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feat: add ZeroShotPrompt

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This commit is contained in:
Ibis Prevedello 2023-03-04 23:06:49 -03:00
commit e909a938c9
5 changed files with 141 additions and 8 deletions
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40
langflow/backend/customs.py Normal file
View file

@ -0,0 +1,40 @@
from langchain.agents.mrkl import prompt
def get_custom_prompts():
return {
"ZeroShotPrompt": {
"template": {
"_type": "zero_shot",
"prefix": {
"type": "str",
"required": False,
"placeholder": "",
"list": False,
"show": True,
"multiline": True,
"value": prompt.PREFIX,
},
"suffix": {
"type": "str",
"required": True,
"placeholder": "",
"list": False,
"show": True,
"multiline": True,
"value": prompt.SUFFIX,
},
"format_instructions": {
"type": "str",
"required": False,
"placeholder": "",
"list": False,
"show": True,
"multiline": True,
"value": prompt.FORMAT_INSTRUCTIONS,
},
},
"description": "Prompt template for Zero Shot Agent.",
"base_classes": ["BasePromptTemplate"],
}
}

95
langflow/backend/endpoints.py
View file

@ -9,6 +9,7 @@ from langchain.llms.loading import load_llm_from_config
from langchain.prompts.loading import load_prompt_from_config
from typing import Any
# build router
router = APIRouter()
@ -26,6 +27,10 @@ def get_type_list():
@router.get("/all")
def get_all():
# library_prompts = {
# prompt: signature.get_prompt(prompt) for prompt in list_endpoints.list_prompts()
# }
# custom_prompts = customs.get_custom_prompts()
return {
"chains": {
chain: signature.get_chain(chain) for chain in list_endpoints.list_chains()
@ -33,6 +38,7 @@ def get_all():
"agents": {
agent: signature.get_agent(agent) for agent in list_endpoints.list_agents()
},
# "prompts": {**library_prompts, **custom_prompts},
"prompts": {
prompt: signature.get_prompt(prompt)
for prompt in list_endpoints.list_prompts()
@ -67,8 +73,22 @@ def get_all():
@router.post("/predict")
def get_load(data: dict[str, Any]):
# Get type list
type_list = get_type_list()
# Substitute ZeroShotPromt with PromptTemplate
for node in data['nodes']:
if node["data"]["type"] == "ZeroShotPrompt":
# Build Prompt Template
tools = [
tool
for tool in data['nodes']
if tool["type"] != "chatOutputNode"
and "Tool" in tool["data"]["node"]["base_classes"]
]
node["data"] = build_prompt_template(prompt=node["data"], tools=tools)
break
# Add input variables
data = payload.extract_input_variables(data)
@ -96,12 +116,75 @@ def get_load(data: dict[str, Any]):
else:
return {"result": "Error: Type should be either agent, chain or llm"}
# elif extracted_json["_type"] in type_list["prompts"]:
# loaded = load_prompt_from_config(extracted_json)
# print(loaded.format(product=''))
# return {'result': loaded.format(product=message)}
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"]
# if type in a["prompts"]:
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])
# return a
prompt["type"] = "PromptTemplate"
# prompt["value"] = value
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

5
langflow/backend/list_endpoints.py
View file

@ -7,6 +7,7 @@ from langchain import llms
from langchain.chains.conversation import memory as memories
from langchain.agents.load_tools import get_all_tool_names
from langflow.backend import util
from langflow.backend import customs
# build router
@ -52,10 +53,12 @@ def list_agents():
@router.get("/prompts")
def list_prompts():
"""List all prompt types"""
return [
custom_prompts = customs.get_custom_prompts()
library_prompts = [
prompt.__annotations__["return"].__name__
for prompt in prompts.loading.type_to_loader_dict.values()
]
return library_prompts + list(custom_prompts.keys())
@router.get("/llms")

6
langflow/backend/payload.py
View file

@ -59,12 +59,16 @@ def build_json(root, nodes, edges):
# if module_type == "Tool":
# pass
if module_type in ["str", "bool", "int", "float", "Any"]:
# print(key)
# try:
value = value["value"]
# except:
# pass
elif "dict" in module_type:
value = {}
else:
# if value['list']:
print(key)
# print(key)
children = []
for c in local_nodes:
module_types = [c["data"]["type"]]

3
langflow/backend/signature.py
View file

@ -10,6 +10,7 @@ from langchain.agents.load_tools import (
from langchain.chains.conversation import memory as memories
from langflow.backend import util
from langflow.backend import customs
# build router
router = APIRouter(
@ -42,6 +43,8 @@ def get_agent(name: str):
def get_prompt(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
)