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Build error
Build error
Update app.py
Browse files
app.py
CHANGED
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@@ -14,6 +14,7 @@ import uuid
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#from query import tasks
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from agent import (
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PREFIX,
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COMPRESS_DATA_PROMPT,
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COMPRESS_DATA_PROMPT_SMALL,
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LOG_PROMPT,
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@@ -24,6 +25,10 @@ api=HfApi()
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client = InferenceClient(
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"mistralai/Mixtral-8x7B-Instruct-v0.1"
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)
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def find_all(url):
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return_list=[]
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@@ -289,7 +294,7 @@ def compress_data_og(c, instruct, history):
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def summarize(inp,history,report_check,data=None,files=None,url=None,pdf_url=None,pdf_batch=None):
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json_box=[]
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if inp == "":
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inp = "Process this data"
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@@ -313,9 +318,6 @@ def summarize(inp,history,report_check,data=None,files=None,url=None,pdf_url=Non
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except Exception as e:
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print(e)
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#data=f'{data}\nError reading URL ({batch_url})'
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-
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-
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if pdf_url.startswith("http"):
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print("PDF_URL")
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out = read_pdf_online(pdf_url)
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@@ -352,41 +354,170 @@ def summarize(inp,history,report_check,data=None,files=None,url=None,pdf_url=Non
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if i == " " or i=="," or i=="\n":
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c +=1
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print (f'c:: {c}')
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for i in str(out):
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if i == " " or i=="," or i=="\n":
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c +=1
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print (f'c2:: {c}')
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rawp = compress_data_og(c,inp,out)
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else:
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rawp = out
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else:
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rawp = "Provide a valid data source"
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#print (rawp)
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#print (f'out:: {out}')
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#history += "observation: the search results are:\n {}\n".format(out)
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#task = "complete?"
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history.clear()
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history.append((inp,rawp))
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yield "", history,error_box,json_out
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#################################
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def clear_fn():
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return "",[(None,None)]
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@@ -399,6 +530,7 @@ with gr.Blocks() as app:
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prompt=gr.Textbox(label = "Instructions (optional)")
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with gr.Column(scale=1):
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report_check=gr.Checkbox(label="Return Report", value=True)
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button=gr.Button()
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#models_dd=gr.Dropdown(choices=[m for m in return_list],interactive=True)
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@@ -421,6 +553,6 @@ with gr.Blocks() as app:
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#text=gr.JSON()
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#inp_query.change(search_models,inp_query,models_dd)
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clear_btn.click(clear_fn,None,[prompt,chatbot])
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go=button.click(summarize,[prompt,chatbot,report_check,data,file,url,pdf_url,pdf_batch],[prompt,chatbot,e_box,json_out])
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stop_button.click(None,None,None,cancels=[go])
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app.queue(default_concurrency_limit=20).launch(server_port=7860,show_api=False)
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#from query import tasks
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from agent import (
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PREFIX,
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+
SAVE_MEMORY,
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COMPRESS_DATA_PROMPT,
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COMPRESS_DATA_PROMPT_SMALL,
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LOG_PROMPT,
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client = InferenceClient(
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"mistralai/Mixtral-8x7B-Instruct-v0.1"
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)
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reponame="Omnibus/tmp"
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save_data=f'https://huggingface.co/datasets/{reponame}/raw/main/'
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token_self = os.environ['HF_TOKEN']
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api=HfApi(token=token_self)
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def find_all(url):
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return_list=[]
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def summarize(inp,history,report_check,sum_mem_check,data=None,files=None,url=None,pdf_url=None,pdf_batch=None):
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json_box=[]
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if inp == "":
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inp = "Process this data"
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except Exception as e:
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print(e)
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#data=f'{data}\nError reading URL ({batch_url})'
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if pdf_url.startswith("http"):
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print("PDF_URL")
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out = read_pdf_online(pdf_url)
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if i == " " or i=="," or i=="\n":
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c +=1
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print (f'c:: {c}')
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if sum_mem_check=="Memory":
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save_memory(inp,out)
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rawp = "Complete"
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if sum_mem_check=="Summarize":
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json_out = compress_data(c,inp,out)
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out = str(json_out)
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if report_check:
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rl = len(out)
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print(f'rl:: {rl}')
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c=1
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for i in str(out):
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if i == " " or i=="," or i=="\n":
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c +=1
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print (f'c2:: {c}')
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rawp = compress_data_og(c,inp,out)
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else:
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rawp = out
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else:
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rawp = "Provide a valid data source"
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history.clear()
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history.append((inp,rawp))
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yield "", history,error_box,json_out
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SAVE_MEMORY = """
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You are attempting to complete the task
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task: {task}
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Data:
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{history}
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Instructions:
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Compile and categorize the data above into a JSON dictionary string
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Include ALL text, datapoints, titles, descriptions, and source urls indexed into an easy to search JSON format
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Your final response should be only the final formatted JSON string enclosed in brackets, and nothing else.
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Required keys:
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"keywords":["short", "list", "of", "keywords", "relevant", "to", "this", "entry"]
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"title":"title of entry"
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"description":"description of entry"
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"content":"full content of data about entry"
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"url":"https://url.source"
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"""
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def save_memory(purpose, history):
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uid=uuid.uuid4()
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history=str(history)
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c=0
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inp = str(history)
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rl = len(inp)
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print(f'rl:: {rl}')
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for i in str(inp):
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if i == " " or i=="," or i=="\n" or i=="/" or i=="." or i=="<":
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c +=1
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print (f'c:: {c}')
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seed=random.randint(1,1000000000)
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print (c)
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#tot=len(purpose)
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#print(tot)
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divr=int(c)/MAX_DATA
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divi=int(divr)+1 if divr != int(divr) else int(divr)
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chunk = int(int(c)/divr)
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print(f'chunk:: {chunk}')
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print(f'divr:: {divr}')
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print (f'divi:: {divi}')
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#out = []
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#out=""
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s=0
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e=chunk
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print(f'e:: {e}')
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new_history=""
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task = f'Index this Data\n'
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for z in range(divi):
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print(f's:e :: {s}:{e}')
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hist = inp[s:e]
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resp = run_gpt(
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SAVE_MEMORY,
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stop_tokens=["observation:", "task:", "action:", "thought:"],
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max_tokens=4096,
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seed=seed,
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purpose=purpose,
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task=task,
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history=hist,
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).strip('\n')
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#new_history = resp
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print (resp)
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#out+=resp
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e=e+chunk
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s=s+chunk
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print ("final1" + resp)
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try:
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resp='[{'+resp.split('[{')[1].split('</s>')[0]
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print ("final2\n" + resp)
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print(f"keywords:: {resp['keywords']}")
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except Exception as e:
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resp = resp
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print(e)
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timestamp=str(datetime.datetime.now())
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timename=timestamp.replace(" ","--").replace(":","-").replace(".","-")
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json_object=resp
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#json_object = json.dumps(out_box)
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#json_object = json.dumps(out_box,indent=4)
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with open(f"tmp-{uid}.json", "w") as outfile:
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outfile.write(json_object)
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api.upload_file(
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path_or_fileobj=f"tmp-{uid}.json",
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path_in_repo=f"/mem-test2/{timename}.json",
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repo_id=reponame,
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#repo_id=save_data.split('datasets/',1)[1].split('/raw',1)[0],
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token=token_self,
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repo_type="dataset",
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)
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lines = resp.strip().strip("\n").split("\n")
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r = requests.get(f'{save_data}mem-test2/main.json')
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print(f'status code main:: {r.status_code}')
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if r.status_code==200:
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lod = json.loads(r.text)
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#lod = eval(lod)
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print (f'lod:: {lod}')
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else:
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lod = []
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for i,line in enumerate(lines):
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key_box=[]
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print(f'LINE:: {line}')
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if ":" in line:
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print(f'line:: {line}')
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if "keywords" in line[:16]:
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print(f'trying:: {line}')
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keyw=line.split(":")[1]
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print (keyw)
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print (keyw.split("[")[1].split("]")[0])
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keyw=keyw.split("[")[1].split("]")[0]
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for ea in keyw.split(","):
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s1=""
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ea=ea.strip().strip("\n")
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for ev in ea:
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if ev.isalnum():
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s1+=ev
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if ev == " ":
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s1+=ev
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#ea=s1
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print(s1)
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key_box.append(s1)
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lod.append({"file_name":timename,"keywords":key_box})
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json_object = json.dumps(lod, indent=4)
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with open(f"tmp2-{uid}.json", "w") as outfile2:
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outfile2.write(json_object)
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api.upload_file(
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path_or_fileobj=f"tmp2-{uid}.json",
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path_in_repo=f"/mem-test2/main.json",
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repo_id=reponame,
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#repo_id=save_data.split('datasets/',1)[1].split('/raw',1)[0],
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token=token_self,
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repo_type="dataset",
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)
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#return [resp]
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#################################
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def clear_fn():
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return "",[(None,None)]
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prompt=gr.Textbox(label = "Instructions (optional)")
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with gr.Column(scale=1):
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report_check=gr.Checkbox(label="Return Report", value=True)
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sum_mem_check=gr.Radio(label="Output",choices=["Summary","Memory"])
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button=gr.Button()
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#models_dd=gr.Dropdown(choices=[m for m in return_list],interactive=True)
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#text=gr.JSON()
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#inp_query.change(search_models,inp_query,models_dd)
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clear_btn.click(clear_fn,None,[prompt,chatbot])
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go=button.click(summarize,[prompt,chatbot,report_check,sum_mem_check,data,file,url,pdf_url,pdf_batch],[prompt,chatbot,e_box,json_out])
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stop_button.click(None,None,None,cancels=[go])
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app.queue(default_concurrency_limit=20).launch(server_port=7860,show_api=False)
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