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Update main.py
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main.py
CHANGED
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@@ -54,63 +54,55 @@ sys_prompts = {
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},
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}
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class QueryModel(BaseModel):
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topic: str = Query(default="market research", description="input query to generate Report")
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description: str = Query(default="", description="additional context for report")
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user_id: str = Query(default="", description="unique user id")
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user_name: str = Query(default="", description="user name")
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internet: bool = Query(default=True, description="Enable Internet search")
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output_format: str = Query(default="Tabular Report", description="Output format for the report", enum=["Chat", "Full Text Report", "Tabular Report", "Tables only"])
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data_format: str = Query(default="Structured data", description="Type of data to extract from the internet", enum=["No presets", "Structured data", "Quantitative data"])
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@app.post("/generate_report")
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@cache(expire=604800)
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async def generate_report(
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description =
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user_id =
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optimized_search_query = ""
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all_text_with_urls = [("","")]
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# Combine query with user keywords
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if
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search_query = description
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# Search for relevant URLs
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try:
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urls,optimized_search_query = search_brave(search_query, num_results=4)
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# Fetch and extract content from the URLs
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all_text_with_urls = fetch_and_extract_content(data_format, urls, query_str)
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# Prepare the prompt for generating the report
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additional_context = limit_tokens(str(all_text_with_urls))
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prompt = f"#### COMPLETE THE TASK: {description} #### IN THE CONTEXT OF ### CONTEXT: {query_str} USING THE #### SCRAPED DATA:{additional_context}"
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except Exception as e:
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print("failed to search/scrape results, falling back to LLM response")
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if not
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prompt = f"#### COMPLETE THE TASK: {description} #### IN THE CONTEXT OF ### CONTEXT: {query_str}"
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md_report = together_response(prompt, model=llm_default_medium, SysPrompt=sys_prompt_output_format)
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if user_id != "test":
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insert_data(user_id, query_str, description,
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references_html = dict()
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for text, url in all_text_with_urls:
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references_html[url] = str(md_to_html(text))
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# Return the generated report
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return {
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"report": md_to_html(md_report),
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"references": references_html,
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"
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}
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app.add_middleware(
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},
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}
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@app.post("/generate_report")
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@cache(expire=604800) # Set cache expiration to 7 days (7 * 24 * 60 * 60 seconds)
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async def generate_report(
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topic: str = Query(default="market research", description="input query to generate Report"),
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description: str = Query(default="", description="additional context for report"),
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user_id: str = Query(default="", description="unique user id"),
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user_name: str = Query(default="", description="user name"),
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internet: bool = Query(default=True, description="Enable Internet search"),
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output_format: str = Query(default="Tabular Report", description="Output format for the report", enum=["Chat", "Full Text Report", "Tabular Report", "Tables only"]),
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data_format: str = Query(default="Structured data", description="Type of data to extract from the internet", enum=["No presets", "Structured data", "Quantitative data"])
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):
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query_str = topic
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internet_status = "online" if internet else "offline"
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sys_prompt_output_format = sys_prompts[internet_status][output_format]
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optimized_search_query = ""
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all_text_with_urls = [("","")]
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# Combine query with user keywords
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if internet:
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search_query = description
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# Search for relevant URLs
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try:
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urls, optimized_search_query = search_brave(search_query, num_results=4)
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# Fetch and extract content from the URLs
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all_text_with_urls = fetch_and_extract_content(data_format, urls, query_str)
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# Prepare the prompt for generating the report
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additional_context = limit_tokens(str(all_text_with_urls))
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prompt = f"#### COMPLETE THE TASK: {description} #### IN THE CONTEXT OF ### CONTEXT: {query_str} USING THE #### SCRAPED DATA:{additional_context}"
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except Exception as e:
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internet = False
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print("failed to search/scrape results, falling back to LLM response")
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if not internet:
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prompt = f"#### COMPLETE THE TASK: {description} #### IN THE CONTEXT OF ### CONTEXT: {query_str}"
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md_report = together_response(prompt, model=llm_default_medium, SysPrompt=sys_prompt_output_format)
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if user_id != "test":
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insert_data(user_id, query_str, description, str(all_text_with_urls), md_report)
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references_html = dict()
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for text, url in all_text_with_urls:
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references_html[url] = str(md_to_html(text))
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# Return the generated report
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return {
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"report": md_to_html(md_report),
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"references": references_html,
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"search_query": optimized_search_query
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}
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app.add_middleware(
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