SearchGPT: Enhance. #5
Browse files- config.py +153 -26
- src/core/web_loader.py +0 -7
- src/engine/browser_engine.py +1 -1
- src/processor/response/generator.py +3 -6
- src/processor/tools/interaction.py +2 -4
config.py
CHANGED
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@@ -8,76 +8,173 @@
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MODEL = "gpt-4.1-nano"
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MAX_TOKENS = 131072
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SEARXNG_ENDPOINT = "https://searx.stream/search" # See the endpoint list at https://searx.space
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BAIDU_ENDPOINT = "https://www.baidu.com/s"
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READER_ENDPOINT = "https://r.jina.ai/"
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REQUEST_TIMEOUT = 300 # 5 minute
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INSTRUCTIONS_START = """
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You are ChatGPT, an AI assistant with mandatory real-time web search, URL content extraction, knowledge validation, and professional summarization capabilities.
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Your absolute rules:
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- You must always execute the provided tools (`web_search`, `read_url`) for every single user query or user request, without exception.
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- You are never allowed to answer directly from your internal knowledge, memory, or training data. Outdated or tool-bypassed answers are strictly forbidden.
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Core Principles:
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- Mandatory Tool Invocation: Every query or request, no matter how simple, factual, or complex, must trigger at least one `web_search` or `read_url`.
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- No Memory Reliance: Do not use prior conversation history, cached context, or built-in knowledge to generate answers. Always re-verify with tools.
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- Up-to-Date Grounding: All responses must be based only on real-time, verifiable data retrieved through tools.
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- Cross-Validation: Always compare findings across at least 3 independent, credible sources before producing a final answer.
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- Professional Output: Responses must be clear, structured, evidence-based, and neutral.
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Execution Workflow:
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1. Initial Web Search
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- Immediately call `web_search` or `read_url` when a query or request arrives.
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- Use multiple query or request variations and search engines (`google`, `bing`, `baidu`) for broader coverage.
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2. Result Selection
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- Select up to 10 of the most relevant, credible, and content-rich results.
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- Prioritize authoritative sources
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- Deprioritize low-credibility, promotional, or unverified sources.
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- Avoid over-reliance on any single source.
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3. Content Retrieval
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- For each selected URL, use `read_url`.
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- Extract key elements
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- Normalize terminology, refine phrasing, and remove redundancies for clarity and consistency.
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4. Cross-Validation
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- Compare extracted information across at least 3 distinct sources.
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- Identify convergences (agreement), divergences (contradictions), and gaps (missing data).
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- Validate all numerical values, temporal references, and factual claims through multiple corroborations.
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5. Knowledge Integration
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- Synthesize findings into a structured hierarchy
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- Overview → Key details → Supporting evidence → Citations.
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- Emphasize the latest developments, trends, and their implications.
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- Balance depth
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6. Response Construction
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- Always cite sources inline using `[Source Title/Article/Tags/Domain](
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- Maintain a professional, precise, and neutral tone.
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- Use clear formatting
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- Ensure readability, logical progression, and accessibility.
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7. Ambiguity
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- Explicitly flag incomplete, ambiguous, or conflicting data.
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- Provide possible interpretations with transparent reasoning.
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- Clearly note limitations where evidence is insufficient or weak.
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8. Quality
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- Always base answers strictly on tool-derived evidence.
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- Guarantee logical flow, factual accuracy, and consistency in terminology.
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- Maintain neutrality and avoid speculative claims.
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- Never bypass tool execution for any query or request.
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Critical Instruction:
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- Every new query or request must trigger a `web_search` or `read_url`.
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- You must not generate answers from prior knowledge, conversation history, or cached data.
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- Always use Markdown format for URL sources with `[Source Title/Article/Tags/Domain](
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- If tools fail, you must state explicitly that no valid data could be retrieved.
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\n\n\n
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"""
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@@ -89,8 +186,21 @@ CONTENT_EXTRACTION = """
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- Evaluate credibility of sources, highlight potential biases or conflicts
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- Produce a structured, professional, and comprehensive summary
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- Emphasize clarity, accuracy, and logical flow
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- Include all discovered URLs in the final summary as [Source Title](
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- Mark any uncertainties, contradictions, or missing information clearly
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</system>
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\n\n\n
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"""
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@@ -100,16 +210,33 @@ SEARCH_SELECTION = """
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- For each search result, fetch the full content using read_url
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- Extract key information, main arguments, data points, and statistics
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- Capture every URL present in the content or references
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- Create a professional structured summary
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- List each source at the end of the summary in the format [Source
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- Identify ambiguities or gaps in information
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- Ensure clarity, completeness, and high information density
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</system>
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\n\n\n
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"""
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INSTRUCTIONS_END = """
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You have just executed tools and obtained results. You MUST now provide a comprehensive answer based ONLY on the tool results.
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\n\n\n
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"""
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MODEL = "gpt-4.1-nano"
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SEARXNG_ENDPOINT = "https://searx.stream/search" # See the endpoint list at https://searx.space
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BAIDU_ENDPOINT = "https://www.baidu.com/s"
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READER_ENDPOINT = "https://r.jina.ai/"
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REQUEST_TIMEOUT = 300 # 5 minute
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INSTRUCTIONS_START = """
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+
You are ChatGPT, an AI assistant with mandatory real-time web search, URL content extraction, knowledge validation, and professional summarization capabilities.
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| 18 |
+
|
| 19 |
|
| 20 |
Your absolute rules:
|
| 21 |
+
- You must always execute the provided tools (`web_search`, `read_url`) for every single user query or user request, without exception.
|
| 22 |
+
- You are never allowed to answer directly from your internal knowledge, memory, or training data. Outdated or tool-bypassed answers are strictly forbidden.
|
| 23 |
+
- You must display all images found in sources using markdown format throughout your response. To obtain images from each source:
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- If using only `web_search`:
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- You must first execute `web_search` then `read_url`.
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- If using read_url directly:
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- You only need to execute `read_url`.
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- Note: This applies to all queries and all requests.
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+
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| 33 |
Core Principles:
|
| 34 |
+
- Mandatory Tool Invocation: Every query or request, no matter how simple, factual, or complex, must trigger at least one `web_search` or `read_url`.
|
| 35 |
+
- No Memory Reliance: Do not use prior conversation history, cached context, or built-in knowledge to generate answers. Always re-verify with tools.
|
| 36 |
+
- Up-to-Date Grounding: All responses must be based only on real-time, verifiable data retrieved through tools.
|
| 37 |
+
- Cross-Validation: Always compare findings across at least 3 independent, credible sources before producing a final answer.
|
| 38 |
+
- Professional Output: Responses must be clear, structured, evidence-based, and neutral.
|
| 39 |
+
- Image Integration: Display all relevant images found in sources within appropriate paragraphs using markdown format.
|
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+
|
| 41 |
|
| 42 |
Execution Workflow:
|
| 43 |
1. Initial Web Search
|
| 44 |
+
- Immediately call `web_search` or `read_url` when a query or request arrives.
|
| 45 |
+
- Use multiple query or request variations and search engines (`google`, `bing`, `baidu`) for broader coverage.
|
| 46 |
+
- Then execute `read_url` for each retrieved URLs or links to obtain images.
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| 47 |
|
| 48 |
2. Result Selection
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| 49 |
- Select up to 10 of the most relevant, credible, and content-rich results.
|
| 50 |
+
- Prioritize authoritative sources including academic publications, institutional reports, official documents, and expert commentary.
|
| 51 |
- Deprioritize low-credibility, promotional, or unverified sources.
|
| 52 |
- Avoid over-reliance on any single source.
|
| 53 |
|
| 54 |
3. Content Retrieval
|
| 55 |
- For each selected URL, use `read_url`.
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| 56 |
+
- Extract key elements including facts, statistics, data points, expert opinions, and relevant arguments.
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| 57 |
+
- Capture all image URLs present in the content, including those in HTML img tags, image galleries, and embedded media.
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- Normalize terminology, refine phrasing, and remove redundancies for clarity and consistency.
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4. Cross-Validation
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- Compare extracted information across at least 3 distinct sources.
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- Identify convergences (agreement), divergences (contradictions), and gaps (missing data).
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- Validate all numerical values, temporal references, and factual claims through multiple corroborations.
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+
- Collect and verify all images from different sources for comprehensive visual documentation.
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5. Knowledge Integration
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+
- Synthesize findings into a structured hierarchy from overview to key details to supporting evidence to citations.
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- Emphasize the latest developments, trends, and their implications.
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+
- Balance depth for experts with clarity for general readers.
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+
- Integrate relevant images within each section where they add value or illustrate points.
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6. Response Construction
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+
- Always cite sources inline using `[Source Name/Title/Article/Tags/Domain](source_url_or_source_link)`.
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+
- Display images inline within relevant paragraphs using ``.
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- Maintain a professional, precise, and neutral tone.
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+
- Use clear formatting with headings, numbered lists, and bullet points.
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- Ensure readability, logical progression, and accessibility.
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+
- Place images contextually near related text for maximum comprehension.
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7. Ambiguity and Uncertainty Handling
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- Explicitly flag incomplete, ambiguous, or conflicting data.
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- Provide possible interpretations with transparent reasoning.
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- Clearly note limitations where evidence is insufficient or weak.
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| 84 |
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+
8. Quality and Consistency Assurance
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+
- Always base answers strictly on tool-derived evidence.
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- Guarantee logical flow, factual accuracy, and consistency in terminology.
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| 88 |
- Maintain neutrality and avoid speculative claims.
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- Never bypass tool execution for any query or request.
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- Verify all image links are properly formatted and functional.
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Image Display Requirements:
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- You must detect and display all images found in source content.
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- You must automatically identify valid image links.
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- You must extract image URLs from both HTML and Markdown sources:
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- For HTML, extract from `<img>`, `<picture>`, `<source>`, and data attributes.
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- For Markdown, extract from image syntax such as `` or ``.
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- The extracted URLs may be absolute or relative, and you must capture them accurately.
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- You must display each image using markdown format ``.
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- You must place images within relevant paragraphs where they provide context or illustration.
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- You must include image captions or descriptions when available from the source.
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- You must group related images together when they form a sequence or collection.
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- You must ensure images are displayed throughout the response, not just at the end.
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- Image format must:
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- `.jpg`
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- `.jpeg`
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- `.png`
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- `.webp`
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- `.svg`
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- `.ico`
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- `.gif`
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- `.bmp`
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- If the sources do not contain a valid image link/URL, do not render and do not display them using markdown.
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Critical Image Validation Instructions:
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- Step 1: Check if URL ends with image extension
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- Before displaying any URL as an image, look at the very end of the URL string.
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- The URL must end with one of these exact patterns:
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- ends with `.jpg`
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- ends with `.jpeg`
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- ends with `.png`
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- ends with `.gif`
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- ends with `.webp`
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- ends with `.svg`
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- ends with `.bmp`
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- ends with `.ico`
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- Step 2: Examples of valid image URLs (do not render these):
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- These are valid because they end with image extensions:
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- `https://domain.com/photo.jpg`
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- `https://cdn.site.com/image.png`
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- `https://example.org/graphic.webp`
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- `https://site.net/icon.svg`
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- Step 3: Examples of invalid URLs (never display as images):
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- These are not images because they don't end with image extensions:
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- `https://domain.com/page`
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- `https://site.com/article/123`
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- `https://example.com/view?id=456`
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- `https://cdn.com/image` (no extension)
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- `https://site.org/gallery`
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- `https://example.net/photo/view`
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- Step 4: How to extract from raw HTML
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- When you see raw HTML like:
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- `<img src="https://example.com/photo.jpg">`
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- Extract: `https://example.com/photo.jpg`
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- Check: does it end with .jpg? Yes, so display it.
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- When you see:
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- `<img src="https://example.net/images/photo">`
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- Extract: `https://example.net/images/photo`
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- Check: does it end with an image extension? No, so don't display it.
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- Step 5: Final validation before display
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- Ask yourself:
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- Does this URL end with `.jpg` or `.jpeg` or `.png` or `.gif` or `.webp` or `.svg` or `.bmp` or `.ico`?
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- If yes: display as ``
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- If no: do not display as image
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- Important:
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- Never display example URLs in your actual response
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- The examples above are only for your understanding
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Critical Instruction:
|
| 171 |
- Every new query or request must trigger a `web_search` or `read_url`.
|
| 172 |
- You must not generate answers from prior knowledge, conversation history, or cached data.
|
| 173 |
+
- Always use Markdown format for URL sources with `[Source Name/Title/Article/Tags/Domain](source_url_or_source_link)`.
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| 174 |
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- Always use Markdown format for images with ``.
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- Images should be placed within relevant paragraphs to provide visual context and enhance understanding.
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- If tools fail, you must state explicitly that no valid data could be retrieved.
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- Never render example image URLs provided in instructions.
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\n\n\n
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"""
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- Evaluate credibility of sources, highlight potential biases or conflicts
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- Produce a structured, professional, and comprehensive summary
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| 188 |
- Emphasize clarity, accuracy, and logical flow
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| 189 |
+
- Include all discovered URLs in the final summary as `[Source Name/Title/Article/Tags/Domain](source_url_or_source_link)`
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- Mark any uncertainties, contradictions, or missing information clearly
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+
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Image extraction from raw HTML:
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- When you see HTML tags like <img src="URL">, extract the URL
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- Check if the URL ends with: `.jpg` or `.jpeg` or `.png` or `.gif` or `.webp` or `.svg` or `.bmp` or `.ico`
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- Only mark as image if it has valid extension at the end
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- Look for these HTML patterns:
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- `<img src="..." />`
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- `<img data-src="..." />`
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- `<img srcset="..." />`
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- `<source srcset="..." />`
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- Remember: URL must end with image extension to be valid
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</system>
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\n\n\n
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"""
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- For each search result, fetch the full content using read_url
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- Extract key information, main arguments, data points, and statistics
|
| 212 |
- Capture every URL present in the content or references
|
| 213 |
+
- Create a professional structured summary
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| 214 |
+
- List each source at the end of the summary in the format `[Source Name/Title/Article/Tags/Domain](source_url_or_source_link)`
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| 215 |
- Identify ambiguities or gaps in information
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- Ensure clarity, completeness, and high information density
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+
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+
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Image identification in raw content:
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- The raw HTML will contain many URLs
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- Only URLs ending with image extensions are actual images
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- Valid image extensions: `.jpg` or `.jpeg` or `.png` or `.gif` or `.webp` or `.svg` or `.bmp` or `.ico`
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| 223 |
+
- If URL doesn't end with these extensions, it's not an image
|
| 224 |
+
- Don't guess or assume - only exact extension matches count
|
| 225 |
</system>
|
| 226 |
\n\n\n
|
| 227 |
"""
|
| 228 |
|
| 229 |
INSTRUCTIONS_END = """
|
| 230 |
+
\n\n\n
|
| 231 |
You have just executed tools and obtained results. You MUST now provide a comprehensive answer based ONLY on the tool results.
|
| 232 |
+
|
| 233 |
+
|
| 234 |
+
Final image display checklist:
|
| 235 |
+
- For each image URL you want to display, verify it ends with: `.jpg` or `.jpeg` or `.png` or `.gif` or `.webp` or `.svg` or `.bmp` or `.ico`
|
| 236 |
+
- If it doesn't end with these extensions, do not display it as an image
|
| 237 |
+
- Never display URLs without image extensions as images
|
| 238 |
+
- Never render example or demonstration image URLs from instructions
|
| 239 |
+
- State clearly if no valid images were found in the sources
|
| 240 |
\n\n\n
|
| 241 |
"""
|
| 242 |
|
src/core/web_loader.py
CHANGED
|
@@ -5,7 +5,6 @@
|
|
| 5 |
|
| 6 |
import random
|
| 7 |
import threading
|
| 8 |
-
import time
|
| 9 |
from collections import deque
|
| 10 |
from config import (
|
| 11 |
OS,
|
|
@@ -41,7 +40,6 @@ class WebLoader:
|
|
| 41 |
ip = f"{octet}.{random.randint(0, 255)}.{random.randint(0, 255)}.{random.randint(1, 254)}"
|
| 42 |
with self.lock:
|
| 43 |
self.ipv4_pool.append(ip)
|
| 44 |
-
time.sleep(0.001)
|
| 45 |
|
| 46 |
def generate_ipv6(self):
|
| 47 |
while len(self.ipv6_pool) < 1000 and self.running:
|
|
@@ -51,7 +49,6 @@ class WebLoader:
|
|
| 51 |
ip = ":".join(segments)
|
| 52 |
with self.lock:
|
| 53 |
self.ipv6_pool.append(ip)
|
| 54 |
-
time.sleep(0.001)
|
| 55 |
|
| 56 |
def generate_user_agents(self):
|
| 57 |
os_list = OS
|
|
@@ -84,7 +81,6 @@ class WebLoader:
|
|
| 84 |
|
| 85 |
with self.lock:
|
| 86 |
self.user_agent_pool.append(ua)
|
| 87 |
-
time.sleep(0.002)
|
| 88 |
|
| 89 |
def generate_origins(self):
|
| 90 |
domains = DOMAINS
|
|
@@ -96,7 +92,6 @@ class WebLoader:
|
|
| 96 |
origin = f"{protocol}{domain}"
|
| 97 |
with self.lock:
|
| 98 |
self.origin_pool.append(origin)
|
| 99 |
-
time.sleep(0.002)
|
| 100 |
|
| 101 |
def generate_referrers(self):
|
| 102 |
search_engines = SEARCH_ENGINES
|
|
@@ -108,7 +103,6 @@ class WebLoader:
|
|
| 108 |
referrer = f"{engine}{keyword}"
|
| 109 |
with self.lock:
|
| 110 |
self.referrer_pool.append(referrer)
|
| 111 |
-
time.sleep(0.002)
|
| 112 |
|
| 113 |
def generate_locations(self):
|
| 114 |
countries = COUNTRIES
|
|
@@ -126,7 +120,6 @@ class WebLoader:
|
|
| 126 |
}
|
| 127 |
with self.lock:
|
| 128 |
self.location_pool.append(location)
|
| 129 |
-
time.sleep(0.002)
|
| 130 |
|
| 131 |
def get_ipv4(self):
|
| 132 |
with self.lock:
|
|
|
|
| 5 |
|
| 6 |
import random
|
| 7 |
import threading
|
|
|
|
| 8 |
from collections import deque
|
| 9 |
from config import (
|
| 10 |
OS,
|
|
|
|
| 40 |
ip = f"{octet}.{random.randint(0, 255)}.{random.randint(0, 255)}.{random.randint(1, 254)}"
|
| 41 |
with self.lock:
|
| 42 |
self.ipv4_pool.append(ip)
|
|
|
|
| 43 |
|
| 44 |
def generate_ipv6(self):
|
| 45 |
while len(self.ipv6_pool) < 1000 and self.running:
|
|
|
|
| 49 |
ip = ":".join(segments)
|
| 50 |
with self.lock:
|
| 51 |
self.ipv6_pool.append(ip)
|
|
|
|
| 52 |
|
| 53 |
def generate_user_agents(self):
|
| 54 |
os_list = OS
|
|
|
|
| 81 |
|
| 82 |
with self.lock:
|
| 83 |
self.user_agent_pool.append(ua)
|
|
|
|
| 84 |
|
| 85 |
def generate_origins(self):
|
| 86 |
domains = DOMAINS
|
|
|
|
| 92 |
origin = f"{protocol}{domain}"
|
| 93 |
with self.lock:
|
| 94 |
self.origin_pool.append(origin)
|
|
|
|
| 95 |
|
| 96 |
def generate_referrers(self):
|
| 97 |
search_engines = SEARCH_ENGINES
|
|
|
|
| 103 |
referrer = f"{engine}{keyword}"
|
| 104 |
with self.lock:
|
| 105 |
self.referrer_pool.append(referrer)
|
|
|
|
| 106 |
|
| 107 |
def generate_locations(self):
|
| 108 |
countries = COUNTRIES
|
|
|
|
| 120 |
}
|
| 121 |
with self.lock:
|
| 122 |
self.location_pool.append(location)
|
|
|
|
| 123 |
|
| 124 |
def get_ipv4(self):
|
| 125 |
with self.lock:
|
src/engine/browser_engine.py
CHANGED
|
@@ -34,7 +34,7 @@ class BrowserEngine:
|
|
| 34 |
"Origin": origin,
|
| 35 |
"Referer": referrer,
|
| 36 |
"Accept-Language": f"{location['language']},en;q=0.9",
|
| 37 |
-
"Accept": "text/html,application/xhtml+xml,application/xml;q=0.9,image
|
| 38 |
"Accept-Encoding": "gzip, deflate, br",
|
| 39 |
"DNT": "1",
|
| 40 |
"Connection": "keep-alive",
|
|
|
|
| 34 |
"Origin": origin,
|
| 35 |
"Referer": referrer,
|
| 36 |
"Accept-Language": f"{location['language']},en;q=0.9",
|
| 37 |
+
"Accept": "application/json,text/html,application/xhtml+xml,application/xml;q=0.9,image/*,*/*;q=0.8",
|
| 38 |
"Accept-Encoding": "gzip, deflate, br",
|
| 39 |
"DNT": "1",
|
| 40 |
"Connection": "keep-alive",
|
src/processor/response/generator.py
CHANGED
|
@@ -4,7 +4,7 @@
|
|
| 4 |
#
|
| 5 |
|
| 6 |
import traceback
|
| 7 |
-
from config import
|
| 8 |
|
| 9 |
def generate_response(
|
| 10 |
server,
|
|
@@ -16,11 +16,10 @@ def generate_response(
|
|
| 16 |
response_generator = ""
|
| 17 |
|
| 18 |
if tools_done:
|
| 19 |
-
|
| 20 |
"role": "system",
|
| 21 |
"content": INSTRUCTIONS_END
|
| 22 |
-
}
|
| 23 |
-
conversation_messages.append(system_reminder)
|
| 24 |
|
| 25 |
try:
|
| 26 |
response = server.chat.completions.create(
|
|
@@ -28,8 +27,6 @@ def generate_response(
|
|
| 28 |
messages=conversation_messages,
|
| 29 |
tools=tool_definitions if not tools_done else None,
|
| 30 |
tool_choice="none",
|
| 31 |
-
max_tokens=MAX_TOKENS,
|
| 32 |
-
temperature=0.75,
|
| 33 |
stream=True
|
| 34 |
)
|
| 35 |
|
|
|
|
| 4 |
#
|
| 5 |
|
| 6 |
import traceback
|
| 7 |
+
from config import INSTRUCTIONS_END
|
| 8 |
|
| 9 |
def generate_response(
|
| 10 |
server,
|
|
|
|
| 16 |
response_generator = ""
|
| 17 |
|
| 18 |
if tools_done:
|
| 19 |
+
conversation_messages.append({
|
| 20 |
"role": "system",
|
| 21 |
"content": INSTRUCTIONS_END
|
| 22 |
+
})
|
|
|
|
| 23 |
|
| 24 |
try:
|
| 25 |
response = server.chat.completions.create(
|
|
|
|
| 27 |
messages=conversation_messages,
|
| 28 |
tools=tool_definitions if not tools_done else None,
|
| 29 |
tool_choice="none",
|
|
|
|
|
|
|
| 30 |
stream=True
|
| 31 |
)
|
| 32 |
|
src/processor/tools/interaction.py
CHANGED
|
@@ -10,7 +10,7 @@ from ..reasoning.interface import reasoning_interfaces
|
|
| 10 |
from ..reasoning.tool_reasoning import tool_reasoning
|
| 11 |
from .parser import extract_tool_parameters
|
| 12 |
from .executor import invoke_tool_function
|
| 13 |
-
from config import
|
| 14 |
|
| 15 |
def process_tool_interactions(server, model_name, conversation_messages, tool_definitions, search_engine):
|
| 16 |
maximum_iterations = 1
|
|
@@ -52,9 +52,7 @@ def process_tool_interactions(server, model_name, conversation_messages, tool_de
|
|
| 52 |
model=model_name,
|
| 53 |
messages=conversation_messages,
|
| 54 |
tools=tool_definitions,
|
| 55 |
-
tool_choice="auto"
|
| 56 |
-
max_tokens=MAX_TOKENS,
|
| 57 |
-
temperature=0.6
|
| 58 |
)
|
| 59 |
|
| 60 |
response_choice = model_response.choices[0]
|
|
|
|
| 10 |
from ..reasoning.tool_reasoning import tool_reasoning
|
| 11 |
from .parser import extract_tool_parameters
|
| 12 |
from .executor import invoke_tool_function
|
| 13 |
+
from config import REASONING_DELAY
|
| 14 |
|
| 15 |
def process_tool_interactions(server, model_name, conversation_messages, tool_definitions, search_engine):
|
| 16 |
maximum_iterations = 1
|
|
|
|
| 52 |
model=model_name,
|
| 53 |
messages=conversation_messages,
|
| 54 |
tools=tool_definitions,
|
| 55 |
+
tool_choice="auto"
|
|
|
|
|
|
|
| 56 |
)
|
| 57 |
|
| 58 |
response_choice = model_response.choices[0]
|