||||
return result, thought
|
||||
|
||||
|
||||
def build_prompt_template(prompt, tools):
|
||||
prefix = prompt["node"]["template"]["prefix"]["value"]
|
||||
suffix = prompt["node"]["template"]["suffix"]["value"]
|
||||
format_instructions = prompt["node"]["template"]["format_instructions"]["value"]
|
||||
|
||||
tool_strings = "\n".join(
|
||||
[
|
||||
f"{tool['data']['node']['name']}: {tool['data']['node']['description']}"
|
||||
for tool in tools
|
||||
]
|
||||
)
|
||||
tool_names = ", ".join([tool["data"]["node"]["name"] for tool in tools])
|
||||
format_instructions = format_instructions.format(tool_names=tool_names)
|
||||
value = "\n\n".join([prefix, tool_strings, format_instructions, suffix])
|
||||
|
||||
prompt["type"] = "PromptTemplate"
|
||||
|
||||
prompt["node"] = {
|
||||
"template": {
|
||||
"_type": "prompt",
|
||||
"input_variables": {
|
||||
"type": "str",
|
||||
"required": True,
|
||||
"placeholder": "",
|
||||
"list": True,
|
||||
"show": False,
|
||||
"multiline": False,
|
||||
},
|
||||
"output_parser": {
|
||||
"type": "BaseOutputParser",
|
||||
"required": False,
|
||||
"placeholder": "",
|
||||
"list": False,
|
||||
"show": False,
|
||||
"multline": False,
|
||||
"value": None,
|
||||
},
|
||||
"template": {
|
||||
"type": "str",
|
||||
"required": True,
|
||||
"placeholder": "",
|
||||
"list": False,
|
||||
"show": True,
|
||||
"multiline": True,
|
||||
"value": value,
|
||||
},
|
||||
"template_format": {
|
||||
"type": "str",
|
||||
"required": False,
|
||||
"placeholder": "",
|
||||
"list": False,
|
||||
"show": False,
|
||||
"multline": False,
|
||||
"value": "f-string",
|
||||
},
|
||||
"validate_template": {
|
||||
"type": "bool",
|
||||
"required": False,
|
||||
"placeholder": "",
|
||||
"list": False,
|
||||
"show": False,
|
||||
"multline": False,
|
||||
"value": True,
|
||||
},
|
||||
},
|
||||
"description": "Schema to represent a prompt for an LLM.",
|
||||
"base_classes": ["BasePromptTemplate"],
|
||||
}
|
||||
|
||||
return prompt
|
||||
123
langflow/backend/langflow_backend/interface/signature.py
Normal file
123
langflow/backend/langflow_backend/interface/signature.py
Normal file
|
|
@ -0,0 +1,123 @@
|
|||
from typing import Dict, Any # noqa: F401
|
||||
from langchain import agents, chains, llms, prompts
|
||||
from langchain.agents.load_tools import (
|
||||
_BASE_TOOLS,
|
||||
_EXTRA_LLM_TOOLS,
|
||||
_EXTRA_OPTIONAL_TOOLS,
|
||||
_LLM_TOOLS,
|
||||
get_all_tool_names,
|
||||
)
|
||||
from langchain.chains.conversation import memory as memories
|
||||
|
||||
from langflow_backend.utils import util
|
||||
from langflow_backend.custom import customs
|
||||
|
||||
|
||||
def get_signature(name: str, object_type: str):
|
||||
"""Get the signature of an object."""
|
||||
return {
|
||||
"chains": get_chain_signature,
|
||||
"agents": get_agent_signature,
|
||||
"prompts": get_prompt_signature,
|
||||
"llms": get_llm_signature,
|
||||
"tools": get_tool_signature,
|
||||
"memories": get_memory_signature,
|
||||
}.get(object_type, lambda name: f"Invalid type: {name}")(name)
|
||||
|
||||
|
||||
def get_chain_signature(name: str):
|
||||
"""Get the chain type by signature."""
|
||||
try:
|
||||
return util.build_template_from_function(
|
||||
name, chains.loading.type_to_loader_dict
|
||||
)
|
||||
except ValueError as exc:
|
||||
raise ValueError("Chain not found") from exc
|
||||
|
||||
|
||||
def get_agent_signature(name: str):
|
||||
"""Get the signature of an agent."""
|
||||
try:
|
||||
return util.build_template_from_class(name, agents.loading.AGENT_TO_CLASS)
|
||||
except ValueError as exc:
|
||||
raise ValueError("Agent not found") from exc
|
||||
|
||||
|
||||
def get_prompt_signature(name: str):
|
||||
"""Get the signature of a prompt."""
|
||||
try:
|
||||
if name in customs.get_custom_prompts().keys():
|
||||
return customs.get_custom_prompts()[name]
|
||||
return util.build_template_from_function(
|
||||
name, prompts.loading.type_to_loader_dict
|
||||
)
|
||||
except ValueError as exc:
|
||||
raise ValueError("Prompt not found") from exc
|
||||
|
||||
|
||||
def get_llm_signature(name: str):
|
||||
"""Get the signature of an llm."""
|
||||
try:
|
||||
return util.build_template_from_class(name, llms.type_to_cls_dict)
|
||||
except ValueError as exc:
|
||||
raise ValueError("LLM not found") from exc
|
||||
|
||||
|
||||
def get_memory_signature(name: str):
|
||||
"""Get the signature of a memory."""
|
||||
try:
|
||||
return util.build_template_from_class(name, memories.type_to_cls_dict)
|
||||
except ValueError as exc:
|
||||
raise ValueError("Memory not found") from exc
|
||||
|
||||
|
||||
def get_tool_signature(name: str):
|
||||
"""Get the signature of a tool."""
|
||||
|
||||
all_tools = {}
|
||||
for tool in get_all_tool_names():
|
||||
if tool_params := util.get_tool_params(util.get_tools_dict(tool)):
|
||||
all_tools[tool_params["name"]] = tool
|
||||
|
||||
# Raise error if name is not in tools
|
||||
if name not in all_tools.keys():
|
||||
raise ValueError("Tool not found")
|
||||
|
||||
type_dict = {
|
||||
"str": {
|
||||
"type": "str",
|
||||
"required": False,
|
||||
"list": False,
|
||||
"show": True,
|
||||
"placeholder": "",
|
||||
"value": "",
|
||||
},
|
||||
"llm": {"type": "BaseLLM", "required": True, "list": False, "show": True},
|
||||
}
|
||||
|
||||
tool_type = all_tools[name]
|
||||
|
||||
if tool_type in _BASE_TOOLS:
|
||||
params = []
|
||||
elif tool_type in _LLM_TOOLS:
|
||||
params = ["llm"]
|
||||
elif tool_type in _EXTRA_LLM_TOOLS:
|
||||
_, extra_keys = _EXTRA_LLM_TOOLS[tool_type]
|
||||
params = ["llm"] + extra_keys
|
||||
elif tool_type in _EXTRA_OPTIONAL_TOOLS:
|
||||
_, extra_keys = _EXTRA_OPTIONAL_TOOLS[tool_type]
|
||||
params = extra_keys
|
||||
else:
|
||||
params = []
|
||||
|
||||
template = {
|
||||
param: (type_dict[param] if param == "llm" else type_dict["str"])
|
||||
for param in params
|
||||
} # type: Dict[str, Any]
|
||||
template["_type"] = tool_type
|
||||
|
||||
return {
|
||||
"template": template,
|
||||
**util.get_tool_params(util.get_tools_dict(tool_type)),
|
||||
"base_classes": ["Tool"],
|
||||
}
|
||||
31
langflow/backend/langflow_backend/interface/types.py
Normal file
31
langflow/backend/langflow_backend/interface/types.py
Normal file
|
|
@ -0,0 +1,31 @@
|
|||
from langflow_backend.interface.listing import list_type
|
||||
from langflow_backend.interface.signature import get_signature
|
||||
|
||||
|
||||
def get_type_list():
|
||||
"""Get a list of all langchain types"""
|
||||
all_types = build_langchain_types_dict()
|
||||
|
||||
all_types.pop("tools")
|
||||
|
||||
for key, value in all_types.items():
|
||||
all_types[key] = [item["template"]["_type"] for item in value.values()]
|
||||
|
||||
return all_types
|
||||
|
||||
|
||||
def build_langchain_types_dict():
|
||||
"""Build a dictionary of all langchain types"""
|
||||
return {
|
||||
"chains": {
|
||||
chain: get_signature(chain, "chains") for chain in list_type("chains")
|
||||
},
|
||||
"agents": {
|
||||
agent: get_signature(agent, "agents") for agent in list_type("agents")
|
||||
},
|
||||
"prompts": {
|
||||
prompt: get_signature(prompt, "prompts") for prompt in list_type("prompts")
|
||||
},
|
||||
"llms": {llm: get_signature(llm, "llms") for llm in list_type("llms")},
|
||||
"tools": {tool: get_signature(tool, "tools") for tool in list_type("tools")},
|
||||
}
|
||||
|
|
@ -10,10 +10,10 @@ from langchain.agents.load_tools import (
|
|||
_EXTRA_LLM_TOOLS,
|
||||
_EXTRA_OPTIONAL_TOOLS,
|
||||
)
|
||||
from typing import Optional
|
||||
from typing import Optional, Dict
|
||||
|
||||
|
||||
def build_template_from_function(name: str, type_to_loader_dict: dict):
|
||||
def build_template_from_function(name: str, type_to_loader_dict: Dict):
|
||||
classes = [
|
||||
item.__annotations__["return"].__name__ for item in type_to_loader_dict.values()
|
||||
]
|
||||
|
|
@ -59,7 +59,7 @@ def build_template_from_function(name: str, type_to_loader_dict: dict):
|
|||
}
|
||||
|
||||
|
||||
def build_template_from_class(name: str, type_to_cls_dict: dict):
|
||||
def build_template_from_class(name: str, type_to_cls_dict: Dict):
|
||||
classes = [item.__name__ for item in type_to_cls_dict.values()]
|
||||
|
||||
# Raise error if name is not in chains
|
||||
|
|
@ -130,8 +130,8 @@ def get_tools_dict(name: Optional[str] = None):
|
|||
"""Get the tools dictionary."""
|
||||
tools = {
|
||||
**_BASE_TOOLS,
|
||||
**_LLM_TOOLS,
|
||||
**{k: v[0] for k, v in _EXTRA_LLM_TOOLS.items()},
|
||||
**_LLM_TOOLS, # type: ignore
|
||||
**{k: v[0] for k, v in _EXTRA_LLM_TOOLS.items()}, # type: ignore
|
||||
**{k: v[0] for k, v in _EXTRA_OPTIONAL_TOOLS.items()},
|
||||
}
|
||||
return tools[name] if name else tools
|
||||
|
|
@ -283,7 +283,7 @@ def format_dict(d, name: Optional[str] = None):
|
|||
"temperature",
|
||||
"model_name",
|
||||
]
|
||||
or any(text in key for text in ["password", "token", "api", "key"])
|
||||
or "api_key" in key
|
||||
)
|
||||
|
||||
# Add password field
|
||||
|
|
|
|||
150
langflow/backend/poetry.lock
generated
150
langflow/backend/poetry.lock
generated
|
|
@ -616,6 +616,25 @@ category = "main"
|
|||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "mypy"
|
||||
version = "1.1.1"
|
||||
description = "Optional static typing for Python"
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[package.dependencies]
|
||||
mypy-extensions = ">=1.0.0"
|
||||
tomli = {version = ">=1.1.0", markers = "python_version < \"3.11\""}
|
||||
typing-extensions = ">=3.10"
|
||||
|
||||
[package.extras]
|
||||
dmypy = ["psutil (>=4.0)"]
|
||||
install-types = ["pip"]
|
||||
python2 = ["typed-ast (>=1.4.0,<2)"]
|
||||
reports = ["lxml"]
|
||||
|
||||
[[package]]
|
||||
name = "mypy-extensions"
|
||||
version = "1.0.0"
|
||||
|
|
@ -796,7 +815,7 @@ python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, !=3.3.*"
|
|||
|
||||
[[package]]
|
||||
name = "pydantic"
|
||||
version = "1.10.5"
|
||||
version = "1.10.6"
|
||||
description = "Data validation and settings management using python type hints"
|
||||
category = "main"
|
||||
optional = false
|
||||
|
|
@ -898,6 +917,14 @@ python-versions = ">=3.6,<4"
|
|||
[package.dependencies]
|
||||
pyasn1 = ">=0.1.3"
|
||||
|
||||
[[package]]
|
||||
name = "ruff"
|
||||
version = "0.0.254"
|
||||
description = "An extremely fast Python linter, written in Rust."
|
||||
category = "dev"
|
||||
optional = false
|
||||
python-versions = ">=3.7"
|
||||
|
||||
[[package]]
|
||||
name = "six"
|
||||
version = "1.16.0"
|
||||
|
|
@ -1132,7 +1159,7 @@ testing = ["big-O", "flake8 (<5)", "jaraco.functools", "jaraco.itertools", "more
|
|||
[metadata]
|
||||
lock-version = "1.1"
|
||||
python-versions = "^3.9"
|
||||
content-hash = "60d773cc238912b3adbe51458a006fcef73b07f9e09de636b37ba4d3c99c022b"
|
||||
content-hash = "e48340fa47860cf68370d1c4b44a2c28267e8182e981508705cd37491213a32b"
|
||||
|
||||
[metadata.files]
|
||||
aiohttp = [
|
||||
|
|
@ -1767,6 +1794,34 @@ multidict = [
|
|||
{file = "multidict-6.0.4-cp39-cp39-win_amd64.whl", hash = "sha256:33029f5734336aa0d4c0384525da0387ef89148dc7191aae00ca5fb23d7aafc2"},
|
||||
{file = "multidict-6.0.4.tar.gz", hash = "sha256:3666906492efb76453c0e7b97f2cf459b0682e7402c0489a95484965dbc1da49"},
|
||||
]
|
||||
mypy = [
|
||||
{file = "mypy-1.1.1-cp310-cp310-macosx_10_9_x86_64.whl", hash = "sha256:39c7119335be05630611ee798cc982623b9e8f0cff04a0b48dfc26100e0b97af"},
|
||||
{file = "mypy-1.1.1-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:61bf08362e93b6b12fad3eab68c4ea903a077b87c90ac06c11e3d7a09b56b9c1"},
|
||||
{file = "mypy-1.1.1-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:dbb19c9f662e41e474e0cff502b7064a7edc6764f5262b6cd91d698163196799"},
|
||||
{file = "mypy-1.1.1-cp310-cp310-musllinux_1_1_x86_64.whl", hash = "sha256:315ac73cc1cce4771c27d426b7ea558fb4e2836f89cb0296cbe056894e3a1f78"},
|
||||
{file = "mypy-1.1.1-cp310-cp310-win_amd64.whl", hash = "sha256:5cb14ff9919b7df3538590fc4d4c49a0f84392237cbf5f7a816b4161c061829e"},
|
||||
{file = "mypy-1.1.1-cp311-cp311-macosx_10_9_x86_64.whl", hash = "sha256:26cdd6a22b9b40b2fd71881a8a4f34b4d7914c679f154f43385ca878a8297389"},
|
||||
{file = "mypy-1.1.1-cp311-cp311-macosx_11_0_arm64.whl", hash = "sha256:5b5f81b40d94c785f288948c16e1f2da37203c6006546c5d947aab6f90aefef2"},
|
||||
{file = "mypy-1.1.1-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:21b437be1c02712a605591e1ed1d858aba681757a1e55fe678a15c2244cd68a5"},
|
||||
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|
||||
{file = "pydantic-1.10.6-cp39-cp39-musllinux_1_1_i686.whl", hash = "sha256:528dcf7ec49fb5a84bf6fe346c1cc3c55b0e7603c2123881996ca3ad79db5bfc"},
|
||||
{file = "pydantic-1.10.6-cp39-cp39-musllinux_1_1_x86_64.whl", hash = "sha256:163e79386c3547c49366e959d01e37fc30252285a70619ffc1b10ede4758250a"},
|
||||
{file = "pydantic-1.10.6-cp39-cp39-win_amd64.whl", hash = "sha256:189318051c3d57821f7233ecc94708767dd67687a614a4e8f92b4a020d4ffd06"},
|
||||
{file = "pydantic-1.10.6-py3-none-any.whl", hash = "sha256:acc6783751ac9c9bc4680379edd6d286468a1dc8d7d9906cd6f1186ed682b2b0"},
|
||||
{file = "pydantic-1.10.6.tar.gz", hash = "sha256:cf95adb0d1671fc38d8c43dd921ad5814a735e7d9b4d9e437c088002863854fd"},
|
||||
]
|
||||
pygments = [
|
||||
{file = "Pygments-2.14.0-py3-none-any.whl", hash = "sha256:fa7bd7bd2771287c0de303af8bfdfc731f51bd2c6a47ab69d117138893b82717"},
|
||||
|
|
@ -2082,6 +2137,25 @@ rsa = [
|
|||
{file = "rsa-4.9-py3-none-any.whl", hash = "sha256:90260d9058e514786967344d0ef75fa8727eed8a7d2e43ce9f4bcf1b536174f7"},
|
||||
{file = "rsa-4.9.tar.gz", hash = "sha256:e38464a49c6c85d7f1351b0126661487a7e0a14a50f1675ec50eb34d4f20ef21"},
|
||||
]
|
||||
ruff = [
|
||||
{file = "ruff-0.0.254-py3-none-macosx_10_7_x86_64.whl", hash = "sha256:dd58c500d039fb381af8d861ef456c3e94fd6855c3d267d6c6718c9a9fe07be0"},
|
||||
{file = "ruff-0.0.254-py3-none-macosx_10_9_x86_64.macosx_11_0_arm64.macosx_10_9_universal2.whl", hash = "sha256:688379050ae05394a6f9f9c8471587fd5dcf22149bd4304a4ede233cc4ef89a1"},
|
||||
{file = "ruff-0.0.254-py3-none-manylinux_2_17_aarch64.manylinux2014_aarch64.whl", hash = "sha256:ac1429be6d8bd3db0bf5becac3a38bd56f8421447790c50599cd90fd53417ec4"},
|
||||
{file = "ruff-0.0.254-py3-none-manylinux_2_17_armv7l.manylinux2014_armv7l.whl", hash = "sha256:059a380c08e849b6f312479b18cc63bba2808cff749ad71555f61dd930e3c9a2"},
|
||||
{file = "ruff-0.0.254-py3-none-manylinux_2_17_i686.manylinux2014_i686.whl", hash = "sha256:b3f15d5d033fd3dcb85d982d6828ddab94134686fac2c02c13a8822aa03e1321"},
|
||||
{file = "ruff-0.0.254-py3-none-manylinux_2_17_ppc64.manylinux2014_ppc64.whl", hash = "sha256:8deba44fd563361c488dedec90dc330763ee0c01ba54e17df54ef5820079e7e0"},
|
||||
{file = "ruff-0.0.254-py3-none-manylinux_2_17_ppc64le.manylinux2014_ppc64le.whl", hash = "sha256:ef20bf798ffe634090ad3dc2e8aa6a055f08c448810a2f800ab716cc18b80107"},
|
||||
{file = "ruff-0.0.254-py3-none-manylinux_2_17_s390x.manylinux2014_s390x.whl", hash = "sha256:0deb1d7226ea9da9b18881736d2d96accfa7f328c67b7410478cc064ad1fa6aa"},
|
||||
{file = "ruff-0.0.254-py3-none-manylinux_2_17_x86_64.manylinux2014_x86_64.whl", hash = "sha256:27d39d697fdd7df1f2a32c1063756ee269ad8d5345c471ee3ca450636d56e8c6"},
|
||||
{file = "ruff-0.0.254-py3-none-musllinux_1_2_aarch64.whl", hash = "sha256:2fc21d060a3197ac463596a97d9b5db2d429395938b270ded61dd60f0e57eb21"},
|
||||
{file = "ruff-0.0.254-py3-none-musllinux_1_2_armv7l.whl", hash = "sha256:f70dc93bc9db15cccf2ed2a831938919e3e630993eeea6aba5c84bc274237885"},
|
||||
{file = "ruff-0.0.254-py3-none-musllinux_1_2_i686.whl", hash = "sha256:09c764bc2bd80c974f7ce1f73a46092c286085355a5711126af351b9ae4bea0c"},
|
||||
{file = "ruff-0.0.254-py3-none-musllinux_1_2_x86_64.whl", hash = "sha256:d4385cdd30153b7aa1d8f75dfd1ae30d49c918ead7de07e69b7eadf0d5538a1f"},
|
||||
{file = "ruff-0.0.254-py3-none-win32.whl", hash = "sha256:c38291bda4c7b40b659e8952167f386e86ec29053ad2f733968ff1d78b4c7e15"},
|
||||
{file = "ruff-0.0.254-py3-none-win_amd64.whl", hash = "sha256:e15742df0f9a3615fbdc1ee9a243467e97e75bf88f86d363eee1ed42cedab1ec"},
|
||||
{file = "ruff-0.0.254-py3-none-win_arm64.whl", hash = "sha256:b435afc4d65591399eaf4b2af86e441a71563a2091c386cadf33eaa11064dc09"},
|
||||
{file = "ruff-0.0.254.tar.gz", hash = "sha256:0eb66c9520151d3bd950ea43b3a088618a8e4e10a5014a72687881e6f3606312"},
|
||||
]
|
||||
six = [
|
||||
{file = "six-1.16.0-py2.py3-none-any.whl", hash = "sha256:8abb2f1d86890a2dfb989f9a77cfcfd3e47c2a354b01111771326f8aa26e0254"},
|
||||
{file = "six-1.16.0.tar.gz", hash = "sha256:1e61c37477a1626458e36f7b1d82aa5c9b094fa4802892072e49de9c60c4c926"},
|
||||
|
|
|
|||
|
|
@ -20,6 +20,8 @@ langchain = {git = "https://github.com/ibiscp/langchain.git", rev = "ibis"}
|
|||
[tool.poetry.group.dev.dependencies]
|
||||
black = "^23.1.0"
|
||||
ipykernel = "^6.21.2"
|
||||
mypy = "^1.1.1"
|
||||
ruff = "^0.0.254"
|
||||
|
||||
[build-system]
|
||||
requires = ["poetry-core"]
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue