Spaces:
Sleeping
Sleeping
File size: 2,502 Bytes
c2ae22f e75797d c2ae22f e75797d c2ae22f e75797d c2ae22f e75797d c2ae22f e75797d c2ae22f e75797d c2ae22f e75797d c2ae22f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 |
from langchain.llms import OpenAI
from langchain_experimental.agents.agent_toolkits import create_pandas_dataframe_agent
import pandas as pd
import environ
env = environ.Env()
environ.Env.read_env()
API_KEY = env("OPENAI_API_KEY")
def create_agent(filename: str):
"""
Create an agent that can access and use a large language model (LLM).
Args:
filename: The path to the CSV file that contains the data.
Returns:
An agent that can access and use the LLM.
"""
# Create an OpenAI object.
llm = OpenAI(openai_api_key=API_KEY)
# Read the CSV file into a Pandas DataFrame.
df = pd.read_csv(filename)
# Create a Pandas DataFrame agent.
return create_pandas_dataframe_agent(llm, df, verbose=False)
def query_agent(agent, query):
"""
Query an agent and return the response as a string.
Args:
agent: The agent to query.
query: The query to ask the agent.
Returns:
The response from the agent as a string.
"""
prompt = (
"""
For the following query, if it requires drawing a table, reply as follows:
{"table": {"columns": ["column1", "column2", ...], "data": [[value1, value2, ...], [value1, value2, ...], ...]}}
If the query requires creating a bar chart, reply as follows:
{"bar": {"columns": ["A", "B", "C", ...], "data": [25, 24, 10, ...]}}
If the query requires creating a line chart, reply as follows:
{"line": {"columns": ["A", "B", "C", ...], "data": [25, 24, 10, ...]}}
There can only be two types of chart, "bar" and "line".
If it is just asking a question that requires neither, reply as follows:
{"answer": "answer"}
Example:
{"answer": "I do not have sufficient information to provide an answer to your query."}
If you do not know the answer, reply as follows:
{"answer": "I do not know."}
Return all output as a string.
All strings in "columns" list and data list, should be in double quotes,
For example: {"columns": ["title", "ratings_count"], "data": [["Gilead", 361], ["Spider's Web", 5164]]}
Lets think step by step.
Below is the query.
Query:
"""
+ query
)
# Run the prompt through the agent.
response = agent.run(prompt)
# Convert the response to a string.
return response.__str__() |